2023-07137. Medicare Program; Prospective Payment System and Consolidated Billing for Skilled Nursing Facilities; Updates to the Quality Reporting Program and Value-Based Purchasing Program for Federal Fiscal Year 2024

AGENCY:

Centers for Medicare & Medicaid Services (CMS), Department of Health and Human Services (HHS).

ACTION:

Proposed rule.

SUMMARY:

This proposed rule would update payment rates, including implementing the second phase of the Patient Driven Payment Model (PDPM) parity adjustment recalibration. This proposed rule also proposes updates to the diagnosis code mappings used under PDPM, the SNF Quality Reporting Program (QRP), and the SNF Value-Based Purchasing (VBP) Program. We are also proposing to eliminate the requirement for facilities to actively waive their right to a hearing in writing, instead treating the failure to submit a timely request for a hearing as a constructive waiver.

DATES:

To be assured consideration, comments must be received at one of the addresses provided below, by June 5, 2023.

ADDRESSES:

In commenting, please refer to file code CMS–1779–P.

Comments, including mass comment submissions, must be submitted in one of the following three ways (please choose only one of the ways listed):

1. Electronically. You may submit electronic comments on this regulation to http://www.regulations.gov. Follow the “Submit a comment” instructions.

2. By regular mail. You may mail written comments to the following address ONLY: Centers for Medicare & Medicaid Services, Department of Health and Human Services, Attention: CMS–1779–P, P.O. Box 8016, Baltimore, MD 21244–8016.

Please allow sufficient time for mailed comments to be received before the close of the comment period.

3. By express or overnight mail. You may send written comments to the following address ONLY: Centers for Medicare & Medicaid Services, Department of Health and Human Services, Attention: CMS–1779–P, Mail Stop C4–26–05, 7500 Security Boulevard, Baltimore, MD 21244–1850.

For information on viewing public comments, see the beginning of the SUPPLEMENTARY INFORMATION section.

FOR FURTHER INFORMATION CONTACT:

[e-mail] for issues related to the SNF PPS.

Heidi Magladry, (410) 786–6034, for information related to the skilled nursing facility quality reporting program.

Alexandre Laberge, (410) 786–8625, for information related to the skilled nursing facility value-based purchasing program.

Lorelei Kahn, (443) 803–8643, for information related to the Civil Money Penalties Waiver of Hearing.

SUPPLEMENTARY INFORMATION:

Inspection of Public Comments: All comments received before the close of the comment period are available for viewing by the public, including any personally identifiable or confidential business information that is included in a comment. We post all comments received before the close of the comment period on the following website as soon as possible after they have been received: http://www.regulations.gov. Follow the search instructions on that website to view public comments. CMS will not post on Regulations.gov public comments that make threats to individuals or institutions or suggest that the individual will take actions to harm the individual. CMS continues to encourage individuals not to submit duplicative comments. We will post acceptable comments from multiple unique commenters even if the content is identical or nearly identical to other comments.

Availability of Certain Tables Exclusively Through the Internet on the CMS Website

As discussed in the FY 2014 SNF PPS final rule (78 FR 47936), tables setting forth the Wage Index for Urban Areas Based on CBSA Labor Market Areas and the Wage Index Based on CBSA Labor Market Areas for Rural Areas are no longer published in the Federal Register . Instead, these tables are available exclusively through the internet on the CMS website. The wage index tables for this proposed rule can be accessed on the SNF PPS Wage Index home page, at https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​SNFPPS/​WageIndex.html.

Readers who experience any problems accessing any of these online SNF PPS wage index tables should contact Kia Burwell at (410) 786–7816.

To assist readers in referencing sections contained in this document, we are providing the following Table of Contents.

Table of Contents

I. Executive Summary

A. Purpose

B. Summary of Major Provisions

C. Summary of Cost and Benefits

D. Advancing Health Information Exchange

II. Background on SNF PPS

A. Statutory Basis and Scope

B. Initial Transition for the SNF PPS

C. Required Annual Rate Updates

III. Proposed SNF PPS Rate Setting Methodology and FY 2024 Update

A. Federal Base Rates

B. SNF Market Basket Update

C. Case-Mix Adjustment

D. Wage Index Adjustment

E. SNF Value-Based Purchasing Program

F. Adjusted Rate Computation Example

IV. Additional Aspects of the SNF PPS

A. SNF Level of Care—Administrative Presumption

B. Consolidated Billing

C. Payment for SNF-Level Swing-Bed Services

D. Revisions to the Regulation Text

V. Other SNF PPS Issues

A. Technical Updates to PDPM ICD–10 Mappings

VI. Skilled Nursing Facility Quality Reporting Program (SNF QRP)

A. Background and Statutory Authority

B. General Considerations Used for the Selection of Measures for the SNF QRP

C. SNF QRP Quality Measure Proposals

D. Principles for Selecting and Prioritizing SNF QRP Quality Measures and Concepts Under Consideration for Future Years: Request for Information (RFI)

E. Health Equity Update

F. Form, Manner, and Timing of Data Submission Under the SNF QRP

G. Proposed Policies Regarding Public Display of Measure Data for the SNF QRP

VII. Skilled Nursing Facility Value-Based Purchasing Program (SNF VBP)

A. Statutory Background

B. SNF VBP Program Measures

C. SNF VBP Performance Period and Baseline Period Proposals

D. SNF VBP Performance Standards

E. Proposed Changes to the SNF VBP Performance Scoring Methodology

F. Proposed Update to the Extraordinary Circumstances Exception Policy Regulation Text

G. Proposal to Update the Validation Process for the SNF VBP Program

H. SNF Value-Based Incentive Payments for FY 2024

I. Public Reporting on the Provider Data Catalog Website

VIII. Civil Money Penalties: Waiver of Hearing, Automatic Reduction of Penalty Amount

IX. Collection of Information Requirements

X. Response to Comments

XI. Economic Analyses

A. Regulatory Impact Analysis

B. Regulatory Flexibility Act Analysis

C. Unfunded Mandates Reform Act Analysis

D. Federalism Analysis

E. Regulatory Review Costs

I. Executive Summary

A. Purpose

This proposed rule would update the SNF prospective payment rates for fiscal year (FY) 2024, as required under section 1888(e)(4)(E) of the Social Security Act (the Act). It also responds to section 1888(e)(4)(H) of the Act, which requires the Secretary to provide for publication of certain specified information relating to the payment update (see section II.C. of this proposed rule) in the Federal Register before the August 1 that precedes the start of each FY. In addition, this proposed rule includes proposals for the Skilled Nursing Facility Quality Reporting Program (SNF QRP) for the FY 2025, FY 2026, and FY 2027 program years. This proposed rule would add three new measures to the SNF QRP, remove three measures from the SNF QRP, and modify one measure in the SNF QRP. This proposed rule would also make policy changes to the SNF QRP, and begin public reporting of four measures. In addition, this proposed rule includes an update on our health equity efforts and requests information on principles we would use to select and prioritize SNF QRP quality measures in future years. Finally, this proposed rule includes proposals for the Skilled Nursing Facility Value-Based Purchasing Program (SNF VBP), including adopting new quality measures for the SNF VBP Program, proposing several updates to the Program's scoring methodology, including a Health Equity Adjustment, and proposing new processes to validate SNF VBP data. We are proposing changes to the current long-term care (LTC) facility requirements that would simplify and streamline the current requirements and thereby increase provider flexibility and reduce unnecessary administrative burden, while also allowing facilities to focus on providing healthcare to residents to meet their needs. This proposal was previously proposed and published in the July 18, 2019 Federal Register in the proposed rule entitled, “Medicare and Medicaid Programs; Requirements for Long-Term Care Facilities: Regulatory Provisions to Promote Efficiency, and Transparency” (84 FR 34718). We are re-proposing this proposed revision for a facility to waive its hearing rights and receive a reduction in civil money penalties in an effort to gather additional feedback from interested parties.

B. Summary of Major Provisions

In accordance with sections 1888(e)(4)(E)(ii)(IV) and (e)(5) of the Act, the Federal rates in this proposed rule would reflect an update to the rates that we published in the SNF PPS final rule for FY 2023 (87 FR 47502, August 3, 2022). In addition, this proposed rule includes a forecast error adjustment for FY 2024 and includes the second phase of the PDPM parity adjustment recalibration. This proposed rule also proposes updates to the diagnosis code mappings used under the PDPM.

Beginning with the FY 2025 SNF QRP, we propose to modify the COVID–19 Vaccination Coverage among Healthcare Personnel measure, adopt the Discharge Function Score measure, and remove the (1) Application of Percent of Long-Term Care Hospital Patients with an Admission and Discharge Functional Assessment and a Care Plan That Addresses Function measure, (2) the Application of IRF Functional Outcome Measure: Change in Self-Care Score for Medical Rehabilitation Patients measure, and (3) the Application of IRF Functional Outcome Measure: Change in Mobility Score for Medical Rehabilitation Patients measure. Beginning with the FY 2026 SNF QRP, we propose to adopt the CoreQ: Short Stay Discharge measure and the COVID–19 Vaccine: Percent of Patients/Residents Who Are Up to Date measure. We also propose changes to the SNF QRP data completion thresholds for the Minimum Data Set (MDS) data items beginning with the FY 2026 SNF QRP and to make certain revisions to regulation text at § 413.360. This proposed rule also contains proposals pertaining to the public reporting of the (1) Transfer of Health Information to the Patient-Post-Acute Care measure, (2) the Transfer of Health Information to the Provider-PAC measure, (3) the Discharge Function Score measure, and (4) the COVID–19 Vaccine: Percent of Patients/Residents Who Are Up to Date measure. In addition, we are seeking information on principles for selecting and prioritizing SNF QRP quality measures and concepts and provide an update on our continued efforts to close the health equity gap, including under the SNF QRP.

We are proposing several updates for the SNF VBP Program We are proposing to adopt a Health Equity Adjustment that rewards top tier performing SNFs that serve higher proportions of SNF residents with dual eligibility status, effective with the FY 2027 program year and to adopt a variable payback percentage to maintain an estimated payback percentage for all SNFs of no less than 60 percent. We are proposing to adopt four new quality measures to the SNF VBP Program, one taking effect beginning with the FY 2026 program year and three taking effect beginning with the FY 2027 program year. We are also proposing to refine the Skilled Nursing Facility 30-Day Potentially Preventable Readmission (SNFPPR) measure specifications and update the name to the Skilled Nursing Facility Within-Stay Potentially Preventable Readmission (SNF WS PPR) measure effective with the FY 2028 program year. We are proposing to adopt new processes to validate SNF VBP program data.

In addition, we are proposing to eliminate the requirement for facilities facing a civil money penalty to actively waive their right to a hearing in writing in order to receive a penalty reduction. We would create, in its place, a constructive waiver process that would operate by default when CMS has not received a timely request for a hearing. The accompanying 35 percent penalty reduction would remain. This proposed revision would result in lower administrative costs for most LTC facilities facing civil money penalties (CMPs), and would streamline and reduce the administrative burden for CMS. This proposal was previously proposed and published in the July 18, 2019 Federal Register .

C. Summary of Cost and Benefits

Table 1—Cost and Benefits

Provision description	Total transfers/costs
FY 2024 SNF PPS payment rate update	The overall economic impact of this proposed rule is an estimated increase of $1.2 billion in aggregate payments to SNFs during FY 2024.
FY 2025 SNF QRP changes	The overall economic impact of this proposed rule to SNFs is an estimated benefit of $1,037,261 to SNFs during FY 2025.
FY 2026 SNF QRP changes	The overall economic impact of this proposed rule to SNFs who would be exempt from the proposed CoreQ: Short Stay Discharge measure reporting requirements and the increase in burden from the addition of the Patient/Resident COVID–19 Vaccine measure is an estimated increase in aggregate cost from FY 2025 of $866,772.
	The overall economic impact of this proposed rule to SNFs who participate in the proposed CoreQ: Short Stay Discharge measure reporting requirements and the increase in burden from the addition of the Patient/Resident COVID–19 Vaccine measure is an estimated increase in aggregate cost from FY 2025 of $61,580,090.
FY 2027 SNF QRP changes	The overall economic impact of this proposed rule to SNFs who would be exempt from the proposed CoreQ: Short Stay Discharge measure reporting requirements is an estimated increase in aggregate cost from FY 2026 of $88,181.
	The overall economic impact of this proposed rule to SNFs who participate in the proposed CoreQ: Short Stay Discharge measure reporting requirements is an estimated increase in aggregate cost from FY 2026 of $63,344,417.
FY 2024 SNF VBP changes	The overall economic impact of the SNF VBP Program is an estimated reduction of $184.85 million in aggregate payments to SNFs during FY 2024.
FY 2026 SNF VBP changes	The overall economic impact of the SNF VBP Program is an estimated reduction of $196.50 million in aggregate payments to SNFs during FY 2026.
FY 2027 SNF VBP changes	The overall economic impact of the SNF VBP Program is an estimated reduction of $166.86 million in aggregate payments to SNFs during FY 2027.
FY 2028 SNF VBP changes	The overall economic impact of the SNF VBP Program is an estimated reduction of $170.98 million in aggregate payments to SNFs during FY 2028.
FY 2024 Enforcement Provisions for LTC Facilities Requirements Changes	The overall impact of this regulatory change is an estimated administrative cost savings of $2,299,716 to LTC facilities and $772,044 to the Federal Government during FY 2024.

D. Advancing Health Information Exchange

The Department of Health and Human Services (HHS) has a number of initiatives designed to encourage and support the adoption of interoperable health information technology and to promote nationwide health information exchange to improve health care and patient access to their digital health information.

To further interoperability in post-acute care settings, CMS and the Office of the National Coordinator for Health Information Technology (ONC) participate in the Post-Acute Care Interoperability Workgroup (PACIO) to facilitate collaboration with interested parties to develop Health Level Seven International® (HL7) Fast Healthcare Interoperability Resource® (FHIR) standards. These standards could support the exchange and reuse of patient assessment data derived from the post-acute care (PAC) setting assessment tools, such as the minimum data set (MDS), inpatient rehabilitation facility -patient assessment instrument (IRF–PAI), Long-Term Care Hospital (LTCH) continuity assessment record and evaluation (CARE) Data Set (LCDS), outcome and assessment information set (OASIS), and other sources.^[1 2] The PACIO Project has focused on HL7 FHIR implementation guides for: functional status, cognitive status and new use cases on advance directives, re-assessment timepoints, and Speech, language, swallowing, cognitive communication and hearing (SPLASCH) pathology.^[3] We encourage PAC provider and health IT vendor participation as the efforts advance.

The CMS Data Element Library (DEL) continues to be updated and serves as a resource for PAC assessment data elements and their associated mappings to health IT standards such as Logical Observation Identifiers Names and Codes (LOINC) and Systematized Nomenclature of Medicine Clinical Terms (SNOMED).^[4] The DEL furthers CMS' goal of data standardization and interoperability. Standards in the DEL can be referenced on the CMS website and in the ONC Interoperability Standards Advisory (ISA). The 2023 ISA is available at https://www.healthit.gov/​sites/​isa/​files/​inline-files/​2023%20Reference%20Edition_​ISA_​508.pdf.

We are also working with ONC to advance the United States Core Data for Interoperability (USCDI), a standardized set of health data classes and constituent data elements for nationwide, interoperable health information exchange.^[5] We are collaborating with ONC and other Federal agencies to define and prioritize additional data standardization needs and develop consensus on recommendations for future versions of the USCDI. We are also directly collaborating with ONC to build requirements to support data standardization and alignment with requirements for quality measurement. ONC has launched the USCDI+ initiative to support the identification and establishment of domain specific datasets that build on the core USCDI foundation.^[6] The USCDI+ quality measurement domain currently being developed aims to support defining additional data specifications for quality measurement that harmonize, where possible, with other Federal agency data needs and inform supplemental standards necessary to support quality measurement, including the needs of programs supporting quality measurement for long-term and post-acute care.

The 21st Century Cures Act (Cures Act) (Public Law 114–255, enacted December 13, 2016) required HHS and ONC to take steps to promote adoption and use of electronic health record (EHR) technology.^[7] Specifically, section 4003(b) of the Cures Act required ONC to take steps to advance interoperability through the development of a Trusted Exchange Framework and Common Agreement aimed at establishing full network-to network exchange of health information nationally. On January 18, 2022, ONC announced a significant milestone by releasing the Trusted Exchange Framework ^[8] and Common Agreement Version 1.^[9] The Trusted Exchange Framework is a set of non-binding principles for health information exchange, and the Common Agreement is a contract that advances those principles. The Common Agreement and the Qualified Health Information Network Technical Framework Version 1 (incorporated by reference into the Common Agreement) establish the technical infrastructure model and governing approach for different health information networks and their users to securely share clinical information with each other, all under commonly agreed to terms. The technical and policy architecture of how exchange occurs under the Common Agreement follows a network-of-networks structure, which allows for connections at different levels and is inclusive of many different types of entities at those different levels, such as health information networks, healthcare practices, hospitals, public health agencies, and Individual Access Services (IAS) Providers.^[10] On February 13, 2023, HHS marked a new milestone during an event at HHS headquarters,^[11] which recognized the first set of applicants accepted for onboarding to the Common Agreement as Qualified Health Information Networks (QHINs). QHINs will be entities that will connect directly to each other to serve as the core for nationwide interoperability.^[12] For more information, we refer readers to https://www.healthit.gov/​topic/​interoperability/​trusted-exchange-framework-and-common-agreement.

We invite providers to learn more about these important developments and how they are likely to affect SNFs.

II. Background on SNF PPS

A. Statutory Basis and Scope

As amended by section 4432 of the Balanced Budget Act of 1997 (BBA 1997) (Pub. L. 105–33, enacted August 5, 1997), section 1888(e) of the Act provides for the implementation of a PPS for SNFs. This methodology uses prospective, case-mix adjusted per diem payment rates applicable to all covered SNF services defined in section 1888(e)(2)(A) of the Act. The SNF PPS is effective for cost reporting periods beginning on or after July 1, 1998, and covers all costs of furnishing covered SNF services (routine, ancillary, and capital-related costs) other than costs associated with approved educational activities and bad debts. Under section 1888(e)(2)(A)(i) of the Act, covered SNF services include post-hospital extended care services for which benefits are provided under Part A, as well as those items and services (other than a small number of excluded services, such as physicians' services) for which payment may otherwise be made under Part B and which are furnished to Medicare beneficiaries who are residents in a SNF during a covered Part A stay. A comprehensive discussion of these provisions appears in the May 12, 1998 interim final rule (63 FR 26252). In addition, a detailed discussion of the legislative history of the SNF PPS is available online at https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​SNFPPS/​Downloads/​Legislative_​History_​2018-10-01.pdf.

Section 215(a) of the Protecting Access to Medicare Act of 2014 (PAMA) (Pub. L. 113–93, enacted April 1, 2014) added section 1888(g) to the Act requiring the Secretary to specify an all-cause all-condition hospital readmission measure and an all-condition risk-adjusted potentially preventable hospital readmission measure for the SNF setting. Additionally, section 215(b) of PAMA added section 1888(h) to the Act requiring the Secretary to implement a VBP program for SNFs. Finally, section 2(c)(4) of the Improving Medicare Post-Acute Care Transformation (IMPACT) Act of 2014 (Pub. L. 113–185, enacted October 6, 2014) amended section 1888(e)(6) of the Act, which requires the Secretary to implement a QRP for SNFs under which SNFs report data on measures and resident assessment data. Finally, section 111 of the Consolidated Appropriations Act, 2021 (CAA 2021) updated section 1888(h) of the Act, authorizing the Secretary to apply up to nine additional measures to the VBP program for SNFs.

B. Initial Transition for the SNF PPS

Under sections 1888(e)(1)(A) and (e)(11) of the Act, the SNF PPS included an initial, three-phase transition that blended a facility-specific rate (reflecting the individual facility's historical cost experience) with the Federal case-mix adjusted rate. The transition extended through the facility's first 3 cost reporting periods under the PPS, up to and including the one that began in FY 2001. Thus, the SNF PPS is no longer operating under the transition, as all facilities have been paid at the full Federal rate effective with cost reporting periods beginning in FY 2002. As we now base payments for SNFs entirely on the adjusted Federal per diem rates, we no longer include adjustment factors under the transition related to facility-specific rates for the upcoming FY.

C. Required Annual Rate Updates

Section 1888(e)(4)(E) of the Act requires the SNF PPS payment rates to be updated annually. The most recent annual update occurred in a final rule that set forth updates to the SNF PPS payment rates for FY 2023 (87 FR 47502, August 3, 2022).

Section 1888(e)(4)(H) of the Act specifies that we provide for publication annually in the Federal Register the following:

• The unadjusted Federal per diem rates to be applied to days of covered SNF services furnished during the upcoming FY.

• The case-mix classification system to be applied for these services during the upcoming FY.
• The factors to be applied in making the area wage adjustment for these services.

Along with other revisions discussed later in this preamble, this proposal would set out the required annual updates to the per diem payment rates for SNFs for FY 2024.

III. Proposed SNF PPS Rate Setting Methodology and FY 2024 Update

A. Federal Base Rates

Under section 1888(e)(4) of the Act, the SNF PPS uses per diem Federal payment rates based on mean SNF costs in a base year (FY 1995) updated for inflation to the first effective period of the PPS. We developed the Federal payment rates using allowable costs from hospital-based and freestanding SNF cost reports for reporting periods beginning in FY 1995. The data used in developing the Federal rates also incorporated a Part B add-on, which is an estimate of the amounts that, prior to the SNF PPS, would be payable under Part B for covered SNF services furnished to individuals during the course of a covered Part A stay in a SNF.

In developing the rates for the initial period, we updated costs to the first effective year of the PPS (the 15-month period beginning July 1, 1998) using a SNF market basket, and then standardized for geographic variations in wages and for the costs of facility differences in case-mix. In compiling the database used to compute the Federal payment rates, we excluded those providers that received new provider exemptions from the routine cost limits, as well as costs related to payments for exceptions to the routine cost limits. Using the formula that the BBA 1997 prescribed, we set the Federal rates at a level equal to the weighted mean of freestanding costs plus 50 percent of the difference between the freestanding mean and weighted mean of all SNF costs (hospital-based and freestanding) combined. We computed and applied separately the payment rates for facilities located in urban and rural areas and adjusted the portion of the Federal rate attributable to wage-related costs by a wage index to reflect geographic variations in wages.

B. SNF Market Basket Update

1. SNF Market Basket

Section 1888(e)(5)(A) of the Act requires us to establish a SNF market basket that reflects changes over time in the prices of an appropriate mix of goods and services included in covered SNF services. Accordingly, we have developed a SNF market basket that encompasses the most commonly used cost categories for SNF routine services, ancillary services, and capital-related expenses. In the SNF PPS final rule for FY 2018 (82 FR 36548 through 36566), we rebased and revised the SNF market basket, which included updating the base year from FY 2010 to 2014. In the SNF PPS final rule for FY 2022 (86 FR 42444 through 42463), we rebased and revised the SNF market basket, which included updating the base year from 2014 to 2018.

The SNF market basket is used to compute the market basket percentage increase that is used to update the SNF Federal rates on an annual basis, as required by section 1888(e)(4)(E)(ii)(IV) of the Act. This market basket percentage increase is adjusted by a forecast error adjustment, if applicable, and then further adjusted by the application of a productivity adjustment as required by section 1888(e)(5)(B)(ii) of the Act and described in section III.B.4. of this proposed rule.

As outlined in this proposed rule, we propose a FY 2024 SNF market basket percentage increase of 2.7 percent based on IHS Global Inc.'s (IGI's) fourth quarter 2022 forecast of the 2018-based SNF market basket (before application of the forecast error adjustment and productivity adjustment). We also propose that if more recent data subsequently become available (for example, a more recent estimate of the market basket and/or the productivity adjustment), we would use such data, if appropriate, to determine the FY 2024 SNF market basket percentage increase, labor-related share relative importance, forecast error adjustment, or productivity adjustment in the SNF PPS final rule.

2. Market Basket Update Factor for FY 2024

Section 1888(e)(5)(B) of the Act defines the SNF market basket percentage increase as the percentage change in the SNF market basket from the midpoint of the previous FY to the midpoint of the current FY. For the Federal rates outlined in this proposed rule, we use the percentage change in the SNF market basket to compute the update factor for FY 2024. This factor is based on the FY 2024 percentage increase in the 2018-based SNF market basket reflecting routine, ancillary, and capital-related expenses. Sections 1888(e)(4)(E)(ii)(IV) and (e)(5)(B)(i) of the Act require that the update factor used to establish the FY 2024 unadjusted Federal rates be at a level equal to the SNF market basket percentage increase. Accordingly, we determined the total growth from the average market basket level for the period of October 1, 2022 through September 30, 2023 to the average market basket level for the period of October 1, 2023 through September 30, 2024. This process yields a percentage increase in the 2018-based SNF market basket of 2.7 percent.

As further explained in section III.B.3. of this proposed rule, as applicable, we adjust the percentage increase by the forecast error adjustment from the most recently available FY for which there is final data and apply this adjustment whenever the difference between the forecasted and actual percentage increase in the market basket exceeds a 0.5 percentage point threshold in absolute terms. Additionally, section 1888(e)(5)(B)(ii) of the Act requires us to reduce the market basket percentage increase by the productivity adjustment (the 10-year moving average of changes in annual economy-wide private nonfarm business total factor productivity (TFP) for the period ending September 30, 2024) which is estimated to be 0.2 percentage point, as described in section III.B.4. of this proposed rule.

We also note that section 1888(e)(6)(A)(i) of the Act provides that, beginning with FY 2018, SNFs that fail to submit data, as applicable, in accordance with sections 1888(e)(6)(B)(i)(II) and (III) of the Act for a fiscal year will receive a 2.0 percentage point reduction to their market basket update for the fiscal year involved, after application of section 1888(e)(5)(B)(ii) of the Act (the productivity adjustment) and section 1888(e)(5)(B)(iii) of the Act (the market basket increase). In addition, section 1888(e)(6)(A)(ii) of the Act states that application of the 2.0 percentage point reduction (after application of section 1888(e)(5)(B)(ii) and (iii) of the Act) may result in the market basket percentage change being less than zero for a fiscal year, and may result in payment rates for a fiscal year being less than such payment rates for the preceding fiscal year. Section 1888(e)(6)(A)(iii) of the Act further specifies that the 2.0 percentage point reduction is applied in a noncumulative manner, so that any reduction made under section 1888(e)(6)(A)(i) of the Act applies only to the fiscal year involved, and that the reduction cannot be taken into account in computing the payment amount for a subsequent fiscal year.

3. Forecast Error Adjustment

As discussed in the June 10, 2003 supplemental proposed rule (68 FR 34768) and finalized in the August 4, 2003 final rule (68 FR 46057 through 46059), § 413.337(d)(2) provides for an adjustment to account for market basket forecast error. The initial adjustment for market basket forecast error applied to the update of the FY 2003 rate for FY 2004 and took into account the cumulative forecast error for the period from FY 2000 through FY 2002, resulting in an increase of 3.26 percent to the FY 2004 update. Subsequent adjustments in succeeding FYs take into account the forecast error from the most recently available FY for which there is final data and apply the difference between the forecasted and actual change in the market basket when the difference exceeds a specified threshold. We originally used a 0.25 percentage point threshold for this purpose; however, for the reasons specified in the FY 2008 SNF PPS final rule (72 FR 43425), we adopted a 0.5 percentage point threshold effective for FY 2008 and subsequent FYs. As we stated in the final rule for FY 2004 that first issued the market basket forecast error adjustment (68 FR 46058), the adjustment will reflect both upward and downward adjustments, as appropriate.

For FY 2022 (the most recently available FY for which there is final data), the forecasted or estimated increase in the SNF market basket was 2.7 percent, and the actual increase for FY 2022 is 6.3 percent, resulting in the actual increase being 3.6 percentage points higher than the estimated increase. Accordingly, as the difference between the estimated and actual amount of change in the market basket exceeds the 0.5 percentage point threshold, under the policy previously described (comparing the forecasted and actual market basket percentage increase), the FY 2024 market basket percentage increase of 2.7 percent would be adjusted upward to account for the forecast error adjustment of 3.6 percentage points, resulting in a SNF market basket percentage increase of 6.3 percent, which is then reduced by the productivity adjustment of 0.2 percentage point, discussed in section III.B.4. of this proposed rule. This results in a proposed SNF market basket update for FY 2024 of 6.1 percent.

Table 2 shows the forecasted and actual market basket increases for FY 2022.

Table 2—Difference Between the Actual and Forecasted Market Basket Increases for FY 2022

Index	Forecasted FY 2022 increase *	Actual FY 2022 increase **	FY 2022 difference
SNF	2.7	6.3	3.6
* Published in Federal Register ; based on second quarter 2021 IGI forecast (2018-based SNF market basket).
** Based on the fourth quarter 2022 IGI forecast (2018-based SNF market basket).

4. Productivity Adjustment

Section 1888(e)(5)(B)(ii) of the Act, as added by section 3401(b) of the Patient Protection and Affordable Care Act (Affordable Care Act) (Pub. L. 111–148, enacted March 23, 2010) requires that, in FY 2012 and in subsequent FYs, the market basket percentage under the SNF payment system (as described in section 1888(e)(5)(B)(i) of the Act) is to be reduced annually by the productivity adjustment described in section 1886(b)(3)(B)(xi)(II) of the Act. Section 1886(b)(3)(B)(xi)(II) of the Act, in turn, defines the productivity adjustment to be equal to the 10-year moving average of changes in annual economy-wide, private nonfarm business multifactor productivity (MFP) (as projected by the Secretary for the 10-year period ending with the applicable FY, year, cost-reporting period, or other annual period).

The U.S. Department of Labor's Bureau of Labor Statistics (BLS) publishes the official measure of productivity for the U.S. We note that previously the productivity measure referenced at section 1886(b)(3)(B)(xi)(II) of the Act was published by BLS as private nonfarm business multifactor productivity. Beginning with the November 18, 2021 release of productivity data, BLS replaced the term MFP with TFP. BLS noted that this is a change in terminology only and will not affect the data or methodology. As a result of the BLS name change, the productivity measure referenced in section 1886(b)(3)(B)(xi)(II) of the Act is now published by BLS as private nonfarm business total factor productivity. We refer readers to the BLS website at www.bls.gov for the BLS historical published TFP data. A complete description of the TFP projection methodology is available on our website at https://www.cms.gov/​Research-Statistics-Data-and-Systems/​Statistics-Trends-and-Reports/​MedicareProgramRatesStats/​MarketBasketResearch. In addition, in the FY 2022 SNF final rule (86 FR 42429) we noted that, effective with FY 2022 and forward, we changed the name of this adjustment to refer to it as the “productivity adjustment,” rather than the “MFP adjustment.”

Per section 1888(e)(5)(A) of the Act, the Secretary shall establish a SNF market basket that reflects changes over time in the prices of an appropriate mix of goods and services included in covered SNF services. Section 1888(e)(5)(B)(ii) of the Act, added by section 3401(b) of the Affordable Care Act, requires that for FY 2012 and each subsequent FY, after determining the market basket percentage described in section 1888(e)(5)(B)(i) of the Act, the Secretary shall reduce such percentage by the productivity adjustment described in section 1886(b)(3)(B)(xi)(II) of the Act. Section 1888(e)(5)(B)(ii) of the Act further states that the reduction of the market basket percentage by the productivity adjustment may result in the market basket percentage being less than zero for a FY and may result in payment rates under section 1888(e) of the Act being less than such payment rates for the preceding fiscal year. Thus, if the application of the productivity adjustment to the market basket percentage calculated under section 1888(e)(5)(B)(i) of the Act results in a productivity-adjusted market basket percentage that is less than zero, then the annual update to the unadjusted Federal per diem rates under section 1888(e)(4)(E)(ii) of the Act would be negative, and such rates would decrease relative to the prior FY.

Based on the data available for this FY 2024 SNF PPS proposed rule, the current proposed productivity adjustment (the 10-year moving average of changes in annual economy-wide private nonfarm business TFP for the period ending September 30, 2024) is projected to be 0.2 percentage point.

Consistent with section 1888(e)(5)(B)(i) of the Act and § 413.337(d)(2), and as discussed previously in section III.B.1. of this proposed rule, the proposed market basket percentage for FY 2024 for the SNF PPS is based on IGI's fourth quarter 2022 forecast of the SNF market basket percentage, which is estimated to be 2.7 percent. This market basket percentage is then increased by 3.6 percentage points, due to application of the forecast error adjustment discussed earlier in section III.B.3. of this proposed rule. Finally, as discussed earlier in section III.B.4. of this proposed rule, we are applying a proposed 0.2 percentage point productivity adjustment to the FY 2024 SNF market basket percentage. Therefore, the resulting proposed productivity-adjusted FY 2024 SNF market basket update is equal to 6.1 percent, which reflects a market basket percentage increase of 2.7 percent, plus the 3.6 percentage points forecast error adjustment, and less the 0.2 percentage point to account for the productivity adjustment. Thus, we propose to apply a net SNF market basket update factor of 6.1 percent in our determination of the FY 2024 SNF PPS unadjusted Federal per diem rates.

5. Unadjusted Federal Per Diem Rates for FY 2024

As discussed in the FY 2019 SNF PPS final rule (83 FR 39162), in FY 2020 we implemented a new case-mix classification system to classify SNF patients under the SNF PPS, the PDPM. As discussed in section V.B.1. of that final rule (83 FR 39189), under PDPM, the unadjusted Federal per diem rates are divided into six components, five of which are case-mix adjusted components (Physical Therapy (PT), Occupational Therapy (OT), Speech-Language Pathology (SLP), Nursing, and Non-Therapy Ancillaries (NTA)), and one of which is a non-case-mix component, as existed under the previous RUG–IV model. We propose to use the SNF market basket, adjusted as described previously in sections III.B.1. through III.B.4. of this proposed rule, to adjust each per diem component of the Federal rates forward to reflect the change in the average prices for FY 2024 from the average prices for FY 2023. We also propose to further adjust the rates by a wage index budget neutrality factor, described later in section III.D. of this proposed rule.

Further, in the past, we used the revised Office of Management and Budget (OMB) delineations adopted in the FY 2015 SNF PPS final rule (79 FR 45632, 45634), with updates as reflected in OMB Bulletin Nos. 15–01 and 17–01, to identify a facility's urban or rural status for the purpose of determining which set of rate tables would apply to the facility. As discussed in the FY 2021 SNF PPS proposed and final rules, we adopted the revised OMB delineations identified in OMB Bulletin No. 18–04 (available at https://www.whitehouse.gov/​wp-content/​uploads/​2018/​09/​Bulletin-18-04.pdf) to identify a facility's urban or rural status effective beginning with FY 2021.

Tables 3 and 4 reflect the updated unadjusted Federal rates for FY 2024, prior to adjustment for case-mix.

Table 3—FY 2024 Unadjusted Federal Rate Per Diem—URBAN

Rate component	PT	OT	SLP	Nursing	NTA	Non-case-mix
Per Diem Amount	$70.08	$65.23	$26.16	$122.15	$92.16	$109.39

Table 4—FY 2024 Unadjusted Federal Rate Per Diem—RURAL

Rate component	PT	OT	SLP	Nursing	NTA	Non-case-mix
Per Diem Amount	$79.88	$73.36	$32.96	$116.71	$88.05	$111.41

C. Case-Mix Adjustment

Under section 1888(e)(4)(G)(i) of the Act, the Federal rate also incorporates an adjustment to account for facility case-mix, using a classification system that accounts for the relative resource utilization of different patient types. The statute specifies that the adjustment is to reflect both a resident classification system that the Secretary establishes to account for the relative resource use of different patient types, as well as resident assessment data and other data that the Secretary considers appropriate. In the FY 2019 final rule (83 FR 39162, August 8, 2018), we finalized a new case-mix classification model, the PDPM, which took effect beginning October 1, 2019. The previous RUG–IV model classified most patients into a therapy payment group and primarily used the volume of therapy services provided to the patient as the basis for payment classification, thus creating an incentive for SNFs to furnish therapy regardless of the individual patient's unique characteristics, goals, or needs. PDPM eliminates this incentive and improves the overall accuracy and appropriateness of SNF payments by classifying patients into payment groups based on specific, data-driven patient characteristics, while simultaneously reducing the administrative burden on SNFs.

The PDPM uses clinical data from the MDS to assign case-mix classifiers to each patient that are then used to calculate a per diem payment under the SNF PPS, consistent with the provisions of section 1888(e)(4)(G)(i) of the Act. As discussed in section IV.A. of this proposed rule, the clinical orientation of the case-mix classification system supports the SNF PPS's use of an administrative presumption that considers a beneficiary's initial case-mix classification to assist in making certain SNF level of care determinations. Further, because the MDS is used as a basis for payment, as well as a clinical assessment, we have provided extensive training on proper coding and the timeframes for MDS completion in our Resident Assessment Instrument (RAI) Manual. As we have stated in prior rules, for an MDS to be considered valid for use in determining payment, the MDS assessment should be completed in compliance with the instructions in the RAI Manual in effect at the time the assessment is completed. For payment and quality monitoring purposes, the RAI Manual consists of both the Manual instructions and the interpretive guidance and policy clarifications posted on the appropriate MDS website at https://www.cms.gov/​Medicare/​Quality-Initiatives-Patient-Assessment-Instruments/​NursingHomeQualityInits/​MDS30RAIManual.html.

Under section 1888(e)(4)(H) of the Act, each update of the payment rates must include the case-mix classification methodology applicable for the upcoming FY. The FY 2024 payment rates set forth in this proposed rule reflect the use of the PDPM case-mix classification system from October 1, 2023, through September 30, 2024. The case-mix adjusted PDPM payment rates for FY 2024 are listed separately for urban and rural SNFs, in Tables 5 and 6 with corresponding case-mix values.

Given the differences between the previous RUG–IV model and PDPM in terms of patient classification and billing, it was important that the format of Tables 5 and 6 reflect these differences. More specifically, under both RUG–IV and PDPM, providers use a Health Insurance Prospective Payment System (HIPPS) code on a claim to bill for covered SNF services. Under RUG–IV, the HIPPS code included the three-character RUG–IV group into which the patient classified, as well as a two-character assessment indicator code that represented the assessment used to generate this code. Under PDPM, while providers still use a HIPPS code, the characters in that code represent different things. For example, the first character represents the PT and OT group into which the patient classifies. If the patient is classified into the PT and OT group “TA”, then the first character in the patient's HIPPS code would be an A. Similarly, if the patient is classified into the SLP group “SB”, then the second character in the patient's HIPPS code would be a B. The third character represents the Nursing group into which the patient classifies. The fourth character represents the NTA group into which the patient classifies. Finally, the fifth character represents the assessment used to generate the HIPPS code.

Tables 5 and 6 reflect the PDPM's structure. Accordingly, Column 1 of Tables 5 and 6 represents the character in the HIPPS code associated with a given PDPM component. Columns 2 and 3 provide the case-mix index and associated case-mix adjusted component rate, respectively, for the relevant PT group. Columns 4 and 5 provide the case-mix index and associated case-mix adjusted component rate, respectively, for the relevant OT group. Columns 6 and 7 provide the case-mix index and associated case-mix adjusted component rate, respectively, for the relevant SLP group. Column 8 provides the nursing case-mix group (CMG) that is connected with a given PDPM HIPPS character. For example, if the patient qualified for the nursing group CBC1, then the third character in the patient's HIPPS code would be a “P.” Columns 9 and 10 provide the case-mix index and associated case-mix adjusted component rate, respectively, for the relevant nursing group. Finally, columns 11 and 12 provide the case-mix index and associated case-mix adjusted component rate, respectively, for the relevant NTA group.

Tables 5 and 6 do not reflect adjustments which may be made to the SNF PPS rates as a result of the SNF VBP Program, discussed in section VII. of this proposed rule, or other adjustments, such as the variable per diem adjustment. Further, in the past, we used the revised OMB delineations adopted in the FY 2015 SNF PPS final rule (79 FR 45632, 45634), with updates as reflected in OMB Bulletin Nos, 15–01 and 17–01, to identify a facility's urban or rural status for the purpose of determining which set of rate tables would apply to the facility. As discussed in the FY 2021 SNF PPS final rule (85 FR 47594), we adopted the revised OMB delineations identified in OMB Bulletin No. 18–04 (available at https://www.whitehouse.gov/​wp-content/​uploads/​2018/​09/​Bulletin-18-04.pdf) to identify a facility's urban or rural status effective beginning with FY 2021.

In the FY 2023 SNF PPS final rule (87 FR 47502), we finalized a proposal to recalibrate the PDPM parity adjustment over 2 years starting in FY 2023, which means that, for each of the PDPM case-mix adjusted components, we lowered the PDPM parity adjustment factor from 46 percent to 42 percent in FY 2023 and we would further lower the PDPM parity adjustment factor from 42 percent to 38 percent in FY 2024. Following this methodology, which is further described in the FY 2023 SNF PPS final rule (87 FR 47525 through 47534), Tables 5 and 6 incorporate the second phase of the PDPM parity adjustment recalibration.

Table 5—PDPM Case-Mix Adjusted Federal Rates and Associated Indexes—URBAN

[Including the parity adjustment recalibration]

PDPM group	PT CMI	PT rate	OT CMI	OT rate	SLP CMI	SLP rate	Nursing CMG	Nursing CMI	Nursing rate	NTA CMI	NTA rate
A	1.45	$101.62	1.41	$91.97	0.64	$16.74	ES3	3.84	$469.06	3.06	$282.01
B	1.61	112.83	1.54	100.45	1.72	45.00	ES2	2.90	354.24	2.39	220.26
C	1.78	124.74	1.60	104.37	2.52	65.92	ES1	2.77	338.36	1.74	160.36
D	1.81	126.84	1.45	94.58	1.38	36.10	HDE2	2.27	277.28	1.26	116.12
E	1.34	93.91	1.33	86.76	2.21	57.81	HDE1	1.88	229.64	0.91	83.87
F	1.52	106.52	1.51	98.50	2.82	73.77	HBC2	2.12	258.96	0.68	62.67
G	1.58	110.73	1.55	101.11	1.93	50.49	HBC1	1.76	214.98
H	1.10	77.09	1.09	71.10	2.7	70.63	LDE2	1.97	240.64
I	1.07	74.99	1.12	73.06	3.34	87.37	LDE1	1.64	200.33
J	1.34	93.91	1.37	89.37	2.83	74.03	LBC2	1.63	199.10
K	1.44	100.92	1.46	95.24	3.5	91.56	LBC1	1.35	164.90
L	1.03	72.18	1.05	68.49	3.98	104.12	CDE2	1.77	216.21
M	1.20	84.10	1.23	80.23			CDE1	1.53	186.89
N	1.40	98.11	1.42	92.63			CBC2	1.47	179.56
O	1.47	103.02	1.47	95.89			CA2	1.03	125.81
P	1.02	71.48	1.03	67.19			CBC1	1.27	155.13
Q							CA1	0.89	108.71
R							BAB2	0.98	119.71
S							BAB1	0.94	114.82
T							PDE2	1.48	180.78
U							PDE1	1.39	169.79
V							PBC2	1.15	140.47
W							PA2	0.67	81.84
X							PBC1	1.07	130.70
Y							PA1	0.62	75.73

Table 6—PDPM Case-Mix Adjusted Federal Rates and Associated Indexes—RURAL

[Including the parity adjustment recalibration]

PDPM group	PT CMI	PT rate	OT CMI	OT rate	SLP CMI	SLP rate	Nursing CMG	Nursing CMI	Nursing rate	NTA CMI	NTA rate
A	1.45	$115.83	1.41	$103.44	0.64	$21.09	ES3	3.84	$448.17	3.06	$269.43
B	1.61	128.61	1.54	112.97	1.72	56.69	ES2	2.90	338.46	2.39	210.44
C	1.78	142.19	1.60	117.38	2.52	83.06	ES1	2.77	323.29	1.74	153.21
D	1.81	144.58	1.45	106.37	1.38	45.48	HDE2	2.27	264.93	1.26	110.94
E	1.34	107.04	1.33	97.57	2.21	72.84	HDE1	1.88	219.41	0.91	80.13
F	1.52	121.42	1.51	110.77	2.82	92.95	HBC2	2.12	247.43	0.68	59.87
G	1.58	126.21	1.55	113.71	1.93	63.61	HBC1	1.76	205.41
H	1.10	87.87	1.09	79.96	2.7	88.99	LDE2	1.97	229.92
I	1.07	85.47	1.12	82.16	3.34	110.09	LDE1	1.64	191.40
J	1.34	107.04	1.37	100.50	2.83	93.28	LBC2	1.63	190.24
K	1.44	115.03	1.46	107.11	3.5	115.36	LBC1	1.35	157.56
L	1.03	82.28	1.05	77.03	3.98	131.18	CDE2	1.77	206.58
M	1.20	95.86	1.23	90.23			CDE1	1.53	178.57
N	1.40	111.83	1.42	104.17			CBC2	1.47	171.56
O	1.47	117.42	1.47	107.84			CA2	1.03	120.21
P	1.02	81.48	1.03	75.56			CBC1	1.27	148.22
Q							CA1	0.89	103.87
R							BAB2	0.98	114.38
S							BAB1	0.94	109.71
T							PDE2	1.48	172.73
U							PDE1	1.39	162.23
V							PBC2	1.15	134.22
W							PA2	0.67	78.20
X							PBC1	1.07	124.88
Y							PA1	0.62	72.36

D. Wage Index Adjustment

Section 1888(e)(4)(G)(ii) of the Act requires that we adjust the Federal rates to account for differences in area wage levels, using a wage index that the Secretary determines appropriate. Since the inception of the SNF PPS, we have used hospital inpatient wage data in developing a wage index to be applied to SNFs. We propose to continue this practice for FY 2024, as we continue to believe that in the absence of SNF-specific wage data, using the hospital inpatient wage index data is appropriate and reasonable for the SNF PPS. As explained in the update notice for FY 2005 (69 FR 45786), the SNF PPS does not use the hospital area wage index's occupational mix adjustment, as this adjustment serves specifically to define the occupational categories more clearly in a hospital setting; moreover, the collection of the occupational wage data under the inpatient prospective payment system (IPPS) also excludes any wage data related to SNFs. Therefore, we believe that using the updated wage data exclusive of the occupational mix adjustment continues to be appropriate for SNF payments. As in previous years, we would continue to use the pre-reclassified IPPS hospital wage data, without applying the occupational mix, rural floor, or outmigration adjustment, as the basis for the SNF PPS wage index. For FY 2024, the updated wage data are for hospital cost reporting periods beginning on or after October 1, 2019 and before October 1, 2020 (FY 2020 cost report data).

We note that section 315 of the Medicare, Medicaid, and SCHIP Benefits Improvement and Protection Act of 2000 (BIPA) (Pub. L. 106–554, enacted December 21, 2000) gave the Secretary the discretion to establish a geographic reclassification procedure specific to SNFs, but only after collecting the data necessary to establish a SNF PPS wage index that is based on wage data from nursing homes. To date, this has proven to be unfeasible due to the volatility of existing SNF wage data and the significant amount of resources that would be required to improve the quality of the data. More specifically, auditing all SNF cost reports, similar to the process used to audit inpatient hospital cost reports for purposes of the IPPS wage index, would place a burden on providers in terms of recordkeeping and completion of the cost report worksheet. Adopting such an approach would require a significant commitment of resources by CMS and the Medicare Administrative Contractors, potentially far in excess of those required under the IPPS, given that there are nearly five times as many SNFs as there are inpatient hospitals. While we continue to believe that the development of such an audit process could improve SNF cost reports in such a manner as to permit us to establish a SNF-specific wage index, we do not believe this undertaking is feasible at this time.

In addition, we propose to continue to use the same methodology discussed in the SNF PPS final rule for FY 2008 (72 FR 43423) to address those geographic areas in which there are no hospitals, and thus, no hospital wage index data on which to base the calculation of the FY 2022 SNF PPS wage index. For rural geographic areas that do not have hospitals and, therefore, lack hospital wage data on which to base an area wage adjustment, we propose to continue using the average wage index from all contiguous Core-Based Statistical Areas (CBSAs) as a reasonable proxy. For FY 2024, there are no rural geographic areas that do not have hospitals, and thus, this methodology will not be applied. For rural Puerto Rico, we propose not to apply this methodology due to the distinct economic circumstances there; due to the close proximity of almost all of Puerto Rico's various urban and non-urban areas, this methodology would produce a wage index for rural Puerto Rico that is higher than that in half of its urban areas. Instead, we would continue using the most recent wage index previously available for that area. For urban areas without specific hospital wage index data, we propose to continue using the average wage indexes of all urban areas within the State to serve as a reasonable proxy for the wage index of that urban CBSA. For FY 2024, the only urban area without wage index data available is CBSA 25980, Hinesville-Fort Stewart, GA.

In the SNF PPS final rule for FY 2006 (70 FR 45026, August 4, 2005), we adopted the changes discussed in OMB Bulletin No. 03–04 (June 6, 2003), which announced revised definitions for MSAs and the creation of micropolitan statistical areas and combined statistical areas. In adopting the CBSA geographic designations, we provided for a 1-year transition in FY 2006 with a blended wage index for all providers. For FY 2006, the wage index for each provider consisted of a blend of 50 percent of the FY 2006 MSA-based wage index and 50 percent of the FY 2006 CBSA-based wage index (both using FY 2002 hospital data). We referred to the blended wage index as the FY 2006 SNF PPS transition wage index. As discussed in the SNF PPS final rule for FY 2006 (70 FR 45041), after the expiration of this 1-year transition on September 30, 2006, we used the full CBSA-based wage index values.

In the FY 2015 SNF PPS final rule (79 FR 45644 through 45646), we finalized changes to the SNF PPS wage index based on the newest OMB delineations, as described in OMB Bulletin No. 13–01, beginning in FY 2015, including a 1-year transition with a blended wage index for FY 2015. OMB Bulletin No. 13–01 established revised delineations for Metropolitan Statistical Areas, Micropolitan Statistical Areas, and Combined Statistical Areas in the United States and Puerto Rico based on the 2010 Census, and provided guidance on the use of the delineations of these statistical areas using standards published in the June 28, 2010 Federal Register (75 FR 37246 through 37252). Subsequently, on July 15, 2015, OMB issued OMB Bulletin No. 15–01, which provided minor updates to and superseded OMB Bulletin No. 13–01 that was issued on February 28, 2013. The attachment to OMB Bulletin No. 15–01 provided detailed information on the update to statistical areas since February 28, 2013. The updates provided in OMB Bulletin No. 15–01 were based on the application of the 2010 Standards for Delineating Metropolitan and Micropolitan Statistical Areas to Census Bureau population estimates for July 1, 2012 and July 1, 2013 and were adopted under the SNF PPS in the FY 2017 SNF PPS final rule (81 FR 51983, August 5, 2016). In addition, on August 15, 2017, OMB issued Bulletin No. 17–01 which announced a new urban CBSA, Twin Falls, Idaho (CBSA 46300) which was adopted in the SNF PPS final rule for FY 2019 (83 FR 39173, August 8, 2018).

As discussed in the FY 2021 SNF PPS final rule (85 FR 47594), we adopted the revised OMB delineations identified in OMB Bulletin No. 18–04 (available at https://www.whitehouse.gov/​wp-content/​uploads/​2018/​09/​Bulletin-18-04.pdf) beginning October 1, 2020, including a 1-year transition for FY 2021 under which we applied a 5 percent cap on any decrease in a hospital's wage index compared to its wage index for the prior fiscal year (FY 2020). The updated OMB delineations more accurately reflect the contemporary urban and rural nature of areas across the country, and the use of such delineations allows us to determine more accurately the appropriate wage index and rate tables to apply under the SNF PPS.

In the FY 2023 SNF PPS final rule (87 FR 47521 through 47525), we finalized a policy to apply a permanent 5 percent cap on any decreases to a provider's wage index from its wage index in the prior year, regardless of the circumstances causing the decline. Additionally, we finalized a policy that a new SNF would be paid the wage index for the area in which it is geographically located for its first full or partial FY with no cap applied because a new SNF would not have a wage index in the prior FY. We amended the SNF PPS regulations at 42 CFR 413.337(b)(4)(ii) to reflect this permanent cap on wage index decreases. A full discussion of the adoption of this policy is found in the FY 2023 SNF PPS final rule.

As we previously stated in the FY 2008 SNF PPS proposed and final rules (72 FR 25538 through 25539, and 72 FR 43423), this and all subsequent SNF PPS rules and notices are considered to incorporate any updates and revisions set forth in the most recent OMB bulletin that applies to the hospital wage data used to determine the current SNF PPS wage index. OMB issued further revised CBSA delineations in OMB Bulletin No. 20–01, on March 6, 2020 (available on the web at https://www.whitehouse.gov/​wp-content/​uploads/​2020/​03/​Bulletin-20-01.pdf). However, we determined that the changes in OMB Bulletin No. 20–01 do not impact the CBSA-based labor market area delineations adopted in FY 2021. Therefore, CMS did not propose to adopt the revised OMB delineations identified in OMB Bulletin No. 20 01 for FY 2022 or 2023, and for these reasons CMS is likewise not making such a proposal for FY 2024.The wage index applicable to FY 2024 is set forth in Tables A and B available on the CMS website at http://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​SNFPPS/​WageIndex.html.

Once calculated, we would apply the wage index adjustment to the labor-related portion of the Federal rate. Each year, we calculate a labor-related share, based on the relative importance of labor-related cost categories (that is, those cost categories that are labor-intensive and vary with the local labor market) in the input price index. In the SNF PPS final rule for FY 2022 (86 FR 42437), we finalized a proposal to revise the labor-related share to reflect the relative importance of the 2018-based SNF market basket cost weights for the following cost categories: Wages and Salaries; Employee Benefits; Professional Fees: Labor-Related; Administrative and Facilities Support services; Installation, Maintenance, and Repair Services; All Other: Labor-Related Services; and a proportion of Capital-Related expenses. The methodology for calculating the labor-related portion beginning in FY 2022 is discussed in detail in the FY 2022 SNF PPS final rule (86 FR 42461 through 42463).

We calculate the labor-related relative importance from the SNF market basket, and it approximates the labor-related portion of the total costs after taking into account historical and projected price changes between the base year and FY 2024. The price proxies that move the different cost categories in the market basket do not necessarily change at the same rate, and the relative importance captures these changes. Accordingly, the relative importance figure more closely reflects the cost share weights for FY 2024 than the base year weights from the SNF market basket. We calculate the labor-related relative importance for FY 2024 in four steps. First, we compute the FY 2024 price index level for the total market basket and each cost category of the market basket. Second, we calculate a ratio for each cost category by dividing the FY 2024 price index level for that cost category by the total market basket price index level. Third, we determine the FY 2024 relative importance for each cost category by multiplying this ratio by the base year (2018) weight. Finally, we add the FY 2024 relative importance for each of the labor-related cost categories (Wages and Salaries; Employee Benefits; Professional Fees: Labor-Related; Administrative and Facilities Support Services; Installation, Maintenance, and Repair Services; All Other: Labor-Related Services; and a portion of Capital-Related expenses) to produce the FY 2024 labor-related relative importance.

Table 7 summarizes the proposed labor-related share for FY 2024, based on IGI's fourth quarter 2022 forecast of the 2018-based SNF market basket, compared to the labor-related share that was used for the FY 2023 SNF PPS final rule.

Table 7—Labor-Related Share, FY 2023 and FY 2024

	Relative importance, labor-related share, FY 2023 22:2 forecast 1	Proposed relative importance, labor-related share, FY 2024 22:4 forecast 2
Wages and salaries	51.9	52.2
Employee benefits	9.5	9.5
Professional fees: Labor-related	3.5	3.4
Administrative & facilities support services	0.6	0.6
Installation, maintenance & repair services	0.4	0.4
All other: Labor-related services	2.0	2.0
Capital-related (.391)	2.9	2.9
Total	70.8	71.0
1  Published in the Federal Register ; Based on the second quarter 2022 IHS Global Inc. forecast of the 2018-based SNF market basket.
2  Based on the fourth quarter 2022 IHS Global Inc. forecast of the 2018-based SNF market basket.

To calculate the labor portion of the case-mix adjusted per diem rate, we would multiply the total case-mix adjusted per diem rate, which is the sum of all five case-mix adjusted components into which a patient classifies, and the non-case-mix component rate, by the FY 2024 labor-related share percentage provided in Table 7. The remaining portion of the rate would be the non-labor portion. Under the previous RUG–IV model, we included tables which provided the case-mix adjusted RUG–IV rates, by RUG–IV group, broken out by total rate, labor portion and non-labor portion, such as Table 9 of the FY 2019 SNF PPS final rule (83 FR 39175). However, as we discussed in the FY 2020 final rule (84 FR 38738), under PDPM, as the total rate is calculated as a combination of six different component rates, five of which are case-mix adjusted, and given the sheer volume of possible combinations of these five case-mix adjusted components, it is not feasible to provide tables similar to those that existed in the prior rulemaking.

Therefore, to aid interested parties in understanding the effect of the wage index on the calculation of the SNF per diem rate, we have included a hypothetical rate calculation in Table 9.

Section 1888(e)(4)(G)(ii) of the Act also requires that we apply this wage index in a manner that does not result in aggregate payments under the SNF PPS that are greater or less than would otherwise be made if the wage adjustment had not been made. For FY 2024 (Federal rates effective October 1, 2023), we apply an adjustment to fulfill the budget neutrality requirement. We meet this requirement by multiplying each of the components of the unadjusted Federal rates by a budget neutrality factor, equal to the ratio of the weighted average wage adjustment factor for FY 2023 to the weighted average wage adjustment factor for FY 2024. For this calculation, we would use the same FY 2022 claims utilization data for both the numerator and denominator of this ratio. We define the wage adjustment factor used in this calculation as the labor portion of the rate component multiplied by the wage index plus the non-labor portion of the rate component. The proposed budget neutrality factor for FY 2024 is 0.9998.

We note that if more recent data become available (for example, revised wage data), we would use such data, as appropriate, to determine the wage index budget neutrality factor in the SNF PPS final rule.

We invite public comment on the proposed SNF wage adjustment for FY 2024.

E. SNF Value-Based Purchasing Program

Beginning with payment for services furnished on October 1, 2018, section 1888(h) of the Act requires the Secretary to reduce the adjusted Federal per diem rate determined under section 1888(e)(4)(G) of the Act otherwise applicable to a SNF for services furnished during a fiscal year by 2 percent, and to adjust the resulting rate for a SNF by the value-based incentive payment amount earned by the SNF based on the SNF's performance score for that fiscal year under the SNF VBP Program. To implement these requirements, we finalized in the FY 2019 SNF PPS final rule the addition of § 413.337(f) to our regulations (83 FR 39178).

Please see section VII. of this proposed rule for further discussion of our proposed updates to the SNF VBP Program.

F. Adjusted Rate Computation Example

Tables 8 through 10 provide examples generally illustrating payment calculations during FY 2024 under PDPM for a hypothetical 30-day SNF stay, involving the hypothetical SNF XYZ, located in Frederick, MD (Urban CBSA 23224), for a hypothetical patient who is classified into such groups that the patient's HIPPS code is NHNC1. Table 8 shows the adjustments made to the Federal per diem rates (prior to application of any adjustments under the SNF VBP Program as discussed previously and taking into account the second phase of the parity adjustment recalibration discussed in section III.C. of this proposed rule) to compute the provider's case-mix adjusted per diem rate for FY 2024, based on the patient's PDPM classification, as well as how the variable per diem (VPD) adjustment factor affects calculation of the per diem rate for a given day of the stay. Table 9 shows the adjustments made to the case-mix adjusted per diem rate from Table 8 to account for the provider's wage index. The wage index used in this example is based on the FY 2024 SNF PPS wage index that appears in Table A available on the CMS website at http://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​SNFPPS/​WageIndex.html. Finally, Table 10 provides the case-mix and wage index adjusted per-diem rate for this patient for each day of the 30-day stay, as well as the total payment for this stay. Table 10 also includes the VPD adjustment factors for each day of the patient's stay, to clarify why the patient's per diem rate changes for certain days of the stay. As illustrated in Table 10, SNF XYZ's total PPS payment for this particular patient's stay would equal $21,677.34.

Table 8—PDPM Case-Mix Adjusted Rate Computation Example

Per diem rate calculation
Component	Component group	Component rate	VPD adjustment factor	VPD adj. rate
PT	N	$98.11	1.00	$98.11
OT	N	92.63	1.00	92.63
SLP	H	70.63	1.00	70.63
Nursing	N	179.56	1.00	179.56
NTA	C	160.36	3.00	481.08
Non-Case-Mix		109.39		109.39
Total PDPM Case-Mix Adj. Per Diem				1,031.40

Table 9—Wage Index Adjusted Rate Computation Example

PDPM wage index adjustment calculation
HIPPS code	PDPM case-mix adjusted per diem	Labor portion	Wage index	Wage index adjusted rate	Non-labor portion	Total case mix and wage index adj. rate
NHNC1	$1,031.40	$732.29	0.9648	$706.51	$299.11	$1,005.62

Table 10—Adjusted Rate Computation Example

Day of stay	NTA VPD adjustment factor	PT/OT VPD adjustment factor	Case mix and wage index adjusted per diem rate
1	3.0	1.0	$1,005.62
2	3.0	1.0	1,005.62
3	3.0	1.0	1,005.62
4	1.0	1.0	692.92
5	1.0	1.0	692.92
6	1.0	1.0	692.92
7	1.0	1.0	692.92
8	1.0	1.0	692.92
9	1.0	1.0	692.92
10	1.0	1.0	692.92
11	1.0	1.0	692.92
12	1.0	1.0	692.92
13	1.0	1.0	692.92
14	1.0	1.0	692.92
15	1.0	1.0	692.92
16	1.0	1.0	692.92
17	1.0	1.0	692.92
18	1.0	1.0	692.92
19	1.0	1.0	692.92
20	1.0	1.0	692.92
21	1.0	0.98	689.20
22	1.0	0.98	689.20
23	1.0	0.98	689.20
24	1.0	0.98	689.20
25	1.0	0.98	689.20
26	1.0	0.98	689.20
27	1.0	0.98	689.20
28	1.0	0.96	685.48
29	1.0	0.96	685.48
30	1.0	0.96	685.48
Total Payment			21,677.34

IV. Additional Aspects of the SNF PPS

A. SNF Level of Care—Administrative Presumption

The establishment of the SNF PPS did not change Medicare's fundamental requirements for SNF coverage. However, because the case-mix classification is based, in part, on the beneficiary's need for skilled nursing care and therapy, we have attempted, where possible, to coordinate claims review procedures with the existing resident assessment process and case-mix classification system discussed in section III.C. of this proposed rule. This approach includes an administrative presumption that utilizes a beneficiary's correct assignment, at the outset of the SNF stay, of one of the case-mix classifiers designated for this purpose to assist in making certain SNF level of care determinations.

In accordance with § 413.345, we include in each update of the Federal payment rates in the Federal Register a discussion of the resident classification system that provides the basis for case-mix adjustment. We also designate those specific classifiers under the case-mix classification system that represent the required SNF level of care, as provided in 42 CFR 409.30. This designation reflects an administrative presumption that those beneficiaries who are correctly assigned one of the designated case-mix classifiers on the initial Medicare assessment are automatically classified as meeting the SNF level of care definition up to and including the assessment reference date (ARD) for that assessment.

A beneficiary who does not qualify for the presumption is not automatically classified as either meeting or not meeting the level of care definition, but instead receives an individual determination on this point using the existing administrative criteria. This presumption recognizes the strong likelihood that those beneficiaries who are correctly assigned one of the designated case-mix classifiers during the immediate post-hospital period would require a covered level of care, which would be less likely for other beneficiaries.

In the July 30, 1999 final rule (64 FR 41670), we indicated that we would announce any changes to the guidelines for Medicare level of care determinations related to modifications in the case-mix classification structure. The FY 2018 final rule (82 FR 36544) further specified that we would henceforth disseminate the standard description of the administrative presumption's designated groups via the SNF PPS website at https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​SNFPPS/​index.html (where such designations appear in the paragraph entitled “Case Mix Adjustment”), and would publish such designations in rulemaking only to the extent that we actually intend to propose changes in them. Under that approach, the set of case-mix classifiers designated for this purpose under PDPM was finalized in the FY 2019 SNF PPS final rule (83 FR 39253) and is posted on the SNF PPS website ( https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​SNFPPS/​index.html), in the paragraph entitled “Case Mix Adjustment.”

However, we note that this administrative presumption policy does not supersede the SNF's responsibility to ensure that its decisions relating to level of care are appropriate and timely, including a review to confirm that any services prompting the assignment of one of the designated case-mix classifiers (which, in turn, serves to trigger the administrative presumption) are themselves medically necessary. As we explained in the FY 2000 SNF PPS final rule (64 FR 41667), the administrative presumption is itself rebuttable in those individual cases in which the services actually received by the resident do not meet the basic statutory criterion of being reasonable and necessary to diagnose or treat a beneficiary's condition (according to section 1862(a)(1) of the Act). Accordingly, the presumption would not apply, for example, in those situations where the sole classifier that triggers the presumption is itself assigned through the receipt of services that are subsequently determined to be not reasonable and necessary. Moreover, we want to stress the importance of careful monitoring for changes in each patient's condition to determine the continuing need for Part A SNF benefits after the ARD of the initial Medicare assessment.

B. Consolidated Billing

Sections 1842(b)(6)(E) and 1862(a)(18) of the Act (as added by section 4432(b) of the BBA 1997) require a SNF to submit consolidated Medicare bills to its Medicare Administrative Contractor (MAC) for almost all of the services that its residents receive during the course of a covered Part A stay. In addition, section 1862(a)(18) of the Act places the responsibility with the SNF for billing Medicare for physical therapy, occupational therapy, and speech-language pathology services that the resident receives during a noncovered stay. Section 1888(e)(2)(A) of the Act excludes a small list of services from the consolidated billing provision (primarily those services furnished by physicians and certain other types of practitioners), which remain separately billable under Part B when furnished to a SNF's Part A resident. These excluded service categories are discussed in greater detail in section V.B.2. of the May 12, 1998 interim final rule (63 FR 26295 through 26297).

Effective with services furnished on or after January 1, 2024, section 4121(a)(4) of the Consolidated Appropriations Act, 2023 (CAA 2023) added marriage and family therapists and mental health counselors to the list of practitioners at section 1888(e)(2)(A)(ii) of the Act whose services are excluded from the consolidated billing provision. We note that there are no rate adjustments required to the per diem to offset these exclusions, as payments for services made under section 1888(e)(2)(A)(ii) of the Act are not specified under the requirement at section 1888(e)(4)(G)(iii) of the Act as services for which the Secretary must “provide for an appropriate proportional reduction . . . equal to the aggregate increase in payments attributable to the exclusion”. See section IV.D. of this proposed rule for a discussion of the proposed regulatory updates implementing this change.

A detailed discussion of the legislative history of the consolidated billing provision is available on the SNF PPS website at https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​SNFPPS/​Downloads/​Legislative_​History_​2018-10-01.pdf. In particular, section 103 of the Medicare, Medicaid, and SCHIP Balanced Budget Refinement Act of 1999 (BBRA 1999) (Pub. L. 106–113, enacted November 29, 1999) amended section 1888(e)(2)(A)(iii) of the Act by further excluding a number of individual high-cost, low probability services, identified by HCPCS codes, within several broader categories (chemotherapy items, chemotherapy administration services, radioisotope services, and customized prosthetic devices) that otherwise remained subject to the provision. We discuss this BBRA 1999 amendment in greater detail in the SNF PPS proposed and final rules for FY 2001 (65 FR 19231 through 19232, April 10, 2000, and 65 FR 46790 through 46795, July 31, 2000), as well as in Program Memorandum AB–00–18 (Change Request #1070), issued March 2000, which is available online at www.cms.gov/​transmittals/​downloads/​ab001860.pdf.

As explained in the FY 2001 proposed rule (65 FR 19232), the amendments enacted in section 103 of the BBRA 1999 not only identified for exclusion from this provision a number of particular service codes within four specified categories (that is, chemotherapy items, chemotherapy administration services, radioisotope services, and customized prosthetic devices), but also gave the Secretary the authority to designate additional, individual services for exclusion within each of these four specified service categories. In the proposed rule for FY 2001, we also noted that the BBRA 1999 Conference report (H.R. Conf. Rep. No. 106–479 at 854 (1999)) characterizes the individual services that this legislation targets for exclusion as high-cost, low probability events that could have devastating financial impacts because their costs far exceed the payment SNFs receive under the PPS. According to the conferees, section 103(a) of the BBRA 1999 is an attempt to exclude from the PPS certain services and costly items that are provided infrequently in SNFs. By contrast, the amendments enacted in section 103 of the BBRA 1999 do not designate for exclusion any of the remaining services within those four categories (thus, leaving all of those services subject to SNF consolidated billing), because they are relatively inexpensive and are furnished routinely in SNFs.

As we further explained in the final rule for FY 2001 (65 FR 46790), and as is consistent with our longstanding policy, any additional service codes that we might designate for exclusion under our discretionary authority must meet the same statutory criteria used in identifying the original codes excluded from consolidated billing under section 103(a) of the BBRA 1999: they must fall within one of the four service categories specified in the BBRA 1999; and they also must meet the same standards of high cost and low probability in the SNF setting, as discussed in the BBRA 1999 Conference report. Accordingly, we characterized this statutory authority to identify additional service codes for exclusion as essentially affording the flexibility to revise the list of excluded codes in response to changes of major significance that may occur over time (for example, the development of new medical technologies or other advances in the state of medical practice) (65 FR 46791).

Effective with items and services furnished on or after October 1, 2021, section 134 in Division CC of the CAA 2021 established an additional category of excluded codes in section 1888(e)(2)(A)(iii)(VI) of the Act, for certain blood clotting factors for the treatment of patients with hemophilia and other bleeding disorders along with items and services related to the furnishing of such factors under section 1842(o)(5)(C) of the Act. Like the provisions enacted in the BBRA 1999, section 1888(e)(2)(A)(iii)(VI) of the Act gives the Secretary the authority to designate additional items and services for exclusion within the category of items and services related to blood clotting factors, as described in that section. Finally, as noted previously in this proposed rule, section 4121(a)(4) CAA 2023 amended section 1888(e)(2)(A)(ii) of the Act to exclude marriage and family therapist services and mental health counselor services from consolidated billing effective January 1, 2024.

In this proposed rule, we specifically invite public comments identifying HCPCS codes in any of these five service categories (chemotherapy items, chemotherapy administration services, radioisotope services, customized prosthetic devices, and blood clotting factors) representing recent medical advances that might meet our criteria for exclusion from SNF consolidated billing. We may consider excluding a particular service if it meets our criteria for exclusion as specified previously. We request that commenters identify in their comments the specific HCPCS code that is associated with the service in question, as well as their rationale for requesting that the identified HCPCS code(s) be excluded.

We note that the original BBRA amendment and the CAA 2021 identified a set of excluded items and services by means of specifying individual HCPCS codes within the designated categories that were in effect as of a particular date (in the case of the BBRA 1999, July 1, 1999, and in the case of the CAA 2021, July 1, 2020), as subsequently modified by the Secretary. In addition, as noted in this section of the preamble, the statute (sections 1888(e)(2)(A)(iii)(II) through (VI) of the Act) gives the Secretary authority to identify additional items and services for exclusion within the five specified categories of items and services described in the statute, which are also designated by HCPCS code. Designating the excluded services in this manner makes it possible for us to utilize program issuances as the vehicle for accomplishing routine updates to the excluded codes to reflect any minor revisions that might subsequently occur in the coding system itself, such as the assignment of a different code number to a service already designated as excluded, or the creation of a new code for a type of service that falls within one of the established exclusion categories and meets our criteria for exclusion.

Accordingly, in the event that we identify through the current rulemaking cycle any new services that would actually represent a substantive change in the scope of the exclusions from SNF consolidated billing, we would identify these additional excluded services by means of the HCPCS codes that are in effect as of a specific date (in this case, October 1, 2023). By making any new exclusions in this manner, we could similarly accomplish routine future updates of these additional codes through the issuance of program instructions. The latest list of excluded codes can be found on the SNF Consolidated Billing website at https://www.cms.gov/​Medicare/​Billing/​SNFConsolidatedBilling.

C. Payment for SNF-Level Swing-Bed Services

Section 1883 of the Act permits certain small, rural hospitals to enter into a Medicare swing-bed agreement, under which the hospital can use its beds to provide either acute- or SNF-level care, as needed. For critical access hospitals (CAHs), Part A pays on a reasonable cost basis for SNF-level services furnished under a swing-bed agreement. However, in accordance with section 1888(e)(7) of the Act, SNF-level services furnished by non-CAH rural hospitals are paid under the SNF PPS, effective with cost reporting periods beginning on or after July 1, 2002. As explained in the FY 2002 final rule (66 FR 39562), this effective date is consistent with the statutory provision to integrate swing-bed rural hospitals into the SNF PPS by the end of the transition period, June 30, 2002.

Accordingly, all non-CAH swing-bed rural hospitals have now come under the SNF PPS. Therefore, all rates and wage indexes outlined in earlier sections of this proposed rule for the SNF PPS also apply to all non-CAH swing-bed rural hospitals. As finalized in the FY 2010 SNF PPS final rule (74 FR 40356 through 40357), effective October 1, 2010, non-CAH swing-bed rural hospitals are required to complete an MDS 3.0 swing-bed assessment which is limited to the required demographic, payment, and quality items. As discussed in the FY 2019 SNF PPS final rule (83 FR 39235), revisions were made to the swing bed assessment to support implementation of PDPM, effective October 1, 2019. A discussion of the assessment schedule and the MDS effective beginning FY 2020 appears in the FY 2019 SNF PPS final rule (83 FR 39229 through 39237). The latest changes in the MDS for swing-bed rural hospitals appear on the SNF PPS website at https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​SNFPPS/​index.html.

D. Revisions to the Regulation Text

We propose to make the following revisions in the regulation text. To reflect the recently-enacted exclusion of marriage and family therapist services and mental health counselor services from SNF consolidated billing at section 1888(e)(2)(A)(ii) of the Act (as discussed in section IV.B of this proposed rule), we propose to redesignate current § 411.15(p)(2)(vi) through (xviii) as §§ 411.15(p)(2)(viii) through (xx), respectively. In addition, we propose to redesignate § 489.20(s)(6) through (18) as § 489.20(s)(8) through (20), respectively. We also propose to add new regulation text at §§ 411.15(p)(2)(vi) and (vii) and 489.20(s)(6) and (7). Specifically, proposed new §§ 411.15(p)(2)(vi) and 489.20(s)(6) would reflect the exclusion of services performed by a marriage and family therapist, as defined in section 1861(lll)(2) of the Act. Proposed new §§ 411.15(p)(2)(vii) and 489.20(s)(7) would reflect the exclusion of services performed by a mental health counselor, as defined in section 1861(lll)(4) of the Act.

V. Other SNF PPS Issues

A. Technical Updates to PDPM ICD–10 Mappings

1. Background

In the FY 2019 SNF PPS final rule (83 FR 39162), we finalized the implementation of the Patient Driven Payment Model (PDPM), effective October 1, 2019. The PDPM utilizes the International Classification of Diseases, 10th Revision, Clinical Modification (ICD–10–CM, hereafter referred to as ICD–10) codes in several ways, including using the patient's primary diagnosis to assign patients to clinical categories under several PDPM components, specifically the PT, OT, SLP and NTA components. While other ICD–10 codes may be reported as secondary diagnoses and designated as additional comorbidities, the PDPM does not use secondary diagnoses to assign patients to clinical categories. The ICD–10 code to clinical category mapping used under PDPM (hereafter referred to as PDPM ICD–10 code mapping) are available on the CMS website at https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​SNFPPS/​PDPM.

In the FY 2020 SNF PPS final rule (84 FR 38750), we outlined the process by which we maintain and update the PDPM ICD–10 code mapping, as well as the SNF Grouper software and other such products related to patient classification and billing, to ensure that they reflect the most up to date codes. Beginning with the updates for FY 2020, we apply nonsubstantive changes to the PDPM ICD–10 code mapping through a subregulatory process consisting of posting the updated PDPM ICD–10 code mapping on the CMS website at https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​SNFPPS/​PDPM. Such nonsubstantive changes are limited to those specific changes that are necessary to maintain consistency with the most current PDPM ICD–10 code mapping.

On the other hand, substantive changes that go beyond the intention of maintaining consistency with the most current PDPM ICD–10 code mapping, such as changes to the assignment of a code to a clinical category or comorbidity list, will be proposed through notice and comment rulemaking because they are changes that affect policy. We note that, in the case of any diagnoses that are either currently mapped to Return to Provider or that we are proposing to classify into this category, this is not intended to reflect any judgment on the importance of recognizing and treating these conditions. Rather, we believe that there are more specific or appropriate diagnoses that would better serve as the primary diagnosis for a Part–A covered SNF stay.

2. Proposed Clinical Category Changes for New ICD–10 Codes for FY 2023

Each year, we review the clinical category assigned to new ICD–10 diagnosis codes and propose changing the assignment to another clinical category if warranted. This year, we are proposing changing the clinical category assignment for the following five new ICD–10 codes that were effective on October 1, 2022:

• D75.84 Other platelet-activating anti-platelet factor 4 (PF4) disorders is mapped to the clinical category of Return to Provider. Patients with anti-PF4 disorders have blood clotting disorders. Examples of disorders to be classified with D75.84 are spontaneous heparin-induced thrombocytopenia (without heparin exposure), thrombosis with thrombocytopenia syndrome, and vaccine-induced thrombotic thrombocytopenia. Due to the similarity of this code to other anti-PF4 disorders, we propose to change the assignment to Medical Management.

• F43.81 Prolonged grief disorder and F43.89 Other reactions to severe stress are mapped to the clinical category of Medical Management. However, while we believe that SNFs serve an important role in providing services to those beneficiaries suffering from mental illness, the SNF setting is not the setting that would be most beneficial to treat a patient for whom these diagnoses are coded as the patient's primary diagnosis. For this reason, we propose changing the clinical category of both codes to Return to Provider. We would encourage providers to continue reporting these codes as secondary diagnoses, to ensure that we are able to identify these patients and that they are receiving appropriate care.

• G90.A Postural orthostatic tachycardia syndrome (POTS) is mapped to the clinical category of Acute Neurologic. POTS is a type of orthostatic intolerance that causes the heart to beat faster than normal when transitioning from sitting or lying down to standing up, causing changes in blood pressure, increase in heart rate, and lightheadedness. The treatment for POTS involves hydration, physical therapy, and vasoconstrictor medications, which are also treatments for codes such as E86.0 Dehydration and E86.1 Hypovolemia that are mapped to the Medical Management category. Since the medical interventions are similar, we propose changing the assignment for POTS to Medical Management.

• K76.82 Hepatic encephalopathy is mapped to the clinical category of Return to Provider. Hepatic encephalopathy is a condition resulting from severe liver disease, where toxins build up in the blood that can affect brain function and lead to a change in medical status. Prior to the development of this code, multiple codes were used to characterize this condition such as K76.6 Portal hypertension, K76.7 Hepatorenal syndrome, and K76.89 Other unspecified diseases of liver, which are mapped to the Medical Management category. Since these codes describe similar liver conditions, we propose to change the assignment to Medical Management.

We invite comments on the proposed substantive changes to the PDPM ICD–10 code mapping discussed in this section, as well as comments on additional substantive and nonsubstantive changes that commenters believe are necessary.

3. Proposed Clinical Category Changes for Unspecified Substance Use Disorder Codes

Effective with stays beginning on and after October 1, 2022, ICD–10 diagnosis codes F10.90 Alcohol use, unspecified, uncomplicated, F10.91 Alcohol use, unspecified, in remission, F11.91 Opioid use, unspecified, in remission, F12.91 Cannabis use, unspecified, in remission, F13.91 Sedative, hypnotic or anxiolytic use, unspecified, in remission, and F14.91 Cocaine use, unspecified, in remission went into effect and were mapped to the clinical category of Medical Management. We reviewed these 6 unspecified substance use disorder (SUD) codes and propose changing the assignment from Medical Management to Return to Provider because the codes are not specific as to if they refer to abuse or dependence, and there are other specific codes available for each of these conditions that would be more appropriate as a primary diagnosis for a SNF stay. For example, diagnosis code F10.90 Alcohol use, unspecified, uncomplicated is not specific as to whether the patient has alcohol abuse or alcohol dependence. There are more specific codes that could be used instead, such as F10.10 Alcohol abuse, uncomplicated or F10.20 Alcohol dependence, uncomplicated, that may serve as the primary diagnosis for a SNF stay and are appropriately mapped to the clinical category of Medical Management.

Moreover, we believe that increased accuracy of coding primary diagnoses aligns with CMS' broader efforts to ensure better quality of care. Therefore, we reviewed all 458 ICD–10 SUD codes from code categories F10 to F19 and propose reassigning 162 additional unspecified SUD codes to Return to Provider from Medical Management because the codes are not specific as to if they refer to abuse or dependence. We would note that this policy change would not affect a large number of SNF stays. Our data from FY 2021 show that the 162 unspecified SUD codes were used as primary diagnoses for only 323 SNF stays (0.02 percent) and as secondary diagnoses for 9,537 SNF stays (0.54 percent). The purpose of enacting this policy is to continue an ongoing effort to refine the PDPM ICD–10 code mapping each year to ensure more accurate coding of primary diagnoses. We would encourage providers to continue reporting these codes as secondary diagnoses, to ensure that we are able to identify these patients and that they are receiving appropriate care.

Table 1, Proposed Clinical Category Changes for Unspecified Substance Use Disorder Codes, which lists all 168 codes included in this proposal, is available on the CMS website at https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​SNFPPS/​PDPM. We invite comments on the proposed substantive changes to the PDPM ICD–10 code mapping discussed in this section, as well as comments on additional substantive and nonsubstantive changes that commenters believe are necessary.

3. Proposed Clinical Category Changes for Certain Subcategory Fracture Codes

Each year, we invite comments on additional substantive and nonsubstantive changes that commenters believe are necessary to the PDPM ICD–10 code mapping. In the FY 2023 final rule (87 FR 47524), we described how one commenter recommended that CMS consider revising the PDPM ICD–10 code mapping to reclassify certain subcategory S42.2—humeral fracture codes. The commenter highlighted that certain encounter codes for humeral fractures, such as those ending in the 7th character of A for an initial encounter for fracture, are permitted the option to be mapped to a surgical clinical category, denoted on the PDPM ICD–10 code mapping as May be Eligible for One of the Two Orthopedic Surgery Categories (that is, major joint replacement or spinal surgery, or orthopedic surgery) if the resident had a major procedure during the prior inpatient stay that impacts the SNF care plan. However, the commenter noted that other encounter codes within the same code family, such as those ending in the 7th character of D for subsequent encounter for fracture with routine healing, are mapped to the Non-Surgical Orthopedic/Musculoskeletal without the surgical option. The commenter requested that we review all subcategory S42.2—fracture codes to ensure that the appropriate surgical clinical category could be selected for joint aftercare. Since then, the commenter has also contacted CMS with a similar suggestion for M84.552D Pathological fracture in neoplastic disease, left femur, subsequent encounter for fracture with routine healing.

We have since reviewed the suggested code subcategories to determine the most efficient manner for addressing this discrepancy. We propose adding the surgical option that allows 45 subcategory S42.2—codes for displaced fractures to be eligible for one of two orthopedic surgery categories. However, we note that this proposal does not extend to subcategory S42.2—codes for nondisplaced fractures, which typically do not require surgery. We also propose adding the surgical option to subcategory 46 M84.5—codes for pathological fractures to certain major weight-bearing bones to be eligible for one of two orthopedic surgery categories.

Table 2, Proposed Clinical Category Changes for S42.2 and M84.5 Fracture Codes, which lists all 91 codes included in this proposal, is available on the CMS website at https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​SNFPPS/​PDPM. We invite comments on the proposed substantive changes to the PDPM ICD–10 code mapping discussed in this section, as well as comments on additional substantive and nonsubstantive changes that commenters believe are necessary.

4. Proposed Clinical Category Changes for Unacceptable Principal Diagnosis Codes

In the FY 2023 final rule (87 FR 47525) we described how several commenters referred to instances when SNF claims were denied for including a primary diagnosis code that is listed on the PDPM ICD–10 code mapping as a valid code, but that is not accepted by some Medicare Administrative Contractors (MACs) that use the Hospital Inpatient Prospective Payment System (IPPS) Medicare Code Editor (MCE) lists when evaluating the primary diagnosis codes listed on SNF claims. In the IPPS, a patient's diagnosis is entered into the Medicare claims processing systems and subjected to a series of automated screens called the MCE. The MCE lists are designed to identify cases that require further review before classification into an MS–DRG. We note that all codes on the MCE lists are able to be reported; however, a code edit may be triggered that the MAC may either choose to bypass or return to the provider to resubmit. Updates to the MCE lists are proposed on an annual basis and discussed through IPPS rulemaking when new codes or policies involving existing codes are introduced.

Commenters recommended that CMS seek to align the PDPM ICD–10 code mapping with the MCE in treating diagnoses that are Return to Provider, specifically referring to the Unacceptable Principal Diagnosis edit code list in the Definition of Medicare Code Edits, which is available on the CMS website at https://www.cms.gov/​medicare/​medicare-fee-for-service-payment/​acuteinpatientpps/​ms-drg-classifications-and-software. The Unacceptable Principal Diagnosis edit code list contains selected codes that describe a circumstance that influences an individual's health status but not a current illness or injury, or codes that are not specific manifestations but may be due to an underlying cause, and which are considered unacceptable as a principal diagnosis.

We have identified 95 codes from the MCE Unacceptable Principal Diagnosis edit code list that are mapped to a valid clinical category on the PDPM ICD–10 code mapping, and that were coded as primary diagnoses for 14,808 SNF stays (0.84 percent) in FY 2021. Table 3, Proposed Clinical Category Changes for Unacceptable Principal Diagnosis Codes, which lists all 95 codes included in this proposal, is available on the CMS website at https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​SNFPPS/​PDPM. As stated previously in this section of this proposed rule, we note that reporting these codes as a primary diagnosis for a SNF stay may trigger an edit that the MAC may either choose to bypass or return to the provider to resubmit, and therefore not all of these 14,808 stays were denied by the MACs.

After clinical review, we concur that these 95 codes listed in Table 3 on the CMS website should be assigned to Return to Provider. For the diagnosis codes listed in Table 3 on the CMS website that are from the category B95 to B97 range and contain the suffix “as the cause of diseases classified elsewhere”, the ICD–10 coding convention for such etiology and manifestation codes, where certain conditions have both an underlying etiology and multiple body system manifestations due to the underlying etiology, dictates that the underlying condition should be sequenced first, followed by the manifestation. The ICD–10 coding guidelines also state that codes from subcategory G92.0— Immune effector cell-associated neurotoxicity syndrome, subcategory R40.2— Coma scale, and subcategory S06.A— Traumatic brain injury should only be reported as secondary diagnoses, as there are more specific codes that should be sequenced first. Additionally, the ICD–10 coding guidelines state that diagnosis codes in categories Z90 and Z98 are status codes, indicating that a patient is either a carrier of a disease or has the sequelae or residual of a past disease or condition, and are not reasons for a patient to be admitted to a SNF. Lastly, our clinicians determined that diagnosis code Z43.9 Encounter for attention to unspecified artificial opening should be assigned to the clinical category Return to Provider because there are more specific codes that identify the site for the artificial opening.

Therefore, we propose to reassign the 95 codes listed in Table 3 on the CMS website from the current default clinical category on the PDPM ICD–10 code mapping to Return to Provider. We also propose to make future updates to align the PDPM ICD–10 code mapping with the MCE Unacceptable Principal Diagnosis edit code list on a subregulatory basis going forward. Moreover, we are soliciting comment on aligning with the MCE Manifestation codes not allowed as principal diagnosis edit code list, which contains diagnosis codes that are the manifestation of an underlying disease, not the disease itself, and therefore should not be used as a principal diagnosis, and the Questionable admission codes edit code list, which contains diagnoses codes that are not usually sufficient justification for admission to an acute care hospital. While these MCE lists were not mentioned by commenters, we believe that some MACs may be applying these edit lists to SNF claims and this could cause continued differences between the PDPM ICD–10 code mapping and the IPPS MCE. If finalized, we also propose to make future updates to align the PDPM ICD–10 code mapping with the MCE Manifestation codes not allowed as principal diagnosis edit code list and the Questionable admission codes edit code list on a subregulatory basis going forward.

We invite comments on the proposed substantive changes to the PDPM ICD–10 code mapping discussed in this section, as well as comments on additional substantive and nonsubstantive changes that commenters believe are necessary.

VI. Skilled Nursing Facility Quality Reporting Program (SNF QRP)

A. Background and Statutory Authority

The Skilled Nursing Facility Quality Reporting Program (SNF QRP) is authorized by section 1888(e)(6) of the Act, and it applies to freestanding SNFs, SNFs affiliated with acute care facilities, and all non-critical access hospital (CAH) swing-bed rural hospitals. Section 1888(e)(6)(A)(i) of the Act requires the Secretary to reduce by 2 percentage points the annual market basket percentage increase described in section 1888(e)(5)(B)(i) of the Act applicable to a SNF for a fiscal year (FY), after application of section 1888(e)(5)(B)(ii) of the Act (the productivity adjustment) and section 1888(e)(5)(B)(iii) of the Act, in the case of a SNF that does not submit data in accordance with sections 1888(e)(6)(B)(i)(II) and (III) of the Act for that FY. Section 1890A of the Act requires that the Secretary establish and follow a pre-rulemaking process, in coordination with the consensus-based entity (CBE) with a contract under section 1890(a) of the Act, to solicit input from certain groups regarding the selection of quality and efficiency measures for the SNF QRP. We have codified our program requirements in our regulations at 42 CFR part 413.

In this proposed rule, we are proposing to adopt three new measures, remove three existing measures, and modify one existing measure. Second, we are seeking information on principles we could use to select and prioritize SNF QRP quality measures in future years. Third, we are providing an update on our health equity efforts. Fourth, we are proposing several administrative changes, including a change to the SNF QRP data completion thresholds and a data submission method for the proposed CoreQ: Short Stay Discharge questionnaire. Finally, we are proposing to begin public reporting of four measures. These proposals are further specified below.

B. General Considerations Used for the Selection of Measures for the SNF QRP

For a detailed discussion of the considerations we use for the selection of SNF QRP quality, resource use, or other measures, we refer readers to the FY 2016 SNF (PPS) final rule (80 FR 46429 through 46431).

1. Quality Measures Currently Adopted for the FY 2024 SNF QRP

The SNF QRP currently has 16 measures for the FY 2024 program year, which are listed in Table 11. For a discussion of the factors used to evaluate whether a measure should be removed from the SNF QRP, we refer readers to § 413.360(b)(2).

Table 11—Quality Measures Currently Adopted for the FY 2024 SNF QRP

Short name	Measure name & data source
Resident Assessment Instrument Minimum Data Set (Assessment-Based)
Pressure Ulcer/Injury	Changes in Skin Integrity Post-Acute Care: Pressure Ulcer/Injury.
Application of Falls	Application of Percent of Residents Experiencing One or More Falls with Major Injury (Long Stay).
Application of Functional Assessment/Care Plan	Application of Percent of Long-Term Care Hospital (LTCH) Patients with an Admission and Discharge Functional Assessment and a Care Plan That Addresses Function.
Change in Mobility Score	Application of IRF Functional Outcome Measure: Change in Mobility Score for Medical Rehabilitation Patients.
Discharge Mobility Score	Application of IRF Functional Outcome Measure: Discharge Mobility Score for Medical Rehabilitation Patients.
Change in Self-Care Score	Application of the IRF Functional Outcome Measure: Change in Self-Care Score for Medical Rehabilitation Patients.
Discharge Self-Care Score	Application of IRF Functional Outcome Measure: Discharge Self-Care Score for Medical Rehabilitation Patients.
DRR	Drug Regimen Review Conducted With Follow-Up for Identified Issues–Post Acute Care (PAC) Skilled Nursing Facility (SNF) Quality Reporting Program (QRP).
TOH-Provider *	Transfer of Health (TOH) Information to the Provider Post-Acute Care (PAC).
TOH-Patient *	Transfer of Health (TOH) Information to the Patient Post-Acute Care (PAC).
Claims-Based
MSPB SNF	Medicare Spending Per Beneficiary (MSPB)—Post Acute Care (PAC) Skilled Nursing Facility (SNF) Quality Reporting Program (QRP).
DTC	Discharge to Community (DTC)—Post Acute Care (PAC) Skilled Nursing Facility (SNF) Quality Reporting Program (QRP).
PPR	Potentially Preventable 30-Day Post-Discharge Readmission Measure for Skilled Nursing Facility (SNF) Quality Reporting Program (QRP).
SNF HAI	SNF Healthcare-Associated Infections (HAI) Requiring Hospitalization.
NHSN
HCP COVID–19 Vaccine	COVID–19 Vaccination Coverage among Healthcare Personnel (HCP).
HCP Influenza Vaccine	Influenza Vaccination Coverage among Healthcare Personnel (HCP).
* In response to the public health emergency (PHE) for the Coronavirus Disease 2019 (COVID–19), we released an Interim Final Rule (85 FR 27595 through 27597) which delayed the compliance date for collection and reporting of the Transfer of Health (TOH) Information measures for at least 2 full fiscal years after the end of the PHE. The compliance date for the collection and reporting of the Transfer of Health Information measures was revised to October 1, 2023 in the FY 2023 SNF PPS final rule (87 FR 47547 through 47551).

C. SNF QRP Quality Measure Proposals

In this proposed rule, we include SNF QRP proposals for the FY 2025, FY 2026, and FY 2027 program years. This proposed rule would add new measures to the SNF QRP as well as remove measures from the SNF QRP. Beginning with the FY 2025 SNF QRP, we are proposing to (1) modify the COVID–19 Vaccination Coverage among Healthcare Personnel (HCP) measure, (2) adopt the Discharge Function Score measure,^[13] which we are specifying under section 1888(e)(6)(B)(i) of the Act, and (3) remove three current measures: (i) the Application of Percent of Long-Term Care Hospital (LTCH) Patients with an Admission and Discharge Functional Assessment and a Care Plan That Addresses Function measure, (ii) the Application of IRF Functional Outcome Measure: Change in Self-Care Score for Medical Rehabilitation Patients measure, and (iii) the Application of IRF Functional Outcome Measure: Change in Mobility Score for Medical Rehabilitation Patients measure.

We are proposing to adopt two new measures beginning with the FY 2026 SNF QRP: (i) the CoreQ: Short Stay Discharge measure which we are specifying under section 1899B(d)(1) of the Act, and (ii) the COVID–19 Vaccine: Percent of Patients/Residents Who Are Up to Date measure, which we are specifying under section 1899B(d)(1) of the Act.

1. SNF QRP Quality Measure Proposals Beginning With the FY 2025 SNF QRP

a. Proposed Modification of the COVID–19 Vaccination Coverage Among Healthcare Personnel (HCP) Measure Beginning With the FY 2025 SNF QRP

(1) Background

On January 31, 2020, the Secretary declared a public health emergency (PHE) for the United States in response to the global outbreak of SARS–CoV–2, a novel (new) coronavirus that causes a disease named “coronavirus disease 2019” (COVID–19).^[14] Subsequently, in the FY 2022 SNF PPS final rule (86 FR 42480 through 42489), we adopted the COVID–19 Vaccination Coverage among Healthcare Personnel (HCP) (HCP COVID–19 Vaccine) measure for the SNF QRP. The HCP COVID–19 Vaccine measure requires each SNF to submit data on the percentage of HCP eligible to work in the SNF for at least one day during the reporting period, excluding persons with contraindications to FDA-authorized or -approved COVID–19 Vaccines, who have received a complete vaccination course against SARS–CoV–2. Since that time, COVID–19 has continued to spread domestically and around the world with more than 102.7 million cases and 1.1 million deaths in the United States as of February 13, 2023.^[15] In recognition of the ongoing significance and complexity of COVID–19, the Secretary has renewed the PHE on April 21, 2020, July 23, 2020, October 2, 2020, January 7, 2021, April 15, 2021, July 19, 2021, October 15, 2021, January 14, 2022, April 12, 2022, July 15, 2022, October 13, 2022, January 11, 2023, and February 9, 2023.^[16] The Department of Health and Human Services (HHS) announced plans to let the PHE expire on May 11, 2023 and stated that the public health response to COVID–19 remains a public health priority with a whole of government approach to combating the virus, including through vaccination efforts.^[17]

In the FY 2022 SNF PPS final rule (86 FR 42480 through 42489) and in the Revised Guidance for Staff Vaccination Requirements,^[18] we stated that vaccination is a critical part of the nation's strategy to effectively counter the spread of COVID–19. We continue to believe it is important to incentivize and track HCP vaccination in SNFs through quality measurement in order to protect HCP, residents, and caregivers, and to help sustain the ability of SNFs to continue serving their communities throughout the PHE and beyond. At the time we issued the FY 2022 SNF PPS final rule, the Food and Drug Administration (FDA) had issued emergency use authorizations (EUAs) for COVID–19 vaccines manufactured by Pfizer-BioNTech,^[19] Moderna,^[20] and Janssen.^[21] The Pfizer-BioNTech vaccine was authorized for ages 12 and older and the Moderna and Janssen vaccines for ages 18 and older. Shortly following the publication of the final rule, on August 23, 2021, the FDA issued an approval for the Pfizer-BioNTech vaccine, marketed as Comirnaty.^[22] The FDA issued approval for the Moderna vaccine, marketed as Spikevax, on January 31, 2022 ^[23] and an EUA for the Novavax vaccine, on July 13, 2022.^[24] The FDA also issued EUAs for single booster doses of the then authorized COVID–19 vaccines. As of November 19, 2021 ^{[25]  [26]  [27]} a single booster dose of each COVID–19 vaccine was authorized for all eligible individuals 18 years of age and older. EUAs were subsequently issued for a second booster dose of the Pfizer-BioNTech and Moderna vaccines in certain populations in March 2022.^[28] FDA first authorized the use of a booster dose of bivalent or “updated” COVID–19 vaccines from Pfizer-BioNTech and Moderna in August 2022.^[29]

(a) Measure Importance

While the impact of COVID–19 vaccines on asymptomatic infection and transmission is not yet fully known, there are now robust data available on COVID–19 vaccine effectiveness across multiple populations against severe illness, hospitalization, and death. Two-dose COVID–19 vaccines from Pfizer-BioNTech and Moderna were found to be 88 percent and 93 percent effective against hospitalization for COVID–19, respectively, over 6 months for adults over age 18 without immunocompromising conditions.^[30] During a SARS–CoV–2 surge in the spring and summer of 2021, 92 percent of COVID–19 hospitalizations and 91 percent of COVID–19-associated deaths were reported among persons not fully vaccinated.^[31] Real-world studies of population-level vaccine effectiveness indicated similarly high rates of efficacy in preventing SARS–CoV–2 infection among frontline workers in multiple industries, with a 90 percent effectiveness in preventing symptomatic and asymptomatic infection from December 2020 through August 2021.^[32] Vaccines have also been highly effective in real-world conditions at preventing COVID–19 in HCP with up to 96 percent efficacy for fully vaccinated HCP, including those at risk for severe infection and those in racial and ethnic groups disproportionately affected by COVID–19.^[33] In the presence of high community prevalence of COVID–19, residents of nursing homes with low staff vaccination coverage had cases of COVID–19 related deaths 195 percent higher than those among residents of nursing homes with high staff vaccination coverage.^[34] Overall, data demonstrate that COVID–19 vaccines are effective and prevent severe disease, hospitalization, and death.

As SARS–CoV–2 persists and evolves, our COVID–19 vaccination strategy must remain responsive. When we adopted the HCP COVID–19 Vaccine measure in the FY 2022 SNF PPS final rule, we stated that the need for booster doses of COVID–19 vaccine had not been established and no additional doses had been recommended (86 FR 42484 through 42485). We also stated that we believed the numerator was sufficiently broad to include potential future boosters as part of a “complete vaccination course” and that the measure was sufficiently specified to address boosters (86 FR 42485). Since we adopted the HCP COVID–19 Vaccine measure in the FY 2022 SNF PPS final rule, new variants of SARS–CoV–2 have emerged around the world and within the United States. Specifically, the Omicron variant (and its related subvariants) is listed as a variant of concern by the Centers for Disease Control and Prevention (CDC) because it spreads more easily than earlier variants.^[35] Vaccine manufacturers have responded to the Omicron variant by developing bivalent COVID–19 vaccines, which include a component of the original virus strain to provide broad protection against COVID–19 and a component of the Omicron variant to provide better protection against COVID–19 caused by the Omicron variant.^[36] These booster doses of the bivalent COVID–19 vaccines have been shown to increase immune response to SARS–CoV–2 variants, including Omicron, particularly in individuals that are more than 6 months removed from receipt of their primary series.^[37] The FDA issued EUAs for booster doses of two bivalent COVID–19 vaccines, one from Pfizer-BioNTech ^[38] and one from Moderna,^[39] and strongly encourages anyone who is eligible to consider receiving a booster dose with a bivalent COVID–19 vaccine to provide better protection against currently circulating variants.^[40] COVID–19 booster doses are associated with a greater reduction in infections among HCP relative to those who only received primary series vaccination, with a rate of breakthrough infections among HCP who received only a two-dose regimen of 21.4 percent compared to a rate of 0.7 percent among boosted HCP.^[41 42]

We believe that vaccination remains the most effective means to prevent the severe consequences of COVID–19, including severe illness, hospitalization, and death. Given the availability of vaccine efficacy data, EUAs issued by the FDA for bivalent boosters, the continued presence of SARS–CoV–2 in the United States, and variance among rates of booster dose vaccination, it is important to update the specifications of the HCP COVID–19 Vaccine measure to reflect recent updates that explicitly specify for HCP to receive primary series and booster vaccine doses in a timely manner. Given the persistent spread of COVID–19, we continue to believe that monitoring and surveillance is important and provides residents, beneficiaries, and their caregivers with information to support informed decision making. Beginning with the FY 2025 SNF QRP, we propose to modify the HCP COVID–19 Vaccine measure to replace the term “complete vaccination course” with the term “up to date” in the HCP vaccination definition. We also propose to update the numerator to specify the time frames within which an HCP is considered up to date with recommended COVID–19 vaccines, including booster doses, beginning with the FY 2025 SNF QRP.

(b) Measure Testing

The CDC conducted beta testing of the modified HCP COVID–19 Vaccine measure by assessing if the collection of information on additional/booster vaccine doses received by HCP was feasible, as information on receipt of booster vaccine doses is required for determining if HCP are up to date with the current COVID–19 vaccination. Feasibility was assessed by calculating the proportion of facilities that reported additional/booster doses of the COVID–19 vaccine. The assessment was conducted in various facility types, including SNFs, using vaccine coverage data for the first quarter of calendar year (CY) 2022 (January–March), which was reported through the CDC's National Healthcare Safety Network (NHSN). Feasibility of reporting additional/booster doses of vaccine is evident by the fact that 99.2 percent of SNFs reported vaccination additional/booster coverage data to the NHSN for the first quarter of 2022.^[43] Additionally, HCP COVID–19 Vaccine measure scores calculated using January 1–March 31, 2022 data had a median of 31.8 percent and an interquartile range of 18.9 to 49.7 percent, indicating a measure performance gap as there are clinically significant differences in booster/additional dose vaccination coverage rates among SNFs.^[44]

(2) Competing and Related Measures

Section 1899B(e)(2)(A) of the Act requires that, absent an exception under section 1899B(e)(2)(B) of the Act, measures specified under section 1899B of the Act be endorsed by a consensus-based entity (CBE) with a contract under section 1890(a). In the case of a specified area or medical topic determined appropriate by the Secretary for which a feasible and practical measure has not been endorsed, section 1899B(e)(2)(B) permits the Secretary to specify a measure that is not so endorsed, as long as due consideration is given to measures that have been endorsed or adopted by a consensus organization identified by the Secretary.

The current version of the HCP COVID–19 Vaccine (“Quarterly Reporting of COVID–19 Vaccination Coverage Among Healthcare Personnel”) measure recently received endorsement by the CBE on July 26, 2022.^[45] However, this measure received endorsement based on its specifications depicted in the FY 2022 SNF PPS final rule (86 FR 42480 through 42489), and does not capture information about whether HCP are up to date with their COVID–19 vaccinations. The proposed modification of this measure utilizes the term up to date in the HCP vaccination definition and updates the numerator to specify the time frames within which an HCP is considered up to date with recommended COVID–19 vaccines, including booster doses. We were unable to identify any CBE-endorsed measures for SNFs that captured information on whether HCP are up to date with their COVID–19 vaccinations, and we found no other feasible and practical measure on this topic.

Therefore, after consideration of other available measures, we find that the exception under section 1899B(e)(2)(B) of the Act applies and are proposing the modified measure, HCP COVID–19 Vaccine, beginning with the FY 2025 SNF QRP. The CDC, the measure developer, is pursuing CBE endorsement for this modified version of the measure.

(3) Measure Applications Partnership (MAP) Review

We refer readers to the FY 2022 SNF PPS final rule (86 FR 42482) for more information on the initial review of the HCP COVID–19 Vaccine measure by the Measure Application Partnership (MAP).

In accordance with section 1890A of the Act, the pre-rulemaking process includes making publicly available a list of quality and efficiency measures, called the Measures Under Consideration (MUC) List, that the Secretary is considering adopting for use in the Medicare program(s), including our quality reporting programs. This allows interested parties to provide recommendations to the Secretary on the measures included on the MUC List. We submitted the updated version of the HCP COVID–19 Vaccine measure on the MUC List entitled “List of Measures under Consideration for December 1, 2022” ^[46] for the 2022–2023 pre-rulemaking cycle for consideration by the MAP. Interested parties submitted four comments to the MAP during the pre-rulemaking process on the proposed modifications of the HCP COVID–19 Vaccine measure. Three commenters noted that it is important that HCP be vaccinated against COVID–19 and supported measurement and reporting as an important strategy to help healthcare organizations assess their performance in achieving high rates of up to date vaccination of their HCP. One of these commenters noted that the measure would provide valuable information to the government as part of its ongoing response to the pandemic. The other two commenters do not believe it should be used in a pay-for-performance program, and one raised concerns of potential unintended consequences, such as frequency of reporting and the potential State regulations with which such a requirement might conflict. One commenter did not support the measure, raising several concerns with the measure, including that the data have never been tested for validity or reliability. Finally, three of the four commenters raised concern about the difficulty of defining up to date for purposes of the modified measure.

Shortly after publication of the MUC List, several MAP workgroups met to provide input on the measure. First, the MAP Health Equity Advisory Group convened on December 6–7, 2022. The MAP Health Equity Advisory Group questioned whether the measure excludes residents with contraindications to FDA authorized or approved COVID–19 vaccines, and whether the measure will be stratified by demographic factors. The measure developer (that is the CDC) confirmed that HCP with contraindications to the vaccines are excluded from the measure denominator, but the measure will not be stratified since the data are submitted at an aggregate rather than an individual level.

The MAP Rural Health Advisory Group met on December 8–9, 2022, during which a few members expressed concerns about data collection burden, given that small rural hospitals may not have employee health software. The measure developer acknowledged the challenge of getting adequate documentation and emphasized their goal is to ensure the measures do not present a burden on the provider. The measure developer also noted that the model used for the HCP COVID–19 Vaccine measure is based on the Influenza Vaccination Coverage among HCP measure (CBE #0431), and it intends to utilize a similar approach to the modified HCP COVID–19 Vaccine measure if vaccination strategy becomes seasonal. The measure developer acknowledged that if COVID–19 becomes seasonal, the measure model could evolve to capture seasonal vaccination.

Next, the MAP Post-Acute Care/Long-Term Care (PAC/LTC) workgroup met on December 12, 2022 and provided input on the on the modification for the HCP COVID–19 Vaccine measure. The MAP PAC/LTC workgroup noted that the previous version of the measure received endorsement from the CBE (CBE #3636),^[47] and that the CDC intends to submit the updated measure for endorsement. The PAC/LTC workgroup voted to support the staff recommendation of conditional support for rulemaking pending testing indicating the measure is reliable and valid, and endorsement by the CBE.

Following the PAC/LTC workgroup meeting, a public comment period was held in which interested parties commented on the PAC/LTC workgroup's preliminary recommendations, and the MAP received three comments. Two supported the update to the measure, one of which strongly supported the vaccination of HCP against COVID–19. Although these commenters supported the measure, one commenter recommended CBE endorsement for the updated measure, and encouraged us to monitor any unintended consequences from the measure. Two commenters noted the challenges associated with the measure's specifications. Specifically, one noted the broad definition of the denominator and another recommended a vaccination exclusion or exception due to religious beliefs. Finally, one commenter raised issues related to the time lag between data collection and public reporting on Care Compare and encouraged us to provide information as to whether the measure is reflecting vaccination rates accurately and encouraging HCP vaccination.

The MAP Coordinating Committee convened on January 24–25, 2023, during which the measure was placed on the consent calendar and received a final recommendation of conditional support for rulemaking pending testing indicating the measure is reliable and valid, and endorsement by the CBE. We refer readers to the final MAP recommendations, titled 2022–2023 MAP Final Recommendations.^[48]

(4) Quality Measure Calculation

The HCP COVID–19 Vaccine measure is a process measure developed by the CDC to track COVID–19 vaccination coverage among HCP in facilities such as SNFs. The HCP COVID–19 Vaccine measure is a process measure and is not risk-adjusted.

The denominator would be the number of HCP eligible to work in the facility for at least one day during the reporting period, excluding persons with contraindications to COVID–19 vaccination that are described by the CDC.^[49] SNFs report the following four categories of HCP to NHSN, and the first three categories are included in the measure denominator:

• Employees: This includes all persons who receive a direct paycheck from the reporting facility (that is, on the facility's payroll), regardless of clinical responsibility or patient contact.

• Licensed independent practitioners (LIPs): This includes physicians (MD, DO), advanced practice nurses, and physician assistants who are affiliated with the reporting facility, but are not directly employed by it (that is, they do not receive a paycheck from the facility), regardless of clinical responsibility or patient contact. Post-residency fellows are also included in this category if they are not on the facility's payroll.

• Adult students/trainees and volunteers: This includes all medical, nursing, or other health professional students, interns, medical residents, or volunteers aged 18 or over who are affiliated with the healthcare facility, but are not directly employed by it (that is, they do not receive a direct paycheck from the facility), regardless of clinical responsibility or patient contact.

• Other contract personnel: Contract personnel are defined as persons providing care, treatment, or services at the facility through a contract who do not fall into any of the above-mentioned denominator categories. This also includes vendors providing care, treatment, or services at the facility who may or may not be paid through a contract. Facilities are required to enter data on other contract personnel for submission in the NHSN application, but data from this category are not included in the HCP COVID–19 Vaccine measure.^[50]

The denominator excludes denominator-eligible individuals with contraindications as defined by the CDC.^[51] We are not proposing any changes to the denominator exclusions.

The numerator would be the cumulative number of HCP in the denominator population who are considered up to date with CDC-recommended COVID–19 vaccines. Providers should refer to the definition of up to date as of the first day of the applicable reporting quarter, which can be found at https://www.cdc.gov/​nhsn/​pdfs/​hps/​covidvax/​UpToDateGuidance-508.pdf. For example, for the proposed updated measure, HCP would be considered up to date during the quarter four of the CY 2022 reporting period for the SNF QRP if they met one of the following criteria:

1. Individuals who received an updated bivalent ^[52] booster dose, or

2a. Individuals who received their last booster dose less than 2 months ago, or

2b. Individuals who completed their primary series ^[53] less than 2 months ago.

We note that for purposes of NHSN surveillance, the CDC used this definition of up to date during quarter 4 2022 surveillance period (September 26, 2022–December 25, 2022).

We refer readers to https://www.cdc.gov/​nhsn/​nqf/​index.html for more details on the measure specifications.

While we are not proposing any changes to the data submission or reporting process for the HCP COVID–19 Vaccine measure, we are proposing that for purposes of meeting FY 2025 SNF QRP compliance, SNFs would report individuals who are up to date beginning in quarter four of CY 2023. Under the data submission and reporting process, SNFs would collect the numerator and denominator for the modified HCP COVID–19 Vaccine measure for at least one self-selected week during each month of the reporting quarter and submit the data to the NHSN Healthcare Personnel Safety (HPS) Component before the quarterly deadline. If a SNF submits more than one week of data in a month, the most recent week's data would be used to calculate the measure. Each quarter, the CDC would calculate a single quarterly HCP COVID–19 vaccination coverage rate for each SNF, which would be calculated by taking the average of the data from the three weekly rates submitted by the SNF for that quarter. Beginning with the FY 2026 SNF QRP, SNFs would be required to submit data for the entire calendar year.

We are also proposing that public reporting of the modified version of the HCP COVID–19 Vaccine measure would begin with the October 2024 Care Compare refresh or as soon as technically feasible.

We invite public comment on our proposal to modify the COVID–19 Vaccination Coverage among Healthcare Personnel (HCP) measure beginning with the FY 2025 SNF QRP.

b. Proposed Adoption of the Discharge Function Score Measure Beginning With the FY 2025 SNF QRP

(1) Background

SNFs provide short-term skilled nursing care and rehabilitation services, including physical and occupational therapy and speech-language pathology services. The most common resident conditions are septicemia, joint replacement, heart failure and shock, hip and femur procedures (not including major joint replacement), and pneumonia.^[54] Septicemia progressing to sepsis is often associated with long-term functional deficits and increased mortality in survivors.^[55] Rehabilitation of function, however, has been shown to be effective and is associated with reducing mortality and improving quality of life.^[56 57]

Section 1888(e)(6)(B)(i) of the Act, cross-referencing subsections (b), (c), and (d) of section 1899B of the Act, requires CMS to develop and implement standardized quality measures from five quality measure domains, including the domain of functional status, cognitive function, and changes in function and cognitive function across the post-acute care (PAC) settings, including SNFs. To satisfy this requirement, we adopted the Application of Percent of Long-Term Care Hospital Patients with an Admission and Discharge Functional Assessment and a Care Plan That Addresses Function (Application of Functional Assessment/Care Plan) measure, for the SNF QRP in the FY 2016 SNF PPS final rule (80 FR 46444 through 46453). While this process measure allowed for the standardization of functional assessments across assessment instruments and facilitated cross-setting data collection, quality measurement, and interoperable data exchange, we believe it is now topped out and are proposing to remove it in section VI.C.1.c. of this proposed rule. While there are other outcome measures addressing functional status ^[58] that can reliably distinguish performance among providers in the SNF QRP, these outcome measures are not cross-setting in nature because they rely on functional status items not collected in all PAC settings. In contrast, a cross-setting functional outcome measure would align measure specifications across settings, including the use of a common set of standardized functional assessment data elements.

(a) Measure Importance

Maintenance or improvement of physical function among older adults is increasingly an important focus of health care. Adults age 65 years and older constitute the most rapidly growing population in the United States, and functional capacity in physical (non-psychological) domains has been shown to decline with age.^[59] Moreover, impaired functional capacity is associated with poorer quality of life and an increased risk of all-cause mortality, postoperative complications, and cognitive impairment, the latter of which can complicate the return of a resident to the community from post-acute care.^{[60 61 62]} Nonetheless, evidence suggests that physical functional abilities, including mobility and self-care, are modifiable predictors of resident outcomes across PAC settings, including functional recovery or decline after post-acute care,^{[63 64 65 66 67]} rehospitalization rates,^{[68 69 70]} discharge to community,^[71 72] and falls.^[73]

The implementation of interventions that improve residents' functional outcomes and reduce the risks of associated undesirable outcomes as a part of a resident-centered care plan is essential to maximizing functional improvement. For many people, the overall goals of SNF care may include optimizing functional improvement, returning to a previous level of independence, maintaining functional abilities, or avoiding institutionalization. Studies have suggested that rehabilitation services provided in SNFs can improve residents' mobility and functional independence for residents with various diagnoses, including cardiovascular and pulmonary conditions, orthopedic conditions, and stroke.^[74 75] Moreover, studies found an association between the level of therapy intensity and better functional improvement, suggesting that assessment of functional status as a health outcome in SNFs can provide valuable information in determining treatment decisions throughout the care continuum, such as the need for rehabilitation services, and discharge planning,^{[76 77 78]} as well as provide information to consumers about the effectiveness of skilled nursing services and rehabilitation services delivered. Because evidence shows that older adults experience aging heterogeneously and require individualized and comprehensive health care, functional status can serve as a vital component in informing the provision of health care and thus indicate a SNF's quality of care.^[79 80]

We are proposing to adopt the Discharge Function Score (DC Function) measure ^[81] in the SNF QRP beginning with the FY 2025 SNF QRP. This assessment-based outcome measure evaluates functional status by calculating the percentage of Medicare Part A SNF residents who meet or exceed an expected discharge function score. If finalized, this measure would replace the topped-out Application of Functional Assessment/Care Plan process measure. Like the cross-setting process measure we are proposing to remove in section VI.C.1.c. of this proposed rule, the proposed DC Function measure is calculated using standardized resident assessment data from the current SNF assessment tool, the Minimum Data Set (MDS).

The DC Function measure supports our current priorities. Specifically, the measure aligns with the Streamline Quality Measurement domain in CMS's Meaningful Measurement 2.0 Framework in two ways. First, the proposed outcome measure would further our objective to prioritize outcome measures by replacing the current cross-setting process measure (see section VI.C.1.c of this proposed rule). This proposed DC Function measure uses a set of cross-setting assessment items which would facilitate data collection, quality measurement, outcome comparison, and interoperable data exchange among PAC settings; existing functional outcome measures do not use a set of cross-setting assessment items. Second, this measure adds no additional provider burden since it would be calculated using data from the MDS that SNFs are already required to collect.

The proposed DC Function measure would also follow a calculation approach similar to the existing functional outcome measures, which are CBE endorsed, with some modifications.^[82] Specifically, the proposed measure (1) considers two dimensions of function (self-care and mobility activities) and (2) accounts for missing data by using statistical imputation to improve the validity of measure performance. The statistical imputation approach recodes missing functional status data to the most likely value had the status been assessed, whereas the current imputation approach implemented in existing functional outcome measures recodes missing data to the lowest functional status. A benefit of statistical imputation is that it uses resident characteristics to produce an unbiased estimate of the score on each item with a missing value. In contrast, the current approach treats residents with missing values and residents who were coded to the lowest functional status similarly, despite evidence suggesting varying measure performance between the two groups, which can lead to less accurate measure performances.

(b) Measure Testing

Our measure developer conducted testing using FY 2019 data on the DC Function measure to assess validity, reliability, and reportability, all of which informed interested parties' feedback and Technical Expert Panel (TEP) input (see section VI.C.1.b.(3) of this proposed rule). Validity was assessed for the measure performance, the risk adjustment model, face validity, and statistical imputation models. Validity testing of measure performance entailed determining Spearman's rank correlations between the proposed measure's performance for providers with 20 or more stays and the performance of other publicly reported SNF quality measures. Results indicated that the measure captures the intended outcome based on the directionalities and strengths of correlation coefficients and are further detailed below in Table 12.

Table 12—Spearman's Rank Correlation Results of DC Function Measure With Publicly Reported SNF Quality Measures

Measure—long name	Measure—short name	ρ
Discharge to Community—PAC SNF QRP	Discharge to Community	0.16
Application of IRF Functional Outcome Measure: Change in Self-Care Score for Medical Rehabilitation Patients	Change in Self-Care Score	0.75
Application of IRF Functional Outcome Measure: Change in Mobility Score for Medical Rehabilitation Patients	Change in Mobility Score	0.78
Application of IRF Functional Outcome Measure: Discharge Self-Care Score for Medical Rehabilitation Patients	Discharge Self-Care Score	0.78
Application of IRF Functional Outcome Measure: Discharge Mobility Score for Medical Rehabilitation Patients	Discharge Mobility Score	0.80
Potentially Preventable 30-Day Post-Discharge Readmission Measure—SNF QRP	Potentially Preventable Readmissions within 30 Days Post-Discharge	−0.10
Medicare Spending Per Beneficiary—PAC SNF QRP	Medicare Spending Per Beneficiary	−0.07

Validity testing of the risk adjustment model showed good model discrimination as the measure model has the predictive ability to distinguish residents with low expected functional capabilities from those with high expected functional capabilities.^[83] The ratios of observed-to-predicted discharge function score across eligible stays, by deciles of expected functional capabilities, ranged from 0.99 to 1.01. Both the Cross-Setting Discharge Function TEPs and resident-family feedback showed strong support for the face validity and importance of the proposed measure as an indicator of quality of care (see section VI.C.1.b.(3) of this proposed rule). Lastly, validity testing of the measure's statistical imputation models indicated that the models demonstrate good discrimination and produce more precise and accurate estimates of function scores for items with missing scores when compared to the current imputation approach implemented in SNF QRP functional outcome measures, specifically the Application of IRF Functional Outcome Measure: Change in Self-Care Score for Medical Rehabilitation Patients measure (Change in Self-Care Score), the Application of IRF Functional Outcome Measure: Change in Mobility Score for Medical Rehabilitation Patients measure (Change in Mobility Score), the Application of IRF Functional Outcome Measure: Discharge Self-Care Score for Medical Rehabilitation Patients measure (Discharge Self-Care Score), and the Application of IRF Functional Outcome Measure: Discharge Mobility Score for Medical Rehabilitation Patients measure (Discharge Mobility Score) measures.

Reliability and reportability testing also yielded results that support the measure's scientific acceptability. Split-half testing revealed the proposed measure's good reliability, indicated by an intraclass correlation coefficient value of 0.81. Reportability testing indicated high reportability (85 percent) of SNFs meeting the public reporting threshold of 20 eligible stays. For additional measure testing details, we refer readers to the document titled Discharge Function Score for Skilled Nursing Facilities (SNFs) Technical Report.^[84]

(2) Competing and Related Measures

Section 1899B(e)(2)(A) of the Act requires that, absent an exception under section 1899B(e)(2)(B) of the Act, measures specified under section 1899B of the Act be endorsed by the CBE with a contract under section 1890(a) of the Act. In the case of a specified area or medical topic determined appropriate by the Secretary for which a feasible and practical measure has not been endorsed, section 1899B(e)(2)(B) of the Act permits the Secretary to specify a measure that is not so endorsed, as long as due consideration is given to measures that have been endorsed or adopted by a CBE identified by the Secretary.

The proposed DC Function measure is not CBE endorsed, so we considered whether there are other available measures that: (1) assess both functional domains of self-care and mobility in SNFs and (2) satisfy the requirement of the Act to specify quality measures with respect to functional status, cognitive function, and changes in function and cognitive function across the PAC settings. While the Application of Functional Assessment/Care Plan measure assesses both functional domains and satisfies the Act's requirement, this cross-setting process measure is not CBE endorsed and the measure's performance among SNFs is so high and unvarying across most SNFs that the measure no longer offers meaningful distinctions in performance. Additionally, after review of other CBE endorsed measures, we were unable to identify any CBE endorsed measures for SNFs that meet the aforementioned requirements. While the SNF QRP includes CBE endorsed outcome measures addressing functional status,^[85] they each assess a single domain of function, and are not cross-setting in nature because they rely on functional status items not collected in all PAC settings.

Therefore, after consideration of other available measures, we find that the exception under section 1899B(e)(2)(B) of the Act applies and are proposing to adopt the DC Function measure, beginning with the FY 2025 SNF QRP. We intend to submit the proposed measure to the CBE for consideration of endorsement when feasible.

(3) Interested Parties and Technical Expert Panel (TEP) Input

In our development and specification of this measure, we employed a transparent process in which we sought input from interested parties and national experts and engaged in a process that allowed for pre-rulemaking input, in accordance with section 1890A of the Act. To meet this requirement, we provided the following opportunities for input from interested parties: a focus group of patient and family/caregiver advocates (PFAs), two TEPs, and public comments through a request for information (RFI).

First, the measure development contractor convened a PFA focus group, during which residents and caregivers provided support for the proposed measure concept. Participants emphasized the importance of measuring functional outcomes and found self-care and mobility to be critical aspects of care. Additionally, they expressed an interest in measures assessing the number of residents discharged from particular facilities with improvements in self-care and mobility, and their views of self-care and mobility aligned with the functional domains captured by the proposed measure. All feedback was used to inform measure development efforts.

The measure development contractor for the DC Function measure subsequently convened TEPs on July 14–15, 2021 and January 26–27, 2022 to obtain expert input on the development of a cross-setting function measure for use in the SNF QRP. The TEPs consisted of interested parties with a diverse range of expertise, including SNF and PAC subject matter knowledge, clinical expertise, resident and family perspectives, and measure development experience. The TEPs supported the proposed measure concept and provided substantive feedback regarding the measure's specifications and measure testing data.

First, the TEP was asked whether they prefer a cross-setting measure that is modeled after the currently adopted Discharge Mobility Score and Discharge Self-Care Score measures, or one that is modeled after the currently adopted Change in Mobility Score and Change in Self-Care Score measures. With the Discharge Mobility Score and Change in Mobility Score measures and the Discharge Self-Care Score and Change in Self-Care Score measures being both highly correlated and not appearing to measure unique concepts, the TEP favored the Discharge Mobility Score and Discharge Self-Care Score measures over the Change in Mobility Score and Change in Self-Care Score measures and recommended moving forward with utilizing the Discharge Mobility Score and Discharge Self-Care Score measures' concepts for the development of a cross-setting measure.

Second, in deciding the standardized functional assessment data elements to include in the cross-setting measure, the TEP recommended removing redundant data elements. Strong correlations between scores of functional items within the same functional domain suggested that certain items may be redundant in eliciting information about resident function and inclusion of these items could lead to overrepresentation of a particular functional area. Subsequently, our measure development contractor focused on the Discharge Mobility Score measure as a starting point for cross-setting development due to the greater number of cross-setting standardized functional assessment data elements for mobility while also identifying redundant functional items that could be removed from a cross-setting functional measure.

Third, the TEP supported including the cross-setting self-care items such that the cross-setting function measure would capture both self-care and mobility. Panelists agreed that self-care items added value to the measure and are clinically important to function. Lastly, the TEP provided refinements to imputation strategies to more accurately represent functional performance across all PAC settings, including the support of using statistical imputation over the current imputation approach implemented in existing functional outcome measures in the PAC QRPs. We considered all recommendations from the TEPs and we applied their recommendations where technically feasible and appropriate. Summaries of the TEP proceedings titled Technical Expert Panel (TEP) for the Refinement of Long-Term Care Hospital (LTCH), Inpatient Rehabilitation Facility (IRF), Skilled Nursing Facility (SNF)/Nursing Facility (NF), and Home Health (HH) Function Measures Summary Report (July 2021 TEP) ^[86] and Technical Expert Panel (TEP) for Cross-Setting Function Measure Development Summary Report (January 2022 TEP) ^[87] are available on the CMS Measures Management System (MMS) Hub.

Finally, we solicited feedback from interested parties on the importance, relevance, and applicability of a cross-setting functional outcome measure for SNFs through an RFI in the FY 2023 SNF PPS proposed rule (87 FR 22754). Commenters were supportive of a cross-setting functional outcome measure that is inclusive of both self-care and mobility items, but also provided information related to potential risk-adjustment methodologies, as well as other measures that could be used to capture functional outcomes across PAC settings (87 FR 47553).

(4) Measure Applications Partnership (MAP) Review

In accordance with section 1890A of the Act, our pre-rulemaking process includes making publicly available a list of quality and efficiency measures, called the Measures Under Consideration (MUC) List, that the Secretary is considering adopting for use in Medicare programs. This allows interested parties to provide recommendations to the Secretary on the measures included on the list.

We included the DC Function measure under the SNF QRP in the publicly available MUC List for December 1, 2022.^[88] After the MUC List was published, the CBE-convened MAP received three comments from interested parties in the industry on the 2022 MUC List. Two commenters were supportive of the measure and one was not. Among the commenters in support of the measure, one commenter stated that function scores are the most meaningful outcome measure in the SNF setting, as they not only assess resident outcomes but also can be used for clinical improvement processes. Additionally, this commenter noted the measure's good reliability and validity and that the measure is feasible to implement. The second commenter noted that the DC Function measure is modeled on an NQF-endorsed measure and has undergone an extensive formal development process. In addition, the second commenter noted that the DC Function measure improves on the existing functional outcome measures, and recommended replacing the existing function measures with the DC Function measure.

One commenter did not support the DC Function measure and raised the following concerns: the “gameability” of the expected discharge score, the measure's complexity, and the difficulty of implementing a composite functional score.

Shortly after, several NQF-convened MAP workgroups met to provide input on the DC Function measure. First, the MAP Health Equity Advisory Group convened on December 6–7, 2022. The MAP Health Equity Advisory Group did not share any health equity concerns related to the implementation of the DC Function measure, and only requested clarification regarding measure specifications from the measure steward. The MAP Rural Health Advisory Group met on December 8–9, 2022, during which some of the group's members provided support for the DC Function measure and other group members did not express rural health concerns regarding the DC Function measure.

The MAP PAC/LTC workgroup met on December 12, 2022 and provided input on the DC Function measure. During this meeting, we were able to address several concerns raised by interested parties after the publication of the MUC List. Specifically, we clarified that the expected discharge scores are not calculated using self-reported functional goals, and are simply calculated by risk-adjusting the observed discharge scores (see section VI.C.1.b.(5) of this proposed rule). Therefore, we believe that these scores cannot be “gamed” by reporting less-ambitious functional goals. We also pointed out that the measure is highly usable as it is similar in design and complexity to existing function measures and that the data elements used in this measure are already in use on the MDS submitted by SNFs. Lastly, we clarified that the DC Function measure is intended to supplement, rather than replace, existing SNF QRP measures for self-care and mobility and implements improvements on the existing Discharge Self-Care Score and Discharge Mobility Score measures that make the measure more valid and harder to game.

The MAP PAC/LTC workgroup went on to discuss other concerns with the DC Function measure, including (1) whether the measure is cross-setting due to denominator populations that differ among settings, (2) whether the measure would adequately represent the full picture of function, especially for residents who may have a limited potential for functional gain, and (3) that the range of expected scores was too large to offer a valid facility-level score. We clarified that the denominator population in each measure setting represents the assessed population within the setting and that the measure satisfies the requirement of section 1888(e)(6) of the Act for a cross-setting measure in the functional status domain specified under section 1899B(c)(1) of the Act. Additionally, we noted that the TEP had reviewed the item set and determined that all the self-care and mobility items were suitable for all settings. Further, we clarified that, because the DC Function measure would assess whether a resident met or exceeded their expected discharge score, it accounts for residents who are not expected to improve. Lastly, we noted that the DC Function measure has a high degree of correlation with the existing function measures and that the range of expected scores is consistent with the range of observed scores. The PAC/LTC workgroup voted to support the NQF staff recommendation of conditional support for rulemaking, with the condition that we seek CBE endorsement.

In response to the PAC/LTC workgroup's preliminary recommendation, the CBE received two more comments supporting the recommendation and one comment that did not. Among the commenters in support of the DC Function measure, one supported the measure under the condition that it be reviewed and refined such that its implementation supports resident autonomy and results in care that aligns with residents' personal functional goals. The second commenter supported the DC Function measure under the condition that it produces statistically meaningful information that can inform improvements in care processes. This commenter also expressed concern that the DC Function measure is not truly cross-setting because it utilizes different resident populations and risk-adjustment models with setting-specific covariates across settings. Additionally, this commenter noted that using a single set of cross-setting section GG items is not appropriate since the items in our standardized patient/resident assessment data instruments may not be relevant across varying resident-setting populations. The commenter who did not support the DC Function measure raised concern with the usability of a composite functional score for improving functional performance, and expressed support for using individual measures, such as the current Change in Mobility Score and Change in Self-Care Score measures, to attain this goal.

Finally, the MAP Coordinating Committee convened on January 24–25, 2023, during which NQF received one comment not in support of the PAC/LTC workgroup's preliminary recommendation for conditional support of the DC Function measure. The commenter expressed concern that the DC Function measure competes with existing self-care and mobility measures in the SNF QRP. We noted that we monitor measures to determine if they meet any of the measure removal factors, set forth in § 413.360(b)(2), and when identified, we may remove such measure(s) through the rulemaking process. We noted again that the TEP had reviewed the item set and determined that all self-care and mobility items were suitable for all settings. The MAP Coordinating Committee members expressed support for reviewing existing measures for removal as well as support for the DC Function measure, favoring the implementation of a single, standardized function measure across PAC settings. The MAP Coordinating Committee unanimously upheld the PAC/LTC workgroup recommendation of conditional support for rulemaking. We refer readers to the final MAP recommendations, titled 2022–2023 MAP Final Recommendations.^[89]

(5) Quality Measure Calculation

The proposed DC Function measure is an outcome measure that estimates the percentage of Medicare Part A SNF residents who meet or exceed an expected discharge score during the reporting period. The proposed DC Function measure's numerator is the number of SNF stays with an observed discharge function score that is equal to or greater than the calculated expected discharge function score. The observed discharge function score is the sum of individual function items values at discharge. The expected discharge function score is computed by risk-adjusting the observed discharge function score for each SNF stay. Risk adjustment controls for resident characteristics such as admission function score, age, and clinical conditions. The denominator is the total number of SNF stays with an MDS record in the measure target period (four rolling quarters) that do not meet the measure exclusion criteria. For additional details regarding the numerator, denominator, risk adjustment, and exclusion criteria, refer to the Discharge Function Score for Skilled Nursing Facilities (SNFs) Technical Report.^[90]

The proposed measure implements a statistical imputation approach for handling “missing” standardized functional assessment data elements. The coding guidance for standardized functional assessment data elements allows for using “Activity Not Attempted” (ANA) codes, resulting in “missing” information about a resident's functional ability on at least some items, at admission and/or discharge, for a substantive portion of SNF residents. Currently, functional outcome measures in the SNF QRP use a simple imputation method whereby all ANA codes or otherwise missing scores, on both admission and discharge records, are recoded to “1” or “most dependent.” Statistical imputation, on the other hand, replaces these missing values with a variable based on the values of other, non-missing variables in the assessment and on the values of other assessments which are otherwise similar to the assessment with a missing value. Specifically, this proposed DC Function measure's statistical imputation allows missing values (for example, the ANA codes) to be replaced with any value from 1 to 6, based on a resident's clinical characteristics and codes assigned on other standardized functional assessment data elements. The measure implements separate imputation models for each standardized functional assessment data element used in the construction of the discharge score and the admission score. Relative to the current simple imputation method, this statistical imputation approach increases precision and accuracy and reduces the bias in estimates of missing item values. We refer readers to the Discharge Function Score for Skilled Nursing Facilities (SNFs) Technical Report  ^[91] for measure specifications and additional details.

We invite public comment on our proposal to adopt the Discharge Function Score measure beginning with the FY 2025 SNF QRP.

c. Proposed Removal of the Application of Percent of Long-Term Care Hospital Patients With an Admission and Discharge Functional Assessment and a Care Plan That Addresses Function Beginning With the FY 2025 SNF QRP

We are proposing to remove the Application of Percent of Long-Term Care Hospital Patients with an Admission and Discharge Functional Assessment and a Care Plan That Addresses Function (Application of Functional Assessment/Care Plan) measure from the SNF QRP beginning with the FY 2025 SNF QRP. Section 413.360(b)(2) of our regulations describes eight factors we consider for measure removal from the SNF QRP, and we believe this measure should be removed because it satisfies two of these factors.

First, the Application of Functional Assessment/Care Plan measure meets the conditions for measure removal factor one: measure performance among SNFs is so high and unvarying that meaningful distinctions in improvements in performance can no longer be made.^[92] Second, this measure meets the conditions for measure removal factor six: there is an available measure that is more strongly associated with desired resident functional outcomes. We believe the proposed DC Function measure discussed in section VI.C.1.b. of this proposed rule better measures functional outcomes than the current Application of Functional Assessment/Care Plan measure. We discuss each of these reasons in more detail below.

In regard to removal factor one, the Application of Functional Assessment/Care Plan measure has become topped out,^[93] with average performance rates reaching nearly 100 percent over the past 3 years (ranging from 99.1 percent to 98.9 percent during CYs 2019–2021).^{[94]  [95]  [96]} For the 12-month period of Q3 2020 through Q2 2021 (July 1, 2020 through June 30, 2021), SNFs had an average score for this measure of 98.8 percent, with nearly 70 percent of SNFs scoring 100 percent ^[97] and for CY 2021, SNFs had an average score of 98.9 percent, with nearly 63 percent of SNFs scoring 100 percent.^[98] The proximity of these mean rates to the maximum score of 100 percent suggests a ceiling effect and a lack of variation that restricts distinction among SNFs.

In regard to measure removal factor six, the proposed DC Function measure is more strongly associated with desired resident functional outcomes than this current process measure, the Application of Functional Assessment/Care Plan measure. As described in section VI.C.1.b.(1)(b) of this proposed rule, the DC Function measure has the predictive ability to distinguish residents with low expected functional capabilities from those with high expected functional capabilities.^[99] We have been collecting standardized functional assessment elements across PAC settings since 2016, which has allowed for the development of the proposed DC Function measure and meets the requirements of the Act to submit standardized patient assessment data and other necessary data with respect to the domain of functional status, cognitive function, and changes in function and cognitive function. In light of this development, this process measure, the Application of Functional Assessment/Care Plan measure, which measures only whether a functional assessment is completed and a functional goal is included in the care plan, is no longer necessary, and can be replaced with a measure that evaluates the SNF's outcome of care on a resident's function.

Because the Application of Functional Assessment/Care Plan measure meets measure removal factors one and six, we are proposing to remove it from the SNF QRP beginning with the FY 2025 SNF QRP. We are also proposing that public reporting of the Application of Functional Assessment/Care Plan measure would end by the October 2024 Care Compare refresh or as soon as technically feasible when public reporting of the proposed DC Function measure would begin (see section VI.G.3. of this proposed rule).

Under our proposal, SNFs would no longer be required to report a Self-Care Discharge Goal (that is, GG0130, Column 2) or a Mobility Discharge Goal (that is, GG0170, Column 2) beginning with residents admitted on or after October 1, 2023. We would remove the items for Self-Care Discharge Goal (that is, GG0130, Column 2) and Mobility Discharge Goal (that is, GG0170, Column 2) with the next release of the MDS. Under our proposal, these items would not be required to meet SNF QRP requirements beginning with the FY 2025 SNF QRP.

We invite public comment on our proposal to remove the Application of Functional Assessment/Care Plan measure from the SNF QRP beginning with the FY 2025 SNF QRP.

d. Proposed Removal of the Application of IRF Functional Outcome Measure: Change in Self-Care Score for Medical Rehabilitation Patients and Removal of the Application of IRF Functional Outcome Measure: Change in Mobility Score for Medical Rehabilitation Patients Beginning With the FY 2025 SNF QRP

We are proposing to remove the Application of the IRF Functional Outcome Measure: Change in Self-Care Score for Medical Rehabilitation Patients (Change in Self-Care Score) and the Application of IRF Functional Outcome Measure: Change in Mobility Score for Medical Rehabilitation Patients (Change in Mobility Score) measures from the SNF QRP beginning with the FY 2025 SNF QRP. Section 413.360(b)(2) of our regulations describe eight factors we consider for measure removal from the SNF QRP, and we believe this measure should be removed because it satisfies measure removal factor eight: the costs associated with a measure outweigh the benefits of its use in the program.

Measure costs are multifaceted and include costs associated with implementing and maintaining the measure. On this basis, we are proposing the removal of these measures for two reasons. First, the costs to SNFs associated with tracking similar or duplicative measures in the SNF QRP outweigh any benefit that might be associated with the measures. Second, our costs associated with program oversight of the measures, including measure maintenance and public display, outweigh the benefit of information obtained from the measures. We discuss each of these in more detail below.

We adopted the Change in Self-Care Score and Change in Mobility Score measures in the FY 2018 SNF PPS final rule (82 FR 36578 through 36593), under section 1888(e)(6)(B)(i)(II) of the Act because the measures meet the functional status, cognitive function, and changes in function and cognitive function domain under section 1899B(c)(1) of the Act. Two additional measures addressing the functional status, cognitive function, and changes in function and cognitive function domain were adopted in the same program year: the Application of IRF Functional Outcome Measure: Discharge Self-Care Score for Medical Rehabilitation Patients (Discharge Self-Care Score) and the Application of IRF Functional Outcome Measure: Discharge Mobility Score for Medical Rehabilitation Patients (Discharge Mobility Score) measures. At the time these four outcome measures were adopted, the amount of rehabilitation services received among SNF residents varied. We believed that measuring residents' functional changes across all SNFs on an ongoing basis would permit identification of SNF characteristics associated with better or worse resident risk adjustment outcomes as well as help SNFs target their own quality improvement efforts.^[100]

We are proposing to remove the Change in Self-Care Score and Change in Mobility Score measures because we believe the SNF costs associated with tracking duplicative measures outweigh any benefit that might be associated with the measures. Since the adoption of these measures in 2018, we have been monitoring the data and found that the scores for the two self-care functional outcome measures, Change in Self-Care Score and Discharge Self-Care Score, are very highly correlated in SNF settings (0.93).^[101] Similarly, in the monitoring data, we have found that the scores for the two mobility score measures, Change in Mobility Score and Discharge Mobility Score, are very highly correlated in SNF settings (0.95).^[102] The high correlation between these measures suggests that the Change in Self-Care Score and Discharge Self-Care Score and the Change in Mobility Score and the Discharge Mobility Score measures provide almost identical information about this dimension of quality to SNFs and are therefore duplicative.

Our proposal to remove the Change in Self-Care Score and the Change in Mobility Score measures is supported by feedback received from the TEP convened for the Refinement of LTCH, IRF, SNF/NF, and HH Function Measures. As described in section VI.C.1.b.(3) of this proposed rule, the TEP panelists were presented with analyses that demonstrated the “Change in Score” and “Discharge Score” measure sets are highly correlated and do not appear to measure unique concepts, and they subsequently articulated that it would be sensible to retire either the “Change in Score” or “Discharge Score” measure sets for both self-care and mobility. Based on responses to the post-TEP survey, the majority of panelists (nine out of 12 respondents) suggested that only one measure set each for self-care and mobility, respectively, is necessary. Of those nine respondents, six preferred retaining the “Discharge Score” measure set over the “Change in Score” measure set.^[103]

Additionally, we are proposing to remove the Change in Self-Care Score and Change in Mobility Score measures because the program oversight costs outweigh the benefit of information that CMS, SNFs, and the public obtain from the measures. We must engage in various activities when administering the QRPs, such as monitoring measure results, producing provider preview reports, and ensuring the accuracy of the publicly reported data. Because these measures essentially provide the same information to SNFs as well as to consumers as the Discharge Self-Care Score and Discharge Mobility Score measures, our costs associated with measure maintenance and public display outweigh the benefit of information obtained from the measures.

Because these measures meet the criteria for measure removal factor eight, we are proposing to remove the Change in Self-Care Score and Change in Mobility Score measures from the SNF QRP beginning with the FY 2025 SNF QRP. We are also proposing that public reporting of the Change in Self-Care Score and the Change in Mobility Score measures would end by the October 2024 Care Compare refresh or as soon as technically feasible.

We invite public comment on our proposal to remove the Change in Self-Care Score and the Change in Mobility Score measures from the SNF QRP beginning with the FY 2025 SNF QRP.

2. SNF QRP Quality Measure Proposal Beginning With the FY 2026 SNF QRP

a. Proposed Adoption of the CoreQ: Short Stay Discharge Measure (NQF #2614) Beginning With the FY 2026 SNF QRP

(1) Background

We define person-centered care as integrated healthcare services delivered in a setting and manner that is responsive to the individual and their goals, values and preferences, in a system that empowers residents and providers to make effective care plans together.^[104] Person-centered care is achieved when healthcare providers work collaboratively with individuals to do what is best for the health and well-being of individuals receiving healthcare services, and allows individuals to make informed decisions about their treatment that align with their preferences and values, such as including more choice in medication times, dining options, and sleeping times. Self-reported measures, including questionnaires assessing the individual's experience and satisfaction in receiving healthcare services, are widely used across various types of providers to assess the effectiveness of their person-centered care practices.

There is currently no national standardized satisfaction questionnaire that measures a resident's satisfaction with the quality of care received by SNFs. We identified resident satisfaction with the quality of care received by SNFs as a measurement gap in the SNF QRP (see section VI.D. of this proposed rule), as did the MAP in its report MAP 2018 Considerations for Implementing Measure in Federal Programs: Post-Acute Care and Long-Term Care.^[105] Currently the SNF QRP includes measures of processes and outcomes that illustrate whether interventions are working to improve delivery of healthcare services. However, we believe that measuring resident satisfaction would provide clinical teams compelling information to use when examining the results of their clinical care, and can help SNFs identify deficiencies that other quality metrics may struggle to identify, such as communication between a resident and the provider.

Measuring individuals' satisfaction with healthcare services using questionnaires has been shown to be a valid indicator for measuring person-centered care practices. The value of measuring consumer satisfaction is supported in the peer-reviewed literature using respondents from SNFs. One study demonstrated higher (that is, better) resident satisfaction is associated with the SNF receiving fewer deficiency citations from regulatory inspections of the SNF, and is also associated with higher perceived service quality.^[106] Other studies of the relationship between resident satisfaction and clinical outcomes suggest that higher overall satisfaction may contribute to lower 30-day readmission rates ^{[107 108 109]} and better adherence to treatment recommendations.^[110 111]

We currently collect patient satisfaction data in other settings, such as home health, hospice, and hospital, using Consumer Assessment of Healthcare Providers and Systems (CAHPS®) patient experience surveys.^[112] These CAHPS® surveys ask individuals (or in some cases their families) about their experiences with, and ratings of, their healthcare providers, and then we publicly report the results of some of these patient experience surveys on Care Compare.^[113] The CAHPS® Nursing Home survey: Discharged Resident Instrument (NHCAHPS–D) was developed specifically for short-stay SNF residents ^[114] by the Agency for Healthcare Research and Quality (AHRQ) and the CAHPS® consortium ^[115] in collaboration with CMS. However, due to its length and the potential burden on SNFs and residents to complete it, we have not adopted it for the SNF QRP.

The CoreQ is another suite of questionnaires developed by a team of nursing home providers and researchers ^[116] to assess satisfaction among residents and their families. The CoreQ suite of five measures is used to capture resident and family data for SNFs and assisted living (AL) facilities. The CoreQ was developed in 2012 by SNFs and ALs that partnered with researchers to develop a valid resident satisfaction survey for SNFs and ALs since, at the time, there was no standard questionnaire or set of identical questions that could be used to compare meaningful differences in quality between SNFs. As part of the development of the CoreQ measures, extensive psychometric testing was conducted to further refine the CoreQ measures into a parsimonious set of questions that capture the domain of resident and family satisfaction. Since 2017, the CoreQ has been used in the American Health Care Association (AHCA) professional recognition program, and several states (including New Jersey, Tennessee, and Georgia) have incorporated the CoreQ into their Medicaid quality incentive programs. In addition, 42 SNF and AL customer satisfaction vendors currently administer the CoreQ measures' surveys or have added the CoreQ questions to their questionnaires.

The CoreQ measures were designed to be different from other resident satisfaction surveys. The primary difference between the CoreQ questionnaires for residents discharged from a SNF after receiving short-stay services and the NHCAHPS–D survey is its length: the CoreQ questionnaire consists of four questions while the NHCAHPS–D has 50 questions. Another difference is that the CoreQ measures provide one score that reflects a resident's overall satisfaction, while other satisfaction surveys do not. The CoreQ questionnaires use a 5-point Likert scale, and the number of respondents with an average score greater than or equal to 3.0 across the four questions is divided by the total number of valid responses to yield the SNF's satisfaction score.^[117]

The CoreQ measures are also instruments that are familiar to the SNF community, and the CoreQ: Short Stay Discharge (CoreQ: SS DC) survey has already been voluntarily adopted by a large number of SNFs with ease. The number of SNFs voluntarily using the CoreQ: SS DC survey increased from 372 in the first quarter of 2016 to over 1,500 in the third quarter of 2019.^[118] Additionally, the measure steward, AHCA, reported that there have been no reported difficulties with the current implementation of the measure, and in fact, providers, vendors, and residents have reported they like the fact that the questionnaire is short and residents report appreciation that their satisfaction (or lack thereof) is being measured.

(a) Measure Importance

Measuring residents' satisfaction is an effective method to assess whether the goals of person-centered care are achieved. Measuring residents' satisfaction can help SNFs identify deficiencies that the other quality metrics adopted in the SNF QRP cannot identify, such as communication between a resident and the SNF's healthcare providers. We believe collecting and assessing satisfaction data from SNF residents is important for understanding residents' experiences and preferences, while the collection process ensures each resident can easily and discreetly share their information in a manner that may help other potential consumers choose a SNF. Collection of resident satisfaction data also aligns with the person-centered care domain of CMS's Meaningful Measures 2.0 Framework,^[119] and would provide SNFs with resident-reported outcome information to incorporate into their quality assessment and performance improvement (QAPI) strategies to improve their quality of care.

The CoreQ: SS DC measure is a resident-reported outcome measure using the CoreQ: SS DC measure questionnaire which calculates the percentage of residents discharged in a 6-month period from a SNF, within 100 days of admission, who are satisfied with their SNF stay. The CoreQ: SS DC measure received initial NQF endorsement in 2016 and re-endorsement in 2020, and is a widely accepted instrument for measuring resident satisfaction. The measure includes a parsimonious set of four questions, and represents an important aspect of quality improvement and person-centered care. We believe it could be used to fill the identified gap in the SNF QRP's measure set, that is, measuring residents' experience of care. Therefore, we are proposing to adopt the CoreQ: SS DC measure for the SNF QRP beginning with the FY 2026 SNF QRP. More information about the CoreQ questionnaire is available at http://www.coreq.org.

(b) Measure Testing

The measure steward, AHCA, conducted extensive testing on the CoreQ: SS DC measure to assess reliability and validity prior to its initial NQF endorsement in 2016 and conducted additional analyses for the CoreQ: SS DC measure's NQF re-endorsement in 2020. These analyses found the CoreQ: SS DC measure to be highly reliable, valid, and reportable.^[120] We describe the results of these analyses in this section.

Reliability testing included administering a pilot survey to 853 residents, re-administering the survey to 100 of these residents, and then examining results at the data element level, the respondent/questionnaire level, and the measure (that is, facility) level. The data elements of the CoreQ: SS DC measure were found to be highly repeatable, with pilot and re-administered responses agreeing between 94 percent and 97 percent of the time, depending on the question. In other words, the same results were produced a high proportion of the time when assessed in the same population in the same time period. The questionnaire-level scores were also highly repeatable, with pilot and re-administered responses agreeing 98 percent of the time. Finally, reliability at the measure (that is, facility) level was also strong. Bootstrapping analyses in which repeated draws of residents were randomly selected from the measure population and scores were recalculated showed that 17.82 percent of scores were within 1 percentage point of the original score, 38.14 percent were within 3 percentage points of the original score, and 61.05 percent were within 5 percentage points of the original score. These results demonstrate that the CoreQ: SS DC measure scores from the same facility are very stable across bootstrapped samples.

The measure steward also conducted extensive validity testing of the CoreQ: SS DC measure's questionnaire, which included examination of the items in the questionnaire, the questionnaire format, and the validity of the CoreQ: SS DC measure itself.^[121]

First, the measure steward tested the items in the CoreQ: SS DC questionnaire to determine if a subset of items could reliably be used to produce an overall indicator of customer satisfaction. The measure steward started with 22 pilot questions, which assessed an individual's satisfaction with a number of concepts, such as food, environment, activities, communication, and responsiveness. Through repeated analyses, the number of questions was narrowed down to four. The four questions in the CoreQ: SS DC measure's final questionnaire were found to have a high degree of criterion validity, supporting that the instrument measures a single concept of “customer satisfaction,” rather than multiple areas of satisfaction.

Next, the validity of the four-question CoreQ: SS DC measure summary score was compared to the more expansive set of 22 pilot questions, and was found to have a correlation value of 0.94, indicating that the CoreQ: SS DC measure's questionnaire consisting of four questions adequately represents the overall satisfaction of the facility.

Finally, the measure steward found moderate levels of construct validity and convergent validity when the CoreQ: SS DC measure's relationship with Certification and Survey Provider Enhanced Reports (CASPER) Quality Indicators, Nursing Home Compare Quality Indicators, Five Star Ratings and staffing levels was examined. Therefore, the CoreQ: SS DC measure's questionnaire format has a high degree of both face validity and content validity.^[122]

Since the CoreQ: SS DC measure's original NQF endorsement in 2018, and its subsequent use by SNFs in quality improvement (see section VI.C.2.a.(1)), the measure steward conducted additional testing, including examining the reportability of the measure. Testing found that when the CoreQ: SS DC measure's questionnaires were administered within one week of facility discharge, the response rate was 8 percent higher than if it was administered 2 weeks after facility discharge. The measure steward analyzed responses when it allowed up to 2 months for a resident to respond, and found the average time to respond to the CoreQ: SS DC questionnaire was 2 weeks, while the response rate dropped much lower in the second month after facility discharge.^[123] The measure steward also conducted additional analyses to determine if there was any bias introduced into the responses to the CoreQ: SS DC's questionnaires that were returned during the second month, and found that average scores for the questionnaires returned in the second month were almost identical to those returned in the first month. Finally, the measure steward examined the time period required to collect the CoreQ: SS DC measure's data, and found that a majority of SNFs (that is, 90 percent) could achieve the minimum sample size of 20 completed CoreQ: SS DC questionnaires necessary for the satisfaction score to be reported as reliable for the SNF, when given up to 6 months. Additionally, once 125 consecutive completed CoreQ: SS DC questionnaires were received for a particular SNF, the measure steward found that including additional CoreQ: SS DC questionnaires had no additional effect on the SNF's satisfaction score. As a result of these additional analyses, the recommendations to allow up to 2 months for CoreQ: SS DC questionnaire returns, a 6-month reporting period, and a ceiling of 125 completed questionnaires in a 6-month period were incorporated into the CoreQ: SS DC measure's specification.

(2) Competing and Related Measures

Section 1899B(e)(2)(A) of the Act requires that, absent an exception under section 1899B(e)(2)(B) of the Act, measures specified under section 1899B of the Act be endorsed by a CBE with a contract under section 1890(a) of the Act. In the case of a specified area or medical topic determined appropriate by the Secretary for which a feasible and practical measure has not been endorsed, section 1899B(e)(2)(B) of the Act permits the Secretary to specify a measure that is not so endorsed, as long as due consideration is given to measures that have been endorsed or adopted by a consensus organization identified by the Secretary.

Although the CoreQ measure is NQF-endorsed for SNFs, we did consider whether there were other CBE-endorsed measures capturing SNF resident satisfaction after discharge from a SNF in less than 100 days. We found several CBE measures used in other programs that assess resident experiences for specific resident populations, such as residents at end of life, residents with low back pain, and residents receiving psychiatric care. However, we did not find other CBE-endorsed measures that assess satisfaction of residents discharged within 100 days of their admission to the SNF.

(3) Interested Parties and Technical Expert Panel (TEP) Input

We employ a transparent process to seek input from interested parties and national experts and engage in a process that allows for pre-rulemaking input on each measure, under section 1890A of the Act. To meet this requirement, we solicited feedback from interested parties through an RFI in the FY 2022 SNF PPS proposed rule (86 FR 19998) on the importance, relevance, and applicability of patient-reported outcome (PRO) measures for SNFs. In the FY 2022 SNF PPS final rule (86 FR 42490 through 42491), we noted that several commenters supported the concept of PROs while others were uncertain what we intended with the term “patient-reported outcomes.” One commenter stressed the importance of PROs since they determine outcomes based on information obtained directly from residents, and therefore provide greater insight into residents' experience of the outcomes of care. Another commenter agreed and stated that residents and caregivers are the best sources of information reflecting the totality of the resident experience.

We solicited public comments from interested parties specifically on the inclusion of the CoreQ: SS DC measure in a future SNF QRP year through an RFI in the FY 2023 SNF PPS proposed rule (87 FR 22761 through 22762). In the FY 2023 SNF PPS final rule (87 FR 47555), we noted that support for the CoreQ: SS DC measure specifically was mixed among commenters. One commenter stated that since the CoreQ: SS DC measure has a limited number of questions, it may not fully reflect resident experience at a given facility. Another commenter would not support the CoreQ: SS DC measure since it excludes residents who leave a facility against medical advice and residents with guardians, and this commenter stated it would be important to hear from both of these resident populations. Two commenters cautioned us to consider the burden associated with contracting with third-party vendors to administer the CoreQ: SS DC measure.

(4) Measure Application Partnership (MAP) Review

The CoreQ: SS DC measure was initially endorsed by the NQF in 2016. It was originally reviewed by the NQF's Person- and Family-Centered Care (PFCC) Committee on June 6, 2016. The PFCC Committee members noted the importance of measuring residents' experiences and their preferences given health care's changing landscape. Overall, the PFCC Committee members liked that there was a conceptual framework associated with the measure submission that linked the CoreQ: SS DC measure with other improvement programs and organizational change initiatives that can help SNFs improve the quality of care they provide. Some PFCC Committee members expressed concern around the consistency of implementation across SNFs and whether scores could be compromised by a low response rate. All PFCC Committee members agreed to not risk-adjust the CoreQ: SS DC measure as it would be inappropriate to control for differences based on sociodemographic factors. We refer readers to the PFCC Final Report—Phase 3.^[124]

The following year, the CoreQ: SS DC measure was included on the publicly available “List of Measures under Consideration for December 1, 2017” ^[125] for the SNF QRP Program, but the MAP did not receive any comments from interested parties. The CBE-convened MAP PAC/LTC workgroup met on December 13, 2017 and provided input on the CoreQ: SS DC measure. The MAP PAC/LTC workgroup offered support of the CoreQ: SS DC measure for rulemaking, noting that it adds value by adding addressing a gap area for the SNF QRP. The MAP PAC/LTC workgroup emphasized the value of resident-reported outcomes and noted that the CoreQ: SS DC measure would reflect quality of care from the resident's perspective. However, the MAP PAC/LTC workgroup also noted the potential burden of collecting the data and cautioned that the implementation of a new data collection requirement should be done with the least possible burden to the SNF.^[126]

(5) Quality Measure Calculation

The proposed CoreQ: SS DC measure is a resident-reported outcome measure based on the CoreQ: SS DC questionnaire that calculates the percentage of residents discharged in a 6-month period from a SNF, within 100 days of admission, who are satisfied with their SNF stay. Unless otherwise exempt from collecting and reporting on the CoreQ: SS DC measure (as discussed in section VI.F.3.b. of this proposed rule), we are proposing that each SNF must contract with an independent CMS-approved CoreQ survey vendor to administer the CoreQ: SS DC measure questionnaire, and report the results to CMS, on behalf of the SNF (as specified in sections VI.F.3.a. and VI.F.3.c of this proposed rule).

The CoreQ: SS DC measure questionnaire utilizes four questions (hereafter referred to as the four primary questions) and uses a 5-point Likert scale as illustrated in Table 13.

Table 13—CoreQ: Short Stay Discharge Primary Questions

Primary questions used in the CoreQ: short stay discharge questionnaire	Response options for the four CoreQ primary questions
1. In recommending this facility to your friends and family, how would you rate it overall?	Poor (1); Average (2); Good (3); Very Good (4); Excellent (5).
2. Overall, how would you rate the staff?
3. How would you rate the care you received?
4. How would you rate how well your discharge needs were met?

We are proposing to add two “help provided” questions to the end (as questions five and six) of the CoreQ: SS DC questionnaire in order to determine whether to count the CoreQ: SS DC questionnaire as a completed questionnaire for the CoreQ: SS DC measure denominator or whether the questionnaire should be excluded as described in the Draft CoreQ: SS DC Survey Protocols and Guidelines Manual ^[127] available on the SNF QRP Measures and Technical Information web page. These two “help provided” questions are:

5. Did someone help you [the resident] complete the survey?

6. How did that person help you [the resident]?

(a) Denominator

The denominator is the sum of all of the questionnaire-eligible residents, regardless of payer, who (1) are admitted to the SNF and discharged within 100 days, (2) receive the CoreQ: SS DC questionnaire, and (3) respond to the CoreQ: SS DC questionnaire within two months of discharge from the SNF. However, certain residents are excluded from the denominator and therefore are not sent a CoreQ: SS DC questionnaire by the CMS-approved CoreQ survey vendor or contacted by the CMS-approved CoreQ survey vendor for a phone interview. The residents who are not eligible to respond to the questionnaire, and therefore are excluded from the denominator for the CoreQ: SS DC measure are: (1) residents discharged to another hospital, another SNF, a psychiatric facility, an IRF, or an LTCH; (2) residents who die during their SNF stay; (3) residents with court-appointed legal guardians with authority to make decisions on behalf of the resident; (4) residents discharged to hospice; (5) residents who have dementia impairing their ability to answer the questionnaire; ^[128] (6) residents who left the SNF against medical advice; and (7) residents with a foreign address. Additionally, residents are excluded from the denominator if after the CoreQ: SS DC questionnaire is returned: (1) the CMS-approved CoreQ survey vendor received the CoreQ: SS DC completed questionnaire more than two months after the resident was discharged from the SNF or the resident did not respond to attempts to conduct the interview by phone within two months of their SNF discharge date; (2) the CoreQ: SS DC questionnaire “help provided” question six indicates the questionnaire answers were answered for the resident by an individual(s) other than the resident; or (3) the received CoreQ: SS DC questionnaire is missing more than one response to the four primary questions (that is, missing two or more responses).

(b) Numerator

The numerator is the sum of the resident respondents in the denominator that submitted an average satisfaction score of greater than or equal to three for the four primary questions on the CoreQ: SS DC questionnaire. If a CoreQ: SS DC questionnaire is received and is missing only one response (out of the four primary questions in the questionnaire), imputation is used which represents the average value from the other three available responses. If a CoreQ: SS DC questionnaire is received and is missing more than one response to the four primary questions (that is, missing two or more responses), the CoreQ: SS DC questionnaire is excluded from the analysis (that is, no imputation will be used for these residents). The CoreQ: SS DC measure is not risk-adjusted by sociodemographic status (SDS), as the measure steward found no statistically significant differences (at the 5 percent level) in scores between the SDS categories.^[129] Additional information about how the CoreQ: SS DC measure is calculated is available in the Draft CoreQ: SS DC Survey Protocols and Guidelines Manual ^[130] on the SNF QRP Measures and Technical Information web page.

We invite public comment on our proposal to adopt the CoreQ: SS DC Measure beginning with the FY 2026 SNF QRP.

b. Proposed Adoption of the COVID–19 Vaccine: Percent of Patients/Residents Who Are Up to Date Measure Beginning With the FY 2026 SNF QRP

(1) Background

COVID–19 has been and continues to be a major challenge for PAC facilities, including SNFs. The Secretary first declared COVID–19 a PHE on January 31, 2020. As of March 23, 2023, the U.S. has reported 103,957,053 cumulative cases of COVID–19 and 1,123,613 total deaths due to COVID–19.^[131] Although all age groups are at risk of contracting COVID–19, older persons are at a significantly higher risk of mortality and severe disease following infection; those over age 80 dying at five times the average rate.^[132] Older adults, in general, are prone to both acute and chronic infections owing to reduced immunity, and are a high-risk population.^[133] Adults age 65 and older comprise over 75 percent of total COVID–19 deaths despite representing 13.4 percent of reported cases.^[134] COVID–19 has impacted older adults' access to care, leading to poorer clinical outcomes, as well as taking a serious toll on their mental health and well-being due to social distancing.^[135]

Since the development of the vaccines to combat COVID–19, studies have shown they continue to provide strong protection against severe disease, hospitalization, and death in adults, including during the predominance of Omicron BA.4 and BA.5 variants.^[136] Initial studies showed the efficacy of FDA-approved or authorized COVID–19 vaccines in preventing COVID–19. Prior to the emergence of the Delta variant of the virus, vaccine effectiveness against COVID–19-associated hospitalizations among adults age 65 and older was 91 percent for those who were fully vaccinated with a full mRNA vaccination (Pfizer-BioNTech or Moderna), and 84 percent for those receiving a viral vector vaccine (Janssen). Adults age 65 and older who were fully vaccinated with an mRNA COVID–19 vaccine had a 94 percent reduction in risk of COVID–19 hospitalizations, while those who were partially vaccinated had a 64 percent reduction in risk.^[137] Further, after the emergence of the Delta variant, vaccine effectiveness against COVID–19-associated hospitalizations for adults who were fully vaccinated was 76 percent among adults age 75 and older.^[138]

More recently, since the emergence of the Omicron variants and the availability of booster doses, multiple studies have shown that while vaccine effectiveness has waned, protection is higher among those receiving booster doses than among those receiving only the primary series.^{[139]  [140]  [141]} CDC data show that, among people age 50 and older, those who have received both a primary vaccination series and booster doses have a lower risk of hospitalization and dying from COVID–19 than their non-vaccinated counterparts.^[142] Additionally, a second vaccine booster dose has been shown to reduce risk of severe outcomes related to COVID–19, such as hospitalization or death, among nursing home residents. Nursing home residents who received their second booster dose were more likely to have additional protection against severe illness compared to those who received only one booster dose after their initial COVID–19 vaccination.^[143] Early evidence also demonstrates that the bivalent boosters, specifically aimed to provide better protection against disease caused by Omicron subvariants, have been quite effective, and underscores the role of up-to-date vaccination protocols in effectively countering the spread of COVID–19.^{[144]  [145]}

(a) Measure Importance

Despite the availability and demonstrated effectiveness of COVID–19 vaccinations, significant gaps continue to exist in vaccination rates.^[146] As of March 22, 2023, vaccination rates among people age 65 and older are generally high for the primary vaccination series (94.3 percent) but lower for the first booster (73.6 percent among those who received a primary series) and even lower for the second booster (59.9 percent among those who received a first booster).^[147] Additionally, though the uptake in boosters among people age 65 and older has been much higher than among people of other ages, booster uptake still remains relatively low compared to primary vaccination among older adults.^[148] Variations are also present when examining vaccination rates by race, gender, and geographic location.^[149] For example, 66.2 percent of the Asian, non-Hispanic population have completed the primary series and 21.2 percent have received a bivalent booster dose, whereas 44.9 percent of the Black, non-Hispanic population have completed the primary series and only 8.9 percent have received the bivalent booster dose. Among Hispanic populations, 57.1 percent of the population have completed the primary series and 8.5 percent have received the bivalent booster dose, while in White, non-Hispanic populations, 51.9 percent have completed the primary series and 16.2 percent have received a bivalent booster dose.^[150] Disparities have been found in vaccination rates between rural and urban areas, with lower vaccination rates found in rural areas.^{[151]  [152]} Data show that 55.2 percent of the eligible population in rural areas have completed the primary vaccination series, as compared to 66.5 percent of the eligible population in urban areas.^[153] Receipt of bivalent booster doses among those eligible has been lower: 18 percent of the urban population have received a booster dose, and 11.5 percent of the rural population have received a booster dose.^[154]

We are proposing to adopt the COVID–19 Vaccine: Percent of Patients/Residents Who Are Up to Date (Patient/Resident COVID–19 Vaccine) measure for the SNF QRP beginning with the FY 2026 SNF QRP. This proposed measure has the potential to increase COVID–19 vaccination coverage of residents in SNFs, as well as prevent the spread of COVID–19 within the SNF resident population. This measure would also support the goal of the CMS Meaningful Measure Initiative 2.0 to “Empower consumers to make good health care choices through patient-directed quality measures and public transparency objectives.” The proposed Patient/Resident COVID–19 Vaccine measure would be reported on Care Compare and would provide residents and caregivers, including those who are at high risk for developing serious complications from COVID–19, with valuable information they can consider when choosing a SNF. The proposed Patient/Resident COVID–19 Vaccine measure would also facilitate resident care and care coordination during the hospital discharge planning process. A discharging hospital, in collaboration with the resident and family, could use this proposed measure's information on Care Compare to coordinate care and ensure resident preferences are considered in the discharge plan. Additionally, the proposed Patient/Resident COVID–19 Vaccine measure would be an indirect measure of SNF action. Since the resident's COVID–19 vaccination status would be reported at discharge from the SNF, if a resident is not up to date with their COVID–19 vaccine per applicable CDC guidance at the time they are admitted, the SNF has the opportunity to educate the resident and provide information on why they should become up to date with their COVID–19 vaccine. SNFs may also choose to administer the vaccine to the resident prior to their discharge from the SNF or coordinate a follow-up visit for the resident to obtain the vaccine at their physician's office or local pharmacy.

(b) Item Testing

Our measure development contractor conducted testing of the proposed standardized patient/resident COVID–19 vaccination coverage assessment item for the Patient/Resident COVID–19 Vaccine measure using resident scenarios, draft guidance manual coding instructions, and cognitive interviews to assess SNFs' comprehension of the item and the associated guidance. A team of clinical experts assembled by our measure development contractor developed these resident scenarios to represent the most common scenarios that SNFs would encounter. The results of the item testing demonstrated that SNFs that used the draft guidance manual coding instructions had strong agreement (that is, 84 percent) with the correct responses, supporting its reliability. The testing also provided information to improve both the item itself and the accompanying guidance.

(2) Competing and Related Measures

Section 1899B(e)(2)(A) of the Act requires that, absent an exception under section 1899B(e)(2)(B) of the Act, each measure specified under section 1899B of the Act be endorsed by a CBE with a contract under section 1890(a) of the Act. In the case of a specified area or medical topic determined appropriate by the Secretary for which a feasible and practical measure has not been endorsed, section 1899B(e)(2)(B) of the Act permits the Secretary to specify a measure that is not so endorsed, as long as due consideration is given to the measures that have been endorsed or adopted by a CBE identified by the Secretary. The proposed Patient/Resident COVID–19 Vaccine measure is not CBE endorsed and, after review of other CBE-endorsed measures, we were unable to identify any CBE endorsed measures for SNFs focused on capturing COVID–19 vaccination coverage of SNF residents. We found only one related measure addressing COVID–19 vaccination, the COVID–19 Vaccination Coverage among Healthcare Personnel (HCP) measure, adopted for the FY 2023 SNF QRP (86 FR 42480 through 42489), which captures the percentage of HCP who receive a complete COVID–19 primary vaccination series, but not booster doses.

Although SNFs' COVID–19 vaccination rates are posted on Care Compare, these data are aggregated at the facility level, and SNFs are not required to report beneficiary-level data to the CDC's NHSN. The COVID–19 vaccination rates currently posted on Care Compare are obtained from CDC's NHSN, and reflect “residents who completed primary vaccination series” and “residents who are up-to-date on their vaccines” across the entire nursing home (NH) resident population. Residents receiving SNF care under the Medicare fee-for-service program differ from residents receiving long-term care in nursing homes in several ways. SNF residents typically enter the facility after an inpatient hospital stay for temporary specialized post-acute care, while NH residents typically have chronic or progressive medical conditions, requiring maintenance and supportive levels of care, and may reside in the NH for years. Additionally, the SNF QRP includes data submitted by non-CAH swing bed units whose data are only represented through the SNF QRP, and are not included in the COVID–19 vaccination data reported to the NHSN by nursing homes. The proposed Patient/Resident COVID–19 Vaccine measure would be calculated using data collected on the MDS (as described in section VI.F.4. of this proposed rule) at the beneficiary level, which would enhance SNFs' ability to monitor their own infection prevention efforts with information on which they can act.

Additionally, the COVID–19 reporting requirements set forth in 42 CFR 483.80(g), finalized in the interim final rule with comment period (IFC) published on May 13, 2021 entitled “Medicare and Medicaid Programs; COVID–19 Vaccine Requirements for Long-Term Care (LTC) Facilities and Intermediate Care Facilities for Individuals with Intellectual Disabilities (ICFs-IID) Residents, Clients, and Staff” (86 FR 26315–26316) (hereafter referred to as the May 2021 IFC) are directed at the LTC facilities' requirements, and are separate from the SNF QRP. The purpose of the May 2021 IFC was to collect information which would allow the CDC to identify and alert us to facilities that may need additional support in regard to vaccine administration and education.

Instead, the purpose of the proposed Patient/Resident COVID–19 Vaccine measure is to allow for the collection of these data under the SNF QRP and subsequent public reporting of SNFs' facility-level resident vaccination rates on Care Compare so that Medicare beneficiaries who require short stays can make side-by-side SNF comparisons. Adoption of this proposed measure would also promote measure harmonization across quality reporting programs and provide Medicare beneficiaries the information to make side-by-side comparisons across other facility types to facilitate informed decision making in an accessible and user-friendly manner. Finally, the proposed Patient/Resident COVID–19 Vaccine measure would generate actionable data on vaccination rates that can be used to target quality improvement among SNFs.

Therefore, after consideration of other available measures that assess COVID–19 vaccination rates among SNF residents, we believe the exception under section 1899B(e)(2)(B) of the Act applies. We intend to submit the proposed measure for to the CBE for consideration of endorsement when feasible.

(3) Interested Parties and Technical Expert Panel (TEP) Input

First, the measure development contractor convened a focus group of patient and family/caregiver advocates (PFAs) to solicit input. The PFAs believed a measure capturing raw vaccination rate, irrespective of SNF action, would be most helpful in resident and caregiver decision-making. Next, TEP meetings were held on November 19, 2021, and December 15, 2021 to solicit feedback on the development of patient/resident COVID–19 vaccination measures and assessment items for the PAC settings. The TEP panelists voiced their support for PAC patient/resident COVID–19 vaccination measures and agreed that developing a measure to report the rate of vaccination in a SNF/NH setting without denominator exclusions was an important goal. We considered the TEP's recommendations, and we applied the recommendations, where technically feasible and appropriate. A summary of the TEP proceedings titled Technical Expert Panel (TEP) for the Development of Long-Term Care Hospital (LTCH), Inpatient Rehabilitation Facility (IRF), Skilled Nursing Facility (SNF)/Nursing Facility (NF), and Home Health (HH) COVID–19 Vaccination-Related Items and Measures Summary Report  ^[155] is available on the CMS MMS Hub.

To seek input on the importance, relevance, and applicability of a patient/resident COVID–19 vaccination coverage measure, we solicited public comments in an RFI for publication in the FY 2023 SNF PPS proposed rule (87 FR 42424). Commenters were mixed on whether they supported the concept of a measure addressing COVID–19 vaccination coverage among SNF residents. Two commenters noted the measure should account for other variables, such as whether the vaccine was offered, as well as excluding residents with medical contraindications to the vaccine (87 FR 47553).

(4) Measure Applications Partnership (MAP) Review

In accordance with section 1890A of the Act, the pre-rulemaking process includes making publicly available a list of quality and efficiency measures, called the Measures Under Consideration (MUC) List, that the Secretary is considering adopting for use in Medicare programs. This allows interested parties to provide recommendations to the Secretary on the measures included on the list. The Patient/Resident COVID–19 Vaccine measure was included on the publicly available 2022 MUC List for the SNF QRP.^[156]

After the MUC List was published, MAP received seven comments by interested parties during the measure's MAP pre-rulemaking process. Commenters were mostly supportive of the measure and recognized the importance of resident COVID–19 vaccination, and that measurement and reporting is one important method to help healthcare organizations assess their performance in achieving high rates of up-to-date vaccination. One commenter also noted that resident engagement is critical at this stage of the pandemic because best available information indicates COVID–19 variants will continue to require additional boosters to avert case surges. Another commenter noted the benefit of less-specific criteria for inclusion in the numerator and denominator of the proposed Patient/Resident COVID–19 Vaccine measure, which would provide flexibility for the measure to remain relevant to current circumstances. Several commenters noted their conditional support, however, and raised several issues about the measure. Specifically, one questioned whether our intent was to replace the required NHSN reporting if this measure were finalized and noted it did not collect data on Medicare Advantage residents. Another commenter suggested that nursing homes might refuse to admit unvaccinated residents, and was concerned about the costs SNFs would incur purchasing the vaccines. Another commenter raised concerns about the measure since it did not directly measure provider actions to increase vaccine uptake in the numerator and that it would only collect vaccination information on Medicare fee-for-service residents, rather than all residents, regardless of payer. Finally, one commenter was concerned because there were no exclusions for residents who refused to become up to date with their COVID–19 vaccination.

Subsequently, several MAP workgroups met to provide input on the measure. First, the MAP Health Equity Advisory Group convened on December 6, 2022. One MAP Health Equity Advisory Group member noted that the percentage of true contraindications for the COVID–19 vaccine is low, and the lack of exclusions on the measure is reasonable in order to minimize variation in what constitutes a contraindication.^[157] The MAP Rural Health Advisory Group met on December 8, 2022, and requested clarification of the term “up to date” and noted concerns with the perceived level of burden for collection of data.^[158]

Next, the MAP PAC/LTC workgroup met on December 12, 2022. The voting workgroup members noted the importance of reporting residents' vaccination status, but discussed their concerns about: (1) the duplication of data collection with the NHSN if an assessment-based measure were adopted into the SNF QRP; (2) how publicly reported rates would differ from the rates reported by the NHSN; (3) that the Patient/Resident COVID–19 Vaccine measure does not account for resident refusals or those who are unable to respond; and (4) the difficulty of implementing the definition of “up to date.” We clarified during the PAC/LTC workgroup meeting that this measure was intended to only include Medicare Part A-covered SNF stays. We further noted that the proposed Patient/Resident COVID–19 Vaccine measure does not have exclusions for resident refusals because the proposed measure was intended to report raw rates of vaccination. We explained that raw rates of vaccination collected by the proposed Patient/Resident COVID–19 Vaccine measure are important for consumer choice and PAC providers, including SNFs, are in a unique position to leverage their care processes to increase vaccination coverage in their settings to protect residents and prevent negative outcomes. We also clarified that the measure defines “up to date” in a manner that provides flexibility to reflect future changes in the CDC's guidance with respect to COVID–19 vaccination. Finally, we clarified that, like the existing HCP COVID–19 Vaccine measure, this measure would continue to be reported quarterly because the CDC has not yet determined whether COVID–19 is seasonal. Ultimately, the PAC/LTC workgroup did not achieve a 60 percent consensus vote to accept the NQF's preliminary analysis assessment of conditional support for the Patient/Resident COVID–19 Vaccine measure for SNF QRP rulemaking pending testing demonstrating the measure is reliable and valid, and CBE endorsement.^[159] Since the PAC/LTC workgroup did not reach consensus to accept, or subsequently to overturn the NQF staff's preliminary analysis assessment, the preliminary analysis assessment became the final recommendation of the PAC/LTC workgroup.

NQF received 10 comments by interested parties in response to the PAC/LTC workgroup recommendations. Interested parties generally understood the importance of COVID–19 vaccinations' role in preventing the spread of COVID–19 infections, although a majority of commenters did not recommend the inclusion of the proposed Patient/Resident COVID–19 Vaccine measure in the SNF QRP and raised several concerns. Specifically, several commenters were concerned about vaccine hesitancy, SNFs' inability to influence measure results based on factors outside of their control, duplication with NHSN reporting requirements, data lag in public reporting of QRP data relative to NHSN's current reporting of the measure, and that the proposed Patient/Resident COVID–19 Vaccine measure is not representative of the full SNF population, noting that the proposed Patient/Resident COVID–19 Vaccine measure has not been fully tested, and encouraged us to monitor the measure for unintended consequences and ensure that the measure has meaningful results. One commenter was in support of the proposed Patient/Resident COVID–19 Vaccine measure and provided recommendations for us to consider, including an exclusion for medical contraindications and submitting the measure for CBE endorsement. Another commenter questioned why the PAC/LTC workgroup recommendation for SNF was not consistent with their recommendation for the proposed Patient/Resident COVID–19 Vaccine measure in other PAC QRPs.

Finally, the MAP Coordinating Committee convened on January 24, 2023, and noted concerns which were previously discussed in the PAC/LTC workgroup, such as the duplication of NHSN reporting requirements and potential for selection bias based on the resident's vaccination status. We were able to clarify that this measure was intended to include only Medicare Part A-covered SNF stays for facilities required to report to the SNF QRP, since the Medicare Advantage resident population is not part of the SNF QRP reporting requirements. We also noted that this measure does not have exclusions for resident refusals since this is a process measure intended to report raw rates of vaccination, and is not intended to be a measure of SNFs' actions. We acknowledged that a measure accounting for variables, such as SNFs' actions to vaccinate residents, could be important, but noted that we are focused on a measure which would provide and publicly report vaccination rates for consumers given the importance of this information to residents and their caregivers.

The MAP Coordinating Committee recommended three mitigation strategies for the Patient/Resident COVID–19 Vaccine measure: (1) reconsider exclusions for medical contraindications, (ii) complete reliability and validity measure testing, and (iii) seek CBE endorsement. The Coordinating Committee ultimately reached 90 percent consensus on its recommendation of “Do not Support with potential for mitigation.” ^[160] Despite the MAP Coordinating Committee's vote, we believe it is still important to propose the Patient/Resident COVID–19 Vaccine measure for the SNF QRP. As we stated in section VI.C.2.b.(3) of this proposed rule, we did not include exclusions for medical contraindications because the PFAs we met with told us that a measure capturing raw vaccination rate, irrespective of any medical contraindications, would be most helpful in patient and family/caregiver decision-making. We do plan to conduct reliability and validity measure testing once we have collected enough data, and we intend to submit the proposed measure to the CBE for consideration of endorsement when feasible. We refer readers to the final MAP recommendations, titled 2022–2023 MAP Final Recommendations.^[161]

(5) Quality Measure Calculation

The proposed Patient/Resident COVID–19 Vaccine measure is a process measure that reports the percent of stays in which residents in a SNF are up to date on their COVID–19 vaccinations per the CDC's latest guidance.^[162] This measure has no exclusions, and is not risk adjusted.

The numerator for this measure would be the total number of Medicare Part A-covered SNF stays in which residents are up to date with their COVID–19 vaccine per CDC's latest guidance during the reporting year. The denominator for this measure would be the total number of Medicare Part A-covered SNF stays discharged during the reporting period. For the SNF QRP, this would apply to all freestanding SNFs, SNFs affiliated with acute care facilities, and all non-CAH swing-bed rural hospitals.

The data source for the proposed Patient/Resident COVID–19 Vaccine measure is the MDS assessment instrument for SNF residents. For more information about the proposed data submission requirements for this proposed measure, we refer readers to section VI.F.4. of this proposed rule. For additional technical information about this proposed measure, we refer readers to the draft measure specifications document titled Patient -Resident-COVID-Vaccine-Draft-Specs.pdf  ^[163] available on the SNF QRP Measures and Technical Information web page.

We invite public comments on our proposal to adopt the Patient/Resident: COVID–19 Vaccine measure beginning with the FY 2026 SNF QRP.

D. Principles for Selecting and Prioritizing SNF QRP Quality Measures and Concepts Under Consideration for Future Years—Request for Information (RFI)

1. Background

We have established a National Quality Strategy (NQS) ^[164] for quality programs which supports a resilient, high-value healthcare system promoting quality outcomes, safety, equity, and accessibility for all individuals. The CMS NQS is foundational for contributing to improvements in health care, enhancing patient outcomes, and informing consumer choice. To advance these goals, leaders from across CMS have come together to move toward a building-block approach to streamline quality measures across our quality programs for the adult and pediatric populations. This “Universal Foundation”^[165] of quality measures will focus provider attention and reduce provider burden, as well as identify disparities in care, prioritize development of interoperable, digital quality measures, allow for cross-comparisons across programs, and help identify measurement gaps. The development and implementation of the Preliminary Adult and Pediatric Universal Foundation Measures will promote the best, safest, and most equitable care for individuals as we all come together on these critical quality areas.

In alignment with the CMS NQS, the SNF QRP endeavors to move toward a more parsimonious set of measures while continually improving the quality of health care for beneficiaries. The purpose of this RFI is to gather input on existing gaps in SNF QRP measures and to solicit public comment on fully developed SNF measures that are not part of the SNF QRP, fully developed quality measures in other programs that may be appropriate for the SNF QRP, and measurement concepts that could be developed into SNF QRP measures, to fill these measurement gaps in the SNF QRP. While we will not be responding to specific comments submitted in response to this RFI in the FY 2024 SNF PPS final rule, we intend to use this input to inform future policies.

This RFI consists of three sections. The first section discusses a general framework or set of principles that we could use to identify future SNF QRP measures. The second section draws from an environmental scan conducted to identify measurement gaps in the current SNF QRP, and measures or measure concepts that could be used to fill these gaps. The final section solicits public comment on: (1) the set of principles for selecting measures for the SNF QRP, (2) identified measurement gaps, and (3) measures that are available for immediate use, or that may be adapted or developed for use in the SNF QRP.

2. Guiding Principles for Selecting and Prioritizing Measures

We have identified a set of principles to guide future SNF QRP measure set development and maintenance. These principles are intended to ensure that measures resonate with beneficiaries and caregivers, do not impose undue burden on providers, align with our PAC program goals, and can be readily operationalized. Specifically, measures incorporated into the SNF QRP should meet the following four objectives:

1. Actionability: Optimally, SNF QRP measures should focus on structural elements, healthcare processes, and outcomes of care that have been demonstrated through clinical evidence or other best practices to be amenable to improvement and feasible for SNFs to implement.

2. Comprehensiveness and Conciseness: SNF QRP measures should assess performance of all SNF core services using the smallest number of measures that comprehensively assess the value of care provided in SNF settings. Parsimony in the QRP measure set minimizes SNFs' burden resulting from data collection and submission.

3. Focus on Provider Responses to Payment: The SNF PPS shapes incentives for care delivery. SNF performance measures should neither exacerbate nor induce unwanted responses to the payment systems. As feasible, measures should mitigate adverse incentives of the payment system.

4. Compliance with CMS Statutory Requirements and Key Program Goals: Measures must comply with the governing statutory authorities and our policy to align measures with our policy initiatives, such as the Meaningful Measures Framework.

3. Gaps in SNF QRP Measure Set and Potential New Measures

We conducted an environmental scan that utilized the previously listed principles and identified measurement gaps in the domains of cognitive function, behavioral and mental health, resident experience and resident satisfaction, and chronic conditions and pain management. We discuss each of these in more detail below.

a. Cognitive Function

Illnesses associated with limitations in cognitive function, which may include stroke, dementia, and Alzheimer's disease, affect an individual's ability to think, reason, remember, problem-solve, and make decisions. Section 1888(e)(6)(B)(i) of the Act requires SNFs to submit data on quality measures under section 1899B(c)(1) of the Act, and cognitive function and changes in cognitive function are key dimensions of clinical care that are not currently represented in the SNF QRP.

Two sources of information on cognitive function currently collected in SNFs include the Brief Interview for Mental Status (BIMS) and Confusion Assessment Method (CAM^© ).^[166] Both the BIMS and CAM^© have been incorporated into the MDS as standardized patient assessment data elements. Scored by SNFs via direct observation, the BIMS is used to determine orientation and the ability to register and recall new information. The CAM^© assesses the presence of delirium and inattention, and level of consciousness. While data from the BIMS and CAM^© are collected and reported via the MDS, these items have not been developed into specific quality measures for the SNF QRP.

Alternative sources of information on cognitive function include the Patient-Reported Outcomes Measurement Information Set (PROMIS) Cognitive Function forms and the PROMIS Neuro-Quality of Life (Neuro-QoL) measures.^[167 168] Developed and tested with a broad range of resident populations, PROMIS Cognitive Function assesses cognitive functioning using items related to resident perceptions regarding performance of cognitive tasks, such as memory and concentration, and perceptions of changes in these activities. The Neuro-QoL, which was specifically designed for use in residents with neurological conditions, assesses resident perceptions regarding oral expression, memory, attention, decision-making, planning, and organization.

The BIMS, CAM^©, PROMIS Cognitive Function short forms, and PROMIS Neuro-QoL include items representing different aspects of cognitive function, from which quality measures may be constructed. Although these instruments have been subjected to feasibility, reliability, and validity testing, additional development and testing would be required prior to transforming the concepts reflected in the BIMS and CAM^© (for example, temporal orientation, recall) into fully specified measures for implementation in the SNF QRP.

Through this RFI, we are requesting comment on the availability of cognitive functioning measures outside of the SNF QRP that may be available for immediate use in the SNF QRP, or that may be adapted or developed for use in the SNF QRP, using the BIMS, CAM^©, PROMIS Cognitive Function short forms, and PROMIS Neuro-QoL, or other instruments. In addition to comment on specific measures and instruments, we seek input on the feasibility of measuring improvement in cognitive functioning during a SNF stay, which averages approximately 30 days; the cognitive skills (for example, executive functions) that are more likely to improve during a SNF stay; conditions for which measures of maintenance—rather than improvement in cognitive functioning—are more practical; and the types of intervention that have been demonstrated to assist in improving or maintaining cognitive functioning.

b. Behavioral and Mental Health

Estimates suggest that one in five Medicare beneficiaries has a “common mental health disorder” and nearly 8 percent have a serious mental illness.^[169] Substance use disorders (SUDs) are also common. Research estimates that approximately 1.7 million Medicare beneficiaries (8 percent) reported a SUD in the past year, with 77 percent attributed to alcohol use and 16 percent to prescription drug use.^[170] In some instances, such as following a knee replacement or stroke, residents may develop depression, anxiety, and/or SUDs. In other instances, residents may have been dealing with mental or behavioral health issues or SUDs long before their post-acute admission. Left unmanaged, however, these conditions could make it difficult for affected residents to actively participate in medical rehabilitation or to adhere to the prescribed treatment regimen, thereby contributing to poor health outcomes.

Information on the availability and appropriateness of behavioral health measures in post-acute settings is limited, and the 2021 National Impact Assessment of the CMS Quality Measures Report ^[171] identified PAC program measurement gaps in the areas of behavioral and mental health. Among the mental health quality measures in current use, the Home Health QRP assesses the extent to which residents have been screened for depression and a follow-up plan is documented.^[172] Although it may be possible to adapt this measure for use in other PAC settings, this process measure does not directly assess performance in the management of depression and related mental health concerns.

Other instruments that may be adapted to assess management of mental health, behavioral health, or SUDs in PAC settings include the CAHPS Experience of Care and Health Outcomes Survey (ECHO), which consists of a series of questions that may be used to understand residents' perspectives concerning mental health services received; ^[173] the PROMIS ^[174] suite of instruments that may be used to monitor and evaluate mental health and quality of life; and the National Institutes of Health (NIH) Toolbox for the Assessment of Neurological and Behavioral Health Function,^[175] which was commissioned by the NIH Blueprint for Neuroscience Research and includes both stand-alone measures and batteries of measures to assess emotional function and psychological well-being.

Like mental health issues, SUDs have been under-studied in the SNF and other PAC settings, even though they are among the fastest-growing disorders in the community-dwelling older adult population.^[176 177] Left untreated, SUDs can lead to overdose deaths, emergency department visits, and hospitalizations. The Substance Abuse and Mental Health Services Administration (SAMHSA) was established by Congress in 1992 to make substance use and mental disorder information, services, and research more accessible. As part of its work, SAMHSA developed the Screening, Brief Intervention, and Referral to Treatment (SBIRT) approach to support providers in using early intervention with at-risk substance users before more severe consequences occur, and has a number of resources available.^[178]

We seek feedback on these and other measures or instruments that may be directly applied, adapted, or developed for use in the SNF QRP. Further, we seek comments on the degree to which measures have been or will require validation and testing prior to application in the SNF QRP. We seek input on the availability of data, the manner in which data could be collected and reported to us, and the burden imposed on SNFs.

c. Resident Experience and Resident Satisfaction

Resident experience measures focus on how residents experienced or perceived selected aspects of their care, whereas resident satisfaction measures focus on whether a resident's expectations were met. Information on resident experience of care is typically collected via a number of instruments that rely on resident self-reported data. The most prominent among these is the CAHPS suite of surveys. The Nursing Home Discharged Resident CAHPS,^[179 180] which is intended for use with residents who had a length of stay less than 100 days, measures resident experience in terms of the care environment, communication with staff, respect received, quality of care, autonomy, and activities. The CoreQ questionnaires are another set of resident satisfaction tools. The CoreQ is a suite of five measures used to capture resident and family data for SNFs and assisted living (AL) facilities. The CoreQ: SS DC measure assesses the level of satisfaction among SNF short-stay (less than 100 days) residents, and we are proposing to adopt it for the SNF QRP beginning with the FY 2026 SNF QRP (see section VI.C.2.a. of this proposed rule).

We seek comment on the feasibility and challenges of adapting existing resident experience measures for use in the SNF QRP, as well as on the value of adapting and/or developing other resident experience and satisfaction measures beyond the CoreQ: SS DC measure proposed for the SNF QRP in this proposed rule. We also seek input on the challenges of adapting existing resident experience measures and instruments, the challenges of collecting and reporting resident experience and resident satisfaction data, and the extent to which resident experience measures offer SNFs sufficient information to assist in quality improvement.

d. Chronic Conditions and Pain Management

Despite the availability of measures focused on SNF clinical care services, existing SNF QRP measures do not directly address aspects of care rendered to populations with chronic conditions or SNFs' management of residents' pain. For example, the measures that address respiratory care relate to staff influenza and COVID–19 vaccination status. Although these measures target provider performance in preventing a respiratory illness with a potentially severe impact on morbidity and mortality, current measures fail to capture SNF performance in treatment or management of residents' chronic respiratory conditions, such as chronic obstructive pulmonary disease (COPD) or asthma.

Existing measures also fail to capture SNF actions concisely for pain management even though pain has been demonstrated to contribute to falls with major injury and restrictions in mobility and daily activity. However, a host of other factors also contribute to these measure domains, making it difficult to directly link provider actions to performance. Instead, a measure of SNFs' actions in reducing pain interference in daily activities, including the ability to sleep, would be a more concise measure of pain management. Beginning October 1, 2023, SNFs will begin collecting new standardized resident assessment data elements, including items that assess pain interference with (1) daily activities, (2) sleep, and (3) participation in therapy, providing an opportunity to develop more-concise measures of provider performance (84 FR 38798 through 38801).

Through this RFI, we are seeking input on measures of chronic condition and pain management that may be used to assess SNF performance. Additionally, we seek general comment on the feasibility and challenges of measuring and reporting SNF performance on existing QRP measures, such as the Discharge Self-Care Score for Medical Rehabilitation Patients and Discharge Mobility Score for Medical Rehabilitation Patients measures, for subgroups of residents defined by type of chronic condition. As examples, measures could assess discharge outcomes for SNF residents with a hip fracture diagnosis or for residents admitted with a diagnosis of congestive heart failure.

4. Solicitation of Comments

We invite general comments on the principles for identifying SNF QRP measures, as well as additional thoughts about measurement gaps, and suitable measures for filling these gaps. Specifically, we solicit comment on the following questions:

• Principles for Selecting and Prioritizing QRP Measures.

++ To what extent do you agree with the principles for selecting and prioritizing measures?

++ Are there principles that you believe CMS should eliminate from the measure selection criteria?

++ Are there principles that you believe CMS should add to the measure selection criteria?

• SNF QRP Measurement Gaps.

++ We request input on the identified measurement gaps, including in the areas of cognitive function, behavioral and mental health, resident experience and resident satisfaction, chronic conditions and pain management.

++ Are there gaps in the SNF QRP measures that have not been identified in this RFI?

• Measures and Measure Concepts Recommended for Use in the SNF QRP.

++ Are there measures that you believe are either currently available for use, or that could be adapted or developed for use in the SNF QRP program to assess performance in the areas of (1) cognitive functioning, (2) behavioral and mental health, (3) resident experience and resident satisfaction, (4) chronic conditions, (5) pain management, or (6) other areas not mentioned in this RFI?

We also seek input on data available to develop measures, approaches for data collection, perceived challenges or barriers, and approaches for addressing challenges.

E. Health Equity Update

1. Background

In the FY 2023 SNF PPS proposed rule (87 FR 22754 through 22760), we included an RFI entitled “Overarching Principles for Measuring Equity and Healthcare Quality Disparities Across CMS Quality Programs.” We define health equity as “the attainment of the highest level of health for all people, where everyone has a fair and just opportunity to attain their optimal health regardless of race, ethnicity, disability, sexual orientation, gender identity, socioeconomic status, geography, preferred language, or other factors that affect access to care and health outcomes.” ^[181] We are working to advance health equity by designing, implementing, and operationalizing policies and programs that support health for all the people served by our programs and models, eliminating avoidable differences in health outcomes experienced by people who are disadvantaged or underserved, and providing the care and support that our beneficiaries need to thrive. Our goals outlined in the CMS Framework for Health Equity 2022–2023  ^[182] are in line with Executive Order 13985, “Advancing Racial Equity and Support for Underserved Communities Through the Federal Government.” ^[183] The goals included in the CMS Framework for Health Equity serve to further advance health equity, expand coverage, and improve health outcomes for the more than 170 million individuals supported by our programs, and set a foundation and priorities for our work, including: strengthening our infrastructure for assessment; creating synergies across the healthcare system to drive structural change; and identifying and working to eliminate barriers to CMS-supported benefits, services, and coverage.

In addition to the CMS Framework for Health Equity, we seek to advance health equity and whole-person care as one of eight goals comprising the CMS National Quality Strategy (NQS).^[184] The NQS identifies a wide range of potential quality levers that can support our advancement of equity, including: (1) establishing a standardized approach for resident-reported data and stratification; (2) employing quality and value-based programs to address closing equity gaps; and (3) developing equity-focused data collections, analysis, regulations, oversight strategies, and quality improvement initiatives.

A goal of this NQS is to address persistent disparities that underlie our healthcare system. Racial disparities in health, in particular, are estimated to cost the U.S. $93 billion in excess medical costs and $42 billion in lost productivity per year, in addition to economic losses due to premature deaths.^[185] At the same time, racial and ethnic diversity has increased in recent years with an increase in the percentage of people who identify as two or more races accounting for most of the change, rising from 2.9 percent to 10.2 percent between 2010 and 2020.^[186] Therefore, we need to consider ways to reduce disparities, achieve equity, and support our diverse beneficiary population through the way we measure quality and display the data.

We solicited public comments via the aforementioned RFI on changes that we should consider in order to advance health equity. We refer readers to the FY 2023 SNF PPS final rule (87 FR 47553 through 47555) for a summary of the public comments and suggestions we received in response to the health equity RFI. We will take these comments into account as we continue to work to develop policies, quality measures, and measurement strategies on this important topic.

2. Anticipated Future State

We are committed to developing approaches to meaningfully incorporate the advancement of health equity into the SNF QRP. One option we are considering is including social determinants of health (SDOH) as part of new quality measures.

Social determinants of health are the conditions in the environments where people are born, live, learn, work, play, worship, and age that affect a wide range of health, functioning, and quality-of-life outcomes and risks. They may have a stronger influence on the population's health and well-being than services delivered by practitioners and healthcare delivery organizations.^[187] Measure stratification is important for understanding differences in outcomes across different groups. For example, when “pediatric measures over the past two decades are stratified by race, ethnicity, and income, they show that outcomes for children in the lowest income households and for Black and Hispanic children have improved faster than outcomes for children in the highest income households or for White children, thus narrowing an important health disparity.^[188] This analysis and comparison of the SDOH items in the assessment instruments support our desire to understand the benefits of measure stratification. Hospital providers receive such information in their confidential feedback reports and we think this learning opportunity would benefit post-acute care providers. The goals of the confidential reporting are to provide SNFs with their results; educate SNFs and offer the opportunity to ask questions; and solicit feedback from SNFs for future enhancements to the methods.

We are considering whether health equity measures we have adopted for other settings, such as hospitals, could be adopted in post-acute care settings. We are exploring ways to incorporate SDOH elements into the measure specifications. For example, we could consider a future health equity measure like screening for social needs and interventions. With 30 percent to 55 percent of health outcomes attributed to SDOH,^[189] a measure capturing and addressing SDOH could encourage SNFs to identify residents' specific needs and connect them with the community resources necessary to overcome social barriers to their wellness. We could specify a health equity measure using the same SDOH data items that we currently collect as standardized patient assessment data elements under the SNF. These SDOH data items assess health literacy, social isolation, transportation problems, and preferred language (including need or want of an interpreter). We also see value in aligning SDOH data items across all care settings as we develop future health equity quality measures under our SNF QRP statutory authority. This would further the NQS to align quality measures across our programs as part of the Universal Foundation.^[190]

As we move this important work forward, we will continue to take input from interested parties.

F. Form, Manner, and Timing of Data Submission Under the SNF QRP

1. Background

We refer readers to the current regulatory text at § 413.360(b) for information regarding the policies for reporting SNF QRP data.

2. Proposed Reporting Schedule for the Minimum Data Set (MDS) Assessment Data for the Discharge Function Score Measure Beginning With the FY 2025 SNF QRP

As discussed in section VI.C.1.b. of this proposed rule, we are proposing to adopt the DC Function measure beginning with the FY 2025 SNF QRP. We are proposing that SNFs would be required to report these MDS assessment data beginning with residents admitted and discharged on October 1, 2023 for purposes of the FY 2025 SNF QRP. Starting in CY 2024, SNFs would be required to submit data for the entire calendar year beginning with the FY 2026 SNF QRP. Because the DC Function measure is calculated based on data that are currently submitted to the Medicare program, there would be no new burden associated with data collection for this measure.

We invite public comment on this proposal.

3. Proposed Method of Data Submission and Reporting Schedule for the CoreQ: Short Stay Discharge Measure Beginning With the FY 2026 SNF QRP

a. Proposed Method of Data Submission To Meet SNF QRP Requirements Beginning With the FY 2026 Program Year

As discussed in section VI.C.2.a. of this proposed rule, we are proposing to adopt the CoreQ: SS DC measure beginning with the FY 2026 SNF QRP. We propose that Medicare-certified SNFs and all non-CAH swing bed rural hospitals would be required to contract with a third-party vendor that is CMS-trained and approved to administer the CoreQ: SS DC survey on their behalf (referred to as a “CMS-approved CoreQ survey vendor”). SNFs would be required to contract with a CMS-approved CoreQ survey vendor to ensure that the data are collected by an independent organization that is trained to collect this type of data, and given the independence of the CMS-approved CoreQ survey vendor from the SNF, ensure that the data collected are unbiased. The CMS-approved CoreQ survey vendor would be the business associate of the SNF and follow the minimum business requirements described in the Draft CoreQ: SS DC Survey Protocols and Guidelines Manual.^[191] It is important that respondents to the CoreQ: SS DC measure questionnaire are comfortable sharing their experiences with persons not directly involved in providing the care. This method of data collection has been used successfully in other settings, including for Medicare-certified home health agencies and hospices. The goal is to ensure that we have comparable data across all SNFs.

CMS-approved CoreQ survey vendors administering the CoreQ: SS DC survey would be required to offer a toll-free assistance line and an electronic mail address which respondents could use to seek help. The toll-free telephone line must have staff that can respond to questions in any language in which the CMS-approved CoreQ survey vendor is offering the CoreQ: SS DC survey. CMS-approved CoreQ survey vendors must accommodate alternate telephone communications, including a teletypewriter (TTY). Interested vendors may apply to become a CMS-approved CoreQ survey vendor beginning in Fall 2023. There will be a web page devoted specifically to the SNF CoreQ: SS DC survey and it will include information including the application process. SNFs interested in viewing similar model web pages are encouraged to visit the Hospital CAHPS website at https://hcahpsonline.org or the Home Health CAHPS website at https://homehealthcahps.org.

We propose to require SNFs to use the protocols and guidelines for the proposed CoreQ: SS DC measure as defined by the Draft CoreQ: SS Survey Protocols and Guidelines Manual in effect at the time the questionnaires are sent to eligible residents. The Draft CoreQ: SS DC Survey Protocols and Guidelines Manual is available on the SNF QRP Measures and Technical Information web page at https://www.cms.gov/​medicare/​quality-initiatives-patient-assessment-instruments/​nursinghomequalityinits/​skilled-nursing-facility-quality-reporting-program/​snf-quality-reporting-program-measures-and-technical-information. We propose that CMS-approved CoreQ survey vendors and SNFs be required to participate in CoreQ: SS DC measure oversight activities to ensure compliance with the protocols, guidelines, and questionnaire requirements. The purpose of the oversight activities is to ensure that SNFs and CMS-approved CoreQ survey vendors follow the procedures in the Draft CoreQ: SS DC Survey Protocols and Guidelines Manual.

We also propose that all CMS-approved CoreQ survey vendors develop a Quality Assurance Plan (QAP) for CoreQ: SS DC survey administration in accordance with the Draft CoreQ: SS DC Survey Protocols and Guidelines Manual.

A list of CMS-approved CoreQ survey vendors would be provided on the website devoted specifically to the SNF CoreQ: SS DC Survey as soon as technically feasible.

At § 413.360, we also propose to redesignate paragraph (b)(2) as paragraph (b)(3) and add new paragraph (b)(2) for the CoreQ: SS DC measure's data submission requirements. Finally, we propose to codify the requirements for being a CMS-approved CoreQ: SS DC survey vendor at paragraphs (b)(2)(ii) through (b)(2)(iii) in regulation. The proposed revisions are outlined in paragraph (b)(2) in the regulation text of this proposed rule.

We invite public comment on this proposal to require Medicare-certified SNFs to contract with a third-party vendor to administer the CoreQ: SS DC measure questionnaire on their behalf beginning with the FY 2026 SNF QRP.

b. Proposed Exemptions for the CoreQ: SS DC Measure Reporting Requirements Beginning With the FY 2026 Program Year

(1) Low Volume Exemptions

We are aware that there is a wide variation in the size of Medicare-certified SNFs. Therefore, we propose that SNFs with less than 60 residents, regardless of payer, discharged within 100 days of SNF admission in the prior calendar year would be exempt from the CoreQ: SS DC measure data collection and reporting requirements. A SNF's total number of short-stay discharged residents for the period of January 1 through December 31 for a given year would be used to determine if the SNF would have to participate in the CoreQ: SS DC measure in the next calendar year. To qualify for the exemptions, SNFs would be required to submit their request using the Participation Exemption Request form no later than December 31 of the CY prior to the reporting CY. These forms would be made available on a web page devoted to the SNF CoreQ: SS DC Survey.

(2) New Provider Exemptions

We also propose that newly Medicare-certified SNFs (that is, those certified on or after January 1, 2024) be excluded from the CoreQ: SS DC measure reporting requirement for CY 2024, because there would be no information from the previous CY to determine whether the SNF would be required to report or exempt from reporting the CoreQ: SS DC measure.

In future years, we are proposing that SNFs certified for Medicare participation on or after January 1 of the reporting year would be excluded from reporting on the CoreQ: SS DC measure for the applicable SNF QRP program year. For example, if a SNF is certified for Medicare participation on November 1, 2024, it would be excluded from the CY 2024 CoreQ: SS DC measure reporting requirement, and therefore, would not be subject to any payment penalty related to the SNF not reporting on the CoreQ: SS DC measure in CY 2024 for the FY 2026 SNF QRP. However, if a SNF is certified for Medicare participation on November 1, 2024, it would be required to meet the CoreQ: SS DC measure reporting requirements in CY 2025 for the FY 2027 SNF QRP unless it expects to meet the low volume exemption as described in section VI.F.3.b.(2) of this proposed rule.

We invite public comment on this proposal to exempt SNFs with less than 60 residents, regardless of payer, discharged within 100 days of SNF admission in the prior calendar year, and to exempt newly Medicare-certified SNFs in their first-year certification, from the CoreQ SS DC measure reporting requirements for the applicable SNF QRP program year.

c. Proposed Reporting Schedule for the Data Submission of the CoreQ: Short Stay Discharge Measure Beginning With the FY 2026 SNF QRP

We propose that the CoreQ: SS DC measure questionnaire be a component of the SNF QRP for the FY 2026 SNF QRP and subsequent years. To comply with the SNF QRP reporting requirements for the FY 2026 SNF QRP, we propose that SNFs would be required to collect data for the CoreQ: SS DC measure by utilizing CMS-approved CoreQ survey vendors in compliance with the proposed provisions at § 413.360(b)(2)(i) through (b)(2)(iii).

For the CoreQ: SS DC measure, we propose that SNFs would send a resident information file to the CMS-approved CoreQ survey vendor on a weekly basis so the CMS-approved CoreQ survey vendor can start administering the CoreQ: SS DC questionnaire within seven days after the reporting week closes. The resident information file, whose data is listed in Table 14, represents the minimum required information the CMS-approved CoreQ survey vendor would need to determine the residents' eligibility for the CoreQ: SS DC measure's questionnaire to administer the survey to eligible residents.

SNF name

SNF CMS Certification Number (CCN)

National Provider Identifier (NPI)

Reporting week

Reporting year

Number of eligible residents

Resident First Name

Resident Middle Initial

Resident Last Name

Resident Date of Birth

Resident Mailing Address 1

Resident Mailing Address 2

Resident address, City

Resident address, State

Resident address, Zip Code

Telephone number, including area code

Resident email address

Gender

Payer

HMO indicator

Dual eligibility indicator

End stage renal disease

Resident date of admission

Resident date of discharge

Brief Interview of Mental Status (BIMS) score

Discharge status

Left against medical advice

Court appointed guardian

Are you of Hispanic, Latino/a, or Spanish origin?

What is your race?

What is your preferred language?

For additional information about the data elements that would be included in the resident information file, see the Draft CoreQ Protocols and Guidelines Manual located at https://www.cms.gov/​medicare/​quality-initiatives-patient-assessment-instruments/​nursinghomequalityinits/​skilled-nursing-facility-quality-reporting-program/​snf-quality-reporting-program-measures-and-technical-information.

For the CoreQ: SS DC measure, we propose that SNFs would be required to meet or exceed two separate data completeness thresholds: (1) one threshold, set at 75 percent, for submission of weekly resident information files to the CMS-approved CoreQ survey vendor for the full reporting year; and (2) a second threshold, set at 90 percent, for completeness of the resident information files. In other words, SNFs would need to submit resident information files on a weekly basis that include at least 90 percent of the required data fields to their CMS-approved CoreQ survey vendors for at least 75 percent of the weeks in a reporting year. SNFs may choose to submit resident information files more frequently, but must meet the minimum threshold to avoid receiving a 2-percentage-point reduction to their Annual Payment Update (APU). Although we are proposing to adopt a 75 percent data submission and 90 percent data completeness threshold for the resident information files initially, we intend to propose to raise the threshold levels for subsequent program years through future rulemaking. We are proposing to codify this data completeness threshold requirement at our regulation at § 413.360(f)(1)(iv).

We propose an initial data submission period from January 1, 2024, through June 30, 2024. As described in Table 15 in this section of this proposed rule, in order to meet the pay-for-reporting requirement of the SNF QRP for the first half of the FY 2026 program year, SNFs would only be required to contract with a CMS-approved CoreQ survey vendor and submit one resident information file to their CMS-approved CoreQ survey vendor for at least one week during January 1, 2024 through June 30, 2024. During this period, the CMS-approved CoreQ survey vendor would follow the procedures as described in the Draft CoreQ: SS DC Survey Protocols and Guidelines Manual.^[192] Beginning July 1, 2024, SNFs would be required to submit weekly resident information files for at least 75 percent of the weeks remaining in CY 2024.

Table 15—Proposed Participation Requirements for the CoreQ: Short Stay Discharge Measure Beginning With the FY 2026 SNF QRP

Data submission quarters	Proposed data submission frequency	Quarterly data submission deadlines	FY 2026 SNF APU compliance thresholds
Q1 2024: January 1, 2024 through March 31, 2024 Q2 2024: April 1, 2024 through June 30, 2024	At least one week during either data submission quarter	August 15, 2024   November 15, 2024.	At least one weekly resident information file containing at least 90% of the required resident information for one resident discharged within 100 days of admission.
Q3 2024: July 1, 2024 through September 30, 2024	No less than weekly	February 18, 2025	A minimum of 18 weekly resident information files that contain at least 90% of required resident information.193
Q4 2024: October 1, 2024 through December 31, 2024	No less than weekly	May 15, 2025

Starting in CY 2025, SNFs would be required to submit resident information files no less than weekly for the entire calendar year beginning with the FY 2027 SNF QRP, as described in Table 16 in this section of this proposed rule.

Table 16—Proposed Participation Requirements for the CoreQ: Short Stay Discharge Measure Beginning With the FY 2027 SNF QRP

Data submission quarters	Proposed data submission frequency	Quarterly data submission deadlines	FY 2027 SNF APU compliance thresholds
Q1 2025: January 1, 2025 through March 31, 2025	No less than weekly	August 15, 2025	A minimum of 35 weekly resident information files that contain at least 90% of required resident information.194
Q2 2025: April 1, 2025 through June 30, 2025	No less than weekly	November 17, 2025.
Q3 2025: July 1, 2025 through September 30, 2025	No less than weekly	February 16, 2026.
Q4 2025: October 1, 2025 through December 31, 2025	No less than weekly	May 15, 2026.

We are proposing that the CMS-approved CoreQ survey vendor administer the CoreQ: SS DC measure's questionnaire to discharged residents within 2 weeks of their discharge date through the U.S. Postal Service or by telephone. If administered by mail, the questionnaires must be returned to the CMS-approved CoreQ survey vendor within 2 months of the resident's discharge date from the SNF.

Although the CMS-approved CoreQ survey vendor would administer the CoreQ: SS DC measure's survey on a SNF's behalf, each SNF would be responsible for ensuring required data is collected and submitted to CMS in accordance with the SNF QRP's requirements. We strongly suggest that SNFs that submit their CoreQ: SS DC measure resident information files to their CMS-approved CoreQ survey vendor follow up with their CMS-approved CoreQ survey vendor to make sure the CMS-approved CoreQ survey vendor submits its CoreQ: SS DC survey information files to the CoreQ Survey Data Center well in advance of each quarterly data submission deadline. Each submitted CoreQ: SS DC survey information file would undergo validation checks before it is accepted, and if it does not pass, the CoreQ: SS DC survey information file would be rejected. Submission of CoreQ: SS DC survey information files early in the data submission period would allow the CMS-approved CoreQ survey vendor to correct any problems detected and resubmit the CoreQ: SS DC survey information file(s) to the CoreQ Survey Data Center before the deadline. We would not allow any CoreQ: SS DC survey information files to be submitted to the CoreQ Survey Data Center after the SNF QRP data submission deadline ends. However, in the event of extraordinary circumstances beyond the control of the provider, the SNF would be able to request an exemption set forth in § 413.360(c). More information on how to request an exemption can be found on the SNF QRP Reconsideration and Exception & Extension web page.^[195]

We also recommend that SNFs submitting CoreQ: SS DC resident information files to their CMS-approved CoreQ survey vendor promptly review the Data Submission Summary Reports that are described in the Draft CoreQ: SS DC Survey Protocols and Guidelines Manual.^[196] These reports will enable the SNF to ensure that its CMS-approved CoreQ survey vendor has submitted its data on time, and that the data have been accepted by the CoreQ Data Center. For more information about the SNF QRP data submission deadlines for each CY quarter, we refer readers to the FY 2016 SNF PPS final rule (80 FR 46427 through 46429).

We invite public comment on the proposed schedule for data submission and the participation requirements for the CoreQ: Short Stay Discharge Measure beginning with the FY 2026 SNF QRP.

4. Proposed Reporting Schedule for the Data Submission of Minimum Data Set (MDS) Assessment Data for the COVID–19 Vaccine: Percent of Patients/Residents Who Are Up to Date Measure Beginning With the FY 2026 SNF QRP

As discussed in section VI.C.2.b. of this proposed rule, we are proposing to adopt the Patient/Resident COVID–19 Vaccine measure beginning with the FY 2026 SNF QRP. We are proposing that SNFs would be required to report this new MDS assessment data item beginning with Medicare Part A residents discharged on October 1, 2024 for purposes of the FY 2026 SNF QRP. Starting in CY 2025, SNFs would be required to submit data for the entire calendar year beginning with the FY 2027 SNF QRP.

We are also proposing to add a new item to the MDS in order for SNFs to report the proposed Patient/Resident COVID–19 Vaccine measure. Specifically, a new item would be added to the MDS discharge item sets to collect information on whether a resident is up to date with their COVID–19 vaccine at the time of discharge from the SNF. A draft of the new item is available in the COVID–19 Vaccine: Percent of Patients/Residents Who Are Up to Date Draft Measure Specifications.^[197]

We invite public comment on this proposal.

5. Proposal To Increase the SNF QRP Data Completion Thresholds for MDS Data Items Beginning With the FY 2026 SNF QRP

In the FY 2016 SNF PPS final rule (80 FR 46458), we finalized that SNFs would need to complete 100 percent of the data on 80 percent of MDSs submitted in order to be in compliance with the SNF QRP reporting requirements for the applicable program year, as codified in regulation at § 413.360(f). We established this data completion threshold because SNFs were accustomed to submitting MDS assessments for other purposes and they should easily be able to meet this requirement for the SNF QRP. We also noted at that time our intent to raise the proposed 80 percent threshold in subsequent program years.^[198]

We are now proposing that, beginning with the FY 2026 SNF QRP, SNFs would be required to report 100 percent of the required quality measure data and standardized patient assessment data collected using the MDS on at least 90 percent of the assessments they submit through the CMS-designated submission system.

Complete data are needed to help ensure the validity and reliability of SNF QRP data items, including risk-adjustment models. The proposed threshold of 90 percent is based on the need for substantially complete records, which allows appropriate analysis of SNF QRP measure data for the purposes of updating quality measure specifications as they undergo yearly and triennial measure maintenance reviews with the CBE. Additionally, we want to ensure complete SNF QRP measure data from SNFs, which will ultimately be reported to the public, allowing our beneficiaries to gain a more complete understanding of SNF performance related to these metrics, helping them to make informed healthcare choices. Finally, this proposal would contribute to further alignment of data completion thresholds across the PAC settings.

We believe SNFs should be able to meet this proposed requirement for the SNF QRP. Our data suggest that the majority of SNFs are already in compliance with, or exceeding, this proposed threshold. The complete list of items required under the SNF QRP is updated annually and posted on the SNF QRP Measures and Technical Information page.^[199]

We are proposing that SNFs would be required to comply with the proposed new data completion threshold beginning with the FY 2026 SNF QRP. Starting in CY 2024, SNFs would be required to report 100 percent of the required quality measures data and standardized patient assessment data collected using the MDS on at least 90 percent of all assessments submitted January 1 through December 31 for that calendar year's payment determination. Any SNF that does not meet the proposed requirement will be subject to a reduction of 2 percentage points to the applicable FY APU beginning with the FY 2026 SNF QRP. We are proposing to update § 413.360(f) of our regulations to reflect this new policy, as well as to clarify and make non-substantive edits to improve clarity of the regulation.

We invite public comment on the proposed schedule for the increase of SNF QRP data completion thresholds for the MDS data items beginning with the FY 2026 program year.

G. Proposed Policies Regarding Public Display of Measure Data for the SNF QRP

1. Background

Section 1899B(g) of the Act requires the Secretary to establish procedures for making the SNF QRP data available to the public, including the performance of individual SNFs, after ensuring that SNFs have the opportunity to review their data prior to public display. For a more detailed discussion about our policies regarding public display of SNF QRP measure data and procedures for the SNF's opportunity to review and correct data and information, we refer readers to the FY 2017 SNF PPS final rule (81 FR 52045 through 52048).

2. Proposed Public Reporting of the Transfer of Health Information to the Provider—Post-Acute Care Measure and Transfer of Health Information to the Patient—Post-Acute Care Measure Beginning With the FY 2025 SNF QRP

We are proposing to begin publicly displaying data for the measures: (1) Transfer of Health (TOH) Information to the Provider—Post-Acute Care (PAC) Measure (TOH-Provider); and (2) TOH Information to the Patient—PAC Measure (TOH-Patient) beginning with the October 2025 Care Compare refresh or as soon as technically feasible.

We adopted these measures in the FY 2020 SNF PPS final rule (84 FR 38761 through 38764). In response to the COVID–19 PHE, we released an Interim Final Rule (85 FR 27595 through 27597) which delayed the compliance date for collection and reporting of the TOH-Provider and TOH-Patient measures to October 1 of the year that is at least two full fiscal years after the end of the COVID–19 PHE. Subsequently, in the FY 2023 SNF PPS final rule (87 FR 47502), the compliance date for the collection and reporting of the TOH-Provider and TOH-Patient measures was revised to October 1, 2023. Data collection for these two assessment-based measures will begin with residents discharged on or after October 1, 2023.

We are proposing to publicly display data for these two assessment-based measures based on four rolling quarters of data, initially using discharges from January 1, 2024, through December 31, 2024 (Quarter 1 2024 through Quarter 4 2024), and to begin publicly reporting these measures with the October 2025 refresh of Care Compare, or as soon as technically feasible. To ensure the statistical reliability of the data, we are proposing that we would not publicly report a SNF's performance on a measure if the SNF had fewer than 20 eligible cases in any four consecutive rolling quarters for that measure. SNFs that have fewer than 20 eligible cases would be distinguished with a footnote that states: “The number of cases/resident stays is too small to report.”

We invite public comment on our proposal for the public display of the (1) Transfer of Health (TOH) Information to the Provider—Post-Acute Care (PAC) Measure (TOH-Provider), and (2) Transfer of Health (TOH) Information to the Patient—Post-Acute Care (PAC) Measure (TOH-Patient) assessment-based measures.

3. Proposed Public Reporting of the Discharge Function Score Measure Beginning With the FY 2025 SNF QRP

We are proposing to begin publicly displaying data for the DC Function measure beginning with the October 2024 refresh of Care Compare, or as soon as technically feasible, using data collected from January 1, 2023 through December 31, 2023 (Quarter 1 2023 through Quarter 4 2023). If finalized as proposed, a SNF's DC Function score would be displayed based on four quarters of data. Provider preview reports would be distributed in July 2024, or as soon as technically feasible. Thereafter, a SNF's DC Function score would be publicly displayed based on four quarters of data and updated quarterly. To ensure the statistical reliability of the data, we are proposing that we would not publicly report a SNF's performance on the measure if the SNF had fewer than 20 eligible cases in any quarter. SNFs that have fewer than 20 eligible cases would be distinguished with a footnote that states: “The number of cases/resident stays is too small to report.”

We invite public comment on the proposal for the public display of the Discharge Function Score assessment-based measure beginning with the October 2024 refresh of Care Compare, or as soon as technically feasible.

4. Proposed Public Reporting of the COVID–19 Vaccine: Percent of Patients/Residents Who Are Up to Date Measure Beginning With the FY 2026 SNF QRP

We are proposing to begin publicly displaying data for the COVID–19 Vaccine: Percent of Patients/Residents Who Are Up to Date measure beginning with the October 2025 refresh of Care Compare or as soon as technically feasible using data collected for Q4 2024 (October 1, 2024 through December 31, 2024). A SNF's Patient/Resident COVID–19 Vaccine percent of residents who are up to date would be displayed based on one quarter of data. Provider preview reports would be distributed in July 2025 for data collected in Q4 2024, or as soon as technically feasible. Thereafter, the percent of SNF residents who are up to date with their COVID–19 vaccinations would be publicly displayed based on one quarter of data updated quarterly. To ensure the statistical reliability of the data, we are proposing that we would not publicly report a SNF's performance on the measure if the SNF had fewer than 20 eligible cases in any quarter. SNFs that have fewer than 20 eligible cases would be distinguished with a footnote that states: “The number of cases/resident stays is too small to report.”

We invite public comment on the proposal for the public display of the COVID–19 Vaccine: Percent of Patients/Residents Who Are Up to Date measure beginning with the October 2025 refresh of Care Compare, or as soon as technically feasible.

VII. Skilled Nursing Facility Value-Based Purchasing (SNF VBP) Program: Proposed Policy Changes

A. Statutory Background

Through the Skilled Nursing Facility Value-Based Purchasing (SNF VBP) Program, we award incentive payments to SNFs to encourage improvements in the quality of care provided to Medicare beneficiaries. The SNF VBP Program is authorized by section 1888(h) to the Act, and it applies to freestanding SNFs, SNFs affiliated with acute care facilities, and all non-CAH swing bed rural hospitals. We believe the SNF VBP Program has helped to transform how Medicare payment is made for SNF care, moving increasingly towards rewarding better value and outcomes instead of merely rewarding volume. Our codified policies for the SNF VBP Program can be found in our regulations at 42 CFR 413.337(f) and 413.338.

B. SNF VBP Program Measures

1. Background

For background on the measures we have adopted for the SNF VBP Program, we refer readers to the following prior final rules:

• In the FY 2016 SNF PPS final rule (80 FR 46411 through 46419), we finalized the Skilled Nursing Facility 30-Day All-Cause Readmission Measure (SNFRM) as required under section 1888(g)(1) of the Act.
• In the FY 2017 SNF PPS final rule (81 FR 51987 through 51995), we finalized the Skilled Nursing Facility 30-Day Potentially Preventable Readmission (SNFPPR) Measure as required under section 1888(g)(2) of the Act.
• In the FY 2020 SNF PPS final rule (84 FR 38821 through 38822), we updated the name of the SNFPPR measure to the “Skilled Nursing Facility Potentially Preventable Readmissions after Hospital Discharge measure” (§ 413.338(a)(14)).
• In the FY 2021 SNF PPS final rule (85 FR 47624), we amended the definition of “SNF Readmission Measure” in our regulations to reflect the updated name for the SNFPPR measure.
• In the FY 2022 SNF PPS final rule (86 FR 42503 through 42507), we finalized a measure suppression policy for the duration of the PHE for COVID–19, and finalized suppression of the SNFRM for scoring and payment purposes for the FY 2022 SNF VBP Program. We also updated the lookback period for risk-adjustment in the FY 2023 performance period (FY 2021).

• In the FY 2023 SNF PPS final rule (87 FR 47559 through 47580), we finalized suppression of the SNFRM for scoring and payment purposes for the FY 2023 SNF VBP Program. We also modified the SNFRM beginning with the FY 2023 program year by adding a risk-adjustment variable for both patients with COVID–19 during the prior proximal hospitalization (PPH) and patients with a history of COVID–19. We also finalized three new quality measures for the SNF VBP Program as permitted under section 1888(h)(2)(A)(ii) of the Act. We finalized two new measures beginning with the FY 2026 program year: (1) Skilled Nursing Facility Healthcare Associated Infections Requiring Hospitalization (SNF HAI) measure; and (2) Total Nursing Hours per Resident Day Staffing (Total Nurse Staffing) measure. We finalized an additional measure beginning with the FY 2027 program year: Discharge to Community—Post-Acute Care Measure for Skilled Nursing Facilities (DTC PAC SNF) measure.

2. Proposal To Refine the SNFPPR Measure Specifications and Update the Measure Name

a. Background

Section 1888(g)(2) of the Act requires the Secretary to specify a resource use measure that reflects an all-condition, risk-adjusted potentially preventable hospital readmission rate for skilled nursing facilities. To meet this statutory requirement, we finalized the Skilled Nursing Facility Potentially Preventable Readmission (SNFPPR) measure in the FY 2017 SNF PPS final rule (81 FR 51987 through 51995). In the FY 2020 SNF PPS final rule (84 FR 38821 through 38822), we updated the SNFPPR measure name to the Skilled Nursing Facility Potentially Preventable Readmissions after Hospital Discharge measure, while maintaining SNFPPR as the measure short name.

Although our testing results indicated that the SNFPPR measure was sufficiently developed, valid, and reliable for use in the SNF VBP at the time we adopted it, we have since engaged in additional measure development work to further align the measure's specifications with the specifications of other potentially preventable readmission (PPR) measures, including the SNF PPR post-discharge (PD) measure specified for the SNF QRP, and the within-stay PPR measure used in the IRF QRP. Based on those efforts, we are now proposing to refine the SNFPPR measure specifications as follows: (1) we are proposing to change the outcome observation window from a fixed 30-day window following acute care hospital discharge to within the SNF stay; and (2) we are proposing to change the length of time allowed between a qualifying prior proximal inpatient discharge (that is, the inpatient discharge that occurs prior to admission to the index SNF stay) and SNF admission from one day to 30 days. To align with those measure refinements, we are also proposing to update the measure name to the “Skilled Nursing Facility Within-Stay Potentially Preventable Readmission (SNF WS PPR) Measure.”

b. Overview of the Proposed Updated Measure

The SNF WS PPR measure estimates the risk-standardized rate of unplanned, potentially preventable readmissions (PPR) that occur during SNF stays among Medicare FFS beneficiaries. Specifically, this outcome measure reflects readmission rates for residents who are readmitted to a short-stay acute-care hospital or long-term care hospital (LTCH) with a principal diagnosis considered to be unplanned and potentially preventable while within SNF care. The measure is risk-adjusted and calculated using 2 consecutive years of Medicare FFS claims data.

We have tested the proposed updated SNF WS PPR measure for reliability and validity. The random split-half correlation tests indicated good reliability with the intraclass correlation coefficient being notably better than that of the SNFRM. In addition, we tested the validity of the SNF WS PPR measure by comparing SNF WS PPR measure scores with those of nine other measures. The testing results indicated that the SNF WS PPR measure is not duplicative of those nine measures and provides unique information about quality of care not captured by the other nine measures. Validity tests also showed that the measure can accurately predict PPRs while controlling for differences in resident case-mix. We refer readers to the SNF WS PPR measure technical specifications available at https://www.cms.gov/​files/​document/​snfvbp-snfwsppr-draft-technical-measure-specification.pdf.

(1) Measure Applications Partnership (MAP) Review

We included the SNF WS PPR measure as a SNF VBP measure under consideration in the publicly available “2022 Measures Under Consideration List.” ^[200] The MAP offered conditional support of the SNF WS PPR measure for rulemaking, contingent upon endorsement by the consensus-based entity, noting that the measure would add value to the Program because PPRs are disruptive and burdensome to patients. We refer readers to the final 2022–2023 MAP recommendations for further details available at https://mmshub.cms.gov/​measure-lifecycle/​measure-implementation/​pre-rulemaking/​lists-and-reports.

c. Data Sources

The SNF WS PPR measure is calculated using 2 consecutive years of Medicare FFS claims data to estimate the risk-standardized rate of unplanned PPRs that occur during SNF stays. Specifically, the stay construction, exclusions, and risk-adjustment model utilize data from the Medicare eligibility files and inpatient hospital claims. Calculating the SNF WS PPR measure using 2 years of data improved the measure's statistical reliability relative to 1 year of data, which is used in the current version of the SNFPPR measure. Because the SNF WS PPR measure is calculated entirely using administrative data, our proposed adoption of the measure would not impose any additional data collection or submission burden for SNFs.

d. Measure Specifications

(1) Denominator

The population included in the measure denominator is Medicare FFS beneficiaries who are admitted to a SNF during a 2-year measurement period who are not then excluded based on the measure exclusion criteria, which we describe in the next section. For SNF residents with multiple SNF stays during the 2-year readmission window, each of those SNF stays is eligible for inclusion in the measure. In addition, the index SNF admission must have occurred within 30 days of discharge from a prior proximal hospital (PPH) stay, which is defined in the measure specifications as an inpatient stay in an IPPS hospital, a CAH, or an inpatient psychiatric facility. Residents who expire during the readmission window are included in the measure.

The measure denominator is the risk-adjusted “expected” number of residents with a PPR that occurred during the SNF stay. This estimate includes risk adjustment for certain resident characteristics without the facility effect, which we further discuss in section VII.B.2.e. of this proposed rule. The “expected” number of residents with a PPR is derived from the predicted number of residents with a PPR if the same residents were treated at the average SNF, which is defined for purposes of this measure as a SNF whose facility effect is zero.

(2) Denominator Exclusions

A SNF stay is excluded from the measure denominator if it meets at least one of the following conditions:

• The SNF resident is less than 18 years old.

• The SNF resident did not have at least 12 months of continuous FFS Medicare enrollment prior to SNF admission, which is defined as the month of SNF admission and the 11 months prior to that admission.

• The SNF resident did not have continuous FFS Medicare enrollment for the entire risk period (defined as enrollment during the month of SNF admission through the month of SNF discharge).
• SNF stays where there was a gap of greater than 30 days between discharge from the PPH and the SNF admission.
• The SNF resident was discharged from the SNF against medical advice.
• SNF stays in which the principal diagnosis for the PPH was for the medical treatment of cancer. Residents with cancer whose principal diagnosis from the PPH was for other medical diagnoses or for surgical treatment of their cancer remain included in the measure).
• SNF stays in which the principle diagnosis for the PPH was for pregnancy (this is an atypical reason for resident to be admitted to SNFs).
• The SNF resident who the SNF subsequently transfers to a Federal hospital. A transfer to a Federal hospital is identified when discharge code 43 is entered for the patient discharge status field on the Medicare claim.
• The SNF resident received care from a provider outside of the United States, Puerto Rico, or a U.S. territory, as identified by the provider's CCN on the Medicare claim.
• SNF stays with data that are problematic (for example, anomalous records for hospital stays that overlap wholly or in part or are otherwise erroneous or contradictory).
• SNF stays that occurred in a CAH swing bed.

For additional details on the denominator exclusions, we refer readers to the SNF WS PPR measure technical specifications available at https://www.cms.gov/​files/​document/​snfvbp-snfwsppr-draft-techical-specification.pdf.

(3) Numerator

The numerator is defined as the number of SNF residents included in the measure denominator who also have an unplanned PPR during an index SNF stay. For the purposes of this measure, an unplanned PPR is defined as a readmission from a SNF to an acute care hospital or a long-term care hospital, with a diagnosis considered to be unplanned and potentially preventable. The numerator only includes unplanned PPRs that occur during the within-SNF stay period (that is, from the date of the SNF admission through and including the date of discharge), which can be a hospital readmission that occurs within the SNF stay or a direct transfer to a hospital on the date of the SNF discharge. Because this measure focuses on potentially preventable and unplanned readmissions, we do not count planned readmissions in the numerator. Further, because we consider readmissions to inpatient psychiatric facilities to be planned, they are also not counted in the numerator.

The measure numerator is the risk-adjusted “predicted” estimate of the number of residents with an unplanned PPR that occurred during a SNF stay. This estimate starts with the unadjusted, observed count of the measure outcome (the number of residents with an unplanned PPR during a SNF stay), which is then risk-adjusted for resident characteristics and a statistical estimate of the SNF's facility effect, to become the risk-adjusted numerator.

e. Risk Adjustment

The SNF WS PPR measure is risk-adjusted to control for risk factor differences across SNF residents and SNF facilities. Specifically, the statistical model utilizes a hierarchical logistic regression to estimate the effect of resident characteristics on the probability of readmission across all SNFs and the effect of each SNF on readmissions that differs from that of the average SNF (“facility effect”). The denominator is risk-adjusted for resident characteristics only, while the numerator is risk-adjusted for both resident characteristics and the facility effect. The specific risk adjustment variables included in the statistical model for this measure are the following:

• Age and sex category.
• Original reason for Medicare entitlement (disability or other).
• Indicator of End-Stage Renal Disease (ESRD).
• Surgery category if present (for example, cardiothoracic, orthopedic), as defined in the Hospital Wide Readmission (HWR) measure model software. The surgical procedures are grouped using the Clinical Classification Software (CCS) classes for ICD–10 procedures developed by the Agency for Healthcare Research and Quality (AHRQ).
• Principal diagnosis on PPH inpatient claim. The ICD–10 codes are grouped clinically using the CCS mappings developed by AHRQ.
• Comorbidities from secondary diagnoses on the PPH inpatient claim and diagnoses from earlier hospital inpatient claims up to 1 year before the date of the index SNF admission (these are clustered using the Hierarchical Condition Categories (HCC) groups used by CMS).
• Length of stay in the PPH stay (categorical to account for nonlinearity).
• Prior acute intensive care unit (ICU) or critical care unit (CCU) utilization.
• Number of prior acute care hospital discharges in the prior year.

For additional details on the risk adjustment model, we refer readers to the SNF WS PPR measure technical specifications available at https://www.cms.gov/​files/​document/​snfvbp-snfwsppr-draft-techical-specification.pdf.

f. Measure Calculation

The SNF WS PPR measure estimates the risk-standardized rate of unplanned PPRs that occur during SNF stays among Medicare FFS beneficiaries. A lower score on this measure indicates better performance. The provider-level risk-standardized readmission rate (RSRR) of unplanned PPRs is calculated by multiplying the standardized risk ratio (SRR) by the mean readmission rate in the population (that is, all Medicare FFS residents included in the measure). The SRR is calculated as the predicted number of readmissions at the SNF divided by the expected number of readmissions for the same residents if treated at the average SNF. For additional details on the calculation method, we refer readers to the SNF WS PPR measure technical specifications available at https://www.cms.gov/​files/​document/​snfvbp-snfwsppr-draft-techical-specification.pdf.

g. Proposed Scoring of SNF Performance on the SNF WS PPR Measure

(1) Background

In the FY 2017 SNF PPS final rule (81 FR 52000 through 52001), we finalized a policy to invert SNFRM measure rates such that a higher measure rate reflects better performance on the SNFRM. In that final rule, we also stated our belief that this inversion is important for incentivizing improvement in a clear and understandable manner, and because a “lower is better” rate could cause confusion among SNFs and the public. In the FY 2023 SNF PPS final rule (87 FR 47568), we applied this policy to the SNF HAI measure such that a higher measure rate reflects better performance on the SNF HAI measure. We also stated our intent to apply this inversion scoring policy to all measures in the Program for which the calculation produces a “lower is better” measure rate. We continue to believe that inverting measure rates such that a higher measure rate reflects better performance on a measure is important for incentivizing improvement in a clear and understandable manner.

The measure rate inversion scoring policy does not change the measure specifications or the calculation method. We use this measure rate inversion only as part of the scoring methodology under the SNF VBP Program. The measure rate inversion is part of the methodology we use to generate measure scores, and resulting SNF Performance Scores, that are clear and understandable for SNFs and the public.

(2) Proposal To Invert the SNF WS PPR Measure Rate for SNF VBP Scoring Purposes

In the previous section, we stated that a lower risk-standardized rate for the SNF WS PPR measure indicates better performance. Therefore, we are proposing to apply our measure rate inversion scoring policy to the SNF WS PPR measure because a “lower is better” rate could cause confusion among SNFs and the public. Specifically, we are proposing to calculate the scores for this measure for the SNF VBP Program by inverting the SNF WS PPR measure rates using the following calculation:

SNF WS PPR Inverted Rate = 1−Facility's SNF WS PPR Risk Standardized Rate

This calculation would invert SNF WS PPR measure rates such that a higher measure rate would reflect better performance.

h. Confidential Feedback Reports and Public Reporting for the Proposed SNF WS PPR Measure

Our confidential feedback reports and public reporting policies are codified at § 413.338(f) of our regulation. In the FY 2023 SNF PPS final rule (87 FR 47591 through 47592), we revised our regulations such that the confidential feedback reports and public reporting policies apply to each measure specified for a fiscal year, which includes the proposed SNF WS PPR measure beginning with the FY 2028 program year.

We invite public comment on our proposal to refine the measure specifications for the SNFPPR measure, and our proposal to update the measure's name to the “Skilled Nursing Facility Within-Stay Potentially Preventable Readmissions (SNF WS PPR) measure.” We also invite public comment on our proposal to invert the SNF WS PPR measure rate for SNF VBP Program scoring purposes.

3. Proposal To Replace the SNFRM With the SNF WS PPR Measure Beginning With the FY 2028 SNF VBP Program Year

Section 1888(h)(2)(B) of the Act requires the Secretary to apply the measure specified under section 1888(g)(2) of the Act, instead of the measure specified under section 1888(g)(1) of the Act as soon as practicable. To meet that statutory requirement, we are proposing to replace the SNFRM with the proposed SNF WS PPR measure beginning with the FY 2028 program year. This is the first program year that we can feasibly implement the SNF WS PPR measure after taking into consideration its proposed performance period and a number of other statutory requirements.

We are proposing a 2-year performance period for the proposed SNF WS PPR, and we believe the earliest the first performance period can occur is FY 2025 and FY 2026 (October 1, 2024 through September 30, 2026). This would provide us with sufficient time to calculate and announce the performance standards for the proposed SNF WS PPR measure at least 60 days before the beginning of that performance period, as required under section 1888(h)(3)(C) of the Act. Additionally, we are required under section 1888(h)(7) of the Act to announce the net payment adjustments for SNFs no later than 60 days prior to the start of the applicable fiscal year. We calculate these payment adjustments using performance period data. To provide us with sufficient time to calculate and announce the net payment adjustments after the end of the proposed performance period (FY 2025 and FY 2026), we believe the earliest program year in which we can feasibly adopt the proposed SNF WS PPR measure is FY 2028.

We invite public comment on our proposal to replace the SNFRM with the SNF WS PPR measure beginning with the FY 2028 SNF VBP program year.

4. Quality Measure Proposals for the SNF VBP Expansion Beginning With the FY 2026 Program Year

a. Background

Section 1888(h)(2)(A)(ii) of the Act (as amended by section 111(a)(2)(C) of the CAA 2021) allows the Secretary to expand the SNF VBP Program to include up to 10 quality measures with respect to payments for services furnished on or after October 1, 2023. These measures may include measures of functional status, patient safety, care coordination, or patient experience. Section 1888(h)(2)(A)(ii) of the Act also requires that the Secretary consider and apply, as appropriate, quality measures specified under section 1899B(c)(1) of the Act.

In the FY 2023 SNF PPS final rule (87 FR 47564 through 47580), we adopted the first three measures for the Program expansion: (1) SNF HAI measure; (2) Total Nurse Staffing measure; and (3) DTC PAC SNF measure. We adopted the SNF HAI and Total Nurse Staffing measures beginning with the FY 2026 program year (FY 2024 is the first performance period). We also adopted the DTC PAC SNF measure beginning with the FY 2027 program year (FY 2024 and FY 2025 is the first performance period).

In this proposed rule, we are proposing to adopt four additional measures for the Program. We are proposing to adopt one new measure beginning with the FY 2026 program year (FY 2024 would be the first performance period): Total Nursing Staff Turnover (“Nursing Staff Turnover”) measure. We are also proposing to adopt three new measures beginning with the FY 2027 program year (FY 2025 would be the first performance period): (1) Percent of Residents Experiencing One or More Falls with Major Injury (Long-Stay) (“Falls with Major Injury (Long-Stay)”) measure; (2) Discharge Function Score for SNFs (“DC Function measure”); and (3) Number of Hospitalizations per 1,000 Long Stay Resident Days (“Long Stay Hospitalization”) measure.

Therefore, for the FY 2024 performance period, SNF data would be collected for five measures: SNFRM, SNF HAI, Total Nurse Staffing, Nursing Staff Turnover, and DTC PAC SNF measures. Performance on the first four measures would affect SNF payment in the FY 2026 program year. Since the DTC PAC SNF measure is a 2-year measure, performance on that measure would affect SNF payment in the FY 2027 program year.

Beginning with the FY 2025 performance period, SNF data would be collected for nine measures: SNFRM, SNF HAI, Total Nurse Staffing, Nursing Staff Turnover, DC Function, Falls with Major Injury (Long-Stay), Long Stay Hospitalization, DTC PAC SNF, and SNF WS PPR measures. Performance on the first seven measures would affect SNF payment in the FY 2027 program year. Since the DTC PAC SNF and SNF WS PPR measures are 2-year measures, performance on those measures would affect SNF payment in the FY 2028 program year. Further, we refer readers to section VII.B.3. of this proposed rule for additional details on our proposal to replace the SNFRM with the SNF WS PPR measure beginning with the FY 2028 program year, as required by statute, which would mean that the FY 2027 and FY 2028 program years would each only have eight measures that would affect SNF payment for those program years. Finally, there is no additional burden on SNFs to submit data on these previously adopted and proposed measures for the SNF VBP Program.

Table 17 provides the list of the currently adopted and newly proposed measures for the SNF VBP Program.

Table 17—Currently Adopted and Proposed New SNF VBP Measures

Measure name	Measure short name	Measure status	First program year	First performance period *
SNF 30-Day All-Cause Readmission Measure	SNFRM	Adopted, implemented	FY 2017 **	FY 2015.
SNF Healthcare-Associated Infections Requiring Hospitalization Measure	SNF HAI Measure	Adopted, not implemented	FY 2026	FY 2024.
Total Nurse Staffing Hours per Resident Day Measure	Total Nurse Staffing Measure	Adopted, not implemented	FY 2026	FY 2024.
Total Nursing Staff Turnover Measure	Nursing Staff Turnover Measure	Proposed	FY 2026 +	FY 2024.
Discharge to Community—Post-Acute Care Measure for SNFs	DTC PAC SNF Measure	Adopted, not implemented	FY 2027	FY 2024 and FY 2025.
Percent of Residents Experiencing One or More Falls with Major Injury (Long-Stay) Measure	Falls with Major Injury (Long-Stay) Measure	Proposed	FY 2027 +	FY 2025.
Discharge Function Score for SNFs Measure	DC Function Measure	Proposed	FY 2027 +	FY 2025.
Number of Hospitalizations per 1,000 Long Stay Resident Days Measure	Long Stay Hospitalization Measure	Proposed	FY 2027 +	FY 2025.
SNF Within-Stay Potentially Preventable Readmissions Measure	SNF WS PPR Measure	Proposed	FY 2028 +	FY 2025 and FY 2026.
* For each measure, we have adopted or are proposing to adopt a policy to automatically advance the beginning of the performance period by 1-year from the previous program year. We refer readers to section VII.C.3 of this proposed rule for additional information.
** Proposed to be replaced with the SNF WS PPR measure beginning with the FY 2028 program year.
+  Proposed first program year in which the measure would be included in the Program.

b. Proposal To Adopt the Total Nursing Staff Turnover Measure Beginning With the FY 2026 SNF VBP Program Year

We are proposing to adopt the Total Nursing Staff Turnover Measure (“Nursing Staff Turnover measure”) beginning with the FY 2026 SNF VBP program year.

(1) Background

Nursing home staffing, including nursing staff turnover, has long been considered an important indicator of nursing home quality.^{[201 202 203]} Longer-tenured nursing staff are more familiar with the residents and are better able to detect changes in a resident's condition. They are also more acclimated to their facility's procedures and thus, operate more efficiently. In contrast, higher nursing staff turnover can mean that nursing staff are less familiar with resident needs and facility procedures, which can contribute to lower quality of care.

There is considerable evidence demonstrating the impact of nursing staff turnover on resident outcomes, with higher turnover associated with poorer quality of care.^{[204 205 206 207 208 209 210]} A recent 2019 study comparing nursing home's annualized turnover rates with the overall five-star ratings for the facilities found that the average total nursing staff annual turnover rates were 53.4 percent among one-star nursing homes and 40.7 percent for five-star facilities.^[211] The same study found a statistically significant relationship between higher turnover rates and lower performance on clinical quality measures, including hospitalization rates, readmission rates, and emergency department visits.^[212] Studies have also shown that nursing staff turnover is a meaningful factor in nursing home quality of care and that staff turnover influences quality outcomes.^[213 214] For example, higher staff turnover is associated with an increased likelihood of receiving an infection control citation.^[215]

Recently, the National Academies of Sciences, Engineering, and Medicine formed the Committee on the Quality of Care in Nursing homes to examine the delivery of care and the complex array of factors that influence the quality of care in nursing homes. The committee published a report in 2022 titled “The National Imperative to Improve Nursing Home Quality.” The report details the complex array of factors that influence care quality in nursing homes, including staffing variables such as staffing levels and turnover, and identifies several broad goals and recommendations to improve the quality of care in nursing homes.^[216] In the 2022 report, the National Academies of Sciences, Engineering, and Medicine highlighted the association between the high turnover of many nursing home staff, including RNs, and lower quality of care delivery in nursing homes.^[217] The report also recognized the need for quality measures that report on turnover rates, citing that increased transparency will improve patient care. Because of its central role in the quality of care of Medicare beneficiaries, HHS and the Biden-Harris Administration are also committed to improving the quality of care in nursing homes with respect to staffing, as stated in the fact sheets entitled “Protecting Seniors by Improving Safety and Quality of Care in the Nation's Nursing Homes” and “Biden-Harris Administration Announces New Steps to Improve Quality of Nursing Homes.” ^[218 219] While much of this research has been conducted in long-term care facilities or nursing homes, we believe this research is relevant to the SNF setting, because approximately 94 percent of long-term care facilities are dually certified as both SNFs and nursing facilities (86 FR 42508).

In light of the strong association between high nursing staff turnover rates and negative resident outcomes, including the nursing staff turnover measure in the SNF VBP Program would provide a comprehensive assessment of the quality of care provided to residents. This measure would also drive improvements in nursing staff turnover that are likely to translate into positive resident outcomes.

Although the proposed Nursing Staff Turnover measure is not specified under section 1899B(c)(1) of the Act, we believe this measure supports the Program's goals to improve the quality of care provided to Medicare beneficiaries throughout their entire SNF stay. We have long identified staffing as one of the vital components of a SNF's ability to provide quality care and use staffing data to gauge a facility's impact on quality of care in SNFs with more accuracy and efficacy. The proposed measure aligns with the topics listed under section 1888(h)(2)(A)(ii) of the Act and with HHS and Biden-Harris Administration priorities. We also believe that the Nursing Staff Turnover measure would complement the Total Nursing Hours per Resident Day (Total Nurse Staffing) measure, adopted in the FY 2023 SNF PPS final rule (87 FR 47570 through 47576). Together, these measures emphasize and align with our current priorities and focus areas for the Program.

(2) Overview of Measure

The Nursing Staff Turnover measure is a structural measure that uses auditable electronic data reported to CMS' PBJ system to calculate annual turnover rates for nursing staff, including registered nurses (RNs), licensed practical nurses (LPNs), and nurse aides. Given the well-documented impact of nurse staffing on patient outcomes and quality of care, this proposed measure would align the Program with the Care Coordination domain of CMS' Meaningful Measures 2.0 Framework. The Nursing Staff Turnover measure is currently being measured and publicly reported for nursing facilities on the Care Compare website ( https://www.medicare.gov/​care-compare/​) and is used in the Five-Star Quality Rating System. For more information on measure specifications and how this measure is used in the Five -Star Quality Rating System, we refer readers to the January 2023 Technical Users' Guide available at https://www.cms.gov/​medicare/​provider-enrollment-and-certification/​certificationandcomplianc/​downloads/​usersguide.pdf.

This proposed measure is constructed using daily staffing information submitted through the PBJ system by nursing facilities. Specifically, turnover is identified based on gaps in days worked, which helps ensure that Nursing Staff Turnover is defined the same way across all nursing facilities with SNF beds and that it does not depend on termination dates that may be reported inconsistently by these facilities. Individuals are identified based on the employee system ID and SNF identifiers in the PBJ data. We refer readers to the Nursing Staff Turnover measure specifications available at https://www.cms.gov/​medicare/​provider-enrollment-and-certification/​certificationandcomplianc/​downloads/​usersguide.pdf.

Payroll data are considered the gold standard for nurse staffing measures and are a significant improvement over the manual data previously used, wherein staffing information was calculated based on a form (CMS–671) filled out manually by the facility.^[220] The PBJ staffing data are electronically submitted and auditable back to payroll and other verifiable sources. Analyses of PBJ-based staffing measures show a relationship between higher nurse staffing levels and higher ratings for other dimensions of quality such as health inspection survey results and quality measures.^[221]

(a) Interested Parties and TEP Input

In 2019 through 2022, CMS tested this measure based on input from the CMS Five-Star Quality Rating Systems' TEP, as well as input from interested parties. We began publicly reporting this measure on the Care Compare website via the Nursing Home Five-Star Rating System in January 2022.

We solicited public feedback on this measure in a “Request for Comment on Additional SNF VBP Program Measure Considerations for Future Years” in the FY 2023 SNF PPS proposed rule (87 FR 22786 through 22787). We considered the input we received as we developed our proposal for this measure. We refer readers to the FY 2023 SNF PPS final rule (87 FR 47592 through 475963) for a detailed summary of the feedback we received on this measure.

(b) Measure Applications Partnership (MAP) Review

We included the Nursing Staff Turnover measure as a SNF VBP measure under consideration in the publicly available “2022 Measures Under Consideration List.” ^[222] The MAP offered conditional support of the Nursing Staff Turnover measure for rulemaking, contingent upon endorsement by the consensus-based entity, noting that the measure would add value to the Program because staffing turnover is a longstanding indicator of nursing home quality, and it addresses the Care Coordination domain of the Meaningful Measures 2.0 Framework. We refer readers to the final 2022–2023 MAP recommendations available at https://mmshub.cms.gov/​measure-lifecycle/​measure-implementation/​pre-rulemaking/​lists-and-reports.

(3) Data Sources

The proposed Nursing Staff Turnover measure is calculated using auditable, electronic staffing data submitted by each SNF for each quarter through the PBJ system. Specifically, this measure utilizes five data elements from the PBJ data, including employee ID, facility ID, hours worked, work date, and job title code.

(4) Inclusion and Exclusion Criteria

We are proposing that SNFs would be excluded from the measure under the following conditions:

• Any SNF with 100 percent total nursing staff turnover for any day in the six-quarter period during which there were at least five eligible nurse staff. A 100 percent daily turnover is typically the result of changes in the employee IDs used by SNFs and does not reflect actual staff turnover.
• SNFs that do not submit staffing data or submitted data that are considered invalid (using the current exclusion rules for the staffing domain) for one or more of the quarters used to calculate the Nursing Staff turnover measure.
• SNFs that do not have resident census information (derived from MDS assessments).
• SNFs with fewer than five eligible nurses (RNs, LPNs and nurse aides) in the denominator.

(a) Denominator

The denominator for the proposed Nursing Staff Turnover measure includes all eligible employees, defined as RNs, LPNs, and nurse aides, who are regular employees and agency staff who work at a Medicare certified SNF and use the same job category codes as other nurse staffing measures that are reported on the Care Compare website. For the purposes of this measure, the RN category is defined as RNs (job code 7), RN director of nursing (job code 5), and RNs with administrative duties (job code 6). The LPN category is defined as LPNs (job code 9) and LPNs with administrative duties (job code 8). The nurse aide category is defined as certified nurse aides (job code 10), aides in training (job code 11), and medication aides/technicians (job code 12). This measure only includes eligible employees who work at least 120 hours in a 90-day period. The timeframe for the 90-day period begins on the first workday observed during the quarter prior to the start of the performance period (termed the baseline quarter) and ends on the last workday, of the last month, of the second quarter of the performance period. Eligible employees who work infrequently (that is, those who work fewer than 120 hours during a 90-day period, including those who only occasionally cover shifts at a nursing home) would be excluded from the denominator calculation.

(b) Numerator

The numerator includes eligible employees who were included in the denominator and who are not identified in the PBJ data as having worked at the SNF for at least 60 consecutive days during the performance period. The 60-day gap must start during the period covered by the turnover measure. The turnover date is defined as the last workday prior to the start of the 60-day gap.

(5) Measure Calculation

The proposed Nursing Staff Turnover measure is calculated using six consecutive quarters of PBJ data. Data from a baseline quarter,^[223] Q0, along with the first two quarters of the performance period, are used for identifying employees who are eligible to be included in the measure (denominator). The four quarters of data (Q1 through Q4) of the performance period are used for identifying the number of employment spells, defined as a continuous period of work, that ended in turnover (numerator). Data from the sixth quarter (Q5), which occurs after the four-quarter numerator (performance) period, are used to identify gaps in days worked that started in the last 60 days of the fifth quarter (Q4) used for the measure. To calculate the measure score, we first determine the measure denominator by identifying the total number of employment spells, defined as a continuous period of work. For example, for the FY 2026 program year, the denominator would be calculated as the number of eligible employees who worked 120 or more hours in a 90-day period with the first workday of the 90-day period occurring in FY 2023 Q4, the quarter prior to the start of the performance period (Q0), through FY 2024 Q2, the first 2 quarters of the performance period (July 1, 2023 through March 31, 2024). The numerator is calculated as the total number of eligible employees who had a 60-day gap from October 1, 2023 through September 30, 2024 during which they did not work. Data from FY 2025 Q1, defined as Q5 above, is also used to identify gaps that start within 60 days of the end of the performance period (August 2, 2024 through September 30, 2024).

We are proposing to calculate the Nursing Staff Turnover measure rate for the SNF VBP Program using the following formula:

We also note that based on analysis and previous research on turnover measures, and a review by a technical expert panel, the Nursing Staff Turnover measure is not risk-adjusted.

We invite public comment on our proposal to adopt the Total Nursing Staff Turnover measure beginning with the FY 2026 SNF VBP program year.

c. Proposal To Adopt the Percent of Residents Experiencing One or More Falls With Major Injury (Long-Stay) Measure Beginning With the FY 2027 SNF VBP Program Year

We are proposing to adopt the Percent of Residents Experiencing One or More Falls with Major Injury (Long-Stay) Measure (“Falls with Major Injury (Long-Stay) measure”) beginning with the FY 2027 SNF VBP program year. The Falls with Major Injury (Long-Stay) measure is an outcome measure that estimates the percentage of long-stay residents who have experienced one or more falls with major injury. We refer readers to the specifications for this proposed measure, which are located in the Minimum Data Set (MDS) 3.0 Quality Measures User's Manual Version 15 available at https://www.cms.gov/​medicare/​quality-initiatives-patient-assessment-instruments/​nursinghomequalityinits/​nhqiqualitymeasures. The Falls with Major Injury (Long-Stay) measure was endorsed by the CBE in 2011. The measure is currently reported by nursing facilities under the CMS Nursing Home Quality Initiative (NHQI) and the Five-Star Quality Rating System and those results are publicly reported on the Care Compare website, available at https://www.medicare.gov/​care-compare/​.

(1) Background

Falls are the leading cause of injury-related death among persons aged 65 years and older. According to the Centers for Disease Control and Prevention (CDC), approximately one in four adults aged 65 years and older fall each year, and fall-related emergency department visits are estimated at approximately 3 million per year.^[224] In 2016, nearly 30,000 U.S. residents aged 65 years and older died as the result of a fall, resulting in an age-adjusted mortality rate of 61.6 deaths per 100,000 people. This represents a greater than 30 percent increase in fall-related deaths from 2007, where the age-adjusted mortality rate was 47.0 deaths per 100,000 people.^[225] Additionally, the death rate from falls was higher among adults aged 85 years and older as indicated by a mortality rate of 257.9 deaths per 100,000 people.^[226]

Of the 1.6 million residents in U.S. nursing facilities, approximately half fall annually, with one in three having two or more falls in a year. One in every ten residents who falls has a serious related injury, and about 65,000 residents suffer a hip fracture each year.^[227] An analysis of MDS data from FY 2019 Q2 found that, among the 14,586 nursing facilities included in the sample, the percent of long-stay residents who experienced one or more falls with major injury ranged from zero percent to nearly 21 percent. This wide variation in facility -level fall rates indicates a performance gap and suggests that there are opportunities to improve performance on this measure.

It is important to monitor injurious falls among the long-stay population because of the potentially negative impacts on resident health outcomes and quality of life. Research has found that injurious falls are one of the leading causes of disability and death for all nursing home residents. Specifically, falls have serious health consequences, such as reduced quality of life, decreased functional abilities, anxiety and depression, serious injuries, and increased risk of morbidity and mortality.^[228 229]

Injurious falls are also a significant cost burden to the entire healthcare system. The U.S. spends approximately $50 billion on medical costs related to non-fatal fall-related injuries and $754 million on medical costs related to fatal falls annually.^[230] Of the amount paid on non-fatal fall injuries, Medicare pays approximately $29 billion, while private or out-of-pocket payers pay $12 billion. Research suggests that acute care costs incurred for falls among nursing home residents range from $979 for a typical case with a simple fracture to $14,716 for a typical case with multiple injuries.^[231] Other research examining hospitalizations of nursing home residents with serious fall-related injuries (intracranial bleed, hip fracture, or other fracture) found an average cost of $23,723.^[232]

Research has found that 78 percent of falls are anticipated physiologic falls, which are defined as falls among individuals who scored high on a risk assessment scale, meaning their risk could have been identified in advance of the fall.^[233] To date, studies have identified a number of risk factors for falls within the long-stay population, including impaired cognitive function, history of falls, difficulties with walking and balancing, vitamin D deficiency, and use of psychotropic medications.^{[234 235 236]} In addition, residents who experience dementia or depression, are underweight, or are over the age of 85 are at a higher risk of falling.^{[237 238 239]} While much of this research has been conducted in long-term care facilities or nursing homes, we believe this research is relevant to the SNF setting, because approximately 94 percent of long-term care facilities are dually certified as both SNFs or nursing facilities (86 FR 42508). Therefore, these risk factors described above suggest that SNFs may be able to identify, reduce, and prevent the incidence of falls among their residents.^{[240 241 242 243]}

Given the effects of falls with major injury, preventing and reducing their occurrence in SNFs is critical to delivering safe and high-quality care. We believe the proposed Falls with Major Injury (Long-Stay) measure aligns with this goal by monitoring the occurrence of falls with major injury and assessing SNFs on their performance on fall prevention efforts. In doing so, we believe the proposed measure would promote patient safety and increase the transparency of care quality in the SNF setting, and it would address the Patient Safety domain of CMS' Meaningful Measures 2.0 Framework.^[244]

We believe there are effective interventions that SNFs can implement to reduce and prevent falls, including those that cause major injury. Specifically, several studies observed that multifactorial interventions such as exercise, medication review, risk assessment, vision assessment, and environmental assessment significantly reduce fall rates.^{[245 246 247]} Another study found that a single intervention of exercise reduced the number of resident falls in the nursing home setting by 36 percent and the number of recurrent fallers by 41 percent.^[248] Additionally, various systematic reviews link facility structural characteristics to falls with major injury. For example, the incorporation of adequate equipment throughout the facility, such as hip protectors or equipment used for staff education tasks, may reduce fall rates or fall-related injuries.^[249 250] In addition, poor communication between staff, inadequate staffing levels, and limited facility equipment have been identified as barriers to implementing fall prevention programs in facilities.^[251] Other studies have shown that proper staff education can significantly reduce fall rates.^[252 253] The effectiveness of these interventions suggest improvement of fall rates among SNF residents is possible through modification of provider-led processes and interventions, which supports the overall goal of the SNF VBP Program.

(2) Overview of Measure

The proposed Falls with Major Injury (Long-Stay) measure is an outcome measure that reports the percentage of long-stay residents in a nursing home who have experienced one or more falls with major injury using 1 year of data from the Minimum Data Set (MDS) 3.0. This measure defines major injuries as bone fractures, joint dislocations, closed head injuries with altered consciousness, or subdural hematomas. Long-stay residents are defined as residents who have received 101 or more cumulative days of nursing home care by the end of the measure reporting period (performance period). This proposed measure is a patient safety measure reported at the facility-level.

Although the Falls with Major Injury (Long-Stay) measure is a long-stay measure, we believe that including a long-stay measure in the SNF VBP Program is appropriate because it would better capture the quality of care provided to the entirety of the population that resides in facilities that are dually certified as SNFs and nursing facilities, including long-stay residents who continue to receive Medicare coverage for certain services provided by nursing facilities. We discussed the potential to include long stay measures in the SNF VBP Program in the FY 2022 SNF PPS final rule Summary of Comments Received on Potential Future Measures for the SNF VBP Program (86 FR 42507 through 42510). Specifically, we stated that the majority of long-stay residents are Medicare beneficiaries, regardless of whether they are in a Medicare Part A SNF stay, because they are enrolled in Medicare Part B and receive Medicare coverage of certain services provided by long-term care facilities even if they are a long-stay resident. We did not receive any negative comments on inclusion of this specific Falls with Major Injury (Long-Stay) measure or long-stay measures generally in the Program in response to this request for comment.

We have adopted a similar measure for the SNF QRP, titled Application of Percent of Residents Experiencing One or More Falls with Major Injury (Long Stay) (80 FR 46440 through 46444), but that measure excludes long-stay residents. We believe it is important to hold SNFs accountable for the quality of care provided to long-stay residents given that the majority of long-term care facilities are dually certified as SNFs and nursing facilities. Additionally, we believe the proposed Falls with Major Injury (Long-Stay) measure satisfies the requirement to consider and apply, as appropriate, quality measures specified under section 1899B(c)(1) of the Act, in which this measure aligns with the domain, incidence of major falls, described at section 1899B(c)(1)(D) of the Act. Therefore, we believe it is appropriate for the SNF VBP program to include a falls with major injury for long-stay resident measure.

Testing for this measure has demonstrated that the Falls with Major Injury (Long-Stay) measure has sufficient reliability and validity. For example, signal-to-noise and split-half reliability analyses found that the measure exhibited moderate reliability. Validity testing showed that there are meaningful differences in nursing facility-level scores for this measure, indicating good validity. For additional details on measure testing, we refer readers to the MAP PAC/LTC: 2022–2023 MUC Cycle Measure Specifications Manual available at https://mmshub.cms.gov/​sites/​default/​files/​map-pac-muc-measure-specifications-2022-2023.pdf.

(a) Interested Parties and TEP Input

In considering the selection of this measure for the SNF VBP Program, CMS convened a TEP in March 2022 which focused on the identification of measurement gaps and measure development priorities for the Program. Panelists were largely supportive of including a falls with major injury measure compared to a general falls measure or a falls with injury measure for several reasons including: (1) the broad definition of falls; and (2) the consensus-based entity endorsement of the Falls with Major Injury (Long-Stay) measure in the Nursing Home Quality Initiative Program. A summary of the TEP meeting is available at https://mmshub.cms.gov/​sites/​default/​files/​SNF-VBP-TEP-Summary-Report-Mar2022.pdf.

(b) Measure Applications Partnership (MAP) Review

We included the Falls with Major Injury (Long-Stay) measure for the SNF VBP in the publicly available “2022 Measures Under Consideration List”.^[254] The MAP supported the Falls with Major Injury (Long-Stay) measure for rulemaking, noting that the measure would add value to the Program because of the lack of an existing falls measure and that it would help improve patient safety. We refer readers to the final 2022–2023 MAP recommendations available at https://mmshub.cms.gov/​measure-lifecycle/​measure-implementation/​pre-rulemaking/​lists-and-reports.

(3) Data Sources

The proposed Falls with Major Injury (Long-Stay) measure is calculated using 1 year of patient data collected through the MDS. The collection instrument is the Resident Assessment Instrument (RAI), which contains the MDS 3.0. The RAI is a tool used by nursing home staff to collect information on residents' strengths and needs. We describe the measure specifications in more detail below and also refer readers to the MDS 3.0 Quality Measures User's Manual Version 15.0 for further details on how these data components are utilized in calculating the Falls with Major Injury (Long-Stay) measure available at https://www.cms.gov/​medicare/​quality-initiatives-patient-assessment-instruments/​nursinghomequalityinits/​nhqiqualitymeasures. Technical information for the MDS 3.0 is also available at https://www.cms.gov/​Medicare/​Quality-Initiatives-Patient-Assessment-Instruments/​NursingHomeQualityInits/​NHQIMDS30TechnicalInformation. The proposed Falls with Major Injury (Long-Stay) measure is calculated using data from the MDS, which all Medicare-certified SNFs and Medicaid-certified nursing facilities are currently required to report. Therefore, this measure would not impose any additional data collection or submission burden for SNFs.

(4) Measure Specifications

(a) Denominator

All long-stay residents with one or more look-back scan assessments no more than 275 days prior to the target assessment, except those that meet the exclusion criteria, are included in the measure denominator. Long-stay residents are defined as those who have 101 or more cumulative days of nursing home care by the end of the measure reporting period (performance period). Residents who return to the nursing home following a hospital discharge would not have their cumulative days in the facility reset to zero, meaning that days of care from a previous admission would be added to any subsequent admissions.

The MDS includes a series of assessments and tracking documents, such as Omnibus Budget Reconciliation Act (OBRA) Comprehensive Assessments, OBRA Quarterly Assessments, OBRA Discharge Assessments or PPS assessments. For the purposes of this measure, a target assessment, which presents the resident's status at the end of the episode of care or their latest status if their episode of care is ongoing, is selected for each long-stay resident. Target assessments may be an Omnibus Budget Reconciliation Act (OBRA) admission, quarterly, annual, or significant change/correction assessment; or PPS 5-day assessments; or discharge assessment with or without anticipated return. For more information on how we define target assessments, we refer readers to the MDS 3.0 Quality Measures User's Manual Version 15.0 available at https://www.cms.gov/​medicare/​quality-initiatives-patient-assessment-instruments/​nursinghomequalityinits/​nhqiqualitymeasures.

(b) Denominator Exclusions

Residents are excluded from the denominator if the number of falls with major injury was not coded for all of the look-back scan assessments. A SNF would not be scored on this measure if it does not have long-stay residents, or residents with 101 or more cumulative days of care. The measure also excludes all SNF swing beds because they are not used for long-stay residents.

(c) Numerator

The measure numerator includes long-stay residents with one or more look-back scan assessments that indicate one or more falls that resulted in major injury. Major injuries include bone fractures, joint dislocations, closed-head injuries with altered consciousness, or subdural hematomas. The selection period for the look-back scan consists of the target assessment and all qualifying earlier assessments in the scan.

An assessment should be included in the scan if it meets all of the following conditions: (1) it is contained within the resident's episode, (2) it has a qualifying Reason for Assessment (RFA), (3) its target date is on or before the target date for the target assessment, and (4) its target date is no more than 275 days prior to the target date of the target assessment. For the purposes of this measure, we define the target date as the event date of an MDS record (that is, entry date for an entry record or discharge date for a discharge record or death-in-facility record) or the assessment reference date (for all records that are not entry, discharge, or death-in-facility). For additional target date details, we refer readers to Chapter 1 of the MDS 3.0 Quality Measures User's Manual Version 15.0 available at https://www.cms.gov/​medicare/​quality-initiatives-patient-assessment-instruments/​nursinghomequalityinits/​nhqiqualitymeasures.

A 275-day time period is used to include up to three quarterly OBRA assessments. The earliest of these assessments would have a look-back period of up to 93 days, which would cover a total of about 1 year. To calculate the measure, we scan these target assessments and any qualifying earlier assessments described in the previous paragraph for indicators of falls with major injury.

(5) Risk Adjustment

The Falls with Major Injury (Long-Stay) measure is not risk-adjusted. We considered risk adjustment during measure development, and we tested various risk-adjustment models, but none had sufficient predictive ability.

(6) Measure Calculation

The Falls with Major Injury (Long-Stay) measure is calculated and reported at the facility level. Specifically, to calculate the measure score, we are proposing to first determine the measure denominator by identifying the total number of long-stay residents with a qualifying target assessment (OBRA, PPS, or discharge), one or more look-back scan assessments, and who do not meet the exclusion criteria. Using that set of residents, we calculate the numerator by identifying the total number of those residents with one or more look-back scan assessments that indicate one or more falls that resulted in major injury. We then divide the numerator by the denominator and multiply the resulting ratio by 100 to obtain the percentage of long-stay residents who experience one or more falls with major injury. A lower measure rate indicates better performance on the measure. For additional details on the calculation method, we refer readers to the specifications for the Falls with Major Injury (Long-Stay) measure included in the MDS 3.0 Quality Measures User's Manual available at https://www.cms.gov/​medicare/​quality-initiatives-patient-assessment-instruments/​nursinghomequalityinits/​nhqiqualitymeasures.

We invite public comment on our proposal to adopt the Percent of Residents Experiencing One or More Falls with Major Injury (Long-Stay) measure beginning with the FY 2027 SNF VBP program year.

d. Proposal To Adopt the Discharge Function Score Measure Beginning With the FY 2027 SNF VBP Program Year

We are proposing to adopt the Discharge Function Score (“DC Function”) measure beginning with the FY 2027 SNF VBP Program.^[255] We are also proposing to adopt this measure in the SNF QRP (see section VI. of this proposed rule).

(1) Background

Maintenance or improvement of physical function among older adults is increasingly an important focus of healthcare. Adults aged 65 years and older constitute the most rapidly growing population in the United States, and functional capacity in physical (non-psychological) domains has been shown to decline with age.^[256] Moreover, impaired functional capacity is associated with poorer quality of life and an increased risk of all-cause mortality, postoperative complications, and cognitive impairment, the latter of which can complicate the return of a resident to the community from post-acute care.^{[257 258 259]} Nonetheless, evidence suggests that physical functional abilities, including mobility and self-care, are modifiable predictors of resident outcomes across PAC settings, including functional recovery or decline after post-acute care,^{[260 261 262 263 264]} rehospitalization rates,^{[265 266 267]} discharge to community,^[268 269] and falls.^[270] Because evidence shows that older adults experience aging heterogeneously and require individualized and comprehensive healthcare, functional status can serve as a vital component in informing the provision of healthcare and thus indicate a SNF's quality of care.^[271 272]

As stated in section VI. of this proposed rule, we are proposing this measure for the SNF QRP, and we are also proposing it for adoption in the SNF VBP Program under section 1888(h)(2)(A)(ii) of the Act. We believe it is important to measure quality across the full range of outcomes for Medicare beneficiaries during a SNF stay. Further, adoption of this measure would ensure that the SNF VBP Program's measure set aligns with the Person-Centered Care domain of CMS' Meaningful Measures 2.0 Framework.

We included the proposed DC Function measure on the 2022–2023 MUC list for the Inpatient Rehabilitation Facility QRP, Home Health QRP, Long Term Care Hospital QRP, SNF QRP, and SNF VBP. While the DC Function measure is not yet implemented in the SNF QRP or other PAC programs, SNFs already report many of the elements that would be used to calculate this measure.^[273] As such, we believe SNFs have had sufficient time to ensure successful reporting of the data elements needed for this measure.

(2) Overview of Measure

The proposed DC Function measure is an outcome measure that estimates the percentage of SNF residents who meet or exceed an expected discharge score during the reporting period. The proposed DC Function measure's numerator is the number of SNF stays with an observed discharge function score that is equal to or higher than the calculated expected discharge function score. The observed discharge function score is the sum of individual function items at discharge. The expected discharge function score is computed by risk adjusting the observed discharge function score for each SNF stay. Risk adjustment controls for resident characteristics, such as admission function score, age, and clinical conditions. The denominator is the total number of SNF stays with a MDS record in the measure target period (four rolling quarters) which do not meet the measure exclusion criteria. For additional details regarding the numerator, denominator, risk adjustment, and exclusion criteria, refer to the Discharge Function Score for Skilled Nursing Facilities (SNFs) Technical Report.^[274]

The proposed DC Function measure implements a statistical imputation approach for handling “missing” standardized functional assessment data elements. The coding guidance for standardized functional assessment data elements allows for using “Activity Not Attempted” (ANA) codes, resulting in “missing” information about a patient's functional ability on at least some items, at admission and/or discharge, for a substantive portion of SNF patients. Currently, functional outcome measures in the SNF QRP use a simple imputation method whereby all ANA codes or otherwise missing scores, on both admission and discharge records, are recoded to “1” or “most dependent.” Statistical imputation, on the other hand, replaces these missing values for a variable based on the values of other, non-missing variables in the data and which are otherwise similar to the assessment with a missing value. Specifically, this proposed DC Function measure's statistical, statistical imputation allows missing values (for example, the ANA codes) to be replaced with any value from 1 to 6, based on a patient's clinical characteristics and codes assigned on other standardized functional assessment data elements. The measure implements separate imputation models for each standardized functional assessment data elements used in measure construction at admission and discharge. Relative to the current simple imputation method, this statistical imputation approach increases the precision and accuracy and reduces the bias in estimates for missing item scores. We refer readers to Discharge Function Score for Skilled Nursing Facilities (SNFs) Technical Report  ^[275] for measure specifications and additional details. We also refer readers to the SNF QRP section VI.C.1.b.(1) of this proposed rule for additional information on Measure Importance and Measure Testing.

(a) Interested Parties and TEP Input

We convened two TEP meetings (July 2021 and January 2022), as well as a Patient and Family Engagement Listening Session, to collect feedback from interested parties on the measure's potential use in quality programs in the future. The TEP members expressed support for the measure's validity and agreed with the conceptual and operational definition of the measure.

The feedback we received during the Patient and Family Engagement Listening Session demonstrated that this measure resonates with patients and caregivers. For example, participants' views of self-care and mobility were aligned with the functional domains captured by the measure, and participants found that those domains included critical aspects of care in post-acute care settings. Participants also emphasized the importance of measuring functional outcomes when assessing quality for SNF residents. We refer readers to the SNF QRP section VI.C.1.b.(3) of this proposed rule for additional discussion on the TEP.

(b) MAP Review

The Discharge Function measure was included as a SNF VBP measure under consideration in the publicly available “2022 Measures Under Consideration List.” ^[276] The MAP offered conditional support of the DC Function measure for rulemaking, contingent upon endorsement by the consensus-based entity, noting that the measure would add value to the Program because there are currently no measures related to functional status in the Program, and this measure serves as an indicator for whether the care provided is effective and high quality. We refer readers to section VI.C.1.b.(4) of this proposed rule for further details on the MAP's recommendations and the final 2022–2023 MAP recommendations available at https://mmshub.cms.gov/​measure-lifecycle/​measure-implementation/​pre-rulemaking/​lists-and-reports.

We invite public comment on our proposal to adopt the Discharge Function Score measure beginning with the FY 2027 SNF VBP program year.

e. Proposal To Adopt the Number of Hospitalizations per 1,000 Long-Stay Resident Days Measure Beginning With the FY 2027 SNF VBP Program Year

We are proposing to adopt the Number of Hospitalization per 1,000 Long Stay Resident Days Measure (“Long Stay Hospitalization measure”) beginning with the FY 2027 SNF VBP Program.

(1) Background

Unplanned hospitalizations of long -stay residents can be disruptive and burdensome to residents. “They can cause discomfort for residents, anxiety for loved ones, morbidity due to iatrogenic events, and excess healthcare costs.” ^[277] Studies have found that many unplanned hospitalizations could have been safely avoided by early intervention by the facility. For example, one structured review by expert clinicians of hospitalizations of skilled nursing facility residents found that two -thirds were potentially avoidable, citing a lack of primary care clinicians on-site and delays in assessments and lab orders as primary reasons behind unplanned hospitalizations.^[278] Another study found that standardizing advanced care planning and physician availability has a considerable impact on reducing hospitalizations.^[279] The Missouri Quality Initiative reduced hospitalizations by 30 percent by having a clinical resource embedded to influence resident care outcomes. Another study found that reducing hospitalizations did not increase the mortality risk for long -stay nursing home residents.^[280]

A review of data that were publicly reported on Care Compare shows that there is considerable variation in performance across nursing homes when it comes to unplanned hospitalizations, suggesting that improvement is possible through modification of facility-led processes and interventions. Specifically, performance on this measure ranges from 0.841 hospital admissions per 1,000 long stay resident days at the 10th percentile to 2.656 hospital admissions per 1,000 long-stay resident days at the 90th percentile.^[281] In other words, the top decile of performers (10th percentile) has half the number of hospitalizations of the bottom decile (90th percentile). We also reported in 2020 that the rate of unplanned hospitalizations was 1.4 per 1,000 nursing home resident days, suggesting these disruptive events are fairly common.^[282] Adopting this measure would align measures between Care Compare and the SNF VBP program without increasing the reporting burden.

Although the proposed Long Stay Hospitalization measure is not specified under section 1899B(c)(1) of the Act, it aligns with the topics listed under section 1888(h)(2)(A)(ii) of the Act. We believe this outcome measure supports the Program's goals to improve the quality of care provided to Medicare beneficiaries throughout their entire SNF stay. Furthermore, the measure would align with the Care Coordination domain of the Meaningful Measures 2.0 Framework.

We examined the relationship between long-stay hospitalization rates and other measures of quality from CMS' Five-Star Quality Rating System using data from the December 2019 Nursing Home Compare update. Analyses showed that facilities with lower hospitalization rates tend to perform better on other dimensions of quality such as health inspection survey results, staffing level, other quality measures, and overall ratings.

Although the Long Stay Hospitalization measure is a long-stay measure, we believe that including a long-stay measure in the SNF VBP Program is appropriate because it would better capture the quality of care provided to the entirety of the population that resides in facilities that are dually certified as SNFs and nursing facilities, including long-stay residents who continue to receive Medicare coverage for certain services provided by nursing facilities. We discussed the potential to include long stay measures in the SNF VBP Program in the FY 2022 SNF PPS final rule Summary of Comments Received on Potential Future Measures for the SNF VBP Program (86 FR 42507 through 42510). Specifically, we stated that the majority of long-stay residents are Medicare beneficiaries, regardless of whether they are in a Medicare Part A SNF stay, because they are enrolled in Medicare Part B and receive Medicare coverage of certain services provided by long-term care facilities even if they are a long-stay resident. We did not receive any negative comments on inclusion of this specific Long Stay Hospitalization measure or long-stay measures generally in the Program in response to the request for comment.

(2) Overview of Measure

The Long Stay Hospitalization measure calculates the number of unplanned inpatient admissions to an acute care hospital or critical access hospital or outpatient observation stays that occurred among long-stay residents per 1,000 long stay resident days using 1 year of Medicare fee-for-service (FFS) claims data. A long-stay day is defined as any day after a resident's one-hundredth cumulative day in the nursing home or the beginning of the 12-month target period (whichever is later) and until the day of discharge, the day of death, or the end of the 12-month target period (whichever is earlier). We are proposing to risk adjust this measure, as we explain in more detail below.

(a) Measure Applications Partnership (MAP) Review

We included the Long Stay Hospitalization measure in the publicly available “2022 Measures Under Consideration List.” ^[283] The MAP offered conditional support of the Long Stay Hospitalization measure for rulemaking, contingent upon endorsement by the consensus-based entity, noting that the measure would add value to the Program because unplanned hospitalizations are disruptive and burdensome to long-stay residents. We refer readers to the final 2022–2023 MAP recommendations available at https://mmshub.cms.gov/​measure-lifecycle/​measure-implementation/​pre-rulemaking/​lists-and-reports.

(3) Data Sources

The Long Stay Hospitalization measure is calculated using Medicare fee-for-service (FFS) claims data. We use the inpatient hospital claims data to determine the hospital admission, outpatient hospital claims data to determine the outpatient observation stay, and items from the Minimum Data Set for building resident stays and for risk-adjustment.

(4) Inclusion and Exclusion Criteria

All Medicare beneficiaries enrolled in both Part A and Part B are included. The measure excludes any resident enrolled in Medicare managed care during any portion of the resident's stay. The measure also excludes all days and any hospital admissions during which the resident was enrolled in hospice.

The measure does not count days prior to a resident's 101st cumulative day, which is when the resident meets long-stay criteria. Furthermore, we do not include any long-stay days prior to the beginning of the applicable performance period. For example, if a resident becomes a long-stay resident on September 25, 2024, and is discharged on October 5, 2024, we would only count 5 days in the denominator during the performance period for the FY 2027 program year.

Any days a resident was not in the facility for any reason would not be counted in the denominator, defined as the total observed number of long stay days at the facility. This means we do not count in the denominator any days the resident is admitted to another type of inpatient facility, or days temporarily residing in the community, so long as the NF with beds that are also certified as SNF beds submits an MDS discharge assessment for the temporary discharge. For example, if a patient became long-stay resident on December 20, but stayed with family on December 24 and December 25 but returned to the facility on December 26, we would not count those two days (24 and 25) in the denominator because the NF with beds that are also certified as SNF beds completed an MDS discharge assessment. We would also not count the days when a resident was admitted to a hospital, and therefore, is not residing at the facility in the denominator.

We would not count an observed hospitalization of a resident, the numerator count, if the hospitalization occurred while the resident was not in the facility and had a completed MDS discharge assessment for the temporary discharge. In the example in the prior paragraph, if the resident was admitted to the hospital on December 25, during which they were residing with family with a completed MDS temporary discharge assessment, the admission would not be counted as a hospitalization for the NF with beds that are also certified as SNF beds (in the numerator). If, however, the resident returned to the NF with beds that are also certified as SNF beds on December 26 and was admitted to the hospital on December 27, then it would count as a hospitalization (in the numerator).

If a resident spends 31 or more days in a row residing outside the NF with beds that are also certified as SNF beds, which could be in another facility or in the community, we would consider the resident discharged and they would no longer meet long-stay status. If a resident is discharged and then admitted to the same facility within 30 days, we would consider the resident still in a long-stay status, and we would count the days in this admission in the measure denominator.

The measure numerator includes all admissions to an acute care hospital or critical access hospital, for an inpatient or outpatient observation stay, that occur while the resident meets the long-stay status criteria. Observation stays are included in the numerator regardless of diagnosis. Planned inpatient admissions are not counted in the numerator since they are unrelated to the quality of care at the facility. Hospitalizations are classified as planned or unplanned using the same version of CMS' Planned Readmissions Algorithm that is used to calculate the percentage of short-stay residents who were re-hospitalized after a nursing home admission in the Nursing Home Compare Five-Star Rating system. The algorithm identifies planned admission using the principal discharge diagnosis category and all procedure codes listed on inpatient claims, coded using the AHRQ Clinical Classification System (CCS) software.

(5) Risk Adjustment

The risk adjustment model used for this measure is a negative binomial regression. Specifically, we are proposing to risk adjust the observed number of hospitalizations after the resident met the long-stay status to determine the expected number of hospitalizations for each long-stay resident given the resident's clinical and demographic profile. The goal of risk adjustment is to account for differences across facilities in medical acuity, functional impairment, and frailty of the long-stay residents but not factors related to the quality of care provided by the facility. The data for the risk adjustment model are derived from Medicare inpatient claims data prior to the day the resident became a long-stay resident and from the most recent quarterly or comprehensive MDS assessment within 120 days prior to the day the resident became a long-stay resident.

The risk adjustment variables derived from the claims-based data include age, sex, number of hospitalizations in the 365 days before the day the resident became a long-stay resident or beginning of the 1-year measurement period (whichever is later), and an outcome-specific comorbidity index. The MDS-based covariates span multiple domains including functional status, clinical conditions, clinical treatments, and clinical diagnoses.

We refer readers to the measure specifications for additional details on the risk-adjustment model for this measure available at https://www.cms.gov/​Medicare/​Provider-Enrollment-and-Certification/​CertificationandComplianc/​Downloads/​Nursing-Home-Compare-Claims-based-Measures-Technical-Specifications-April-2019.pdf.

(6) Measure Calculation

To get the risk adjusted rate (risk standardized rate), we take the observed Long Stay Hospitalization rate divided by the expected Long Stay Hospitalization rate, multiplied by the national Long Stay Hospitalization rate, as shown by the following formula:

The observed Long Stay Hospitalization rate is the actual number of hospital admissions or observation stays that met the inclusion criteria discussed in section VII.B.4.e.(4) of this proposed rule divided by the actual total number of long-stay days that met the inclusion criteria discussed in section VII.B.4.e.(4) of this proposed rule divided by 1,000 days. The observed rate is shown by the following formula:

The expected Long Stay Hospitalization rate is the expected number of hospital admission or observation stays that were calculated using the risk adjustment methodology discussed in section VII.B.4.e.(5) of this proposed rule, divided by the actual total number of long-stay days that met the inclusion criteria discussed in section VII.B.4.e.(4) of this proposed rule divided by 1,000 days. The expected Long Stay Hospitalization rate is shown by the following formula:

The national Long Stay Hospitalization rate is the total number of inpatient hospital admission or observation stays meeting the numerator criteria, divided by the total number of all long stay days that met the denominator criteria divided by 1,000. The national Long Stay Hospitalization rate is shown by the following formula:

We refer readers to the measure specification for additional details for this measure calculation available at https://www.cms.gov/​Medicare/​Provider-Enrollment-and-Certification/​CertificationandComplianc/​Downloads/​Nursing-Home-Compare-Claims-based-Measures-Technical-Specifications-April-2019.pdf.

We invite public comment on our proposal to adopt the Number of Hospitalizations per 1,000 Long-Stay Resident Days measure beginning with the FY 2027 SNF VBP program year.

f. Proposed Scoring of SNF Performance on the Nursing Staff Turnover, Falls With Major Injury (Long-Stay), and Long Stay Hospitalization Measures

(1) Background

In the FY 2017 SNF PPS final rule (81 FR 52000 through 52001), we finalized a policy to invert SNFRM measure rates such that a higher measure rate reflects better performance on the SNFRM. In that final rule, we also stated our belief that this inversion is important for incentivizing improvement in a clear and understandable manner because a “lower is better” rate could cause confusion among SNFs and the public. In the FY 2023 SNF PPS final rule (87 FR 47568), we applied this policy to the SNF HAI measure such that a higher measure rate reflects better performance on the SNF HAI measure. We also stated our intent to apply this inversion scoring policy to all measures in the Program for which the calculation produces a “lower is better” measure rate. We continue to believe that inverting measure rates such that a higher measure rate reflects better performance on a measure is important for incentivizing improvement in a clear and understandable manner.

This measure rate inversion scoring policy does not change the measure specifications or the calculation method. We use this measure rate inversion as part of the scoring methodology under the SNF VBP Program. The measure rate inversion is part of the methodology we use to generate measure scores, and resulting SNF Performance Scores, that are clear and understandable for SNFs and the public.

(2) Proposal To Invert the Nursing Staff Turnover, Falls With Major Injury (Long-Stay), and Long Stay Hospitalization Measures Rates for SNF VBP Program Scoring Purposes

In sections VII.B.4.b., VII.B.4.c., and VII.B.4.e. of this proposed rule, we stated that a lower measure rate for the Nursing Staff Turnover, Falls with Major Injury (Long-Stay), and Long Stay Hospitalization measures indicate better performance on those measures. Therefore, we are proposing to apply our measure rate inversion scoring policy to these measures. We are proposing to calculate the score for these measures for the SNF VBP Program by inverting the measure rates using the calculations shown in Table 18. We are not proposing to apply this policy to the DC Function measure because that measure, as currently specified and calculated, produces a “higher is better” measure rate.

We believe that inverting the measure rates for the Nursing Staff Turnover, Falls with Major Injury (Long-Stay), and Long Stay Hospitalization measure is important for incentivizing improvement in a clear and understandable manner, and for ensuring a consistent message that a higher measure rate reflects better performance on the measures.

We invite public comment on our proposal to invert the measure rates for the Nursing Staff Turnover, Falls with Major Injury (Long-Stay), and Long Stay Hospitalization measures for the purposes of scoring under the SNF VBP Program.

g. Confidential Feedback Reports and Public Reporting for Proposed Quality Measures

Our confidential feedback reports and public reporting policies are codified at § 413.338(f) of our regulations. In the FY 2023 SNF PPS final rule (87 FR 47591 through 47592), we revised our regulations such that the confidential feedback reports and public reporting policies apply to each measure specified for a fiscal year, which includes the proposed Nursing Staff Turnover measure beginning with the FY 2026 program year, and the proposed Falls with Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization measures beginning with the FY 2027 program year.

C. SNF VBP Performance Periods and Baseline Proposals

1. Background

We refer readers to the FY 2016 SNF PPS final rule (80 FR 46422) for a discussion of our considerations for determining performance periods and baseline periods under the SNF VBP Program. In the FY 2019 SNF PPS final rule (83 FR 39277 through 39278), we adopted a policy whereby we will automatically adopt the performance period and baseline period for a SNF VBP program year by advancing the performance period and baseline period by 1 year from the previous program year. In the FY 2023 SNF PPS final rule (87 FR 47580 through 47583), we adopted performance periods and baseline periods for three new quality measures beginning with the FY 2026 program year: (1) SNF HAI measure, (2) Total Nurse Staffing measure, and (3) DTC PAC SNF measure, and finalized the application of our policy to automatically adopt performance periods and baseline periods for subsequent program years to those new measures.

2. SNFRM Performance and Baseline Periods for the FY 2024 SNF VBP Program Year

Under the policy finalized in the FY 2019 SNF PPS final rule (83 FR 39277 through 39278), the baseline period for the SNFRM for the FY 2024 program year would be FY 2020 and the performance period for the SNFRM for the FY 2024 program year would be FY 2022. However, in the FY 2022 SNF PPS final rule (85 FR 42512 through 42513), we updated the FY 2024 baseline period for the SNFRM to FY 2019 since the ECE we granted on March 22, 2020, due to the PHE for COVID–19, excepted qualifying claims for a 6-month period in FY 2020 (January 1, 2020 through June 30, 2020) from the calculation of the SNFRM.^{[284]  [285]} We refer readers to that final rule for additional discussion of our considerations for updating the FY 2024 baseline period for the SNFRM. Therefore, for the FY 2024 program year, the baseline period for the SNFRM is FY 2019 and the performance period for the SNFRM is FY 2022.

3. Proposed Performance Periods and Baseline Periods for the Nursing Staff Turnover, Falls With Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization Measures

a. Proposed Performance Periods for the Nursing Staff Turnover, Falls With Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization Measures

In considering the appropriate performance periods for the Nursing Staff Turnover, Falls with Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization measures, we recognize that we must balance the length of the performance periods with our need to calculate valid and reliable performance scores and announce the resulting payment adjustments no later than 60 days prior to the program year involved, in accordance with section 1888(h)(7) of the Act. In addition, we refer readers to the FY 2017 SNF PPS final rule (81 FR 51998 through 51999) for a discussion of the factors we should consider when specifying performance periods for the SNF VBP Program, as well as our stated preference for 1-year performance periods. Based on these considerations, we believe that 1-year performance periods for these measures would be operationally feasible for the SNF VBP Program and would provide sufficiently accurate and reliable measure rates and resulting performance scores for the measures.

We also recognize that we must balance our desire to specify performance periods for a fiscal year as close to the fiscal year's start date as possible to ensure clear connections between quality measurement and value-based payment with our need to announce the net results of the Program's adjustments to Medicare payments not later than 60 days prior to the fiscal year involved, in accordance with section 1888(h)(7) of the Act. In considering these constraints, and in alignment with other SNF VBP measures, we believe that performance periods that occur 2 fiscal years prior to the applicable fiscal program year is most appropriate for these measures.

For these reasons, we are proposing to adopt the following performance periods:

• FY 2024 (October 1, 2023 through September 30, 2024) as the performance period for the Nursing Staff Turnover measure for the FY 2026 SNF VBP program year.
• FY 2025 (October 1, 2024, through September 30, 2025) as the performance period for the Falls with Major Injury (Long-Stay) measure for the FY 2027 SNF VBP program year.
• FY 2025 (October 1, 2024 through September 30, 2025) as the performance period for the DC Function measure for the FY 2027 SNF VBP program year.
• FY 2025 (October 1, 2024 through September 30, 2025) as the performance period for the Long Stay Hospitalization measure for the FY 2027 SNF VBP program year.

In alignment with the previously adopted SNF VBP measures, we are also proposing that, for these measures, we would automatically adopt the performance period for a SNF VBP program year by advancing the beginning of the performance period by 1 year from the previous program year.

We invite public comment on our proposals to adopt performance periods for the Nursing Staff Turnover, Falls with Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization measures.

b. Proposed Baseline Periods for the Nursing Staff Turnover, Falls With Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization Measures

In the FY 2016 SNF PPS final rule (80 FR 46422) we discussed that, as with other Medicare quality programs, we generally adopt baseline periods for a fiscal year that occurs prior to the performance periods for that fiscal year to establish measure performance standards. We also discussed our intent to adopt baseline periods that are as close as possible in duration as performance periods for a fiscal year, as well as our intent to seasonally align baseline periods with performance periods to avoid any effects on quality measurement that may result from tracking SNF performance during different times in a year. Therefore, to align with the proposed performance period length for the Nursing Staff Turnover, Falls with Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization measures, we are proposing to adopt 1-year baseline periods for those measures.

We also recognize that we are required, under section 1888(h)(3)(C) of the Act, to calculate and announce performance standards no later than 60 days prior to the start of performance periods. Therefore, we believe that baseline periods that occur 4 fiscal years prior to the applicable fiscal program year, and 2 fiscal years prior to the performance periods, is most appropriate for these measures and would provide sufficient time to calculate and announce performance standards prior to the start of the performance periods.

For these reasons, we are proposing to adopt the following baseline periods:

• FY 2022 (October 1, 2021 through September 30, 2022) as the baseline period for the Nursing Staff Turnover measure for the FY 2026 SNF VBP program year.
• FY 2023 (October 1, 2022 through September 30, 2023) as the baseline period for the Falls with Major Injury (Long-Stay) measure for the FY 2027 SNF VBP program year.
• FY 2023 (October 1, 2022 through September 30, 2023) as the baseline period for the Discharge Function measure for the FY 2027 SNF VBP program year.
• FY 2023 (October 1, 2022 through September 30, 2023) as the baseline period for the Long Stay Hospitalization measure for the FY 2027 SNF VBP program year.

In alignment with the previously adopted SNF VBP measures, we are also proposing that, for these measures, we would automatically adopt the baseline period for a SNF VBP program year by advancing the beginning of the baseline period by 1 year from the previous program year.

We invite public comment on our proposals to adopt baseline periods for the Nursing Staff Turnover, Falls with Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization measures.

4. Proposed Performance Periods and Baseline Periods for the SNF WS PPR Measure Beginning With the FY 2028 SNF VBP Program Year

a. Proposed Performance Period for the SNF WS PPR Measure Beginning With the FY 2028 SNF VBP Program Year

The proposed SNF WS PPR measure is calculated using 2 consecutive years of Medicare FFS claims data, and therefore, we are proposing to adopt a 2-year performance period for this measure. During the re-specification process for the SNF WS PPR measure, we determined that using 2 years of data improved the measure reliability. Specifically, the intraclass correlation coefficient (with the Spearman-Brown correction applied) for the SNF WS PPR measure was 0.71 compared to 0.56 for the SNFRM. We refer readers to section VII.B.2. of this proposed rule and the SNF WS PPR measure technical specifications, available at https://www.cms.gov/​files/​document/​snfvbp-snfwsppr-draft-techical-specification.pdf, for additional details.

Accordingly, we are proposing to adopt October 1, 2024 through September 30, 2026 (FY 2025 and FY 2026) as the performance period for the SNF WS PPR measure for the FY 2028 SNF VBP program year. We believe that using October 1, 2024 through September 30, 2026 (FY 2025 and FY 2026) as the performance period for the FY 2028 program year best balances our need for sufficient data to calculate valid and reliable performance scores with our requirement under section 1888(h)(7) of the Act to announce the resulting payment adjustments no later than 60 days prior to the program year involved.

In alignment with the previously adopted SNF VBP measures, we are also proposing that for the SNF WS PPR measure, we would automatically adopt the performance period for a SNF VBP program year by advancing the beginning of the performance period by 1 year from the previous program year.

We invite public comment on our proposals related to the performance periods for the SNF WS PPR measure beginning with the FY 2028 program year.

b. Proposed Baseline Period for the SNF WS PPR Measure Beginning With the FY 2028 SNF VBP Program Year

Our policy is to generally adopt a baseline period for a fiscal year that occurs prior to the performance period for that fiscal year in order to establish a measure's performance standards. We also generally adopt baseline periods that are as close as possible in duration as the performance period for a fiscal year, as well as seasonally aligning the baseline periods with performance periods to avoid any effects on quality measurement that may result from tracking SNF performance during different times in a year. Therefore, to align with the proposed performance period length for the SNF WS PPR measure, we are proposing a 2-year baseline period for this measure.

We also recognize that we are required, under section 1888(h)(3)(C) of the Act, to calculate and announce performance standards no later than 60 days prior to the start of the performance period. Therefore, we believe that a baseline period that begins 6 fiscal years prior to the applicable fiscal program year, and 3 fiscal years prior to the applicable performance period, is most appropriate for the SNF WS PPR measure and would provide sufficient time to calculate and announce performance standards prior to the start of the performance period. For these reasons, we are proposing to adopt October 1, 2021 through September 30, 2023 (FY 2022 and FY 2023) as the baseline period for the SNF WS PPR measure for the FY 2028 SNF VBP program year.

In alignment with the previously adopted SNF VBP measures, we are also proposing that for the SNF WS PPR measure, we would automatically adopt the baseline period for a SNF VBP program year by advancing the beginning of the baseline period by 1 year from the previous program year.

We invite public comment on our proposals related to the baseline period for the SNF WS PPR measure beginning with FY 2028 SNF VBP program year.

c. SNFRM and SNF WS PPR Performance Period and Baseline Period Considerations

As discussed in the previous section, we are proposing that the first performance period for the SNF WS PPR measure would be October 1, 2024 through September 30, 2026 (FY 2025 and FY 2026), and the first baseline period would be October 1, 2021 through September 30, 2023 (FY 2022 and FY 2023). In section VII.B.3. of this proposed rule, we are proposing to replace the SNFRM with the SNF WS PPR beginning with the FY 2028 program year. Therefore, the last program year that would include the SNFRM would be FY 2027. The last performance period for the SNFRM would be FY 2025 and the last baseline period would be FY 2023. We note that because the SNF WS PPR measure is a 2-year measure and the SNFRM is a 1-year measure, the data used to calculate the baseline and performance period for the SNF WS PPR measure for the FY 2028 program year would include data that is also used to calculate the baseline and performance period for the SNFRM for the FY 2027 program year. We believe the overlap is necessary to ensure that we can transition from the SNFRM to the SNF WS PPR seamlessly, without any gaps in the use of either measure.

D. SNF VBP Performance Standards

1. Background

We refer readers to the FY 2017 SNF PPS final rule (81 FR 51995 through 51998) for a summary of the statutory provisions governing performance standards under the SNF VBP Program and our finalized performance standards policy. In the FY 2019 SNF PPS final rule (83 FR 39276 through 39277), we also adopted a policy allowing us to correct the numerical values of the performance standards. Further, in the FY 2023 SNF PPS final rule (87 FR 47583 through 47584), we amended the definition of “Performance Standards,” redesignated that definition as § 413.338(a)(12), and added additional detail for our performance standards correction policy at § 413.338(d)(6).

We adopted the final numerical values for the FY 2024 performance standards in the FY 2022 SNF PPS final rule (86 FR 42513) and adopted the final numerical values for the FY 2025 performance standards in the FY 2023 SNF PPS final rule (87 FR 47584).

We are not proposing any changes to these performance standards policies in this proposed rule.

2. Estimated Performance Standards for the FY 2026 Program Year

In the FY 2023 SNF PPS final rule (87 FR 47564 through 47576), we adopted two new quality measures for the FY 2026 program year: SNF HAI and Total Nurse Staffing measures. In section VII.B.4.b. of this proposed rule, we are proposing to adopt the Nursing Staff Turnover measure beginning with the FY 2026 program year. We are also proposing that the performance period for the Nursing Staff Turnover measure for the FY 2026 program year would be FY 2024 (October 1, 2023 through September 30, 2024). Therefore, the FY 2026 program year would consist of four measures (SNFRM, SNF HAI, Total Nurse Staffing, and Nursing Staff Turnover measures).

To meet the requirements at section 1888(h)(3)(C) of the Act, we are providing estimated numerical performance standards for the FY 2026 program year for the three previously adopted measures (SNFRM, SNF HAI, and Total Nurse Staffing measures), as well as the proposed Nursing Staff Turnover measure. In accordance with our previously finalized methodology for calculating performance standards (81 FR 51996 through 51998), the estimated numerical values for the FY 2026 program year performance standards are shown in Table 19.

Table 19—Estimated FY 2026 SNF VBP Program Performance Standards

Measure short name	Achievement threshold	Benchmark
SNFRM	0.78526	0.82818
SNF HAI Measure	0.91468	0.94766
Total Nurse Staffing Measure	3.33289	5.98339
Nursing Staff Turnover Measure	0.37500	0.72925

3. Estimated Performance Standards for the DTC PAC SNF Measure for the FY 2027 Program Year

In the FY 2023 SNF PPS final rule (87 FR 47576 through 47580), we adopted the DTC PAC SNF measure beginning with the FY 2027 program year. In that final rule (87 FR 47582 through 47583), we also finalized that the baseline and performance periods for the DTC PAC SNF measures would be 2 consecutive years, and that FY 2024 and FY 2025 would be the performance period for the DTC PAC SNF measure for the FY 2027 program year.

To meet the requirements at section 1888(h)(3)(C) of Act, we are providing estimated numerical performance standards for the DTC PAC SNF measure for the FY 2027 program year. In accordance with our previously finalized methodology for calculating performance standards (81 FR 51996 through 51998), the estimated numerical values for the DTC PAC SNF measure for the FY 2027 program year performance standards are shown in Table 20.

We note that we will provide the estimated numerical performance standard values for the remaining measures applicable in the FY 2027 program year in the FY 2025 SNF PPS proposed rule.

Table 20—Estimated FY 2027 SNF VBP Program Performance Standards for the DTC PAC SNF Measure

Measure short name	Achievement threshold	Benchmark
DTC PAC SNF Measure	0.44087	0.68956

E. SNF VBP Performance Scoring Methodology

1. Background

Our performance scoring policies are codified at § 413.338(d) and (e) of our regulations. We also refer readers to the following prior final rules for detailed background on the scoring methodology for the SNF VBP Program:

• In the FY 2017 SNF PPS final rule (81 FR 52000 through 52005), we finalized several scoring methodology policies, including a policy to use the higher of a SNF's achievement and improvement scores as that SNF's performance score for a given program year.
• In the FY 2018 SNF PPS final rule (82 FR 36614 through 36616), we finalized: (1) a rounding policy, (2) a logistic exchange function, (3) a 60 percent payback percentage, and (4) a SNF performance ranking policy.
• In the FY 2019 SNF PPS final rule (83 FR 39278 through 39281), we finalized several scoring methodology policies, including a scoring policy for SNFs without sufficient baseline period data and an extraordinary circumstances exception policy.
• In the FY 2022 SNF PPS final rule (86 FR 42513 through 42515), we finalized a special scoring and payment policy for the FY 2022 SNF VBP Program due to the impact of the PHE for COVID–19.
• In the FY 2023 SNF PPS final rule (87 FR 47584 through 47590), we finalized a special scoring and payment policy for the FY 2023 SNF VBP Program due to the continued impact of the PHE for COVID–19. In that final rule, we also finalized several scoring methodology policies to accommodate the addition of new measures to the Program, including: (1) case minimum and measure minimum policies, including case minimums for the SNFRM, SNF HAI, Total Nurse Staffing, and DTC PAC SNF measures, (2) updates to the scoring policy for SNFs without sufficient baseline period data, (3) removal of the low-volume adjustment policy, and (4) a measure-level and normalization scoring policy to replace the previously adopted scoring methodology policies beginning with the FY 2026 program year.

2. Proposed Case Minimum and Measure Minimum Policies

a. Background

We refer readers to the FY 2023 SNF PPS final rule (87 FR 47585 through 47587) for a detailed description of our considerations for adopting case minimums and measure minimums. Our case minimum and measure minimum policies are also codified at § 413.338(b) of our regulations.

As discussed in section VII.B.4. of this proposed rule, we are proposing to adopt the Nursing Staff Turnover measure beginning with the FY 2026 program year; the Falls with Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization measures beginning with the FY 2027 program year; and the SNF WS PPR measure beginning with the FY 2028 program year. Therefore, we are also proposing to adopt case minimums for the new measures and proposing to update the previously finalized measure minimum for the FY 2027 program year. Although the addition of the Nursing Staff Turnover measure beginning with FY 2026 would increase the total number of measures for that program year, we believe that the previously finalized measure minimum of two measures remains sufficient for that program year.

b. Proposed Case Minimums During a Performance Period for the Nursing Staff Turnover, Falls With Major Injury (Long-Stay), DC Function, Long Stay Hospitalization, and SNF WS PPR Measures

In this proposed rule, we are proposing to adopt the Nursing Staff Turnover measure beginning with the FY 2026 program year; the Falls with Major Injury (Long-Stay), Long Stay Hospitalization, and DC Function measures beginning with the FY 2027 program year; and the SNF WS PPR measure beginning with the FY 2028 program year. Therefore, to meet the requirements at section 1888(h)(1)(C)(i) of the Act, we are concurrently proposing to adopt case minimums for those proposed measures.

For the Nursing Staff Turnover measure, we are proposing that SNFs must have a minimum of 1 eligible stay during the 1-year performance period and at least 5 eligible nursing staff (RNs, LPNs, and nurse aides) during the 3 quarters of PBJ data included in the measure denominator. SNFs must meet both of these requirements in order to be eligible to receive a score on the measure for the applicable program year. We believe this case minimum requirement is appropriate and consistent with the findings of measure testing analyses and the measure specifications. For example, using FY 2021 data, we estimated that 80 percent of SNFs met the 5-eligible nursing staff minimum. In addition, we note that the 1-eligible stay and 5-eligible nursing staff minimums were determined to be appropriate for publicly reporting this measure on the Care Compare website. We believe these case minimum standards for public reporting purposes are also appropriate standards for establishing a case minimum for this measure under the SNF VBP Program. We also believe this case minimum requirement supports our objective, which is to establish case minimums that appropriately balance quality measure reliability with our continuing desire to score as many SNFs as possible on this measure.

For the Falls with Major Injury (Long-Stay) measure, we are proposing that SNFs must have a minimum of 20 residents in the measure denominator during the 1-year performance period to be eligible to receive a score on the measure for the applicable fiscal program year. We believe this case minimum requirement is appropriate and consistent with the findings of measure testing analyses. For example, using FY 2021 data, we estimated that nearly 96 percent of SNFs met the 20-resident minimum. In addition, testing results indicated that a 20-resident minimum produced moderately reliable measure rates for the purposes of public reporting.^[286] We believe these case minimum standards for public reporting purposes are also appropriate standards for establishing a case minimum for this measure under the SNF VBP Program. We also believe this case minimum requirement supports our objective, which is to establish case minimums that appropriately balance quality measure reliability with our continuing desire to score as many SNFs as possible on this measure.

For the Long Stay Hospitalization measure, we are proposing that SNFs must have a minimum of 20 eligible stays during the 1-year performance period to be eligible to receive a score on the measures for the applicable fiscal program year. We believe this case minimum requirement is appropriate and consistent with the findings of measure testing analyses. For example, using CY 2021 data, we estimated that approximately 80 percent of SNFs met the 20-eligible stay minimum. In addition, we note that the 20-eligible stay minimum was determined to be appropriate for publicly reporting this measure under the Five-Star Quality Rating System. We believe these case minimum standards for public reporting purposes are also appropriate standards for establishing a case minimum for this measure under the SNF VBP Program. We also believe this case minimum requirement supports our objective, which is to establish case minimums that appropriately balance quality measure reliability with our continuing desire to score as many SNFs as possible on this measure.

For the DC Function measure, we are proposing that SNFs must have a minimum of 20 eligible stays during the 1-year performance period in order to be eligible to receive a score on the measure for the applicable fiscal program year. We believe this case minimum requirement is appropriate and consistent with the findings of measure testing analyses. For example, testing results, which used FY 2019 data, found that nearly 84 percent of SNFs met the 20-eligible stay minimum.^[287] In addition, those testing results indicated that a 20-eligible stay minimum produced sufficiently reliable measure rates. We believe this case minimum requirement supports our objective, which is to establish case minimums that appropriately balance quality measure reliability with our continuing desire to score as many SNFs as possible on this measure.

For the SNF WS PPR measure, we are proposing that SNFs must have a minimum of 25 eligible stays during the 2-year performance period in order to be eligible to receive a score on the measure for the applicable fiscal program year. We believe this case minimum requirement is appropriate and consistent with the findings of measure testing analyses. For example, using FY 2020 through FY 2021 data, we estimated that nearly 91 percent of non-swing bed SNFs met the 25-eligible stay minimum. In addition, testing results indicated that a 25-eligible stay minimum produced sufficiently reliable measure rates.^[288] We believe this case minimum requirement supports our objective, which is to establish case minimums that appropriately balance quality measure reliability with our continuing desire to score as many SNFs as possible on this measure.

We invite public comment on our proposal to adopt case minimums for the Nursing Staff Turnover, Falls with Major Injury (Long-Stay), Long Stay Hospitalization, DC Function, and SNF WS PPR measures.

c. FY 2026 Measure Minimum

In the FY 2023 SNF PPS final rule (87 FR 47587), we finalized the measure minimum for the FY 2026 program year. Specifically, we finalized that for the FY 2026 program year, SNFs must report the minimum number of cases for two of the three measures during the applicable performance period to receive a SNF Performance Score and value-based incentive payment.

In this proposed rule, we are proposing to adopt an additional measure for the FY 2026 program year: Nursing Staff Turnover measure, which means the FY 2026 SNF VBP measure set would consist of a total of four measures. Although we are proposing the Nursing Staff Turnover measure beginning with the FY 2026 program year, which would increase the total number of measures applicable in FY 2026, we believe that our previously finalized minimum of two measures for FY 2026 remains sufficient because if we required a minimum of three or four measures, all swing-bed facilities would be excluded from the Program. Two of the four measures that would be included in the FY 2026 program year are PBJ-based measures. Since swing-bed facilities do not submit PBJ data, those facilities would not meet the measure minimum of reporting three or four measures to the Program. Therefore, to ensure swing-bed facilities continue to have the opportunity to be included in the Program, we are not proposing to update the measure minimum for the FY 2026 program year. SNFs must report the minimum number of cases for two of the four measures during the performance period to be included in the FY 2026 program year.

d. Proposal To Update the FY 2027 Measure Minimum

In the FY 2023 SNF PPS final rule (87 FR 47587), we finalized the measure minimum for the FY 2027 program year. Specifically, we finalized that for the FY 2027 program year, SNFs must report the minimum number of cases for three of the four measures during the performance period to receive a SNF Performance Score and value-based incentive payment.

In addition to our proposal to adopt the Nursing Staff Turnover measure beginning with the FY 2026 program year, we are proposing to adopt three additional measures beginning with the FY 2027 program year: Falls with Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization measures. Therefore, the FY 2027 SNF VBP measure set would consist of a total of eight measures. Given the proposed changes to the number of measures applicable in FY 2027, we are also proposing to update the measure minimum for the FY 2027 program year.

Specifically, we are proposing that for the FY 2027 program year, SNFs must report the minimum number of cases for four of the eight measures during the performance period to receive a SNF Performance Score and value-based incentive payment. SNFs that do not meet these minimum requirements would be excluded from the FY 2027 program and would receive their full Federal per diem rate for that fiscal year. Under these proposed minimum requirements, we estimate that approximately 8 percent of SNFs would be excluded from the FY 2027 Program. We found that increasing the measure minimum requirement from three to four measures out of a total of eight measures would cause the number of SNFs excluded from the Program to increase from approximately 3 percent to 8 percent of SNFs for FY 2027. However, the measure minimum requirement that we finalized for FY 2027 in the FY 2023 SNF PPS final rule (87 FR 47587), which was based on a measure set of four measures, excluded approximately 16 percent of SNFs. We also found that increasing the measure minimum requirement would have little effect on the percentage of SNFs that would receive a net-positive incentive payment multiplier (IPM) of the overall distribution of IPMs. Based on these testing results, we believe the proposed update to the measure minimum for FY 2027 aligns with our desire to ensure that as many SNFs as possible can receive a reliable SNF Performance Score and value-based incentive payment.

We invite public comment on our proposal to update the measure minimum for the FY 2027 SNF VBP program year.

3. Proposed Application of the SNF VBP Scoring Methodology to Proposed Measures

a. Background

In the FY 2023 SNF PPS final rule (87 FR 47588 through 47590), we finalized several updates to the scoring methodology for the SNF VBP Program beginning with the FY 2026 program year. We finalized a measure-level scoring policy such that SNFs have the opportunity to earn a maximum of 10 points on each measure for achievement, and a maximum of nine points on each measure for improvement. The higher of these two scores will then be the SNF's score for each measure and used to calculate the SNF Performance Score, except if the SNF does not meet the case minimum for a given measure during the applicable baseline period, in which case that SNF will only be scored on achievement for that measure. We also finalized a normalization policy such that we will calculate a raw point total for each SNF by adding up that SNF's score on each of the measures applicable for the given program year. We will then normalize the raw point totals such that the SNF Performance Score is reflected on a 100-point scale.

In this proposed rule, we are proposing to adopt the Nursing Staff Turnover measure beginning with the FY 2026 program year; and the Falls with Major Injury (Long-Stay), Long Stay Hospitalization, and DC Function measures beginning with the FY 2027 program year. To accommodate those proposed measures in our scoring methodology, we are also proposing to adjust our scoring methodology for the FY 2026 and FY 2027 program years, which we discuss in the next section.

We also note that we are proposing to replace the SNFRM with the SNF WS PPR measure beginning with the FY 2028 program year, which would not affect the total number of measures applicable in the Program for FY 2028. We intend to address the FY 2028 performance scoring methodology in future rulemaking.

b. Proposed FY 2026 Performance Scoring

We are proposing to adopt the Nursing Staff Turnover measure beginning with the FY 2026 program year, and therefore, the FY 2026 program year measure set would include four measures (SNFRM, SNF HAI, Total Nurse Staffing, and Nursing Staff Turnover measures).

We are proposing to apply our previously finalized scoring methodology, which is codified at § 413.338(e) of our regulations, to the proposed Nursing Staff Turnover measure. Specifically, we would award up to 10 points based on achievement, and up to nine points based on improvement, so long as the SNF meets the case minimum for the measure. The higher of these two scores would be the SNF's score for the measure for FY 2026, except in the instance that the SNF does not meet the case minimum for the measure during the applicable baseline period, in which case that SNF would only be scored on achievement for the measure.

As previously finalized, we would then add the score for each of the four measures for which the SNF met the case minimum to get the raw point total. The maximum raw point total for the FY 2026 program year would be 40 points. We would then normalize each SNF's raw point total, based on the number of measures for which that SNF met the case minimum, to get a SNF Performance Score that is on a 100-point scale using our previously finalized normalization policy. We would only award a SNF Performance Score to SNFs that meet the measure minimum for FY 2026.

We invite public comment on our proposal to apply our previously finalized scoring methodology to the proposed Nursing Staff Turnover measure beginning with the FY 2026 SNF VBP program year.

c. Proposed FY 2027 Performance Scoring

We are proposing to adopt the Falls with Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization measures beginning with the FY 2027 program year, and therefore, the FY 2027 program year measure set would include eight measures.

Our current scoring methodology is codified at § 413.338(e) of our regulations. Under that scoring methodology, we award up to 10 points for each measure based on achievement, and up to nine points for each measure based on improvement, so long as the SNF meets the case minimum for a given measure. The higher of these two scores would be the SNF's score on that measure for FY 2027, except in the instance that the SNF does not meet the case minimum for a given measure during the applicable baseline period, in which case that SNF would only be scored on achievement for that measure. As previously finalized, we would then sum the scores for each of the eight measures for which the SNF met the case minimum to get the raw measure point total. The maximum raw measure point total for the FY 2027 program year would be 80 points.

We are proposing to apply these elements of the scoring methodology to the proposed Falls with Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization measures. In addition, and as discussed further in section VII.E.4. of this proposed rule, we are proposing to adopt a Health Equity Adjustment in which eligible SNFs could earn a maximum of two points for each measure (including all previously finalized and newly proposed measures) if they are a top tier performing SNF, which we are proposing to define as a SNF whose score on the measure for the program year falls in the top third of performance (greater than or equal to the 66.67th percentile) on a given measure, and the SNF's resident population during the performance period that applies to the program year includes at least 20 percent of residents with dual eligibility status (DES). This combination of a SNF's performance and proportion of residents with DES would be used to determine a SNF's Health Equity Adjustment (HEA) bonus points. We would then add the total number of HEA bonus points to the normalized measure point total on a scale from 0 to 100, and that total would be the SNF Performance Score earned by the SNF for the program year. We would only award a SNF Performance Score to SNFs that meet the proposed measure minimum for FY 2027.

4. Proposal To Incorporate Health Equity Into the SNF VBP Program Scoring Methodology Beginning With the FY 2027 Program Year

a. Background

Significant and persistent inequities in health outcomes exist in the U.S. Belonging to a racial or ethnic minority group; living with a disability; being a member of the lesbian, gay, bisexual, transgender, queer, and intersex (LGBTQI+) communities; living in a rural area; being a member of a religious minority; being near or below the poverty level; or being dually enrolled in Medicare and Medicaid, is often associated with worse health outcomes.^{[289]  [290]  [291]  [292]  [293]  [294]  [295]  [296]  [297]} Executive Order 13985 on Advancing Racial Equity and Support for Underserved Communities Through the Federal Government, (January 20, 2021) defines “equity” as “the consistent and systematic fair, just, and impartial treatment of all individuals, including individuals who belong to underserved communities that have been denied such treatment, such as Black, Latino, and Indigenous and Native American persons, Asian Americans and Pacific Islanders and other persons of color; members of religious minorities; lesbian, gay, bisexual, transgender, queer, [and intersex] (LGBTQ[I] +); ^[298] persons with disabilities; persons who live in rural areas; and persons otherwise adversely affected by persistent poverty or inequality” (86 FR 7009). CMS defines “health equity” as the “attainment of the highest level of health for all people, where everyone has a fair and just opportunity to attain their optimal health regardless of race, ethnicity, disability, sexual orientation, gender identity, socioeconomic status, geography, preferred language, or other factors that affect access to care and health outcomes.” ^[299]

Advancing health equity is a key pillar of CMS' strategic vision,^[300] and we are working to advance health equity by designing, implementing, and operationalizing policies and programs aimed at identifying and reducing health disparities. This includes the CMS Mapping Medicare Disparities Tool,^[301] the CMS Innovation Center's Accountable Health Communities Model,^[302] the CMS Disparity Methods stratified reporting program,^[303] the collection of standardized patient assessment data elements in the post-acute care setting,^[304] and health equity program adjustments like the Medicare Shared Savings Program's recently adopted health equity adjustment for Accountable Care Organizations that report all-payer eCQMs/MIPS CQMs (87 FR 69838 through 69857). Further, the 2022–2032 CMS Framework for Health Equity outlines CMS' priorities to advance health equity, expand coverage, and improve health outcomes for the more than 170 million individuals supported by CMS programs.^[305] We also recently updated the CMS National Quality Strategy (NQS), which includes advancing health equity as one of eight strategic goals.^[306] As we continue to leverage our programs to improve quality of care, we note it is important to implement strategies that “create aligned incentives that drive providers to improve health outcomes for all beneficiaries.” ^[307]

Prioritizing the achievement of health equity is essential in the SNF VBP Program because disparities in SNFs appear to be widespread, from admissions to quality of care to nurse staffing and turnover.^{[308]  [309]} In the 2016 Report to Congress, the Office of the Assistant Secretary for Planning and Evaluation (ASPE) reported that individuals with social risk factors, such as dual eligibility status, had worse outcomes and were more likely to be cared for by lower-quality SNFs.^[310] Individuals with dual eligibility status (DES) are those who are eligible for both Medicare and Medicaid coverage. Individuals with DES are more likely to have disabilities or functional impairments, more likely to be medically complex, more likely to have greater social needs, and have a greater risk of negative health outcomes compared to individuals without DES.^[311] They are also more likely to be admitted to SNFs that have lower staffing levels, have a higher share of residents who are enrolled in Medicaid in their total resident population, and experience resource constraints.^[312] In addition, studies have found that DES is an important predictor of admission to a low-quality SNF.^[313] All of these factors indicate that individuals with DES represent an underserved population that is more clinically complex, has greater social needs and is more often admitted to lower-resourced SNFs than those without DES. This presents significant challenges to provide quality care to patients with greater resource-intensive needs by providers that may have fewer resources, as effectively implementing quality improvement initiatives requires time, money, staff, and technology.^{[314]  [315]  [316]  [317]} As a result, competitive programs, like the current SNF VBP Program, may place some SNFs that serve this underserved population at a disadvantage.

In the FY 2023 SNF PPS proposed rule (87 FR 22789), we requested public comments on policy changes that we should consider on the topic of health equity. In the FY 2023 SNF PPS final rule (87 FR 47596 through 47597), we provided a detailed summary of the feedback we received on this topic. Commenters overwhelmingly supported our commitment to advancing health equity for SNF residents, with some suggesting that we examine factors that may lead to care inequities. One commenter suggested we adopt risk adjustment or incentive payments for SNFs that admit individuals that other SNFs will not admit. Another commenter recommended pairing clinical data measures with social risk metrics to help providers deliver more comprehensive care. Overall, commenters were interested in understanding where disparities may exist and wanted us to work with SNFs and other interested parties to understand the greatest needs in achieving health equity to ensure any revisions to the Program could be implemented with minimal data burden. We considered all the comments we received as we developed our Health Equity Adjustment proposal described below.

We believe that SNFs and providers across all settings can consistently perform well even when caring for a high proportion of individuals who are underserved,^[318] and, with the right program components,VBP programs can create meaningful incentives for SNFs that serve a high proportion of individuals who are underserved to deliver high quality care.^{[319]  [320]  [321]  [322]  [323]  [324]} We believe updating the scoring methodology, as detailed in the following sections, would appropriately measure performance and create these meaningful incentives for those who care for a high proportions of residents with DES.

b. Health Equity Adjustment Proposal Summary

Section 1888(h)(4)(A) of the Act requires the Secretary to develop a methodology for assessing the total performance of each SNF based on performance standards established under section 1888(h)(3) of the Act with respect to the measures applied under section 1888(h)(2) of the Act. To further align with our goals to achieve health equity, address health disparities, and assess SNF performance more accurately and completely under the SNF VBP Program, we are proposing to apply an adjustment that would be added to the normalized sum of a SNF's measure points on SNF VBP Program measures. As described previously, residents with DES are an underserved population that is clinically complex, has significant social needs and is more frequently admitted to SNFs that have larger populations of Medicaid residents and fewer resources than SNFs that do not care for individuals with DES.^{[325]  [326]  [327]} These lower-resourced SNFs are less likely to receive positive payment adjustments, which is a considerable limitation of the current SNF VBP program's ability to incentivize equitable care.^[328] Careful consideration must be taken to modify the Program in a way that addresses this issue and ensures that we provide appropriate rewards and incentives to all SNFs, including those that serve residents with DES. The goal of this Health Equity Adjustment is to not only appropriately measure performance by rewarding SNFs that overcome the challenges of caring for higher proportions of SNF residents with DES but also to incentivize those who have not achieved such high-quality care to work towards improvement. We believe this Health Equity Adjustment incentivizes high-quality care across all SNFs. We also believe this scoring change, through the creation of an adjustment designed to award points based on the quality of care provided and the proportion of residents with DES, is consistent with our strategy to advance health equity.^[329]

The Health Equity Adjustment (HEA) would be calculated using a methodology that considers both the SNF's performance on the SNF VBP Program measures, and the proportion of residents with DES out of the total resident population in a given program year at each SNF. To be eligible to receive HEA bonus points, a SNF's performance would need to meet or exceed a certain threshold and its resident population during the applicable performance period for the program year would have to include at least 20 percent of residents with DES. Thus, SNFs that perform well on quality measures and serve a higher proportion of SNF residents with DES would receive a larger adjustment. The specific methodology for the proposed calculation of the HEA is described in section VII.E.4.d. of this proposed rule. By providing this HEA to SNFs that serve higher proportions of SNF residents with DES and that perform well on quality measures, we believe we can appropriately recognize the resource intensity expended to achieve high performance on quality measures by SNFs that serve a high proportion of SNF residents with DES, while also mitigating the worse health outcomes experienced by underserved populations through incentivizing better care across all SNFs.

An analysis of payment from October 2018 for the SNF VBP Program found that SNFs that served higher proportions of Medicaid residents were less likely to receive positive payment adjustments. As noted previously, residents with DES are more likely to be admitted to SNFs with higher proportions of Medicaid residents ^[330] suggesting that SNFs serving higher proportions of SNF residents with DES face challenges in utilizing their limited resources to improve the quality of care for their complex residents.^[331] Thus, we aimed to adjust the current program scoring methodology to ensure that all SNF residents, including those with DES, receive high-quality care. We conducted an analysis utilizing FY 2018–2021 measure data for our finalized and proposed measures, including a simulation of performance from all 8 finalized and proposed measures for the FY 2027 Program and found that the HEA significantly increased the proportion of SNFs with high proportions of SNF residents with DES that received a positive value-based incentive payment adjustment indicating that this approach would modify the SNF VBP program in the way it is intended.

We are proposing to call this proposed adjustment the Health Equity Adjustment (HEA) and to adopt it beginning with the FY 2027 program year.

c. Proposed Health Equity Adjustment Beginning With the FY 2027 SNF VBP Program Year

We propose to define the term “underserved population” as residents with DES for purposes of this HEA. DES has been established in the literature, including research specifically looking at SNFs,^{[332]  [333]} and has been found to be an important factor that impacts pay for performance and other quality programs.^{[334]  [335]} In addition, DES is currently utilized in the Hospital Readmissions Reduction Program.

The Medicare Shared Savings Program recently adopted a health equity adjustment for Accountable Care Organizations that report all-payer eCQMs/MIPS CQMs, are high-performing on quality, and serve a large proportion of underserved beneficiaries, as defined by dual-eligibility/enrollment in the Medicare Part D low income subsidy (LIS) (meaning the individual is enrolled in a Part D plan and receives LIS) and an Area Deprivation Index (ADI) score of 85 or above, as detailed in the CY 2023 PFS final rule (87 FR 69838 through 69857). At this time, for the SNF VBP Program's proposed HEA, we believe that it is preferable to use DES to identify SNF residents who are underserved. We also explored alternative indicators to identify populations that are underserved for purposes of this proposal, such as a resident's eligibility for the Medicare Part D Low-Income Subsidy (LIS) program or whether the resident lives in an area with high deprivation, as measured by the Area Deprivation Index (ADI), however, we determined that for the current proposal, utilizing residents with DES to identify underserved populations would best serve the goals of the adjustment. Individuals who are eligible for the LIS program have incomes up to 150 percent of the Federal poverty level.^[336] Utilizing residents who are eligible for the LIS program would include most residents with DES, as well as additional residents who may be underserved; however, the data on the LIS program are only available for those enrolled in Medicare Part D, which may limit its effectiveness, and it is not uniform across both States and territories. Further, those eligible for the LIS program have not been studied extensively in the SNF setting and the effect of using those eligible for the LIS program to determine a SNF's underserved population has also not been studied extensively. Geographic-based or neighborhood-level economic indices, such as the ADI, have been utilized to look at characteristics of healthcare facilities in low-resourced areas and could be used as a proxy for negative health outcomes due to medical and social risk factors.^{[337]  [338]} ADI appears to be an important predictor of poor health outcomes, even when adjusting for individual characteristics, suggesting neighborhood or geography may play an even more important role in health than individual characteristics.^{[339]  [340]} However, there is not much literature or analysis that has been conducted linking these indices to negative health outcomes specifically in the SNF setting. Therefore, we propose to only use DES data at this time to identify SNF residents who are underserved for this HEA proposal, given that the DES data are readily available, are evidenced based in the SNF setting, and are already used in the Hospital Readmissions Reduction Program. We intend to consider how to best incorporate the LIS, ADI, and other indicators to identify those who are underserved in future health equity adjustment proposals for the SNF VBP Program as more research is made available. We are seeking comment on the potential future use of these additional indicators in the RFI in section VII.E.5 of this proposed rule. We provide additional detail on how we would calculate SNF residents with DES for the purpose of this adjustment later in this section of this proposal.

In order to calculate the HEA, we first propose to assign to each SNF 2 points for each measure for which it is a top tier performing SNF. We propose to define a top tier performing SNF as a SNF whose performance during the program year is in the top third (greater than or equal to the 66.67th percentile) of the performance of all SNFs on the measure during the same program year. Each measure would be assessed independently such that a SNF that is a top tier performing SNF for one measure would be assigned 2 points for that measure even if they are not a top tier performing SNF for any other measure. Similarly, if a SNF is a top tier performing SNF for all measures, they would be assigned 2 points for all measures.

We also propose to assign a measure performance scaler for each SNF that would be equal to the total number of assigned points that the SNF earns on all measures as a result of its performance. Under this approach, for the FY 2027 Program Year, a SNF would receive a maximum measure performance scaler of 16 if the SNF is a top tier performing SNF on all 8 measures (both proposed and already finalized) for that program year. As described in more detail in the following paragraph and in section VII.E.4.e of this proposed rule, we decided on assigning a maximum point value of 2 for each measure because we believe that it provides an appropriate incentive to top tier performing SNFs that serve a high proportion of SNF residents with DES to continue their quality efforts, as well as an incentive for all SNFs that serve SNF residents with DES to improve their quality.

Based on our calculation of measure data from FY 2018–2021 the average SNF Performance Score for SNFs in the top third of performance that care for high proportions of residents with DES (SNFs with proportions of residents with DES in the top third) is 8.4 points lower than the SNF Performance Score for SNFs in the top third of performance that do not care for high proportions of residents with DES (40.8 for high performing SNFs with high proportions of residents with DES and 49.2 for all other high performing SNFs). Allowing for a maximum measure performance scaler of 16 for the FY 2027 program year would provide an opportunity for top tier performing SNFs that treat a high proportion of SNF residents with DES to close this gap. We also considered assigning 3 points for each measure to calculate the measure performance scaler. However, we determined that the maximum measure performance scaler a SNF could earn based on the assignment of 3 points per measure, 24 points, would exceed the number of points that many SNFs receive for their SNF Performance Score based on all Program measures, which diminishes the intent of the HEA as a bonus. We further discuss this option in section VII.E.4.e of this proposed rule. We also considered assigning a point value of 2 to SNFs in the middle third of performance (SNFs whose performance falls between the 33.33rd percentile and 66.67th percentile in performance) and assigning a point value of 4 to top tier performing SNFs for each measure to align with the Medicare Shared Savings Program's health equity adjustment (87 FR 69843 through 69845). This approach would provide a greater number of SNFs with the opportunity to benefit from the adjustment. However, in the SNF VBP, this approach could reduce the size of the payment adjustment available to SNFs whose performance is in the top tier, reducing the incentives to improve and deviating considerably from the primary goal of the program to appropriately assess performance and reward high quality performance among SNFs that care for high proportions of residents with DES.

We propose to define the term “underserved multiplier” for a SNF as the number representing the SNF's proportion of residents with DES out of its total resident population in the applicable program year, translated using a logistic exchange function. Due to the structure of the logistic exchange function, those SNFs with lower proportions of residents with DES have smaller underserved multipliers than their actual proportion of residents with DES and those SNFs with higher proportions of SNF residents with DES have underserved multipliers higher than their proportion of SNF residents with DES. The specific logistic function used to translate the SNF's proportion of residents with DES is described in section VII.E.4.d. of this proposed rule. We propose to define the total resident population at each SNF as Medicare beneficiaries identified from the SNF's Part A claims during the performance period of the 1-year measures. We propose to define residents with DES, for purposes of this proposal, as the percentage of Medicare SNF residents who are also eligible for Medicaid. We propose to assign DES for any Medicare beneficiary who was deemed by Medicaid agencies to be eligible to receive Medicaid benefits for any month during the performance period of the 1-year measures. For example, during the FY 2027 program year, we would calculate the proportion of residents with DES during any month of FY 2025 (October 1, 2024—September 30, 2025), which is the performance period of the FY 2027 Program year's 1-year measures. Similarly, a SNF's total resident population of Medicare beneficiaries identified from the SNF's Part A claims would be calculated from the SNF's Part A claims during FY 2025. Data on DES is sourced from the State Medicare Modernization Act (MMA) file of dual eligible beneficiaries, which each of the 50 States and the District of Columbia submit to CMS at least monthly. This file is utilized to deem individuals with DES automatically eligible for the Medicare Part D Low Income Subsidy, as well as other CMS program needs and thus can be considered the gold standard for determining DES. We note that this is the same file used for determining DES in the Hospital Readmissions Reduction Program. More detail on this file can be found on the CMS website at https://www.cms.gov/​Medicare-Medicaid-Coordination/​Medicare-and-Medicaid-Coordination/​Medicare-Medicaid-Coordination-Office/​DataStatisticalResources/​StateMMAFile and at the Research Data Assistance Center website at https://resdac.org/​cms-data/​variables/​monthly-medicare-medicaid-dual-eligibility-code-january.

We are proposing to calculate an underserved multiplier for a SNF if that SNF's proportion of residents with DES out of its total resident population during the applicable performance period of the 1-year measures is at least 20 percent. Imposing a floor of 20 percent for the underserved multiplier for a SNF to be eligible to receive HEA bonus points, reinforces that the adjustment is intended to appropriately measure performance by rewarding SNFs that are serving higher proportions of SNF residents with DES while also achieving high levels of quality performance. We describe this 20 percent floor in further detail in section VII.E.4.d. of this proposed rule. Lastly, we propose to define HEA bonus points for a SNF as the product of the SNF's measure performance scaler and the SNF's underserved multiplier. The HEA bonus points would then be added to the normalized sum of all points a SNF is awarded for each measure.

Through the proposed HEA bonus points, we seek to improve outcomes by providing incentives to SNFs to strive for high performance across measures, as well as to care for high proportions of residents with DES. The HEA bonus points calculation is purposefully designed to not reward poor quality. Instead, the HEA incentivizes SNFs that care for higher proportions of SNF residents with DES to improve their overall quality of care across the entire SNF population. As described more fully in section VII.E.4.d. of this proposed rule, the combination of the measure performance scaler and the underserved multiplier would result in a range of possible HEA bonus points that is designed to give the highest rewards to SNFs caring for a larger proportion of SNF residents with DES and delivering high quality care.

We welcome comments on this proposal. We are proposing to amend our regulations at § 413.338(a) to define these new scoring methodology terms, including underserved population, the measure performance scaler, top tier performing SNF, the underserved multiplier, and the HEA bonus points. We are also proposing to amend our regulations by adding a new paragraph (k) in § 413.338 that implements the Health Equity Adjustment beginning with the FY 2027 program year.

d. Proposed Calculation Steps and Examples

In this section, we outline the calculation steps and provide examples of the determination of HEA bonus points and the application of these HEA bonus points to the normalized sum of a SNF's measure points. These example calculations illustrate possible HEA bonus points resulting from the proposed approach, which accounts for both a SNF's quality performance and its proportion of residents with DES. For each SNF, the HEA bonus points would be calculated according to the following formula:

HEA bonus points = measure performance scaler × underserved multiplier

The proposed calculation of the HEA bonus points would be as follows:

Step One—Calculate the Number of Measure Performance Scaler Points for Each SNF

We propose to first calculate a measure performance scaler based on a SNF's score on each of the SNF VBP program measures. We would assign a point value of 2 for each measure where a SNF is a top tier performing SNF on that measure, such that for the FY 2027 program year, a SNF could receive a maximum 16 point measure performance scaler for being a top tier performing SNF for each of the 8 finalized and proposed measures. Top tier performance on each measure is calculated by determining the percentile that the SNF falls in based on their score on the measure as compared to the score earned by other SNFs who are eligible to receive a score on the measure. A SNF whose score is greater than or equal to the 66.67th (two-thirds) percentile on a given measure compared to all other SNFs would be considered a top tier performing SNF and would be assigned a point value of 2 for that measure. This is depicted in Table 21 for the FY 2027 program year. We note that if a SNF performs in the bottom two-thirds (less than 66.67th percentile) of performance on all measures, that SNF would be assigned a point value of 0 for each measure, resulting in a measure performance scaler of 0.

As described previously, we are proposing to assign to each SNF a point value of 2 for each measure for which it is a top tier performing SNF, and we are proposing that the measure performance scaler would be the sum of the point values assigned to each measure in the SNF VBP Program. We modeled this proposed measure performance scaler after the performance scaler finalized in the Medicare Shared Savings Program's health equity adjustment (87 FR 69843 through 69845) for consistency across CMS programs, although that adjustment allows for a middle performance group as well. However, as described previously, because we aim to specifically target the highest performing SNFs for this adjustment, we are limiting our adjustment to the top third of performers only.

Table 21—Example of the Measure Performance Scaler Assigned to SNFs Based on Performance by Measure

Measure	Example SNF 1		Example SNF 2		Example SNF 3		Example SNF 4
	Performance group	Value	Performance group	Value	Performance group	Value	Performance group	Value
SNFRM *	Top third	2	Top Third	2	Top Third	2	Bottom Two-Thirds	0
SNF HAI Measure	Top third	2	Top Third	2	Top Third	2	Bottom Two-Thirds	0
Total Nurse Staffing Measure	Top third	2	Bottom Two-Thirds	0	Bottom Two-Thirds	0	Top Third	2
DTC–PAC SNF Measure	Top third	2	Top Third	2	Bottom Two-Thirds	0	Bottom Two-Thirds	0
Falls with Major Injury (Long-Stay) Measure **	Top Third	2	Top Third	2	Bottom Two-Thirds	0	Bottom Two-Thirds	0
Discharge Function Measure **	Top Third	2	Top Third	2	Top Third	2	Bottom Two-Thirds	0
Long Stay Hospitalization Measure **	Top Third	2	Top Third	2	Top Third	2	Bottom Two-Thirds	0
Nursing Staff Turnover Measure **	Top Third	2	Top Third	2	Top Third	2	Bottom Two-Thirds	0
	Measure Performance Scaler	16	Measure Performance Scaler	14	Measure Performance Scaler	10	Measure Performance Scaler	2
Notes:
* We are proposing to replace the SNFRM would be replaced with the SNF WS PPR beginning with the FY 2028 program year.
** We are proposing to adopt the Nursing Staff Turnover Measure beginning with the FY 2026 program year and the Falls with Major Injury (Long-Stay) Measure, Discharge Function Measure, and Long Stay Hospitalization Measure beginning with the FY 2027 program year.

Step Two—Calculate the Underserved Multiplier

We propose to calculate an underserved multiplier, which, as stated previously, we propose to define as, for a SNF, the number representing the SNF's proportion of residents with DES out of its total resident population in the applicable program year, translated using a logistic exchange function. As stated previously, the primary goal of the adjustment is to appropriately measure performance by rewarding SNFs that are able to overcome the challenges of caring for high proportions of residents with DES while still providing high quality care. Another way that we are able to accomplish the goal of this adjustment is by utilizing a logistic exchange function to calculate the underserved multiplier, which would provide SNFs who care for the highest proportions of SNF residents with DES with the most HEA bonus points. Thus, we are proposing to utilize a logistic exchange function to calculate the underserved multiplier for scoring SNFs such that there would be a lower rate of increase at the beginning and the end of the curve. The formula for the underserved multiplier using a logistic exchange function would be as follows:

Due to the structure of the logistic exchange function, those SNFs with lower proportions of residents with DES have smaller underserved multipliers than their actual proportion of residents with DES and those SNFs with higher proportions of SNF residents with DES have underserved multipliers higher than their proportion of SNF residents with DES. A logistic exchange function assumes a large difference between SNFs treating the most and fewest residents with DES. Therefore, the logistic exchange function provides higher HEA bonus points to SNFs serving greater proportions of SNF residents with DES. For example, as shown in Figure A, if a SNF serves 70 percent of SNF residents with DES, the SNF would receive an underserved multiplier of 0.78.

Figure A—Determining the Underserved Multiplier From a SNF's Proportion of Residents With DES Using the Logistic Exchange Function

We propose that SNFs would receive an underserved multiplier of 0 if the SNF's proportions of SNF residents with DES is less than 20 percent, thereby establishing a “floor” on the magnitude of the SNF's underserved population proportion in order for the SNF to be eligible for any HEA bonus points. Because SNFs with proportions of SNF residents with DES below 20 percent receive a value of 0 for their underserved multiplier, any multiplication with the measure performance scaler would be 0 and would lead to those SNFs receiving no HEA bonus points. Imposing a floor of 20 percent for the underserved multiplier for a SNF to be eligible to receive HEA bonus points, reinforces that the adjustment is intended to appropriately measure performance by rewarding SNFs that are serving higher proportions of SNF residents with DES while also achieving high levels of quality performance. We believe this approach is necessary to remain consistent with the goal to reward high quality care specifically among SNFs that care for higher proportions of SNF residents with DES. We anticipate the vast majority of SNFs would be able to earn HEA bonus points despite this floor, and we expect the percent of SNFs meeting the 20 percent floor for the underserved multiplier might increase over time, as existing SNFs seek to expand their resident population to earn HEA bonus points. We also believe that the challenges associated with caring for residents with DES, a complex resident population, would be negligible if 80 percent of a SNF's resident population is not underserved. This 20 percent floor is consistent with the new health equity adjustment for ACOs that report all payer eCQMs/MIPS CQMs, as finalized in the CY 2023 PFS final rule (87 FR 69849 through 69852).

Alternatively, we considered establishing a floor of 60 percent such that all SNFs with proportions of SNF residents with DES below 60 percent would receive an underserved multiplier of 0, and therefore, would not receive any HEA bonus points. Although this would provide a greater value-based incentive payment amount to top tier performing SNFs that serve the highest proportions of SNF residents with DES and thus would support the primary goal of the adjustment, it would also mean SNFs that care for high proportions of SNF residents with DES who likely face similar challenges, albeit to a lesser extent, would receive no adjustment at all.

Step Three—Calculate the HEA Bonus Points

We are proposing to calculate the HEA bonus points that apply to a SNF for a program year by multiplying the measure performance scaler by the underserved multiplier. We believe that combining the measure performance scaler and the underserved multiplier to calculate the HEA bonus points allows for us to reward those SNFs with high quality that are also serving high proportions of SNF residents with DES, while incentivizing other SNFs to improve their performance (by a higher measure performance scaler) and serve more SNF residents with DES (by a higher underserved multiplier) in order to earn more HEA bonus points. Table 22 shows examples of how the measure performance scaler and underserved multiplier would be used to calculate the HEA bonus points. It also demonstrates how the logistic exchange function that we are proposing to use to calculate the underserved multiplier interacts with the measure performance scaler and results in SNFs serving higher proportion of SNF residents with DES receiving more HEA bonus points. For instance, example SNF 1 with 16 points and a proportion of residents with DES of 50 percent received a measure performance scaler of 16 and an underserved multiplier of 0.22. In other words, they would receive 22 percent of the points from their measure performance scaler because of how the logistic exchange function translates their proportion of residents with DES. Their measure performance scaler of 16 and underserved multiplier of 0.22 would then be multiplied together to get their HEA bonus points of 3.52. Alternatively, example SNF 2 with 14 points and a proportion of residents with DES of 70 percent, received an underserved multiplier of 0.78. Their measure performance scaler of 14 and underserved multiplier of 0.78 would then be multiplied together to get their HEA bonus points of 10.92. Note that although SNF 1 had a higher measure performance scaler, they received fewer HEA bonus points because they had a lower proportion of residents with DES. Finally, example SNF 3 had a proportion of SNF residents with DES of less than 20 percent and so they received an underserved multiplier of 0, resulting in no HEA bonus points

HEA Bonus Points = Measure Performance Scaler × Underserved Multiplier

Table 22—Example of the HEA Bonus Points Calculation

Example SNF	Measure performance scaler	Proportion of residents with DES (%)	Underserved multiplier	HEA bonus points
	[A]	[B]	[C]	[D] ([A] * [C])
SNF 1	16	50	0.22	3.52
SNF 2	14	70	0.78	10.92
SNF 3	10	10	0	0
SNF 4	2	80	0.92	1.84

Step Four—Add HEA Bonus Points to the Normalized Sum of all Points Awarded for Each Measure

Finally, we are proposing that we would add a SNF's HEA bonus points as calculated in Step Three of this section to the normalized sum of all points awarded to a SNF for each measure. This normalized sum would be the SNF Performance Score earned by the SNF for the program year, except that we would cap the SNF's Performance Score at 100 points to ensure the HEA creates a balanced incentive that has the potential to increase the SNF Performance Score without dominating the score and creating unintended incentives. Table 23 displays the final HEA bonus points added to the normalized sum of all points awarded to a SNF for each measure for 4 example SNFs.

Table 23—Example of the HEA Bonus Points Calculation

Example SNF	Normalized sum of all points awarded for each measure	HEA bonus points (step 3, column [D])	SNF performance score
	[A]	[B]	([A] + [B])
SNF 1	80	3.52	83.52
SNF 2	65	10.92	75.92
SNF 3	42	0	42.00
SNF 4	10	1.84	11.84

By adding these HEA bonus points to the normalized sum of all points awarded to a SNF for each measure, SNFs can be rewarded for delivering excellent care to all residents they serve and can be appropriately recognized for the resource intensity expended to achieve high performance when caring for higher proportion of SNF residents with DES. We believe this scoring adjustment, designed to advance health equity through the SNF VBP Program, is consistent with CMS's goal to incentivize greater inclusion of underserved populations, as well as the delivery of high-quality care to all.

We invite public comment on this proposed scoring change and calculations including the use of the measure performance scaler, underserved multiplier, and HEA bonus points. We are proposing to amend our regulations at § 413.338(e) and (k) to update the steps for performance scoring with the incorporated health equity scoring adjustment.

e. Proposal To Increase the Payback Percentage To Support the HEA

We adopted 60 percent as the SNF VBP Program's payback percentage for FY 2019 and subsequent fiscal years, subject to increases as needed to implement the Program's Low-Volume Adjustment policy for SNFs without sufficient data on which to base measure scores. We based this decision on numerous considerations, including our estimates of the number of SNFs that would receive a positive payment adjustment under the Program, the marginal incentives for all SNFs to reduce hospital readmissions and make quality improvements, and the Medicare Program's long-term sustainability. We also stated that we intended to monitor the effects of the payback percentage policy on Medicare beneficiaries, on participating SNFs, and on their measured performance, and we stated that we intended to consider proposing to adjust the payback percentage in future rulemaking.

In previous rules, we have received many public comments urging us to increase the payback percentage. For example, in the FY 2018 SNF PPS final rule (82 FR 36620), we responded to comments urging us to finalize a 70 percent payback percentage. We stated at that time that we did not believe that a 70 percent payback percentage appropriately balanced the policy considerations that we considered when we proposed the 60 percent policy. We responded to similar comments in the FY 2019 SNF PPS final rule (83 FR 39281), where commenters urged us to revisit the payback percentage policy and adopt 70 percent as the Program's policy. We reiterated that we did not believe it was appropriate to revisit the payback percentage at that time, which was prior to the Program's first incentive payments taking effect on October 1, 2018.

As part of our ongoing monitoring and evaluation efforts associated with the SNF VBP Program, we have considered whether to revise the Program's payback percentage policy to support the proposed HEA. Specifically, in conjunction with our HEA bonus point proposal, we are proposing to increase the total amount available for a fiscal year to fund the value-based incentive payment amounts beginning with the FY 2027 program year.

We are proposing this update to our payback percentage policy both to increase SNFs' incentives under the Program to undertake quality improvement efforts and to minimize the impact of the proposed HEA on the distribution of value based incentive payments to SNFs that do not earn the HEA. Because the SNF VBP Program's value-based incentive payment amounts depend on the distribution of SNF Performance Scores in each SNF VBP program year, providing additional incentives to SNFs serving higher proportions of SNF residents with DES without increasing the payback percentage could reduce other SNFs' value-based incentive payment amounts. While we do not believe that those reductions would be significant, we view a change to the payback percentage to further increase SNFs' quality improvement incentives to be more effective.

In determining how to modify the payback percentage, we considered the maximum number of HEA bonus points that would be awarded, as it is important that those points translate into meaningful enough rewards for SNFs to meet our goals of this adjustment to appropriately measure performance by rewarding SNFs that overcome the challenges of caring for higher proportions of SNF residents with DES and to incentivize SNFs who have not achieved such high-quality care to work towards improvement. However, we also have to ensure that the additional HEA bonus points available do not lead to value-based incentive payments that exceed the maximum 70 percent payback percentage authorized under section 1888(h)(5)(C)(ii)(III) of the Act. Additionally, we considered the maximum number of HEA bonus points that would be awarded in comparison to the average SNF Performance Score as we believe providing more HEA bonus points for our proposed HEA relative to the average a SNF receives for their performance on the Program measures could undermine the incentives for SNFs to perform in the SNF VBP Program.

We conducted an analysis utilizing FY 2018–2021 measure data for our finalized and proposed measures, including a simulation of performance from all 8 finalized and proposed measures for the FY 2027 Program, to determine what would be the greatest amount we could increase the payback percentage by for the HEA while not exceeding the 70 percent maximum or allowing for too many HEA bonus points. We examined the interaction of the two factors that directly impact the size of the incentives, the assigned point value for each measure and the payback percentage. For the first factor, as stated previously, we are proposing to assign 2 points per measure to each SNF that is a top tier performing SNF for that measure. This assigned point value would be used to calculate the measure performance scaler and resulting HEA bonus points. In this analysis, we also tested alternatives of assigning a point value of 1 or 3 per measure to determine how each option would impact the payback percentage and resulting value-based incentive payment amounts. For the payback percentage factor, we tested increasing the payback percentage to a fixed amount of 65 percent. We also tested an option in which we allow the payback percentage to vary based on performance data such that SNFs that do receive the HEA would not experience a decrease in their value-based incentive payment amount, to the greatest extent possible, relative to no HEA in the Program and maintaining a payback percentage of 60 percent.

Table 24 has three columns representing possible point values assigned to each measure that are then used to calculate the measure performance scaler. As shown in Table 24, regardless of the assigned points per measure, 78 percent of SNFs would receive the HEA in this analysis. This means that 78 percent of SNFs were top tier performing SNFs for at least 1 measure and had at least 20 percent of their residents with DES, so would have received some HEA bonus points. Table 24 also shows the mean number of HEA bonus points per SNF receiving the HEA, as well as the HEA bonus points at the 90th percentile and the maximum HEA bonus points that would have been received for the HEA. Table 24 then provides an estimate of the payback percentage that would have been required such that SNFs that do receive the HEA would not experience a decrease in their value-based incentive payment amount, to the greatest extent possible, relative to no HEA in the Program and maintaining a payback percentage of 60 percent. This analysis also identified that the average SNF, prior to the implementation of the HEA, would have received a SNF Performance Score of 31.6 and that the 90th percentile SNF Performance Score was 49.7.

As stated previously, we are proposing to assign a point value of 2 for each measure in which a SNF is a top tier performing SNF. Table 24 shows that assigning a point value of 2 per measure would have resulted in a 66 percent payback percentage, meaning once all SNFs have been awarded HEA bonus points, the value-based incentive payment amounts would result in a payback percentage of 66 percent. Assigning a point value of any higher number, such as 3 points per measure could result in the payback percentage exceeding the 70 percent maximum. This is because the amount of HEA bonus points would vary with performance, and so we expect the HEA bonus points to vary from year to year, creating a significant risk that assigning a point value of 3 for each measure would result in a payback percentage above the 70 percent maximum. Further, assigning a point value of 3 for each measure would result in HEA bonus points as high as 20. Considering the average SNF Performance Score during this same time period would have been 31.6, the addition of 20 bonus points puts far too much weight on the HEA compared to each of the Program measures.

Table 24—Estimated HEA Bonus Points and Payment Adjustments Resulting From Scoring Options Based on FY 2018–2021 Data

	1 assigned point value per measure	2 assigned point value per measure	3 assigned point value per measure
SNFs receiving HEA
Total Number of SNFs receiving HEA	10,668	10,668	10,668
Percentage of SNFs receiving HEA	78%	78%	78%
HEA bonus points (among SNFs receiving HEA)
Mean	0.89	1.78	2.68
90th percentile	2.25	4.50	6.76
Max	6.67	13.33	20.00
Assume payback will vary based on assigned points per measure
Estimate of percent payback required such that SNFs not receiving the HEA would not experience a decrease in their value-based incentive payment amount *	63%	66%	69%
Amount to SNFs receiving HEA ($MM)	$ 23.5	$ 27.6	$ 35.6
Notes:
* Relative to no HEA in the Program and maintaining a payback percentage of 60 percent.

Because we are proposing to assign a point value of 2 for each measure in the Program and based on this analysis, we propose that the payback percentage would vary by program year to account for the application of the HEA such that SNFs that do receive the HEA would not experience a decrease in their value-based incentive payment amount, to the greatest extent possible, relative to no HEA in the Program and maintaining a payback percentage of 60 percent. Utilizing a variable approach ensures a very limited number of SNFs (if any) that do not receive HEA bonus points will experience a downward payment adjustment. For a given program year, we propose to calculate the final payback percentage using the following steps. First, we would calculate SNF value-based incentive payment amounts with a payback percentage of 60 percent and without the application of the proposed HEA. Second, we would identify which SNFs receive the HEA and which do not based on their proportion of residents with DES and individual measure performance. Third, while maintaining the value-based incentive payment amounts calculated in the first step for those SNFs that do not receive the HEA, we would calculate the payback percentage needed to apply the HEA as described in section VII.E.4.d. of this proposed rule. As shown in Table 25, through our analysis, we estimate that assigning 2 points per measure would require an increase in the 60 percent payback percentage of 6.02 percentage points for the FY 2027 program year and 5.40 percentage points for the FY 2028 program year. These are estimates and we would expect some variation that could be the result of SNFs with high proportions of residents with DES significantly changing their performance, changes in Medicaid eligibility requirements such that the proportions of residents with DES changes, changes to the Program such as adding additional measures which could add additional points available for the HEA, and other possible factors. For the last factor, increasing the points available could result in an increased payback percentage beyond the 70 percent maximum; however, we intend to adjust the number of points available through the rulemaking process if we add measures to the Program. With our current proposal of assigning a point value of 2 for each measure, we do not anticipate that any factors would result in an increase in payback beyond the 70 percent maximum. However, we will continue to monitor the data closely and intend to make further proposals if necessary in future rulemaking. Thus, as shown in Table 25, a variable payback percentage would allow all SNFs that receive the HEA to also receive increased value-based incentive payment amounts, and would also mean that SNFs that do receive the HEA would not experience a decrease in their value-based incentive payment amount, to the greatest extent possible, relative to no HEA in the Program and maintaining a payback percentage of 60 percent.

We also explored setting a fixed payback percentage of 65 percent. This would mean that despite assigning higher point values for each measure, the resulting value-based incentive payment amounts would be capped to ensure the payback percentage would not exceed 65 percent. This would ensure that the payback percentage is below the 70 percent maximum. However, as shown in Table 25, including a 65 percentage payback would result in some SNFs, including SNFs that care for the highest quintile of residents with DES and almost one-third of rural SNFs, receiving reduced value-based incentive payment amounts compared to the absence of the HEA in the Program. This would be a significant negative consequence of this proposal, and our proposal is structured to avoid this outcome. We do not want SNFs that provide high quality care and that serve large proportions of residents who are underserved to be disadvantaged by this HEA.

Table 25—Estimated Differences for the FY 2027 and 2028 Program Years Between a Variable Payback Percentage and a Fixed Payback Percentage Based on FY 2018–2021 Data *

	FY 2027 Program		FY 2028 Program
	Variable **	Fixed	Variable **	Fixed
Payback percentage	66.02%	65%	65.40%	65%
# (%) SNFs *** among . . .
All SNFs	0 (0%)	5,233 (38%)	0 (0%)	4,105 (29%)
Rural SNFs	0 (0%)	1,146 (32%)	0 (0%)	853 (23%)
SNFs that care for highest quintile of residents with DES	0 (0%)	372 (14%)	0 (0%)	409 (15%)
Mean value-based incentive payment amount change per SNF among . . .
All SNFs	$2,162	$1,796	$1,901	$1,759
SNFs that are worse off ***	0	(366)	0	(162)
SNFs that are better off ***	2,771	3,136	2,433	2,552
Rural SNFs	969	808	940	877
SNFs that care for highest quintile of residents with DES	5,997	5,691	4,949	4,846
Value-based incentive payment amounts
Amount of value-based incentive payments with HEA ($MM)	324.18	319.17	323.23	321.24
Amount of value-based incentive payments without HEA (60% of withhold) ($MM)	294.62	294.62	296.53	296.53
Amount of increase due to HEA ($MM)	29.56	24.55	26.70	24.71
Notes:
* Based on assigning a point value of 2 for each measure in which the SNF is a top tier performing SNF.
** Actual payback percentage may change from what was modeled based on final Program data.
*** Payment changes, “worse off”, and “better off” all compare to the absence of the HEA in the Program and a payback percentage of 60 percent.

We welcome public comment on this proposal to adopt a variable payback percentage. We are also proposing to amend our regulations at § 413.338(c)(2)(i) to update this change to the payback percentage for FY 2027 and subsequent fiscal years.

In developing this HEA proposal, we considered approaches other than providing HEA bonus points to top tier performing SNFs with a high proportion of SNF residents with DES that could be implemented in the SNF VBP Program. More specifically, we considered the addition of risk adjustment to the payment methodology, peer grouping, or providing an opportunity to earn additional improvement points. First, we considered risk adjusting the measures used in the SNF VBP program. Currently, most measures in the SNF VBP Program are risk adjusted for the clinical characteristics of the resident that are included in the calculation of the measure. We do not risk adjust for social risk factors. Although it would require us to respecify the measures and then revisit the pre-rulemaking process for each measure, it is an operationally feasible approach. However, there is a significant concern around adding additional risk adjustment to the measures in the Program to account for social risk factors. Although additional risk adjustment can help account for factors outside of a SNF's control, such as social risk factors like socioeconomic status,^[341] it can also have potential unintended consequences. For instance, in a 2021 Report to Congress on Medicare and the Health Care Delivery System, the Medicare Payment Advisory Commission (MedPAC) recommended against adjusting SNF VBP measures results for social risk factors, stating that those types of adjustments can mask disparities.^[342] This would mean that disparities that currently exist would be more challenging to identify in the data, and thus harder for providers or the Program to eliminate. Additionally, in an analysis conducted by ASPE, it did not appear that additional risk adjustment would significantly impact SNF performance in the Program.^[343] Thus, we decided against incorporating additional risk adjustment into the SNF VBP Program at this time.

Second, we considered adding a peer grouping component to our scoring methodology, under which we would divide SNFs into groups based on the proportion of residents with DES that a SNF serves. With this peer grouping, different performance standards would then be set for each group, and thus payment adjustments would be made based on the group or strata in which a SNF falls.^[344] However, ASPE noted in their second report to congress on Social Risk Factors and Performance in Medicare's Value-Based Purchasing Program that although they support stratifying quality measures by DES to identify disparities, they had concerns that peer grouping could risk setting different standards of care for SNFs caring for underserved populations.^[345]

Finally, we considered an approach of adding additional improvement points to the Program. This could be achieved by either providing bonus points to SNFs for measures in which they had significant improvement or by increasing the points available for improvement from 9 points to some higher quantity, such as 15 points. It is important that even poorer performing SNFs be provided incentives to improve as all residents should have the opportunity to receive high quality care, and currently lower performers have the greatest opportunity for improvement. Since SNFs that care for higher proportions of SNF residents with DES tend to have lower SNF Performance Scores compared to SNFs that do not care for higher proportions of SNF residents with DES, this Program adjustment could address health equity by providing lower performing SNFs that care for higher proportions of SNF residents with DES additional incentives to improve the care they provide. However, we had concerns with this approach. First, this approach is not focused specifically on populations that are underserved, and it is unclear whether the additional improvement points available would provide sufficient incentives for SNFs that care for higher proportions of SNF residents with DES to invest the limited resources they have to make the changes necessary to benefit from it. We were also concerned that this change could primarily incentivize poorer performing SNFs that do not care for a higher proportion of SNF residents with DES. Although we aim to incentivize improvement in care for all SNFs, this alternative approach has a significant risk of not meeting the goals of a health equity-focused adjustment in the Program. Therefore, in considering how to modify the existing SNF VBP Program to advance health equity, we believe that rather than utilizing risk adjustment, peer grouping or adjusting the improvement point allocation process, it would be more appropriate to adopt an approach that rewards overall high-quality performance and incentivizes health equity.

In conclusion, we believe the HEA proposal would allow us to appropriately measure performance by rewarding SNFs that overcome the challenges of caring for higher proportions of SNF residents with DES and to incentivize those who have not achieved such high-quality care to work towards improvement. As the Program greatly expands beyond one measure, we believe this HEA will support high-quality care for all populations and recognize top tier performing SNFs serving residents with DES. We seek comment on all aspects of the proposed methodology. In particular, we seek comment on the following:

• Using the proportion of SNF residents with DES as a measure of the proportion of residents who are underserved.
• The requirement that a SNF be in the top third of performance for a measure to receive any points for the measure performance scaler.
• Assigning a point value of 2 for each measure as opposed to a higher point value such as 3.
• Using a logistic exchange function based off the proportion of SNF residents with DES to calculate the underserved multiplier.
• The requirement that a SNF's proportion of residents with DES be at least 20 percent for a SNF to be eligible for HEA bonus points.
• Increasing the payback percentage and allowing for it to vary such that SNFs that do receive the HEA would not experience a decrease in their value-based incentive payment amounts, to the greatest extent possible, relative to no HEA in the Program and maintaining a payback percentage of 60 percent.

Given that the proposed approach, if finalized, would be the initial implementation of a health equity adjustment under the SNF VBP Program, we note our intent to monitor the impact of the adjustment to ensure it achieves the goal of rewarding SNFs for high-quality performance while caring for higher proportions of SNF residents with DES. As necessary, we would consider modifications to the design of the HEA through future rulemaking. We invite public comment on our proposal to adopt the HEA proposal beginning with the FY 2027 program year.

5. Health Equity Approaches Under Consideration for Future Program Years: Request for Information (RFI)

As described in section VII.E.4. of this proposed rule, we are committed to achieving equity in health outcomes for residents by promoting SNF accountability for health disparities, supporting SNFs' quality improvement activities to reduce these disparities, and incentivizing better care for all residents. The proposed Health Equity Adjustment, as described previously, would revise the SNF VBP scoring methodology to reward SNFs that provide high quality care to residents with DES and create an incentive for all SNFs to treat residents with DES. We also aim to incentivize the achievement of health equity in the SNF VBP Program in other ways, including focusing specifically on reducing disparities to ensure we are incentivizing improving care for all populations, including residents who may be underserved. In order to do so, we are seeking comments on possible health equity advancement approaches to incorporate into the Program in future program years that could supplement the proposed Health Equity Adjustment described in section VII.E.4 of this proposed rule. We are also seeking input on potential ways to assess improvements in health equity in SNFs. As is the case across healthcare settings, significant disparities persist in the skilled nursing environment.^{[346]  [347]  [348]  [349]} The goal of explicitly incorporating health equity-focused components into the Program is to both measure and incentivize equitable care in SNFs. By doing so, we not only aim to encourage SNFs to focus on achieving equity for all residents, but also to afford individuals and families the opportunity to make more informed decisions about their healthcare.

This RFI consists of four main sections. The first section requests input on resident-level demographic and social risk indicators, as well as geographic-level indices that could be used to assess health equity gaps. The second section requests input on possible health equity advancement approaches that could be added to the Program and describes questions that should be considered for each. The third section requests input on other approaches that could be considered for inclusion in the SNF VBP Program in conjunction with the approaches described in the second section. Finally, the fourth section requests input on adopting domains that could incorporate health equity.

a. Resident-Level Indicators and Geographic-Level Indices To Assess Disparities in Healthcare Quality

To identify SNFs that care for residents who are underserved and determine their performance among these populations, we need to select an appropriate indicator of such. Identifying and prioritizing social risk or demographic variables to consider for measuring equity can be challenging. This is due to the high number of variables that have been identified in the literature as risk factors for poorer health outcomes and the limited availability or quality of standardized data. Each source of data has advantages and disadvantages in identifying populations to assess the presence of underlying disparities. Income-based indicators are a frequently used measure for assessing disparities,^[350] but other social risk indicators can also provide important insights. As described in section VII.E.4. of this proposed rule, we are proposing to utilize dual eligibility status (DES) to measure the underserved population in SNFs, as this data is readily available and DES as a metric has been used extensively to study the SNF population.^{[351]  [352]} However, as additional data and research becomes available we may be able to utilize other social risk factors to define the underserved population. We refer readers to the ASPE Report to Congress on Social Risk Factors and Performance Under Medicare's Value-Based Purchasing Programs for additional indicators we could consider for use in the Program, including the LIS Program, ADI, and others.^[353] We invite comment on which demographic variables, social risk indicators, or combination of indicators would be most appropriate for assessing disparities and measuring improvements in health equity in the SNF VBP Program for the health equity approaches described in this RFI.

b. Approaches To Assessing Health Equity Advancement in the SNF VBP Program

CMS is interested in developing approaches that would incentivize the advancement of health equity for all SNFs, focusing on improving care for all residents, including those who may currently face disparities in their care. Such an approach would aim to include as many SNFs as possible and would not be restricted to those serving 20 percent or more of residents with DES like the Health Equity Adjustment proposed in section VII.E.4. of this proposed rule. There are many different ways to add a health equity-focused component or adjustment to the Program to meet these objectives. In the FY 2023 proposed rule (87 FR 22789), we requested commenters' views on which adjustments would be most effective for the SNF VBP Program to account for any equity gaps that we may observe in the SNF setting. Although many commenters were supportive of incorporating health equity-focused adjustments into the Program, there was no clear consensus on the type of adjustment that would be most effective. In this proposed rule, we are requesting additional comments on potential approaches to assessing health equity advancement in the Program. We have outlined approaches to assess underlying equity gaps or designed to promote health equity, which may be considered for use in the Program and grouped them into three broad categories for assessment: applying points to current measures, equity-focused measures, and composite measures. The remainder of this section discusses these categories and relevant questions to consider for each. We also highlight two methods used for calculating disparities.

We identified four key considerations that CMS should consider when employing quality measurement as a tool to address health disparities and advance health equity. When considering which equity-focused measures could be prioritized for development for SNF VBP, we examined past reports that assess such measures and encourage commenters to review each category against the following considerations:^{[354]  [355]}

• To what extent does the approach support consumer choice? It is essential that quality measures reflect consumer needs and allow consumers to make informed choices about their care.^{[356]  [357]} In the Program, measure data is available on the Provider Data Catalog website. Having access to and understanding this data would empower consumers with more information in selecting their optimal SNF, including one that demonstrates greater performance in advancing equity.

• How long would it take to include this approach in the program? Some approaches may take considerably longer than others to include in the Program. For instance, we intend to consult the CMS appointed consensus-based entity for any new measures we propose to ensure we have appropriate feedback, which would add additional time to their development. Although we do not want this time to deter interested parties from recommending their inclusion in the program, we are interested in understanding commenters' prioritization of measures as it relates to the amount of time they may take to implement when deciding on the best approach for the Program.

• Is this approach aligned with other Medicare quality reporting and VBP programs? Implementing quality initiatives requires time and resources.^[358] It is one of our top priorities to ensure alignment between quality programs to limit the burden of quality reporting and implementation. Thus, it is important for us to consider in developing a health equity component, if and how other programs are incorporating health equity to align and standardize measures wherever possible.

• What is the impact on populations that are underserved or the SNFs that serve these populations? Although the goal of a health equity-focused adjustment to the Program would be to decrease disparities and incentivize high-quality care for all populations including those who are underserved, we also want to create appropriate guardrails that protect SNFs against potential unintended consequences. It is important for us to understand if any proposed approach may create potential negative consequences for residents who are underserved or the SNFs that treat these individuals and any steps we can take to mitigate that.

(1) Applying Points to Current Measures To Assess Health Equity

The first category of health equity advancement approaches we are requesting comments on are mechanisms that apply points to current measures to assess health equity, rewarding SNFs based on the extent to which they provide equitable care. This category affords each SNF the ability to score additional points for all measures where they demonstrate a high level of equity or a reduction in disparities over time. An approach that applies points to current measures to assess health equity could include, but is not limited to, the following:

• Points applied to one, some, or all measures for SNFs that achieve higher health equity performance on those measures. This would include measuring a SNF's performance on each measure for residents who are undeserved and comparing that to the same SNF's performance among all other residents on the same measures effectively assessing health equity gaps. This approach would utilize a Within-Facility Disparity method for assessing disparities, as described in more detail later in this section of this proposed rule.
• Points applied to one, some, or all measures for SNFs that have better performance among residents who are underserved. This would include only measuring performance among residents who are underserved and comparing that performance across all SNFs. This approach would utilize an Across-Facility Disparity method for assessing disparities, as described in more detail later in this section of this proposed rule.
• Points applied to one, some, or all measures based on a weighted average of each SNF's performance among resident groups with the worst and best outcomes for each measure. We could define resident groups by any social risk indicator, for example DES. This approach measures performance among all residents in the SNF and places greater weight on the performance of the worst performing group, with the goal of raising the quality floor at every SNF.

Note, any social risk indicator could be used to assess health equity gaps. We welcome comments on any approach in this section or any other approach that applies additional points to current measures to assess health equity that should be considered for inclusion in the SNF VBP Program.

(2) New Measure Approach

The second category of health equity advancement approaches we are requesting comments on is a new health equity-focused measure, which would be included as one of the 10 allowable measures in the Program. This category includes the development of a new measure that assesses health equity and could include a structural, process, or outcome measure. A health equity-focused measure would be included as one of the measures in the program and thus would be included in the scoring calculations like other measures. A health equity-focused measure could include, but is not limited to, the following:

• A structural measure. For example, a facility commitment to health equity measure, in which SNFs are assessed on factors like leadership engagement, data collection, and improvement activities that support addressing disparities in quality outcomes. This measure could be similar to the “Hospital Commitment to Health Equity” measure that was finalized in the FY 2023 Inpatient Prospective Payment System/Long Term Care Hospital Prospective Payment System final rule (87 FR 48785).
• A process measure. For example, a drivers of health measure, in which residents are screened for specific health-related social needs (HRSNs) to ensure a successful transition home, like transportation or food insecurity. This measure could be similar to the “Screening for Social Drivers of Health” measure that was finalized in the FY 2023 Inpatient Prospective Payment System/Long Term Care Hospital Prospective Payment System final rule (87 FR 48785).
• An outcome measure. For example, a measure that is calculated using data stratified for specific populations that are underserved, such as residents with DES.

Note each of these possible measures are only suggestions for what might be included in the Program. We welcome comments on any measures that should be considered for inclusion in the SNF VBP Program including the ones described in this section and what data sources should be considered to construct those measures.

(3) Composite Measure Approach

The third category of health equity advancement approaches we are requesting comments on is the development and implementation of a new health equity-focused composite measure. An equity-focused composite measure would be included as one of the 10 allowable measures in the program and thus would be included in the scoring calculations like other measures. Generally, a composite measure can provide a simplified view of a rather complex topic by combining multiple factors into one measure. A composite measure could include, but is not limited to, the following:

• A composite of all measure scores for residents who are underserved to compare across all SNFs. This could utilize an Across-Facility Disparity method for assessing disparities, as described in more detail later in this section of this proposed rule.
• A composite of the health disparity performance within each SNF for some or all measures. This approach could utilize a Within-Facility Disparity method for assessing disparities, as described in more detail later in this section of this proposed rule.

Note any social risk indicator could be used to assess health equity gaps. We welcome comments on each of the composite measures described in this section. We also welcome comments on the specific factors or measures that should be included in a composite measure.

In considering whether to include in the Program any of the approaches described in this section, points applied to current measures based on equity, new measures, or composite measures, we encourage commenters to consider the following questions:

To what extent do these approaches support consumer choice? What approaches described in this section best support consumer choice? Would any approach be easier to interpret than others? Would any of the approaches described in this section provide information that other approaches would not that would aid consumer choice? Are there other factors we should consider in developing any of the approaches described in this section that are easiest for consumers to utilize and understand? How should any of the approaches described in this section be displayed and shared with consumers to facilitate understanding of how to interpret the approach?

How long would it take to include this approach in the program? If some approaches would take longer to implement, should they still be considered for inclusion in the Program or should a different approach be prioritized? For instance, a measure that is already being utilized by another program could be implemented sooner than a measure that still needs to be developed. Should any of the approaches described in this section be considered regardless of the time it would take to include the approach in the Program?

Is this approach aligned with other Medicare quality reporting and VBP programs? Are there similar approaches to those described in this section that are aligned with other programs that we should consider for SNF VBP? If any of the approaches described in this section are not aligned with other programs, should they still be considered for inclusion in the Program? If these approaches are only aligned somewhat with other programs, should they still be considered for inclusion in the Program? Several other programs, including the End-Stage Renal Disease Quality Incentive Program, the Merit-based Incentive Payment System, the Hospital Inpatient Quality Reporting Program, the Inpatient Psychiatric Facility Quality Reporting Program, and the PPS-Exempt Cancer Hospital Quality Reporting Program also submitted equity-focused measures to the 2022 MUC List that could be considered for the Program.^[359] Further, we are in the process of developing a Hospital Equity Index. Should any of these measures be considered for SNF VBP?

What is the impact on populations that are underserved or the SNFs that serve these populations? Are there any potential impacts, including negative or positive unintended consequences, that could occur when implementing the approaches described in this section? Are there steps we should take to mitigate any potential negative unintended consequences? How can we ensure these approaches provide a strong enough incentive to improve care for all populations by identifying areas of inequities? We are interested in all perspectives and particularly of those living in and serving underserved communities.

(4) Disparity Method Approaches

Many of the approaches described previously in this section of this proposed rule would rely on calculating disparities. There are several different conceptual approaches to calculating disparities to assess health equity gaps. Currently in the acute care setting, two complementary approaches are used to confidentially provide disparity information to hospitals for a subset of existing measures. The first approach, referred to as the Within-Facility Disparity method, compares measure performance results for a single measure between subgroups of patients with and without a given factor. This type of comparison directly estimates disparities in outcomes between subgroups and can be helpful to identify potential disparities in care. This type of approach can be used with most measures that include patient-level data. The second approach, referred to as the Across-Facility Disparity method, provides performance on measures for only the subgroup of patients with a particular social risk factor. These approaches can be used by a SNF to compare their own measure performance on a particular subgroup of patients against subgroup-specific State and national benchmarks. Alone, each approach may provide an incomplete picture of disparities in care for a particular measure, but when reported together with overall quality performance, these approaches may provide detailed information about where differences in care may exist or where additional scrutiny may be appropriate. For example, the Across-Facility Disparity method indicates that a SNF underperformed (when compared to other SNFs on average) for patients with a given social risk indicator, which would signal the need to improve care for this population. However, if the SNF also underperformed for patients without that social risk indicator (the Within-Facility Disparity method, as described earlier in this section), the measured difference, or disparity in care, could be negligible even though performance for the group that particular social risk factor remains poor. We refer readers to the technical report describing the CMS Disparity Methods in detail, as well as the FY 2018 IPPS/LTCH PPS final rule (82 FR 38405 through 38407) and the posted Disparity Methods Updates and Specifications Report posted on the QualityNet website at https://qualitynet.cms.gov/​inpatient/​measures/​disparity-methods.

We request comments on whether similar approaches to the two discussed in the previous paragraph could be used for calculating disparities to assess health equity in a SNF. These calculations would then be used for scoring purposes for each of the approaches described previously in this section, either to calculate a SNF's performance on a new measure or a composite measure, or to determine the amount of points that should be applied to current measures to assess heath equity.

c. Other Approaches To Assessing Health Equity Advancement in the SNF VBP Program

There are also many other health equity approaches that could be considered for inclusion in the Program. In particular, we explored risk adjustment, stratification/peer grouping, and adding improvement points when developing the proposed Health Equity Adjustment in section VII.E.4. We have specific concerns when applying each of these approaches to the SNF VBP Program independently; however, we are requesting comment on the potential of incorporating these approaches in conjunction with the approaches outlined previously in this section of this proposed rule.

d. The Development of Domains and Domain Weighting for Inclusion in the SNF VBP Program

As we expand the number of measures on which we assess performance under the SNF VBP, we are considering whether we should group the measures into measure domains. Creating domains would align SNF VBP with other CMS programs such as the Hospital Value-Based Purchasing (VBP) Program. The HVBP Program currently groups its measures into four domains that are defined based on measure type, and then weights the sum of a hospital's performance score on each measure in the domain such that the domain is weighted at 25 percent of the hospital's total performance score. Although the HVBP Program uses four domains, each with a 25 percent weight, we could consider for the SNF VBP grouping measures into a different number of domains and then weighting each domain by different amounts.

We request comments on whether we should consider proposing the addition of quality domains for future program years. We also request comments on if those domains should be utilized to advance health equity in the Program.

F. Proposed Update to the Extraordinary Circumstances Exception Policy Regulation Text

In the FY 2019 SNF PPS final rule (83 FR 39280 through 39281), we adopted an Extraordinary Circumstances Exception (ECE) policy for the SNF VBP Program. We have also codified this policy in our regulations at § 413.338(d)(4).

To accommodate the SNF VBP Program's expansion to additional quality measures and apply the ECE policy to those measures, we are proposing to update our regulations at § 413.338(d)(4)(v) to remove the specific reference to the SNF Readmission Measure. The proposed new language would specify, in part, that CMS would calculate a SNF performance score for a program year that does not include the SNF's “performance during the calendar months affected by the extraordinary circumstance.”

We invite public comment on this proposal.

G. Proposal to Update the Validation Processes for the SNF VBP Program

1. Background

Section 1888(h)(12) of the Act requires the Secretary to apply a validation process to SNF VBP Program measures and “the data submitted under [section 1888(e)(6)] [. . .] as appropriate[. . .].”

We have finalized a validation approach for the SNFRM and codified that approach at section 413.338(j) of our regulations. In the FY 2023 SNF PPS proposed rule, we requested comment on the validation of additional SNF measures and assessment data (87 FR 22788 through 22789). In the FY 2023 SNF PPS final rule, we summarized commenters' views and stated that we would take this feedback into consideration as we develop our policies for future rulemaking (87 FR 47595 through 47596).

Beginning with the FY 2026 program year, the SNFRM will no longer be the only measure in the SNF VBP. We have adopted a second claims-based measure, SNF HAI, beginning with that program year and have proposed to replace the SNFRM with another claims-based measure, the SNF WS PPR measure, beginning with the FY 2028 program year. We have adopted the DTC PAC SNF measure beginning with the FY 2027 program year and we are proposing to adopt a fourth claims-based measure, Long Stay Hospitalization, beginning with that program year. We have adopted the total nurse staffing measure, which is calculated using Payroll Based Journal (PBJ) data, beginning with the FY 2026 program year and are proposing to adopt the nursing staff turnover measure, which is also calculated using PBJ data, beginning with the FY 2026 program year. We are also proposing to adopt the DC Function and the Falls with Major Injury (Long-Stay) measures calculated using Minimum Data Set (MDS) data beginning with the FY 2027 program year. The addition of measures calculated from these data sources has prompted us to consider the most feasible way to expand our validation program under the SNF VBP Program.

After considering our existing validation process and the data sources for the new measures, and for the reasons discussed more fully below, we are proposing to: (1) apply the validation process we have adopted for the SNFRM to all claims-based measures; (2) adopt a validation process that would apply to SNF VBP measures for which the data source is PBJ data; and (3) adopt a validation process that would apply to SNF VBP measures for which the data source is MDS data. We believe these proposals would ensure that the data we use to calculate the SNF VBP measures are accurate for quality measurement purposes.

We note that these proposals would apply only to the SNF VBP Program, and we intend to propose a validation process that would apply to the data SNFs report under the SNF QRP, in future rulemaking.

2. Proposal To Apply the Existing Validation Process for the SNFRM to All Claims-Based Measures Reported in the SNF VBP Program

Beginning with the FY 2026 program year, we would need to validate the SNF HAI measure and beginning with the FY 2027 program year, we would need to validate the Long Stay Hospitalization and DTC PAC SNF measures to meet our statutory requirements. Beginning with the FY 2028 program year, we would also need to validate the SNF WS PPR measure. Therefore, we are proposing to expand the previously adopted SNFRM validation process to include all claims-based measures, including the SNF HAI, Long Stay Hospitalization, DTC PAC SNF, and SNF WS PPR measures, as well as any other claims-based measures we could adopt for the SNF VBP in the future.

The SNF HAI measure is calculated using Medicare SNF FFS claims data and Medicare inpatient hospital claims data. As discussed in the FY 2023 SNF PPS final rule (87 FR 47590), information reported through claims are validated for accuracy by Medicare Administrative Contractors (MACs) who use software to determine whether billed services are medically necessary and should be covered by Medicare, review claims to identify any ambiguities or irregularities, and use a quality assurance process to help ensure quality and consistency in claim review and processing. They conduct prepayment and post-payment audits of Medicare claims, using both random selection and targeted reviews based on analyses of claims data.

Beginning with the FY 2027 program year, we are proposing to adopt the Long Stay Hospitalization measure in the SNF VBP Program. This measure utilizes SNF FFS claims and inpatient hospital claims data. We believe that adopting the existing MAC's process of validating claims for medical necessity through targeted and random audits, as detailed in the prior paragraph, would satisfy our statutory requirement to adopt a validation process for the Long Stay Hospitalization measure for the SNF VBP Program.

The DTC PAC SNF measure also uses claims-based data, including data from the “Patient Discharge Status Code”. We refer readers to the FY 2023 SNF PPS final rule (87 FR 47577 through 47578) for additional discussion of the data source for the DTC PAC SNF measure. We also refer readers to the FY 2017 SNF PPS final rule (81 FR 52021 through 52029) for a thorough analysis on the accuracy of utilizing the discharge status field. We believe that adopting the existing MAC's process for validating the claims portion of the DTC PAC SNF measure for payment accuracy would satisfy our statutory requirement to adopt a validation process for the SNF VBP Program because MACs review claims for medical necessity, ambiguities and quality assurance through random and targeted reviews, as detailed in the second paragraph in this section.

Beginning with the FY 2028 program year, we are proposing to replace the SNFRM with the SNF WS PPR. The SNFRM and SNF WS PPR utilize the same claims-based data sources. Therefore, the SNFRM's validation process based on data that are validated for accuracy by MACs as detailed in the second paragraph in this section, would fulfill the statutory requirement to adopt a validation process for the SNF WS PPR measure for the SNF VBP Program.

We invite the public to comment on this proposal and also propose to codify it at § 413.338(j).

3. Proposal To Adopt a Validation Process That Applies to SNF VBP Measures That Are Calculated Using PBJ Data

Beginning with the FY 2026 program year, the Total Nurse Staffing measure, adopted in the FY 2023 SNF PPS final rule, and the Nursing Staff Turnover measure, which we are proposing to adopt in this proposed rule, would be calculated using PBJ data that nursing facilities with SNF beds are already required to report to CMS. PBJ data includes direct care staffing information (including agency and contract staff) based on payroll and other auditable data.^[360] CMS conducts quarterly audits aimed at verifying that the staffing hours submitted by facilities are aligned with the hours staff were paid to work over the same timeframe. The PBJ audit process requires selected facilities to submit documentation, that may include payroll, invoice, or contractual obligation data, supporting the staffing hours reported in the PBJ data.^[361] This documentation of hours is compared against the reported PBJ staffing hours data and a facility whose audit identifies significant inaccuracies between the hours reported and the hours verified will be presumed to have low levels of staffing. We believe that this existing PBJ data audit process is sufficient to ensure that the PBJ data we use to calculate the Total Nurse Staffing and Nursing Staff Turnover measures are an accurate representation of a facility's staffing. Accordingly, we are proposing to adopt that process for purposes of validating SNF VBP measures that are calculated using PBJ data. We are also proposing to codify this policy at § 413.338(j) in our regulations.

We invite public comment on this proposal.

4. Proposal To Adopt a Validation Process That Applies to SNF VBP Measures That Are Calculated Using MDS Data

In section VII.B.4. of this proposed rule, we are proposing to adopt two MDS measures in the SNF VBP Program, the DC Function and Falls with Major Injury (Long Stay) measures beginning with the FY 2027 program year/FY 2025 performance period. The MDS is a federally mandated resident assessment instrument that is required to be completed for all residents in a Medicare or Medicaid certified nursing facility, and for patients whose stay is covered under SNF PPS in a non-critical access hospital swing bed facility. The MDS “includes the resident in the assessment process, and [uses] standard protocols used in other settings. . .supporting the primary legislative intent that MDS be a tool to improve clinical assessment and supports the credibility of programs that rely on MDS”.^[362] There is no current process to verify that the MDS data submitted by providers to CMS for quality measure calculations is accurate for use in our SNF quality reporting and value-based purchasing programs. While MDS data are audited to ensure accurate payments, we do not believe that this audit process focuses sufficiently on the Program's quality measurement data for use in a quality reporting or value-based purchasing program. While the update to MDS 3.0 was designed to improve the reliability, accuracy, and usefulness of reporting than prior versions,^[363] we believe we need to validate MDS data when those data would be used for the purpose of a quality reporting or value-based purchasing program. We are proposing to adopt a new validation method that we would apply to the SNF VBP measures that are calculated using MDS data to meet our statutory requirement. This proposed method is similar to the method we use to validate measures reported by hospitals under the Hospital Inpatient Quality Reporting Program.

We are proposing to validate the MDS data used to calculate these measures as follows:

• We propose to randomly select, on an annual basis, up to 1,500 active and current SNFs, including non-critical access hospital swing bed facilities providing SNF-level services, that submit at least one MDS record in the calendar year 3 years prior to the fiscal year of the relevant program year or were included in the SNF VBP Program in the year prior to the relevant program year. For example, for the FY 2027 SNF VBP Program, we would choose up to 1,500 SNFs that submitted at least one MDS record in calendar year 2024 or were participating in the FY 2026 SNF VBP Program/FY 2024 performance period for validation in FY 2025.
• We propose that the validation contractor would, for each quarter that applies to validation, request up to 10 randomly selected medical charts from each of the selected SNFs.
• We propose that the validation contractor would request either digital or paper copies of the randomly selected medical charts from each SNF selected for audit. The SNF would have 45 days from the date of the request (as documented on the request) to submit the requested records to the validation contractor. If the SNF has not complied within 30 days, the validation contractor would send the SNF a reminder to inform the SNF that it must return digital or paper copies of the requested medical records within 45 calendar days following the date of the initial validation contractor medical record request.

We believe the process would be minimally burdensome on SNFs selected to submit up to 10 charts.

We intend to propose a penalty that would apply to a SNF that either does not submit the requested number of charts or that we otherwise conclude has not achieved a certain validation threshold in future rulemaking. We also intend to propose in future rulemaking the process by which we would evaluate the submitted medical charts against the MDS to determine the validity of the MDS data used to calculate the measure results. We invite public comment on what that process could include.

We invite the public to comment on our proposal to adopt the above validation process for MDS measures beginning with the FY 2027 program year.

H. SNF Value-Based Incentive Payments for FY 2024

We refer readers to the FY 2018 SNF PPS final rule (82 FR 36616 through 36621) for discussion of the exchange function methodology that we have adopted for the Program, as well as the specific form of the exchange function (logistic, or S-shaped curve) that we finalized, and the payback percentage of 60 percent of the amounts withheld from SNFs' Medicare payments as required by the SNF VBP Program statute.

We also discussed the process that we undertake for reducing SNFs' adjusted Federal per diem rates under the Medicare SNF PPS and awarding value-based incentive payments in the FY 2019 SNF PPS final rule (83 FR 39281 through 39282).

For the FY 2024 SNF VBP Program Year, we will reduce SNFs' adjusted Federal per diem rates for the fiscal year by the applicable percentage specified under section 1888(h)(6)(B) of the Act, 2 percent, and will remit value-based incentive payments to each SNF based on their SNF Performance Score, which is calculated based on their performance on the Program's quality measure.

I. Public Reporting on the Provider Data Catalog Website

Section 1888(g)(6) of the Act requires the Secretary to establish procedures to make SNFs' performance information on SNF VBP Program measures available to the public on the Nursing Home Compare website or a successor website, and to provide SNFs an opportunity to review and submit corrections to that information prior to its publication. We began publishing SNFs' performance information on the SNFRM in accordance with this directive and the statutory deadline of October 1, 2017. In December 2020, we retired the Nursing Home Compare website and are now using the Provider Data Catalog website ( https://data.cms.gov/​provider-data/​) to make quality data available to the public, including SNF VBP performance information.

Additionally, section 1888(h)(9)(A) of the Act requires the Secretary to make available to the public certain information on SNFs' performance under the SNF VBP Program, including SNF Performance Scores and their ranking. Section 1888(h)(9)(B) of the Act requires the Secretary to post aggregate information on the Program, including the range of SNF Performance Scores and the number of SNFs receiving value-based incentive payments, and the range and total amount of those payments.

In the FY 2017 SNF PPS final rule (81 FR 52006 through 52009), we discussed the statutory requirements governing confidential feedback reports and public reporting of SNFs' performance information under the SNF VBP Program and finalized our two-phased review and correction process. In the FY 2018 SNF PPS final rule (82 FR 36621 through 36623), we finalized additional requirements for phase two of our review and correction process, a policy to publish SNF VBP Program performance information on the Nursing Home Compare or a successor website after SNFs have had the opportunity to review and submit corrections to that information. In that final rule, we also finalized the requirements to rank SNFs and adopted data elements that are included in the ranking to provide consumers and interested parties with the necessary information to evaluate SNF's performance under the Program. In the FY 2020 SNF PPS final rule (84 FR 38823 through 38825), we finalized a policy to suppress from public display SNF VBP performance information for low-volume SNFs, and finalized updates to the phase one review and correction deadline. In the FY 2021 SNF PPS final rule (85 FR 47626 through 47627), we finalized additional updates to the phase one review and correction deadline. In the FY 2022 SNF PPS final rule (86 FR 42516 through 42517), we finalized a phase one review and correction claims “snapshot” policy. In the FY 2023 SNF PPS final rule (87 FR 47591 through 47592), we finalized updates to our data suppression policy for low-volume SNFs due to the addition of new measures and case and measure minimum policies.

IX. Civil Money Penalties: Waiver of Hearing, Automatic Reduction of Penalty Amount

Section 488.436 provides a facility the option to waive its right to a hearing in writing and receive a 35 percent reduction in the amount of civil money penalties (CMPs) owed in lieu of contesting the enforcement action. This regulation was first adopted in a 1994 final rule (59 FR 56116, 56243), with minor corrections made to the regulation text in 1997 (62 FR 44221) and in 2011 (76 FR 15127) to implement section 6111 of the Affordable Care Act of 2010. Over the years, we have observed that most facilities who have been imposed CMPs do not request a hearing to appeal the survey findings of noncompliance on which their CMPs are based.

In CY 2016, 81 percent of LTC facilities submitted a written waiver of a hearing and an additional 15 percent of facilities failed to submit a waiver although they did not contest the penalty and its basis. Only 4 percent of facilities availed themselves of the full hearing process. The data from CY 2018 and CY 2019 stayed fairly consistent with 80 percent of facilities submitting a written waiver of a hearing and 14 percent of facilities failing to submit the waiver nor contest the penalty and its basis. Only 6 percent of facilities availed themselves of the full hearing process. In CY 2020, 81 percent of facilities submitted a written waiver of the hearing, 15 percent of facilities did not submit a waiver nor contest the penalty and its basis, and only 4 percent of facilities availed themselves of the full hearing process. In CY 2021, 91 percent of facilities submitted a written waiver of the hearing, 7 percent of facilities did not submit the waiver nor contest the penalty and its basis, and only 2 percent of facilities utilized the full hearing process. Data from CY 2022 continues this trend showing that 81 percent of LTC facilities submitted a written waiver of their hearing rights and 17 percent of facilities did not submit a waiver of appeal rights but did not contest the penalty nor its basis. Again, only 2 percent of facilities availed themselves of the full hearing process in CY2022. Therefore, based on our experience with LTC facilities with imposed CMPs and the input provided by our CMS Locations (formerly referred to as Regional Offices) who impose and collect CMPs, we propose to revise these requirements at § 488.436 by creating a constructive waiver process that would produce the same results for less money and effort.

Specifically, we propose to revise the current express written waiver process to one that seamlessly flows to a constructive waiver and retains the accompanying 35 percent penalty reduction. Removal of the facility's requirement to submit a written request to avail itself of this widely used option would result in lower costs for most LTC facilities facing CMPs and would streamline and reduce the administrative burden for all interested parties. We propose to amend the language at § 488.436(a), by eliminating the requirement to submit a written waiver and create in its place a constructive waiver process that would operate by default when a timely request for a hearing has not been received. Facilities that wish to request a hearing to contest the noncompliance leading to the imposition of the CMP would continue to follow all applicable appeals process requirements, including those at § 498.40, as currently referenced at § 488.431(d).

Specifically, we propose to revise § 488.436(a) to state that a facility is deemed to have waived its rights to a hearing if the time period for requesting a hearing has expired and timely request for a hearing has not been received. We have observed that many facilities submitting a request for a waiver of hearing wait until close to the end of the 60-day timeframe within which a waiver must be submitted, thus delaying the ultimate due date of the CMP amount. Under this proposed process, the 35 percent reduction would be applied after the 60-day timeframe.

We note that we continue to have the opportunity under § 488.444, to settle CMP cases at any time prior to a final administrative decision for Medicare-only SNFs, State-operated facilities, or other facilities for which our enforcement action prevails, in accordance with § 488.30. This provides the opportunity to settle a case, even if the facility's hearing right was not previously waived. Even if a hearing had been requested, if all parties can reach an agreement over deficiencies to be corrected and the CMP to be paid until corrections are made (for example, CMS agrees to lower a CMP amount based on actions the facility has taken to protect resident health and safety), then costly hearing procedures could be avoided. We believe that eliminating the current requirements at § 488.436 for a written waiver will not negatively impact facilities, and as such, we especially welcome comments from the public addressing any potential circumstances in which facilities' needs or the public interest could best be met or only be met by the use of an express, written waiver.

In addition to the changes to § 488.436(a), we propose corresponding changes to §§ 488.432 and 488.442 which currently reference only the written waiver process. We propose to make conforming changes that establish that a facility is deemed to have waived its rights to a hearing if the time period for requesting a hearing has expired, in lieu of a written waiver of appeal rights. Finally, we note that the current requirements at § 488.436(b) would remain unchanged.

These proposed revisions were previously proposed and published in the July 18, 2019 proposed rule entitled, “Medicare and Medicaid Programs; Requirements for Long-Term Care Facilities: Regulatory Provisions to Promote Efficiency, and Transparency” (84 FR 34737, 34751). Although on July 14, 2022, we announced an extension of the timeline for publication of the final rule for the 2019 proposals ( see87 FR 42137), we are withdrawing that proposal revising § 488.436 and are re-proposing here the proposed revisions for a facility to waive its hearing rights in an effort to gather additional feedback from interested parties. While this regulatory action is administrative in nature, in the future, we may assess whether the 35 percent penalty reduction is functioning as intended to make the civil money penalties administrative process more efficient, or whether a lesser penalty reduction is warranted.

IX. Collection of Information Requirements

Under the Paperwork Reduction Act of 1995 (PRA) (44 U.S.C. 3501 et seq.), we are required to provide 60-day notice in the Federal Register and solicit public comment before a “collection of information” requirement is submitted to the Office of Management and Budget (OMB) for review and approval. For the purpose of the PRA and this section of the preamble, collection of information is defined under 5 CFR 1320.3(c) of the PRA's implementing regulations.

To fairly evaluate whether an information collection should be approved by OMB, section 3506(c)(2)(A) of the PRA requires that we solicit comment on the following issues:

• The need for the information collection and its usefulness in carrying out the proper functions of our agency.
• The accuracy of our estimate of the information collection burden.
• The quality, utility, and clarity of the information to be collected.
• Recommendations to minimize the information collection burden on the affected public, including automated collection techniques.

We are soliciting public comment (see section IX.D. of this proposed rule) on each of these issues for the following sections of this document that contain information collection requirements. Comments, if received, will be responded to within the subsequent final rule.

A. Wage Estimates

To derive average private sector costs, we used data from the U.S. Bureau of Labor Statistics' (BLS') May 2021 National Occupational Employment and Wage Estimates for all salary estimates ( http://www.bls.gov/​oes/​current/​oes_​nat.htm). In this regard, Table 26 presents BLS' mean hourly wage, our estimated cost of fringe benefits and other indirect costs (calculated at 100 percent of salary), and our adjusted hourly wage.

Table 26—National Occupational Employment and Wage Estimates

Occupation title	Occupation code	Mean hourly wage ($/hr)	Fringe benefits and other indirect costs ($/hr)	Adjusted hourly wage ($/hr)
Computer Programmer	15–1251	46.46	46.46	92.92
Licensed Vocational Nurse (LVN)	29–2061	24.93	24.93	49.86
Medical Records Specialist	29–2072	23.23	23.23	46.46
Occupational Therapist (OT)	29–1122	43.02	43.02	86.04
Physical Therapist (PT)	29–1123	44.67	44.67	89.34
Registered Nurse (RN)	29–1141	39.78	39.78	79.56
Speech Language Pathologist (SLP)	29–1127	41.26	41.26	82.52

As mentioned above, we have adjusted the private sector's employee hourly wage estimates by a factor of 100 percent. This is necessarily a rough adjustment, both because fringe benefits and other indirect costs vary significantly across employers, and because methods of estimating these costs vary widely across studies. Nonetheless, we believe that doubling the hourly wage to estimate total cost is a reasonably accurate estimation method.

Cost for Beneficiaries We believe that the cost for beneficiaries undertaking administrative and other tasks on their own time is a post-tax wage of $20.71/hr.

The Valuing Time in U.S. Department of Health and Human Services Regulatory Impact Analyses: Conceptual Framework and Best Practices ^[364] identifies the approach for valuing time when individuals undertake activities on their own time. To derive the costs for beneficiaries, a measurement of the usual weekly earnings of wage and salary workers of $998, divided by 40 hours to calculate an hourly pre-tax wage rate of $24.95/hr. This rate is adjusted downwards by an estimate of the effective tax rate for median income households of about 17%, resulting in the post-tax hourly wage rate of $20.71/hr. Unlike our private sector wage adjustments, we are not adjusting beneficiary wages for fringe benefits and other indirect costs since the individuals' activities, if any, would occur outside the scope of their employment.

B. Proposed Information Collection Requirements (ICRs)

1. ICRs Regarding the Skilled Nursing Facility Quality Reporting Program (SNF QRP)

In accordance with section 1888(e)(6)(A)(i) of the Act, the Secretary must reduce by 2-percentage points the otherwise applicable annual payment update to a SNF for a fiscal year if the SNF does not comply with the requirements of the SNF QRP for that fiscal year.

In section VI.C. of this proposed rule, we are proposing to modify one measure, adopt three new measures, and remove three measures from the SNF QRP. In section VI.F. of this proposed rule, we are also proposing to increase the data completion thresholds for the MDS items. We discuss these information collections below.

As stated in section VI.C.1.a. of this rule, we are proposing to modify the COVID–19 Vaccination Coverage Among Healthcare Personnel (HCP COVID–19 Vaccine) measure beginning with the FY 2025 SNF QRP. While we are not proposing any changes to the data submission process for the HCP COVID–19 Vaccine measure, we are proposing that for purposes of meeting FY 2025 SNF QRP compliance, SNFs would report data on the modified measure beginning with reporting period of the fourth quarter of CY 2023. Under the proposal, SNFs would continue to report data for the HCP COVID–19 Vaccine measure to the CDC's National Healthcare Safety Network (NHSN) for at least one self-selected week during each month of the reporting quarter. The burden associated with the HCP COVID–19 Vaccine measure is accounted for under OMB control number 0920–1317, entitled “[NCEZID] National Healthcare Safety Network (NHSN) Coronavirus (COVID–19) Surveillance in Healthcare Facilities.” Because we are not proposing any updates to the form, manner, and timing of data submission for this measure, we are not proposing any changes to the currently approved (active) requirements or burden estimates under control number 0920–1317. See the FY 2022 SNF PPS final rule (86 FR 42480 through 42489) for a discussion of the form, manner, and timing of data submission of this measure.

In this proposed rule, we are proposing to adopt three new measures and remove two measures from the SNF QRP. We present the burden associated with these proposals in the same order they were proposed in section VI.C. of this proposed rule.

As stated in section VI.C.1.b. of this rule, we propose to adopt the Discharge Function Score (DC Function) measure beginning with the FY 2025 SNF QRP. This proposed assessment-based quality measure would be calculated using data from the minimum data set (MDS) that are already reported to the Medicare program for payment and quality reporting purposes. The burden is currently approved under OMB control number 0938–1140 (CMS–10387). Under this proposal, there would be no additional burden for SNFs since it does not require the collection of new or revised data elements.

As stated in section VI.C.1.c. of this rule, we propose to remove the Application of Percent of Long-Term Care Hospital (LTCH) Patients with an Admission and Discharge Functional Assessment and a Care Plan that Addresses Function (Application of Functional Assessment/Care Plan) measure beginning with the FY 2025 SNF QRP. We believe that the removal of the measure would result in a decrease of 18 seconds (0.3 min or 0.005 hr) of clinical staff time at admission beginning with the FY 2025 SNF QRP. We believe that the MDS item affected by the proposed removal of the Application of Functional Assessment/Care Plan measure is completed by Occupational Therapists (OT), Physical Therapists (PT), Registered Nurses (RN), Licensed Practical and Licensed Vocational Nurses (LVN), and/or Speech-Language Pathologists (SLP) depending on the functional goal selected. We identified the staff type per MDS item based on past SNF burden calculations. Our assumptions for staff type were based on the categories generally necessary to perform an assessment, however, individual SNFs determine the staffing resources necessary. Therefore, we averaged BLS' National Occupational Employment and Wage Estimates (See Table 26) for these labor types and established a composite cost estimate using our adjusted wage estimates. The composite estimate of $86.21/hr was calculated by weighting each hourly wage based on the following breakdown (see Table 27) regarding provider types most likely to collect this data: OT 45 percent at $86.04/hr; PT 45 percent at $89.34/hr; RN 5 percent at $79.56/hr; LVN 2.5 percent at $49.86/hr; and SLP 2.5 percent at $82.52/hr.

For purposes of deriving the composite wage we also estimate 2,406,401 admission assessments from 15,471 SNFs annually.

Table 27—Estimated Composite Wage for the Application of Functional Assessment/Care Plan Measure

Occupation title	Occupation code	Mean hourly wage, fringe benefits, and other indirect costs ($/hr)	Percent of assessments collected	Number of assessments collected *	Total hours	Total burden ($)
Occupational Therapist (OT)	29–1122	86.04	45	1,082,880.5	5,414	465,855
Physical Therapist (PT)	29–1123	89.34	45	1,082,880.5	5,414	483,723
Registered Nurse (RN)	29–1141	79.56	5	120,320	602	47,863
Licensed Vocational Nurse (LVN)	29–2061	49.86	2.5	60,160	301	14,998
Speech Language Pathologist (SLP)	29–1127	82.52	2.5	60,160	301	24,822
Total	n/a	n/a	100	2,406,401	12,032	1,037,261
Composite Wage		$1,037,261/12,032 hours = $86.2085/hour

We estimate the total burden for complying with the SNF QRP requirements would be decreased by minus 12,032 hours (0.005 hr × 2,406,401 admission assessments) and minus $1,037,261 (12,032 hrs × $86.2085/hr) for all SNFs annually based on the proposed removal of the Application of Functional Assessment/Care Plan measure. The burden associated with the Application of Functional Assessment/Care Plan measure is included in the currently approved (active) burden estimates under OMB control number 0938–1140 (CMS–10387). The proposal to remove this measure in section VI.C.1.c. of this rule would remove this burden.

As stated in section VI.C.1.d. of this rule, we propose to remove the Application of IRF Functional Outcome Measure: Change in Self-Care Score for Medical Rehabilitation Patients (Change in Self-Care Score) measure as well as the Application of IRF Functional Outcome Measure: Change in Mobility Score for Medical Rehabilitation Patients (Change in Mobility) measure beginning with the FY 2025 SNF QRP. While these assessment-based quality measures are proposed for removal, the data elements used to calculate the measures would still be reported by SNFs for other payment and quality reporting purposes. Therefore, we believe that the proposal to remove the Change in Self-Care and Change in Mobility measures would not have any impact on our currently approved reporting burden for SNFs.

As stated in section VI.C.3.a. of this rule, we propose to adopt the COVID–19 Vaccine: Percent of Patients/Residents Who Are Up to Date (Patient/Resident COVID–19 Vaccine) measure beginning with the FY 2026 SNF QRP. This proposed assessment-based quality measure would be collected using the MDS. The MDS 3.0 is currently approved under OMB control number 0938–1140 (CMS–10387). One data element would need to be added to the MDS at discharge in order to allow for the collection of the Patient/Resident COVID–19 Vaccine measure. We believe this would result in an increase of 18 seconds (0.3 min or 0.005 hr) of clinical staff time at discharge beginning with the FY 2026 SNF QRP. We believe that the added data element for the proposed Patient/Resident COVID–19 Vaccine measure would be completed equally by registered nurses (0.0025 hr/2 at $79.56/hr) and licensed vocational nurses (0.0025 hr/2 at $49.86/hr), however, individual SNFs determine the staffing resources necessary. Therefore, we averaged BLS' National Occupational Employment and Wage Estimates (see Table 26) for these labor types and established a composite cost estimate using our adjusted wage estimates. The composite estimate of $64.71/hr was calculated by weighting each hourly wage based on the following breakdown (see Table 28) regarding provider types most likely to collect this data: RN 50 percent at $79.56/hr and LVN 50 percent at $49.86/hr.

For purposes of deriving the burden impact, we estimate a total of 2,406,401 discharges from 15,471 SNFs annually.

Table 28—Estimated Composite Wage for the Application of Functional Assessment/Care Plan Measure

Occupation title	Occupation code	Mean hourly wage, fringe benefits, and other indirect costs ($/hr)	Percent of assessments collected	Number of assessments collected *	Total hours	Total burden ($)
Registered Nurse (RN)	29–1141	79.56	50	1,203,200.5	6,016	478,633
Licensed Vocational Nurse (LVN)	29–2061	49.86	50	1,203,200.5	6,016	299,958
Total	n/a	n/a	100	2,406,401	12,032	778,591
Composite Wage		$778,591/12,032 hours = $64.71/hour

We estimate the total burden for complying with the SNF QRP requirements would be increased by 12,032 hours (0.005 hr × 2,406,401 discharge assessments) and $778,591 (12,032 hrs × $64.71/hr) for all SNFs annually based on the proposed adoption of the Patient/Resident COVID–19 Vaccine measure. The burden would be accounted for in a future revised information collection request under OMB control number 0938–1140 (CMS–10387).

As stated in section VI.F.6. of this rule, we propose to increase the SNF QRP data completion thresholds for MDS data items beginning with the FY 2026 SNF QRP. We propose that SNFs would be required to report 100 percent of the required quality measures data and standardized patient assessment data collected using the MDS on at least 90 percent of the assessments they submit through the CMS designated submission system. Because SNFs have been required to submit MDS quality measures data and standardized patient assessment data for the SNF QRP since October 1, 2016, we are not making any changes to the burden that is currently approved by OMB under control number 0938–1140 (CMS–10387).

In summary, we estimate the proposed SNF QRP changes associated with proposed removal of the Application of Functional Assessment/Care Plan measure and the proposed adoption of Patient/Resident COVID–19 measure would result in no change in the total time and a decrease of $258,670 (see Table 29).

Table 29—Proposals Associated With OMB Control Number 0938–1140 (CMS–10387)

Requirement	Number respondents	Total responses	Time per response (hr)	Total time (hr)	Wage ($/hr)	Total cost ($)
Change in Burden associated with proposed removal of the Application of Functional Assessment/Care Plan measure beginning with the FY 2025 SNF QRP	15,471 SNFs	(2,406,401)	(0.005)	(12,032)	Varies	(1,037,261)
Change in Burden associated with proposed Patient/Resident COVID–19 Vaccine measure beginning with the FY 2026 SNF QRP	15,471 SNFs	2,406,401	0.005	12,032	Varies	778,591
Total Change	n/a	0	0	0	n/a	(258,670)

In section VI.C.2.a. of this rule, we propose to adopt the CoreQ: Short Stay Discharge (CoreQ: SS DC) measure, beginning with the FY 2026 SNF QRP. We describe in this section the following sources of burden associated with the proposed adoption of the CoreQ: SS DC measure: (1) exemption requests; (2) vendor costs; (3) submission of resident information files; and (4) costs to beneficiaries. We have provided an estimate burden here and in Tables 28 and 29, and note that the increase in burden would be accounted for in a new information collection request.

Under this proposal, SNFs would be required to participate in the CoreQ: SS DC measure's survey requirements unless they meet the proposed low volume exemption criteria (see section VI.F.3.b.(1) of this proposed rule). Using data from July 1, 2021 through June 30, 2022, we estimate 3,272 SNFs (out of 15,435 total SNFs) would meet the proposed low volume exemption criteria for the measure's reporting requirements, and therefore would be expected to request an exemption. We believe the submission of a request for exemption would be completed by a medical record specialist. Our assumption for staff type is based on our experience with the home health and hospice Community Assessment of Healthcare Providers and Systems (CAHPS®) surveys which have been in place since 2010 and 2015, respectively. However, individual SNFs determine the staffing resources necessary. We believe it would take 35 minutes (0.58 hr) at $46.46/hr for a medical record specialist to submit a request for exemption from the CoreQ: SS DC measure's survey requirement. In aggregate, we estimate a burden of 1,898 hours (3,272 exemptions × 0.58 hr per request at a cost of $88,181 (1,898 hr × $46.46./hr) for all SNFs requesting an exemption from the CoreQ: SS DC measure survey requirement.

Under this proposal, SNFs that do not qualify for an exemption would be required to contract with a CMS-approved CoreQ survey vendor to administer the CoreQ: SS DC measure's survey on their behalf and submit the results to the CoreQ Survey Data Center (see section VI.F.3. of this proposed rule). We estimate a SNF's annual cost of contracting with a CMS-approved CoreQ survey vendor to be $4,000. Our assumption for the cost of a CMS-approved CoreQ survey vendor is based on our experience with the home health and hospice CAHPS® surveys which have been in place since 2010 and 2015, respectively. Therefore, we estimate the cost to SNFs participating in the CoreQ SS DC measure (15,435 total SNFs−3,272 SNF exemptions = 12,163 SNFs) would be increased by $48,652,000 ($4,000 × 12,163 SNFs).

After contracting with a CMS-approved CoreQ survey vendor, SNFs would be required to submit one resident information file (as described in section VI.F.3.c. of this proposed rule) to their CMS-approved CoreQ survey vendor during the initial submission period from January 1, 2024 through June 30, 2024. Beginning July 1, 2024, SNFs would be required to submit resident information files to their CMS-approved CoreQ survey vendor no less than weekly for the remainder of CY 2024. Our assumptions for staff type who would be responsible for collecting information for the proposed CoreQ: SS DC measure were based on our experience with the home health and hospice CAHPS® surveys which have been in place since 2010 and 2015, respectively. However, individual SNFs determine the staffing resources necessary. We believe it would take 4 hours at $92.92/hr for a computer programmer to complete the initial set-up of the resident information files. After the initial set-up, we believe it would take 30 minutes per week (or 26 hr/year) at $46.46/hr for a medical record specialist to create and submit the resident information file to the CMS-approved CoreQ survey vendor.

For the FY 2026 SNF QRP (data submission period January 1, 2024 through December 31, 2024), we estimate a burden of 212,853 hours (12,163 SNFs × [4 hr for a computer programmer/SNF + (0.5 hr for a medical record specialist × 27 resident information files/SNF)]) at a cost of $12,149,449 (12,163 SNFs × [4 hr × $92.92/hr to initially set up the resident information file/SNF) + (13.5 hr × $46.46/hr to submit 27 resident information files to the CMS-approved CoreQ survey vendor/SNF]).

Beginning with the FY 2027 SNF QRP (data submission period January 1, 2025 through December 31, 2025), we estimate a burden of 316,238 hours (12,163 SNFs × [0.5 hr for a medical record specialist × 52 weeks]) at a cost of $14,692,417 (316,238 hrs across all SNFs × $46.46/hr to submit resident information files to the CMS-approved CoreQ survey vendor).

The CoreQ: SS DC measure's survey contains a total of 6 questions (four primary questions and two help provided questions) and is estimated to require a SNF respondent an average of 6 minutes (0.1 hr) to complete. This is based on the original testing of the CoreQ: SS DC measure described in the CoreQ National Quality Forum (NQF) application. Using data from July 1, 2021 through June 30, 2022, we estimate there would be 1,330,284 completed surveys (27 weeks/52 weeks = 0.52); (0.52 × 2,558,238 completed surveys) in the first year of data submission (January 1, 2024 through December 31, 2024). In aggregate, we estimate a burden of 133,028 hours (1,330,284 × 0.1 hr/completed survey) at a cost of $2,755,010 (133,028 hr × $20.71/hr for beneficiaries). Beginning with the FY 2027 SNF QRP (data submission period January 1, 2025 through December 31, 2025), we estimate a burden of 255,824 hr (2,558,238 completed surveys × 0.1 hr/survey) at a cost of $5,298,115 = (255,824 hrs × $20.71/hr).

Table 30 estimates the overall SNF burden for the proposed CoreQ: SS DC measure while Table 31 estimates the overall respondent burden for the proposed CoreQ: SS DC Measure.

Table 30—Proposed SNF Burden for the CoreQ Survey (OMB 0938–TBD, CMS–10852)

Requirement	Number of respondents	Total responses	Time per response (hr)	Total time (hr)	Wage ($/hr)	Total cost ($)
FY 2026 CoreQ: SS DC Measure Burden
Requesting an exemption to the CoreQ: SS DC measure survey reporting requirements	3,272 SNFs	3,272	0.58	1,898	46.46	88,181
Contracting with a CMS-approved CoreQ survey vendor	12,163 SNFs	12,163	NA	NA	NA	48,652,000 (12,163 × $4,000)
Data submission requirements for the proposed CoreQ: SS DC measure for the FY 2026 SNF QRP *	12,163 SNFs	328,401	0.50/wk after initial 4 hr set-up	212,853	* Varies	12,149,499
Total	15,435 SNFs	331,673	5.05	214,751	Varies	88,181 for exempted SNFs 60,801,499 for participating SNFs
Burden Beginning with the FY 2027 CoreQ: SS DC Measure
Requesting an exemption to the CoreQ: SS DC measure survey reporting requirements	3,272 SNFs	3,272	0.58	1898	$46.46	88,181
Contracting with a CMS-approved CoreQ survey vendor	12,163 SNFs	12,163	NA	NA	4,000	48,652,000 (12,163 × $4,000)
Data submission requirements for the proposed CoreQ: SS DC measure beginning with the FY 2027 SNF QRP	12,163 SNFs	632,476	0.50	316,238	46.46	14,692,417
Total	15,435 SNFs	635,748	1.08	318,147	NA	88,181 for exempted SNFs 63,344,417 for participating SNFs
* For the first year of implementation (January 1, 2024 through December 31, 2024), we estimate 4 hours of computer programmer time and 13.5 hours of medical record specialist time.
** Burden is calculated based on 27 weeks of required participation: submission at least one weekly resident information file to the CMS-approved CoreQ survey vendor January 1, 2024 through June 30, 2024; submission of resident information file to the CMS-approved CoreQ survey vendor no less than weekly July 1, 2024 through December 31, 2024.

Table 31—Proposed Burden to Beneficiaries for the CoreQ Survey (OMB 0938–TBD, CMS–10852)

Requirement	Number of respondents	Total responses	Time per response (hr)	Total time (hr)	Wage ($/hr)	Total cost ($)
FY 2026 CoreQ: SS DC Measure Beneficiary Burden
Completing the CoreQ: SS DC survey	1,330,284	1,330,284	0.1	133,028	20.71	2,755,010
FY 2027 CoreQ: SS DC Measure Beneficiary Burden
Completing the CoreQ: SS DC survey	2,558,238	2,558,238	0.1	255,824	20.71	5,298,115

2. ICRs Regarding the Skilled Nursing Facility Value-Based Purchasing Program

In section VII.B.3. of this rule, we are proposing to replace the SNFRM with the SNF WS PPR measure beginning with the FY 2028 SNF VBP program year. The measure is calculated using Medicare FFS claims data, which are the same data we use to calculate the SNFRM, and therefore, this measure would not create any new or revised burden for SNFs.

We are also proposing to adopt four new quality measures in the SNF VBP Program as discussed in section VII.B.4. of this proposed rule. One of the measures is the Total Nursing Staff Turnover Measure beginning with the FY 2026 SNF VBP Program Year. This measure is calculated using PBJ data that nursing facilities with SNF beds currently report to CMS as part of the Five Star Quality Rating System, and therefore, this measure would not create new or revised burden for SNFs. We are also proposing to adopt three additional quality measures beginning with the FY 2027 SNF VBP Program Year: (1) the Percent of Residents Experiencing One or More Falls with Major Injury (Long-Stay) Measure (“Falls with Major Injury (Long-Stay) measure”), (2) the Skilled Nursing Facility Cross-Setting Discharge Function Score Measure (“DC Function measure”), and (3) the Number of Hospitalizations per 1,000 Long-Stay Resident Days Measure (“Long-Stay Hospitalizations measure”). The Falls with Major Injury (Long-Stay) measure, and the DC Function measure are calculated using MDS 3.0 data and are calculated by CMS under the Nursing Home Quality Initiative and SNF QRP Program, respectively. The Long-Stay Hospitalization measure is calculated using Medicare FFS claims data. Therefore, these three measures would not create new or revised burden for SNFs.

Furthermore, in section VII.F. of this proposed rule, we are proposing to update the validation process for the SNF VBP Program, including adopting a new process for the Minimum Data Set (MDS) measures beginning with the FY 2027 SNF VBP program year. Under this proposal, we would validate data used to calculate the measures used in the SNF VBP Program, and 1,500 randomly selected SNFs a year would be required to submit up to 10 charts that would be audited to validate the MDS measures.

Finally, in section VII.E.5. of this rule, we are proposing to adopt a Health Equity Adjustment beginning with FY 2027 SNF VBP program year. The source of data we would use to calculate this adjustment is the State Medicare Modernization Act (MMA) file of dual eligibility, and therefore our calculation of this adjustment would not create any additional reporting burden for SNFs.

The aforementioned FFS-related claims submission requirements and burden, which are previously mentioned in the preceding paragraphs, are active and approved by OMB under control number 0938–1140 (CMS–10387). The aforementioned MDS submission requirements and burden are active and approved by OMB under control number 0938–1140 and the burden associated with the items used to calculate the measures is already accounted for in the currently approved information collection since it is used for the SNF QRP. The aforementioned PBJ submission requirements and burden are PRA exempt (as are all nursing home requirements for participation). The increase in burden for the SNFs would be accounted for in the submission of up to 10 charts for review, and the proposed process would not begin until FY 2025. The required 60-day and 30-day notices would be published in the Federal Register and the comment periods would be separate from those associated with this rulemaking. The proposals in this proposed rule would have no impact on any of the requirements and burden that are currently approved under these control numbers.

C. Summary of Proposed Burden Estimates

Table 32—Summary of Proposed Burden Estimates for FY 2025

Regulatory section(s) under title 42 of the CFR	OMB Control No. (CMS ID No.)	Number of respondents	Total number of responses	Time per response (hr)	Total time (hr)	Labor cost ($/hr)	Total cost ($)
413.360(b)(1)	0938–1140 CMS–10387	15,471 SNFs	(2,406,401)	0.005	(12,032)	86.21	(1,037,261)

Table 33—Summary of Proposed Burden Estimates for FY 2026

Regulatory section(s) under title 42 of the CFR	OMB Control No. (CMS ID No.)	Number of respondents	Total number of responses	Time per response (hr)	Total time (hr)	Labor cost ($/hr)	Total cost ($)
413.360	0938–1140 CMS–10387	15,471 SNFs	2,406,401	0.005	12,032	79.56	778,591
413.360	0938–TBD CMS–10852	3,272 exempted SNFs	3,272	0.58	1,898	46.46	88,181
413.360(b)(2)	0938–INSERT CMS–10852	1,330,284 beneficiaries	1,330,284	0.1	133,028	20.71	2,755,010
413.360(b)(2)	0938–TBD CMS–10852	12,163 participating SNFs	328,401	0.5/wk after initial 4 hr set up	212,853	Varies	12,149,449
413.360(b)(2)	0938–INSERT CMS–10852	12,163 participating SNFs	12,163	NA	NA	NA	48,652,000 (12,163 × $4,000)
Total for SNFs exempt from CoreQ AND reporting Patient/Resident COVID–19 Vaccine measure data		18,743	2,409,673	Varies	13,930	Varies	866,772
Total for SNFs not exempt from CoreQ AND reporting Patient/Resident COVID–19 Vaccine measure data *		1,370,081	4,077,249	Varies	357,913	Varies	61,580,040

Table 34—Summary of Proposed Burden Estimates for FY 2027

Regulatory section(s) under title 42 of the CFR	OMB Control No. (CMS ID No.)	Number of respondents	Total number of responses	Time per response (hr)	Total time (hr)	Labor cost ($/hr)	Total cost ($)
413.360	0938–TBD CMS–10852	3,272 exempted SNFs	3,272	0.58	1,898	46.46	88,181
413.360(b)(2)	0938–INSERT CMS–10852	2,558,238 beneficiaries	2,558,238	0.1	255,824	20.71	5,298,115
413.360(b)(2)	0938–TBD CMS–10852	12,163 participating SNFs	632,476	0.5	316,238	Varies	14,692,417
413.360(b)(2)	0938–TBD CMS–10852	12,163 participating SNFs	12,163	NA	NA	NA	48,652,000 (12,163 × $4,000)
Total for SNFs exempt from CoreQ reporting requirements		3,272	3,272	0.58	1,878	46.46	88,181
Total for SNFs not exempt from CoreQ reporting requirements *		2,582,564	3,202,877	0.6	572,062	Varies	63,344,417
*  Totals represent SNF burden only and do not include the beneficiary burden.

D. Submission of PRA-Related Comments

We have submitted a copy of this proposed rule's information collection requirements to OMB for their review. The requirements are not effective until they have been approved by OMB.

To obtain copies of the supporting statement and any related forms for the proposed collections discussed above, please visit the CMS website at https://www.cms.gov/​regulations-and-guidance/​legislation/​paperworkreductionactof1995/​pra-listing, or call the Reports Clearance Office at 410–786–1326.

We invite public comments on these potential information collection requirements. If you wish to comment, please submit your comments electronically as specified in the DATES and ADDRESSES sections of this proposed rule and identify the rule (CMS–1779–P), the ICR's CFR citation, and OMB control number.

X. Response to Comments

Because of the large number of public comments we normally receive on Federal Register documents, we are not able to acknowledge or respond to them individually. We will consider all comments we receive by the date and time specified in the DATES section of this preamble, and, when we proceed with a subsequent document, we will respond to the comments in the preamble to that document.

XI. Economic Analyses

A. Regulatory Impact Analysis

1. Statement of Need

a. Statutory Provisions

This rule proposes updates to the FY 2024 SNF prospective payment rates as required under section 1888(e)(4)(E) of the Act. It also responds to section 1888(e)(4)(H) of the Act, which requires the Secretary to provide for publication in the Federal Register before the August 1 that precedes the start of each FY, the unadjusted Federal per diem rates, the case-mix classification system, and the factors to be applied in making the area wage adjustment. These are statutory provisions that prescribe a detailed methodology for calculating and disseminating payment rates under the SNF PPS, and we do not have the discretion to adopt an alternative approach on these issues.

With respect to the SNF QRP, this proposed rule proposes updates beginning with the FY 2025, FY 2026, and FY 2027 SNF QRP. Specifically, we are proposing a modification to a current measure in the SNF QRP beginning with the FY 2025 SNF QRP, which we believe will encourage healthcare personnel to remain up to date with the COVID–19 vaccine, resulting in fewer cases, less hospitalizations, and lower mortality associated with the virus. We are proposing three new measures: (1) one to meet the requirements of the IMPACT Act which would replace the current cross-setting process measure with one more strongly associated with desired patient functional outcomes beginning with the FY 2025 SNF QRP; (2) one that supports the goals of CMS Meaningful Measures Initiative 2.0 to empower consumers, as well as assist SNFs leverage their care processes to increase vaccination coverage in their settings to protect residents and prevent negative outcomes beginning with the FY 2027 SNF QRP; and (3) one that would measure residents' satisfaction in order to assess whether the goals of person-centered care are achieved beginning with the FY 2026 SNF QRP. We are proposing the removal of three measures from the SNF QRP, beginning with the FY 2025 SNF QRP, as they meet the criteria specified at § 413.360(b)(2) for measure removal. We are further proposing to increase the data completion threshold for Minimum Data Set (MDS) data items, beginning with the FY 2026 SNF QRP, which we believe would improve our ability to appropriately analyze quality measure data for the purposes of monitoring SNF outcomes. For consistency in our regulations, we are also proposing conforming revisions to the requirements related to these proposals under the SNF QRP at § 413.360.

With respect to the SNF VBP Program, this rule proposes updates to the SNF VBP Program requirements for FY 2024 and subsequent years. Section 1888(h)(2)(A)(ii) of the Act (as amended by section 111(a)(2)(C) of the CAA 2021) allows the Secretary to add up to nine new measures to the SNF VBP Program. We are proposing to adopt four new measures for the SNF VBP Program. We propose to adopt one new measure beginning with the FY 2026 SNF VBP program year and three new measures beginning with the FY 2027 program year. We are also proposing to replace the SNFRM with the SNF WS PPR measure beginning with the FY 2028 SNF VBP Program year. Additionally, to better address health disparities and achieve health equity we are proposing to adopt a Health Equity Adjustment (HEA) beginning with the FY 2027 program year. As part of the HEA, we plan to adopt a variable payback percentage (for additional information on the HEA and the fluctuating payback percentage see section VII.E.4. of this proposed rule). Section 1888(h)(3) of the Act requires the Secretary to establish and announce performance standards for SNF VBP Program measures no later than 60 days before the performance period, and this proposed rule estimates numerical values of the performance standards for the SNFRM, the SNF Healthcare-Associated Infection Requiring Hospitalization (SNF HAI), Total Nurse Staffing, Nursing Staff Turnover, and the Discharge to Community—Post-Acute Care (DTC PAC SNF) measures. Section 1888(h)(12)(A) of the Act requires the Secretary to apply a validation process to SNF VBP Program measures and “the data submitted under [section 1888(e)(6)] [. . .] as appropriate[. . .].” We are proposing to adopt new validation processes for measures beginning in FY 2026.

b. Discretionary Provisions

In addition, this proposed rule includes the following discretionary provisions:

(1) PDPM Parity Adjustment Recalibration

In the FY 2023 SNF final rule (87 FR 47502), we finalized a recalibration of the PDPM parity adjustment with a 2-year phase-in period, resulting in a reduction of 2.3 percent, or $780 million, in FY 2023 and a planned reduction in FY 2024 of 2.3 percent. We finalized the phased-in approach to implementing this adjustment based on a significant number of comments supporting this approach. Accordingly, we are implementing the second phase of the 2-year phase-in period, resulting in a reduction of 2.3 percent, or approximately $745 million, in FY 2024.

(2) SNF Forecast Error Adjustment

Each year, we evaluate the SNF market basket forecast error for the most recent year for which historical data is available. The forecast error is determined by comparing the projected SNF market basket increase in a given year with the actual SNF market basket increase in that year. In evaluating the data for FY 2022, we found that the forecast error for FY 2022 was 3.6 percentage points, exceeding the 0.5 percentage point threshold we established in regulation for proposing adjustments to correct for forecast error. Given that the forecast error exceeds the 0.5 percentage point threshold, current regulations require that the SNF market basket percentage increase for FY 2024 be adjusted upward by 3.6 percentage points to account for forecasting error in the FY 2022 SNF market basket update.

(3) Technical Updates to ICD–10 Mappings

In the FY 2019 SNF PPS final rule (83 FR 39162), we finalized the implementation of the PDPM, effective October 1, 2019. The PDPM utilizes ICD–10 codes in several ways, including using the patient's primary diagnosis to assign patients to clinical categories under several PDPM components, specifically the PT, OT, SLP and NTA components. In this proposed rule, we propose several substantive changes to the PDPM ICD–10 code mapping.

(4) Civil Money Penalties: Waiver of Hearing, Automatic Reduction of Penalty Amount

We are proposing to eliminate the requirement for facilities to actively waive their right to a hearing in writing and create in its place a constructive waiver process that would operate by default when CMS has not received a timely request for a hearing. The accompanying 35 percent penalty reduction would remain. This revision eliminating the LTC requirement to submit a written request for a reduced penalty amount when a hearing has been waived would simplify and streamline the current requirement, while maintaining a focus on providing high quality care to residents. Ultimately, this proposal would reduce administrative burden for facilities and for CMS.

2. Introduction

We have examined the impacts of this proposed rule as required by Executive Order 12866 on Regulatory Planning and Review (September 30, 1993), Executive Order 13563 on Improving Regulation and Regulatory Review (January 18, 2011), the Regulatory Flexibility Act (RFA, September 19, 1980, Pub. L. 96–354), section 1102(b) of the Act, section 202 of the Unfunded Mandates Reform Act of 1995 (UMRA, March 22, 1995; Pub. L. 104–4), Executive Order 13132 on Federalism (August 4, 1999).

Executive Orders 12866 and 13563 direct agencies to assess all costs and benefits of available regulatory alternatives and, if regulation is necessary, to select regulatory approaches that maximize net benefits (including potential economic, environmental, public health and safety effects, distributive impacts, and equity). Executive Order 13563 emphasizes the importance of quantifying both costs and benefits, of reducing costs, of harmonizing rules, and of promoting flexibility. Based on our estimates, OMB's Office of Information and Regulatory Affairs has determined this rulemaking is “significant” as measured by the $100 million threshold. Accordingly, we have prepared a regulatory impact analysis (RIA) as further discussed below.

3. Overall Impacts

This rule updates the SNF PPS rates contained in the SNF PPS final rule for FY 2023 (87 FR 47502). We estimate that the aggregate impact will be an increase of approximately $1.2 billion (3.7 percent) in Part A payments to SNFs in FY 2024. This reflects a $2 billion (6.1 percent) increase from the proposed update to the payment rates and a $745 million (2.3 percent) decrease as a result of the second phase of the parity adjustment recalibration. We note in this proposed rule that these impact numbers do not incorporate the SNF VBP Program reductions that we estimate would total $184.85 million in FY 2024. We note that events may occur to limit the scope or accuracy of our impact analysis, as this analysis is future-oriented, and thus, very susceptible to forecasting errors due to events that may occur within the assessed impact time period.

In accordance with sections 1888(e)(4)(E) and (e)(5) of the Act and implementing regulations at § 413.337(d), we are updating the FY 2023 payment rates by a factor equal to the market basket percentage increase adjusted for the forecast error adjustment and reduced by the productivity adjustment to determine the payment rates for FY 2024. The impact to Medicare is included in the total column of Table 35. The annual update in this rule applies to SNF PPS payments in FY 2024. Accordingly, the analysis of the impact of the annual update that follows only describes the impact of this single year. Furthermore, in accordance with the requirements of the Act, we will publish a rule or notice for each subsequent FY that will provide for an update to the payment rates and include an associated impact analysis.

4. Detailed Economic Analysis

The FY 2024 SNF PPS payment impacts appear in Table 35. Using the most recently available data, in this case FY 2022 we apply the current FY 2023 CMIs, wage index and labor-related share value to the number of payment days to simulate FY 2023 payments. Then, using the same FY 2022 data, we apply the FY 2024 CMIs, wage index and labor-related share value to simulate FY 2024 payments. We tabulate the resulting payments according to the classifications in Table 35 (for example, facility type, geographic region, facility ownership), and compare the simulated FY 2023 payments to the simulated FY 2024 payments to determine the overall impact. The breakdown of the various categories of data in Table 35 is as follows:

• The first column shows the breakdown of all SNFs by urban or rural status, hospital-based or freestanding status, census region, and ownership.
• The first row of figures describes the estimated effects of the various proposed changes on all facilities. The next six rows show the effects on facilities split by hospital-based, freestanding, urban, and rural categories. The next nineteen rows show the effects on facilities by urban versus rural status by census region. The last three rows show the effects on facilities by ownership (that is, government, profit, and non-profit status).
• The second column shows the number of facilities in the impact database.
• The third column shows the effect of the second phase of the parity adjustment recalibration discussed in section III.C. of this rule.
• The fourth column shows the effect of the annual update to the wage index. This represents the effect of using the most recent wage data available as well as accounts for the 5 percent cap on wage index transitions. The total impact of this change is 0.0 percent; however, there are distributional effects of the proposed change.
• The fifth column shows the effect of all of the changes on the FY 2024 payments. The update of 6.1 percent is constant for all providers and, though not shown individually, is included in the total column. It is projected that aggregate payments would increase by 6.1 percent, assuming facilities do not change their care delivery and billing practices in response.

As illustrated in Table 35, the combined effects of all of the changes vary by specific types of providers and by location. For example, due to changes in this proposed rule, rural providers would experience a 3.0 percent increase in FY 2024 total payments.

In this chart and throughout the rule, we use a multiplicative formula to derive total percentage change. This formula is:

(1 + Parity Adjustment Percentage) * (1 + Wage Index Update Percentage) * (1 + Payment Rate Update Percentage)−1 = Total Percentage Change

For example, the figures shown in Column 5 of Table 35 are calculated by multiplying the percentage changes using this formula. Thus, the Total Change figure for the Total Group Category is 3.7 percent, which is (1−2.3%) * (1 + 0.0%) * (1 + 6.1%)−1.

As a result of rounding and the use of this multiplicative formula based on percentages, derived dollar estimates may not sum.

Table 35—Impact to the SNF PPS for FY 2024

Impact categories	Number of facilities	Parity adjustment recalibration (%)	Update wage data (%)	Total change (%)
Group
Total	15,435	−2.3	0.0	3.7
Urban	11,206	−2.3	0.1	3.8
Rural	4,229	−2.2	−0.7	3.0
Hospital-based urban	359	−2.3	0.1	3.7
Freestanding urban	10,847	−2.3	0.1	3.8
Hospital-based rural	375	−2.2	−0.4	3.3
Freestanding rural	3,854	−2.2	−0.7	3.0
Urban by region
New England	734	−2.3	−0.7	2.9
Middle Atlantic	1,468	−2.4	1.4	5.1
South Atlantic	1,935	−2.3	0.0	3.7
East North Central	2,176	−2.3	−0.7	3.0
East South Central	555	−2.2	0.0	3.7
West North Central	957	−2.3	−0.7	3.0
West South Central	1,432	−2.3	0.0	3.7
Mountain	545	−2.3	−0.8	2.9
Pacific	1,398	−2.4	0.2	3.7
Outlying	6	−2.0	−2.5	1.4
Rural by region
New England	114	−2.3	−1.0	2.6
Middle Atlantic	205	−2.2	−0.4	3.3
South Atlantic	484	−2.2	−0.1	3.7
East North Central	906	−2.2	−0.8	2.9
East South Central	490	−2.2	−1.0	2.8
West North Central	1,009	−2.2	−0.9	2.8
West South Central	732	−2.2	−0.5	3.3
Mountain	197	−2.3	−0.6	3.1
Pacific	91	−2.3	−2.0	1.5
Outlying	1	−2.3	0.0	3.6
Ownership
For profit	10,884	−2.3	0.0	3.7
Non-profit	3,550	−2.3	0.0	3.6
Government	1,001	−2.3	−0.4	3.3
Note: The Total column includes the FY 2024 6.1 percent market basket update factor. The values presented in Table 35 may not sum due to rounding.

5. Impacts for the Skilled Nursing Facility Quality Reporting Program (SNF QRP) for FY 2025

Estimated impacts for the SNF QRP are based on analysis discussed in section VI.C. of this proposed rule. In accordance with section 1888(e)(6)(A)(i) of the Act, the Secretary must reduce by 2 percentage points the annual payment update applicable to a SNF for a fiscal year if the SNF does not comply with the requirements of the SNF QRP for that fiscal year.

As discussed in section VI.C.1.a. of this proposed rule, we propose to modify one measure in the SNF QRP beginning with the FY 2025 SNF QRP, the COVID–19 Vaccination Coverage among Healthcare Personnel (HCP COVID–19 Vaccine) measure. We believe that the burden associated with the SNF QRP is the time and effort associated with complying with the non-claims-based measures requirements of the SNF QRP. The burden associated with the COVID–19 Vaccination Coverage among HCP measure is accounted for under the CDC PRA package currently approved under OMB control number 0938–1317 (expiration January 31, 2024).

As discussed in section VI.C.1.b. of this proposed rule, we propose that SNFs would collect data on one new quality measure, the Discharge Function Score (DC Function) measure, beginning with resident assessments completed on October 1, 2023. However, the DC Function measure utilizes data items that SNFs already report to CMS for payment and quality reporting purposes, and therefore, the burden is accounted for in the PRA package approved under OMB control number 0938–1140 (expiration November 30, 2025).

As discussed in section VI.C.1.c. of this proposed rule, we propose to remove a measure from the SNF QRP, the Application of Percent of Long-Term Care Hospital Patients with an Admission and Discharge Functional Assessment and a Care Plan That Addresses Function (Application of Functional Assessment/Care Plan) measure, beginning with admission assessments completed on October 1, 2023. Although the proposed decrease in burden will be accounted for in a revised information collection request under OMB control number (0938–1140), we are providing impact information.

With 2,406,401 admissions from 15,471 SNFs annually, we estimate an annual burden decrease of 12,032 fewer hours (2,406,401 admissions × 0.005 hr) and a decrease of $1,037,261 (12,038 hrs × $86.2085/hr). For each SNF we estimate an annual burden decrease of 0.78 hours [(12,032 hours/15,471 SNFs) at a savings of $67.05 ($1,037,261 total burden/15,471 SNFs).

As discussed in section VI.C.1.d. of this rule, we propose to remove two measures from the SNF QRP, the Application of IRF Functional Outcome Measure: Change in Self-Care Score for Medical Rehabilitation Patients (Change in Self-Care Score) and Application of IRF Functional Outcome Measure: Change in Mobility Score for Medical Rehabilitation Patients (Change in Mobility Score) measures, beginning with assessments completed on October 1, 2023. However, the data items used in the calculation of the Change in Self-Care Score and Change in Mobility Score measures are used for other payment and quality reporting purposes, and therefore there is no change in burden associated with this proposal.

As discussed in section VI.C.3.a. of this rule, we propose to add a second measure to the SNF QRP, the COVID–19 Vaccine: Percent of Patients/Residents Who are Up to Date (Patient/Resident COVID–19 Vaccine) measure, which would result in an increase of 0.005 hours of clinical staff time beginning with discharge assessments completed on October 1, 2024. Although the proposed increase in burden will be accounted for in a revised information collection request under OMB control number (0938–1140), we are providing impact information. With 2,406,401 discharges from 15,471 SNFs annually, we estimate an annual burden increase of 12,032 hours (2,406,401 discharges × 0.005 hr) and an increase of $778,5914 (12,032 hrs × $64.71/hr). For each SNF we estimate an annual burden increase of 0.78 hours (12,032 hrs/15,471 SNFs) at an additional cost of $50.33 ($778,591 total burden/15,471 SNFs).

We also propose in section VI.F.5. of this proposed rule that SNFs would begin reporting 100 percent of the required quality measures data and standardized patient assessment data collected using the MDS on at least 90 percent of the assessments they submit through the CMS designated submission system beginning January 1, 2024. As discussed in section IX.B.1. of this proposed rule, this change would not affect the information collection burden for the SNF QRP.

Finally, we propose in section VI.C.2. of this proposed rule to adopt the CoreQ: Short Stay Discharge (CoreQ: SS DC) measure to the SNF QRP beginning with the FY 2026 SNF QRP. Although the proposed increase in burden will be accounted for in a new information collection request, we are providing impact information. The impact of the proposed CoreQ: SS DC measure is discussed in three parts: (1) the burden for small SNFs requesting an exemption; (2) the burden for participating SNFs in the first year of national implementation; and (3) the burden for participating SNFs beginning with the second year of implementation. We describe each of these next and in Table 36.

As described in section VI.C.2.a.(5)(i) of this proposed rule, eligible SNFs may request an exemption from the proposed CoreQ: SS DC measure's reporting requirements. We estimate an increase of 0.58 hours of staff time for SNFs who request this exemption.

We estimate 3,272 SNFs would request an exemption, resulting in an annual burden increase of 1,898 hours (3,272 SNFs × 0.58 hrs) and an increase of $88,181 [3,272 SNFs × (0.58 hrs × $46.46/hr)]. For each SNF requesting an exemption, we estimate an annual burden increase of 0.58 hours and $26.95 (0.58 hrs × $46.46/hr).

In the first year of implementation of the proposed CoreQ: SS DC measure (January 1, 2024 through December 31, 2024), participating SNFs would need to contract with an independent, CMS approved survey vendor to administer the CoreQ survey on their behalf and submit the results to the CoreQ Data Center. We estimate $4,000 annual cost for a participating SNF to contract with a survey vendor, resulting in an annual cost increase of $48,652,000 ($4,000 × 12,163 estimated participating SNFs). Participating SNFs would also incur an increase of 17.5 hours of staff time to assemble and submit the resident information files, specifically four hours of computer programmer's time and 30 minutes per week for 27 weeks of a medical record specialist's time. We estimate a burden increase in CY 2024 of 212,853 hours (12,163 SNFs × 17.5 hours) and an increase of $12,149,499 [((4 hours × $92.92) + (13.5 hours × $46.46)) × 12,163]. For each SNF, we estimate an annual burden increase of 17.5 hours [4 + ((27 weeks × 30 min)/60)] and $998.89 [(4 hours × $92.92) + (13.5 hours × $46.46)].

Beginning with the second year of implementation of the proposed CoreQ: SS DC measure (January 1, 2025 through December 31, 2025), the potential impact of requesting an exemption or contracting with a survey vendor would not change and be the same as described above. However, as described in section VI.F.5.b. of this proposed rule, the second year of implementation of the proposed CoreQ measure requires participating SNFs to submit data for the entire CY. Therefore, we estimate the additional impact for participating SNFs would be 26 hours of medical record specialist time to assemble and submit the resident information files (52 weeks × 0.5 hr). We estimate an additional impact in CY 2025 of 316,238 hours (12,163 SNFs × 26 hours) and an increase of $14,692,417 [(26 hours × $46.46) × 12,163]. For each participating SNF, we estimate an additional impact of 26 hours and $1,207.96 (26 hours × $46.46).

Table 36—Estimated SNF QRP Program Impacts for FY 2025 Through FY 2027

Total benefit for the FY2025 SNF QRP	Per SNF		All SNFs
	Change in annual burden hours	Change in annual cost	Change in annual burden hours	Change in annual cost
Decrease in burden from the removal of the Functional Assessment/Care Plan measure	(0.78)	($67)	(12,032)	($1,037,261)
Total burden for the FY2026 SNF QRP
Total burden for SNFs exempt from the proposed CoreQ: SS DC measure reporting AND Increase in burden from the addition of the Patient/Resident COVID–19 Vaccine measure	1.36	77	13,941	866,772
Total burden for SNFs participating in the proposed CoreQ: SS DC measure reporting AND Increase in burden from the addition of the Patient/Resident COVID–19 Vaccine measure	18.28	5,049	224,885	61,580,090
Total burden for the FY 2027 SNF QRP
Total for SNFs exempt from the proposed CoreQ: SS DC measure reporting	0.58	26.95	1,898	88,181
Total for SNFs participating in the proposed CoreQ: SS DC measure reporting	26	1,208	316,238	63,344,417

We invite public comments on the overall impact of the SNF QRP proposals for FY 2025, 2026 and 2027.

6. Impacts for the SNF VBP Program

The estimated impacts of the FY 2024 SNF VBP Program are based on historical data and appear in Table 37. We modeled SNF performance in the Program using SNFRM data from FY 2019 as the baseline period and FY 2021 as the performance period. Additionally, we modeled a logistic exchange function with a payback percentage of 60 percent, as we finalized in the FY 2018 SNF PPS final rule (82 FR 36619 through 36621).

For the FY 2024 year, we will award each participating SNF 60 percent of their 2 percent withhold. Additionally, in the FY 2023 SNF PPS final rule (87 FR 47585 through 47587), we finalized our proposal to apply a case minimum requirement for the SNFRM. As a result of these provisions, SNFs that do not meet the case minimum specified for the SNFRM for the FY 2024 program year will be excluded from the Program and will receive their full Federal per diem rate for that fiscal year. As previously finalized, this policy will maintain the overall payback percentage at 60 percent for the FY 2024 program year. Based on the 60 percent payback percentage, we estimated that we would redistribute approximately $277.27 million (of the estimated $462.12 million in withheld funds) in value-based incentive payments to SNFs in FY 2024, which means that the SNF VBP Program is estimated to result in approximately $184.85 million in savings to the Medicare Program in FY 2024.

Our detailed analysis of the impacts of the FY 2024 SNF VBP Program is shown in Table 37.

Table 37—Estimated SNF VBP Program Impacts for FY 2024

Characteristic	Number of facilities	Mean risk- standardized readmission rate (SNFRM) (%)	Mean performance score	Mean incentive payment multiplier	Percent of total payment
Group
Total *	11,176	20.47	28.3029	0.99140	100.00
Urban	8,710	20.58	27.1026	0.99084	87.12
Rural	2,436	20.07	32.7202	0.99346	12.88
Hospital-based urban **	196	19.92	36.8240	0.99531	1.72
Freestanding urban **	8,501	20.60	26.8949	0.99074	85.38
Hospital-based rural **	87	19.58	39.2697	0.99636	0.36
Freestanding rural **	2,275	20.08	32.6780	0.99347	12.38
Urban by region
New England	627	20.62	27.4602	0.99121	5.45
Middle Atlantic	1,287	20.35	30.2740	0.99220	18.03
South Atlantic	1,691	20.83	25.4855	0.99011	17.75
East North Central	1,593	20.88	22.3914	0.98856	12.69
East South Central	468	20.83	24.1778	0.98938	3.55
West North Central	620	20.24	29.7294	0.99207	3.87
West South Central	912	21.11	18.7872	0.98700	6.75
Mountain	384	19.95	34.9771	0.99429	3.79
Pacific	1,125	19.93	36.2085	0.99528	15.24
Outlying	3	20.46	23.6945	0.98431	0.00
Rural by region
New England	75	19.51	40.6317	0.99752	0.55
Middle Atlantic	164	19.56	39.1621	0.99692	0.91
South Atlantic	340	20.37	29.6459	0.99162	2.06
East North Central	602	19.94	33.4406	0.99376	3.07
East South Central	383	20.48	28.5196	0.99167	2.14
West North Central	364	19.81	34.7097	0.99451	1.29
West South Central	345	20.74	24.3765	0.98937	1.68
Mountain	92	19.34	42.4305	0.99792	0.53
Pacific	71	18.48	58.5164	1.00597	0.64
Outlying	0
Ownership
Government	464	19.98	34.5948	0.99435	2.86
Profit	8,101	20.60	26.4146	0.99049	75.05
Non-Profit	2,581	20.16	33.2172	0.99378	22.08
* The total group category excludes 3,721 SNFs that failed to meet the finalized measure minimum policy. The total group category includes 30 SNFs that did not have facility characteristics in the CMS Provider of Services (POS) file or historical payment data used for this analysis.
** The group category which includes hospital-based/freestanding by urban/rural excludes 87 swing bed SNFs that satisfied the current measure minimum policy.

In section VII.B.4.b. of this proposed rule, we are proposing to adopt one additional measure (Nursing Staff Turnover measure) beginning with the FY 2026 program year. Additionally, in section VII.E.2.b. of this proposed rule, we are proposing to adopt a case minimum requirement for the Nursing Staff Turnover measure. In section VII.E.2.c. of this proposed rule, we are proposing to maintain the previously finalized measure minimum for FY 2026. Therefore, we are providing estimated impacts of the FY 2026 SNF VBP Program, which are based on historical data and appear in Tables 38 and 39. We modeled SNF performance in the Program using measure data from FY 2019 as the baseline period and FY 2021 as the performance period for the SNFRM, SNF HAI, Total Nurse Staffing, and Nursing Staff Turnover measures. Additionally, we modeled a logistic exchange function with a payback percentage of 60 percent. Based on the 60 percent payback percentage, we estimated that we will redistribute approximately $294.75 million (of the estimated $491.24 million in withheld funds) in value-based incentive payments to SNFs in FY 2026, which means that the SNF VBP Program is estimated to result in approximately $196.50 million in savings to the Medicare Program in FY 2026.

Our detailed analysis of the impacts of the FY 2026 SNF VBP Program is shown in Tables 38 and 39.

Table 38—Estimated SNF VBP Program Impacts for FY 2026

Characteristic	Number of facilities	Mean risk- standardized readmission rate (SNFRM) (%)	Mean total nursing hours per resident day (total nurse staffing)	Mean risk-standardized rate of hospital- acquired infections (SNF HAI) (%)	Mean total nursing staff turnover rate (nursing staff turnover) (%)
Group
Total *	13,879	20.39	3.91	7.67	52.74
Urban	10,266	20.52	3.93	7.69	52.43
Rural	3,613	20.04	3.87	7.61	53.62
Hospital-based urban **	239	20.01	5.22	6.52	45.90
Freestanding urban **	10,018	20.53	3.90	7.72	52.57
Hospital-based rural **	143	19.75	4.82	6.88	45.57
Freestanding rural **	3,399	20.04	3.83	7.68	53.93
Urban by region
New England	706	20.54	4.04	7.09	45.50
Middle Atlantic	1,408	20.31	3.68	7.55	46.06
South Atlantic	1,810	20.77	4.01	7.86	51.79
East North Central	1,956	20.74	3.59	7.72	55.47
East South Central	538	20.73	3.96	8.02	55.78
West North Central	839	20.18	4.19	7.41	57.73
West South Central	1,207	20.97	3.74	8.02	59.10
Mountain	490	19.94	4.15	7.15	56.54
Pacific	1,309	19.98	4.45	7.84	46.97
Outlying	3	20.46	3.30	6.20	N/A
Rural by region
New England	106	19.55	4.30	6.63	54.74
Middle Atlantic	192	19.60	3.42	7.17	53.04
South Atlantic	432	20.24	3.72	7.79	52.83
East North Central	802	19.94	3.63	7.46	53.02
East South Central	451	20.43	3.93	8.18	51.90
West North Central	802	19.85	4.12	7.50	53.49
West South Central	577	20.58	3.82	7.99	55.76
Mountain	168	19.54	4.18	7.16	55.96
Pacific	83	18.64	4.34	6.73	53.75
Outlying	0
Ownership
Government	735	20.00	4.34	7.36	48.93
Profit	9,975	20.51	3.72	7.89	54.29
Non-Profit	3,169	20.11	4.43	7.04	48.74
* The total group category excludes 1,028 SNFs that failed to meet the finalized measure minimum policy.
** The group category that includes hospital-based/freestanding by urban/rural excludes 80 swing bed SNFs that satisfied the proposed measure minimum policy.
N/A = Not available because no facilities in this group received a measure result.

Table 39—Estimated SNF VBP Program Impacts for FY 2026

Characteristic	Number of facilities	Mean performance score	Mean incentive payment multiplier	Percent of total payment
Group
Total *	13,879	24.5877	0.99108	100.00
Urban	10,266	24.4964	0.99106	85.88
Rural	3,613	24.8470	0.99112	14.12
Hospital-based urban **	239	40.2184	1.00671	1.60
Freestanding urban **	10,018	24.1217	0.99069	84.26
Hospital-based rural **	143	41.0606	1.00583	0.38
Freestanding rural **	3,399	24.0807	0.99041	13.62
Urban by region
New England	706	30.1328	0.99463	5.31
Middle Atlantic	1,408	26.0014	0.99182	17.27
South Atlantic	1,810	24.1128	0.99014	17.07
East North Central	1,956	18.8610	0.98737	12.69
East South Central	538	21.3335	0.98858	3.49
West North Central	839	26.4267	0.99302	3.99
West South Central	1,207	16.8688	0.98557	7.20
Mountain	490	27.4320	0.99295	3.81
Pacific	1,309	34.7925	0.99925	15.02
Outlying	3	21.6999	0.98682	0.00
Rural by region
New England	106	33.4096	0.99729	0.59
Middle Atlantic	192	22.9268	0.98939	0.91
South Atlantic	432	21.3377	0.98797	2.10
East North Central	802	22.3282	0.98960	3.20
East South Central	451	24.1187	0.99020	2.17
West North Central	802	29.2268	0.99485	1.80
West South Central	577	21.1394	0.98792	2.10
Mountain	168	30.0191	0.99532	0.63
Pacific	83	37.8989	1.00119	0.62
Outlying	0			0.00
Ownership
Government	735	33.4591	0.99976	3.20
Profit	9,975	21.0738	0.98806	75.04
Non-Profit	3,169	33.5907	0.99856	21.76
* The total group category excludes 1,028 SNFs that failed to meet the finalized measure minimum policy.
** The group category that includes hospital-based/freestanding by urban/rural excludes 80 swing bed SNFs that satisfied the proposed measure minimum policy.
N/A = Not available because no facilities in this group received a measure result.

In section VII.B.4. of this proposed rule, we are proposing to adopt three additional measures (Falls with Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization measures) beginning with the FY 2027 program year. Additionally, in section VII.E.2.b. of this proposed rule, we are proposing to adopt case minimum requirements for the Falls with Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization measures. In section VII.E.2.d. of this proposed rule, we are also proposing to update our previously finalized measure minimum for the FY 2027 program year. Therefore, we are providing estimated impacts of the FY 2027 SNF VBP Program, which are based on historical data and appear in Tables 40 and 41. We modeled SNF performance in the Program using measure data from FY 2019 (SNFRM, SNF HAI, Total Nurse Staffing, Nursing Staff Turnover, Falls with Major Injury (Long-Stay), and DC Function measures), CY 2019 (Long Stay Hospitalization measure), and FY 2018 through FY 2019 (DTC PAC SNF measure) as the baseline period and FY 2021 (SNFRM, SNF HAI, Total Nurse Staffing, Nursing Staff Turnover, Falls with Major Injury (Long-Stay), and DC Function measures), CY 2021 (Long Stay Hospitalization measure), and FY 2020 through FY 2021 (DTC PAC SNF measure) as the performance period. Additionally, we modeled a logistic exchange function with an approximate payback percentage of 66.02 percent, as we propose in section VII.E.4.e. of this proposed rule. Based on the increase in payback percentage, we estimated that we will redistribute approximately $324.18 million (of the estimated $491.03 million in withheld funds) in value-based incentive payments to SNFs in FY 2027, which means that the SNF VBP Program is estimated to result in approximately $166.86 million in savings to the Medicare Program in FY 2027.

Our detailed analysis of the impacts of the FY 2027 SNF VBP Program is shown in Tables 40 and 41.

Table 40—Estimated SNF VBP Program Impacts for FY 2027

Characteristic	Number of facilities	Mean risk- standardized readmission rate (SNFRM) (%)	Mean case-mix adjusted total nursing hours per resident day (total nurse staffing)	Mean risk- standardized hospital- acquired infection rate (SNF HAI) (%)	Mean total nursing staff turnover rate (nursing staff turnover) (%)	Mean risk- standardized discharge to community rate (DTC PAC) (%)	Mean number of risk-adjusted hospitalizations per 1,000 long- stay resident days (long stay hospitalization) (Hosp. per 1,000)	Mean percentage of stays meeting or exceeding expected discharge function score (DC function) (%)	Mean percentage of stays with a fall with major injury (falls with major injury (long-stay)) (%)
Group
Total *	13,672	20.39	3.92	7.68	52.64	51.28	1.47	51.96	3.36
Urban	10,083	20.52	3.94	7.69	52.30	52.03	1.50	51.72	3.07
Rural	3,589	20.03	3.86	7.63	53.58	49.18	1.39	52.61	4.16
Hospital-based urban **	227	20.00	5.26	6.47	46.33	60.97	1.10	46.90	2.17
Freestanding urban **	9,852	20.53	3.91	7.72	52.42	51.82	1.51	51.84	3.09
Hospital-based rural **	138	19.72	4.84	6.86	45.96	52.78	1.07	49.82	4.22
Freestanding rural **	3,409	20.04	3.82	7.68	53.87	48.80	1.40	52.85	4.16
Urban by region
New England	706	20.54	4.05	7.09	45.51	55.47	1.41	56.04	3.67
Middle Atlantic	1,397	20.31	3.67	7.56	45.98	49.63	1.40	54.87	2.95
South Atlantic	1,805	20.76	4.02	7.86	51.79	52.38	1.52	50.96	3.10
East North Central	1,871	20.76	3.62	7.72	55.11	52.56	1.52	48.29	3.23
East South Central	533	20.75	3.97	8.04	55.79	50.89	1.49	48.03	3.37
West North Central	827	20.17	4.19	7.41	57.62	51.24	1.51	55.00	3.82
West South Central	1,183	20.98	3.74	8.03	58.96	49.37	1.73	52.38	3.24
Mountain	472	19.93	4.16	7.13	56.75	57.52	1.17	55.02	2.96
Pacific	1,286	19.97	4.44	7.84	47.08	52.86	1.52	49.62	1.89
Outlying	3	20.46	3.30	6.20	N/A	66.54	N/A	50.77	0.00
Rural by region
New England	108	19.54	4.32	6.65	54.60	53.27	1.04	57.92	4.18
Middle Atlantic	191	19.57	3.41	7.13	52.89	47.82	1.13	53.15	3.99
South Atlantic	421	20.24	3.73	7.79	52.89	48.10	1.42	49.41	3.84
East North Central	799	19.94	3.63	7.47	52.80	51.48	1.30	49.59	4.14
East South Central	439	20.42	3.92	8.25	51.98	48.11	1.57	48.57	3.65
West North Central	800	19.84	4.10	7.51	53.61	47.74	1.35	56.70	4.77
West South Central	577	20.55	3.82	8.02	55.64	47.69	1.73	53.31	4.17
Mountain	173	19.55	4.17	7.16	55.65	51.94	1.02	58.19	4.22
Pacific	81	18.63	4.32	6.76	54.33	54.64	0.96	55.69	3.11
Outlying	0
Rural by region
Government	717	19.96	4.34	7.38	49.01	50.37	1.41	51.75	3.80
Profit	9,825	20.52	3.73	7.90	54.16	50.32	1.53	51.24	3.17
Non-Profit	3,130	20.10	4.44	7.04	48.71	54.49	1.33	54.25	3.85
* The total group category excludes 1,235 SNFs that failed to meet the proposed four out of eight measure minimum policy.
** The group category that includes hospital-based/freestanding by urban/rural excludes 46 swing bed SNFs that satisfied the proposed measure minimum policy.
N/A = Not available because no facilities in this group received a measure result.

Table 41—Estimated SNF VBP Program Impacts for FY 2027

Characteristic	Number of facilities	Mean health equity bonus points ***	Mean performance score ****	Mean incentive payment multiplier	Percent of total payment
Group
Total *	13,672	1.3922	32.9455	0.99185	100.00
Urban	10,083	1.4065	33.2266	0.99208	85.82
Rural	3,589	1.3522	32.1558	0.99119	14.18
Hospital-based urban **	227	1.0527	45.8943	1.00332	1.59
Freestanding urban **	9,852	1.4151	32.9329	0.99182	84.23
Hospital-based rural **	138	1.0851	43.4161	1.00072	0.38
Freestanding rural **	3,409	1.3752	31.5523	0.99069	13.70
Urban by region
New England	706	1.6512	37.2281	0.99477	5.32
Middle Atlantic	1,397	1.5283	34.0874	0.99249	17.29
South Atlantic	1,805	1.2317	32.5500	0.99129	17.10
East North Central	1,871	0.9931	28.9562	0.98911	12.59
East South Central	533	0.9183	29.0674	0.98909	3.49
West North Central	827	0.7315	32.7553	0.99175	3.98
West South Central	1,183	1.3010	27.3676	0.98777	7.18
Mountain	472	1.0725	39.2626	0.99648	3.82
Pacific	1,286	2.8460	42.4505	0.99940	15.04
Outlying	3	0.0000	36.5564	0.99256	0.00
Rural by region
New England	108	1.9869	42.3485	0.99953	0.61
Middle Atlantic	191	1.7348	31.4130	0.99020	0.91
South Atlantic	421	1.6187	29.0528	0.98846	2.09
East North Central	799	1.1916	31.2626	0.99059	3.22
East South Central	439	1.6169	29.8730	0.98945	2.16
West North Central	800	0.6760	33.9294	0.99251	1.81
West South Central	577	1.7368	29.1213	0.98892	2.12
Mountain	173	1.3443	39.8837	0.99746	0.64
Pacific	81	2.3226	45.2226	1.00188	0.62
Outlying	0				0.00
Ownership
Government	717	1.5059	37.5369	0.99586	3.17
Profit	9,825	1.5991	30.8612	0.99018	75.10
Non-Profit	3,130	0.7168	38.4361	0.99618	21.72
* The total group category excludes 1,235 SNFs that failed to meet the proposed four out of eight measure minimum policy.
** The group category that includes hospital-based/freestanding by urban/rural excludes 46 swing bed SNFs that satisfied the proposed measure minimum policy.
*** Because performance scores are capped at 100 points, SNFs may not receive all health equity bonus points they earn.
**** The mean total performance score is calculated by adding the proposed Health Equity Adjustment bonus points to the normalized sum of individual measure scores.
N/A = Not available because no facilities in this group received a measure result.

In section VII.B.3. of this proposed rule, we are proposing to replace the SNFRM with the SNF WS PPR measure beginning with the FY 2028 program year. Additionally, in section VII.E.2.b. of this rule, we are proposing to adopt a case minimum requirement for the SNF WS PPR measure. Therefore, we are providing estimated impacts of the FY 2028 SNF VBP Program, which are based on historical data and appear in Tables 42 and 43. We modeled SNF performance in the Program using measure data from FY 2019 (SNF HAI, Total Nurse Staffing, Nursing Staff Turnover, Falls with Major Injury (Long-Stay), and DC Function measures), CY 2019 (Long Stay Hospitalization measure), FY 2018 through FY 2019 (DTC PAC SNF measure), and FY 2019 through FY 2020 (SNF WS PPR measure) as the baseline period and FY 2021 (SNF HAI, Total Nurse Staffing, Nursing Staff Turnover, Falls with Major Injury (Long-Stay), and DC Function measures), CY 2021 (Long Stay Hospitalization measure), FY 2020 through FY 2021(DTC PAC SNF measure), and FY 2020 through FY 2021 (SNF WS PPR measure) as the performance period. Additionally, we modeled a logistic exchange function with an approximate payback percentage of 65.4 percent, as we propose in section VII.E.4.e. of this proposed rule. Based on the increase in payback percentage, we estimated that we will redistribute approximately $323.23 million (of the estimated $494.21 million in withheld funds) in value-based incentive payments to SNFs in FY 2028, which means that the SNF VBP Program is estimated to result in approximately $170.98 million in savings to the Medicare Program in FY 2028.

Our detailed analysis of the impacts of the FY 2028 SNF VBP Program is shown in Tables 42 and 43.

Table 42—Estimated SNF VBP Program Impacts for FY 2028

Characteristic	Number of facilities	Mean SNF within-stay potentially preventable readmission rate (SNF WS PPR) (%)	Mean total nursing hours per resident day (total nurse staffing)	Mean risk-standardized hospital-acquired infection rate (SNF HAI) (%)	Mean total nursing staff turnover rate (nursing staff turnover) (%)	Mean risk-standardized discharge to community rate (DTC PAC) (%)	Mean number of risk-adjusted hospitalizations per 1,000 long-stay resident days (Long Stay Hospitalization) (Hosp. per 1,000)	Mean percentage of stays meeting or exceeding expected discharge function score (DC Function) (%)	Mean percentage of stays with a fall with major injury (falls with major injury (long-stay)) (%)
Group
Total *	14,048	11.57	3.92	7.67	52.74	51.18	1.47	51.96	3.36
Urban	10,313	11.71	3.94	7.69	52.41	51.94	1.51	51.75	3.07
Rural	3,735	11.18	3.87	7.62	53.66	49.10	1.39	52.53	4.15
Hospital-based urban **	230	9.07	5.26	6.48	46.22	60.88	1.10	46.91	2.27
Freestanding urban **	10,079	11.77	3.91	7.72	52.53	51.73	1.51	51.87	3.09
Hospital-based rural **	142	9.44	4.84	6.88	45.96	52.54	1.06	49.90	4.19
Freestanding rural **	3,548	11.30	3.83	7.67	53.95	48.71	1.40	52.75	4.14
Urban by region
New England	712	10.70	4.05	7.09	45.49	55.47	1.41	55.98	3.67
Middle Atlantic	1,411	11.66	3.67	7.56	46.02	49.60	1.40	54.80	2.95
South Atlantic	1,827	11.86	4.04	7.85	51.78	52.34	1.53	51.03	3.11
East North Central	1,935	11.88	3.61	7.73	55.28	52.39	1.52	48.33	3.22
East South Central	539	11.77	3.96	8.03	55.87	50.88	1.49	48.20	3.34
West North Central	858	11.27	4.17	7.41	57.92	51.11	1.51	55.12	3.83
West South Central	1,235	12.75	3.73	8.02	59.06	49.27	1.73	52.68	3.21
Mountain	482	10.17	4.17	7.14	56.57	57.32	1.17	54.76	2.98
Pacific	1,310	11.70	4.45	7.84	47.13	52.81	1.53	49.52	1.90
Outlying	4	8.14	4.70	6.52	N/A	64.89	N/A	47.36	0.00
Rural by region
New England	112	9.98	4.33	6.67	54.86	52.92	1.05	57.56	4.20
Middle Atlantic	195	10.38	3.41	7.16	53.05	47.85	1.14	52.95	3.94
South Atlantic	436	11.43	3.72	7.76	53.00	48.14	1.42	49.32	3.79
East North Central	824	10.90	3.63	7.48	53.03	51.45	1.30	49.40	4.12
East South Central	451	12.06	3.93	8.23	51.93	48.13	1.57	48.54	3.64
West North Central	854	10.77	4.12	7.50	53.54	47.56	1.34	56.37	4.72
West South Central	603	12.40	3.83	8.02	55.74	47.62	1.72	53.46	4.16
Mountain	178	10.02	4.17	7.15	55.81	51.79	1.03	58.21	4.25
Pacific	82	9.32	4.37	6.76	54.33	54.46	0.97	56.23	3.12
Outlying	0
Ownership
Government	737	10.84	4.36	7.38	48.97	50.33	1.42	51.79	3.85
Profit	10,119	11.98	3.72	7.90	54.28	50.25	1.52	51.27	3.17
Non-Profit	3,192	10.45	4.45	7.04	48.74	54.35	1.32	54.19	3.85
* The total group category excludes 859 SNFs that failed to meet the proposed four of eight measure minimum policy.
** The group category that includes hospital-based/freestanding by urban/rural excludes 49 swing bed SNFs that satisfied the proposed measure minimum policy.
N/A = Not available because no facilities in this group received a measure result.

Table 43—Estimated SNF VBP Program Impacts for FY 2028

Characteristic	Number of facilities	Mean health equity bonus points ***	Mean performance score ****	Mean incentive payment multiplier	Percent of total payment
Group
Total *	14,048	1.3866	33.7117	0.99216	100.00
Urban	10,313	1.3834	33.8699	0.99229	85.72
Rural	3,735	1.3952	33.2749	0.99180	14.28
Hospital-based urban **	230	1.0999	50.6699	1.00718	1.59
Freestanding urban **	10,079	1.3903	33.4786	0.99194	84.13
Hospital-based rural **	142	1.1789	46.3840	1.00274	0.38
Freestanding rural **	3,548	1.4162	32.4459	0.99108	13.80
Urban by region
New England	712	1.6450	38.8562	0.99580	5.30
Middle Atlantic	1,411	1.4441	34.5592	0.99248	17.19
South Atlantic	1,827	1.2259	33.1678	0.99158	17.04
East North Central	1,935	1.0242	29.8652	0.98953	12.61
East South Central	539	0.9089	30.1968	0.98983	3.48
West North Central	858	0.7433	33.4543	0.99206	4.01
West South Central	1,235	1.2998	28.0800	0.98804	7.28
Mountain	482	1.1398	41.1899	0.99784	3.83
Pacific	1,310	2.7134	41.8142	0.99832	14.99
Outlying	4	0.0000	49.0903	1.00665	0.00
Rural by region
New England	112	2.1095	43.5189	1.00029	0.61
Middle Atlantic	195	1.6914	32.6276	0.99092	0.91
South Atlantic	436	1.6562	30.1287	0.98926	2.10
East North Central	824	1.2515	32.2562	0.99102	3.24
East South Central	451	1.6207	30.7335	0.99007	2.16
West North Central	854	0.7418	35.6622	0.99352	1.85
West South Central	603	1.7832	29.8043	0.98910	2.14
Mountain	178	1.4983	41.1638	0.99796	0.64
Pacific	82	2.2569	45.2986	1.00159	0.62
Outlying	0				0.00
Ownership
Government	737	1.5601	38.6989	0.99642	3.18
Profit	10,119	1.5762	31.3261	0.99022	75.13
Non-Profit	3,192	0.7454	40.1229	0.99730	21.69
* The total group category excludes 859 SNFs that failed to meet the proposed four out of eight measure minimum policy.
** The group category that includes hospital-based/freestanding by urban/rural excludes 49 swing bed SNFs that satisfied the proposed measure minimum policy.
*** Because performance scores are capped at 100 points, SNFs may not receive all health equity bonus points they earn.
**** The mean total performance score is calculated by adding the proposed Health Equity Adjustment bonus points to the normalized sum of individual measure scores.
N/A = Not available because no facilities in this group received a measure result.

7. Impacts for Civil Money Penalties (CMP): Waiver Process Changes

Current requirements at § 488.436(a) set forth a process for submitting a written waiver of a hearing to appeal deficiencies that lead to the imposition of a CMP which, when properly filed, results in the reduction by CMS or the State of a facility's CMP by 35 percent, as long as the CMP has not also been reduced by 50 percent under § 488.438. We propose to restructure the waiver process by establishing a constructive waiver at § 488.436(a) that would operate by default when CMS has not received a timely request for a hearing. Since a large majority of facilities facing CMPs typically submit the currently required express, written waiver, this proposed change to provide for a constructive waiver (after the 60-day timeframe in which to file an appeal following notice of CMP imposition) would reduce the costs and paperwork burden for most facilities.

In CY 2022, 81 percent of facilities facing CMPs filed an express waiver; whereas only 2 percent of facilities facing CMPs filed an appeal and went through the hearing process. The remaining 17 percent of facilities are those who fail to waive at all or fail to waive timely when they do not appeal. We estimate that moving to a constructive waiver process would eliminate the time and paperwork necessary to complete and send in a written waiver and would thereby result, as detailed below, in a total annual savings of $2,299,716 in administrative costs for LTC facilities facing CMPs as estimated in the following savings estimates ($861,678 plus $1,438,038 = $2,299,716).

We estimate that, at a minimum, facilities would save the routine cost of preparing and filing a letter (estimated at $200 per letter) to waive their hearing rights. In CY 2022, there were 5,319 facilities who were imposed CMPs. Roughly 81 percent (4,308) of these facilities filed an express, written waiver, therefore, we estimate an annual savings of $861,678 (4,308 × $200) since such letters would no longer be required to receive a 35 percent penalty reduction.

In addition, we believe that nationally some 17 percent of facilities fail to submit a waiver even though they had no intention of contesting the penalty and its basis. Under the proposed change to offer a constructive waiver by default, this 17 percent of facilities would now be eligible for the 35 percent CMP amount cost reduction. We note that in CY 2022, CMS imposed a combined total of $190,967,833 in per day and per instance CMPs, with a median total amount due of $4,545. Since CMS imposed CMPs on 5,319 facilities in CY 2022, we estimate a cost savings for 904 facilities (17 percent of 5,319), the typical 17 percent who fail to submit a timely waiver request. We estimate the annual cost savings for these facilities at $1,438,038 ((35 percent × $4,545) × 904 facilities).

Furthermore, we believe that the proposal to offer facilities a constructive waiver process would also ease the administrative burden for the CMS Locations. Based on our knowledge and experience, we estimate that, together, an array of individuals in each CMS Location collectively spend close to one hour (0.80 hours) per cases where a CMP is imposed to track and manage receipt of paperwork from facilities expressly requesting a waiver. Given that in CY 2022, CMS imposed a total of 11,475 CMPs on 5,319 facilities, with an average of 2.16 CMPs per facility, we estimate that CMS Locations spend a total of 9,191 hours each year (0.80 hours per CMP × 5,319 facilities × 2.16 CMPs per facility) to manage the waiver paperwork. As noted previously in this section, in CY 2022 we saw that 81 percent (4,308) of the 5,319 facilities with imposed CMPs submitted written waivers. Because the activities involved in processing facilities' written waivers requires input from individuals at varying levels within CMS, we base our estimate on the rate of $84.00 per hour on average, assuming a GS–12, step 5 salary rate of $42.00 per hour with a 100 percent benefits and overhead package. Thus, we estimate that CMS would save $772,044 per year ($84.00 per hour × 9,191 hours per year).

Total annual savings from these reforms to facilities and the Federal government together would therefore be $3,071,760 ($2,299,716 plus $772,044).

8. Alternatives Considered

As described in this section, we estimate that the aggregate impact of the provisions in this proposed rule will result in an increase of approximately $1.2 billion (3.7 percent) in Part A payments to SNFs in FY 2024. This reflects a $2 billion (6.1 percent) increase from the proposed update to the payment rates and a $745 million (2.3 percent) decrease as a result of the second phase of the parity adjustment recalibration, using the formula to multiply the percentage change described in section III.A.4. of this proposed rule.

Section 1888(e) of the Act establishes the SNF PPS for the payment of Medicare SNF services for cost reporting periods beginning on or after July 1, 1998. This section of the statute prescribes a detailed formula for calculating base payment rates under the SNF PPS, and does not provide for the use of any alternative methodology. It specifies that the base year cost data to be used for computing the SNF PPS payment rates must be from FY 1995 (October 1, 1994, through September 30, 1995). In accordance with the statute, we also incorporated a number of elements into the SNF PPS (for example, case-mix classification methodology, a market basket update, a wage index, and the urban and rural distinction used in the development or adjustment of the Federal rates). Further, section 1888(e)(4)(H) of the Act specifically requires us to disseminate the payment rates for each new FY through the Federal Register , and to do so before the August 1 that precedes the start of the new FY; accordingly, we are not pursuing alternatives for this process.

With regard to the proposal to modify the COVID–19 Vaccination Coverage Among Healthcare Personnel (HCP COVID–19 Vaccine) measure and to adopt the COVID–19 Vaccine: Percent of Patients/Residents Who are Up to Date (Patient/Resident COVID–19 Vaccine) measure to the SNF QRP Program, the COVID–19 pandemic has exposed the importance of implementing infection prevention strategies, including the promotion of COVID–19 vaccination for healthcare personnel (HCP) and patients/residents. We believe these measures would encourage healthcare personnel to be “up to date” with the COVID–19 vaccine, in accordance with current recommendations of the Centers for Disease Control and Prevention (CDC), and increase vaccine uptake in residents resulting in fewer cases, less hospitalizations, and lower mortality associated with the virus. However, we were unable to identify any alternative methods for collecting the data. There is still an overwhelming public need to target infection control and related quality improvement activities among SNF providers as well as provide data to patients and caregivers about the rate of COVID–19 vaccination among SNFs' healthcare personnel and residents through transparency of data. Therefore, these proposed measures have the potential to generate actionable data on COVID–19 vaccination rates for SNFs.

While we proposed to remove the Application of Percent of Long-Term Care Hospital Patients with an Admission and Discharge Functional Assessment and a Care Plan That Addresses Function (Application of Functional Assessment/Care Plan) process measure, we also propose to adopt the Discharge Function Score (DC Function) measure, which has strong scientific acceptability, and satisfies the requirement that there be at least one cross-setting function measure in the Post-Acute Care QRPs that uses standardized functional assessment data elements from standardized patient assessment instruments. We considered the alternative of delaying the proposal of the DC Function measure, but given its strong scientific acceptability, the fact that it provides an opportunity to replace the current cross-setting process measure with an outcome measure, and uses standardized functional assessment data elements that are already collected, we believe further delay is unwarranted. With regard to the proposal to remove the Application of Functional Assessment/Care Plan, the removal of this measure meets measure removal factors one and six set forth in § 413.360(b)(2), and no longer provides meaningful distinctions in improvements in performance.

The proposal to remove the Change in Self-Care Score and Change in Mobility Score measures meets measure removal factor eight set forth in § 413.360(b)(2), and the costs associated with a measure outweigh the benefits of its use in the program. Therefore, no alternatives were considered.

With regard to the proposal to adopt the CoreQ: Short Stay Discharge (CoreQ: SS DC) measure, the proposed measure fills a significant measurement gap in the SNF QRP: resident satisfaction with the quality of care received by SNFs. While the SNF QRP currently includes measures of process and outcomes that provide information on whether structural processes and interventions are working, measuring resident satisfaction would provide SNFs compelling information to use when examining the results of their clinical care, and can help SNFs identify deficiencies that other quality metrics may struggle to identify, such as communication between a resident and the SNF's clinical staff Additionally, the CoreQ survey, the basis of the CoreQ: SS DC measure, is already in use across the country by over 1,500 SNFs, and those SNFs that use the CoreQ survey(s) have reported they like the fact that the questionnaire is short (four questions), and residents report appreciation that their satisfaction (or lack thereof) is being measured. Therefore, given the importance of adding this domain measuring resident satisfaction to the SNF QRP, and the fact that the CoreQ: SS DC measure is a parsimonious survey that is highly reliable, valid and reportable, we believe adoption of the CoreQ: SS DC measure represents an essential addition to the SNF QRP measure set and no comparable alternative exists.

With regard to the proposal to increase the data completion threshold for the Minimum Data Set (MDS) items submitted to meet the SNF QRP reporting requirements, the proposed increased threshold of 90 percent is based on the need for substantially complete records, which allows appropriate analysis of quality measure data for the purposes of updating quality measure specifications. These data are ultimately reported to the public, allowing our beneficiaries to gain a more complete understanding of SNF performance related to these quality metrics, and helping them to make informed healthcare choices. We considered the alternative of not increasing the data completion threshold, but our data suggest that SNFs are already in compliance with or exceeding this proposed threshold, and therefore, there is no additional burden anticipated.

With regard to the proposals for the SNF VBP Program, we discuss alternatives considered within those sections. In section VII.E.5. of this proposed rule, we discuss other approaches to incorporating health equity into the program.

9. Accounting Statement

As required by OMB Circular A–4 (available online at https://obamawhitehouse.archives.gov/​omb/​circulars_​a004_​a-4/​), in Tables 44 through 49, we have prepared an accounting statement showing the classification of the expenditures associated with the provisions of this proposed rule for FY 2024. Tables 35 and 44 provide our best estimate of the possible changes in Medicare payments under the SNF PPS as a result of the policies in this proposed rule, based on the data for 15,435 SNFs in our database. Tables 36 and 45 through 47 provide our best estimate of the additional cost to SNFs to submit the data for the SNF QRP as a result of the policies in this proposed rule. Table 48 provides our best estimate of the possible changes in Medicare payments under the SNF VBP as a result of the policies for this program. Table 49 provides our best estimate of the amount saved by LTC facilities and CMS by removing the requirement to submit a written request and establishing a constructive waiver process instead at § 488.436(a) that would operate by default when CMS has not received notice of a facility's intention to submit a timely request for a hearing.

Table 44—Accounting Statement: Classification of Estimated Expenditures, From the 2023 SNF PPS Fiscal Year to the 2024 SNF PPS Fiscal Year

Category	Transfers
Annualized Monetized Transfers	$1.2 billion.*
From Whom To Whom?	Federal Government to SNF Medicare Providers.
* The net increase of $1.2 billion in transfer payments reflects a 3.7 percent increase, which is the product of the multiplicative formula described in section XI.A.4 of this rule. It reflects the proposed 6.1 percent SNF payment update increase (approximately $2 billion) from the proposed update to the payment rates, as well as a negative 2.3 percent decrease (approximately $745 million) from the second phase of the parity adjustment recalibration. Due to rounding and the nature of the multiplicative formula, dollar figures are approximations and may not sum.

Table 45—Accounting Statement: Classification of Estimated Expenditures for the FY 2025 QRP Program

Category	Transfers/costs
Savings to SNFs to Submit Data for QRP	($1,037,261)

Table 46—Accounting Statement: Classification of Estimated Expenditures for the FY 2026 SNF QRP Program

Category	Transfers/costs
Costs for SNFs to Submit Data for QRP	$61,668,221

Table 47—Accounting Statement: Classification of Estimated Expenditures for the FY 2027 SNF QRP Program

Category	Transfers/costs
Costs for SNFs to Submit Data for QRP	$63,432,598

Table 48—Accounting Statement: Classification of Estimated Expenditures for the FY 2024 SNF VBP Program

Category	Transfers
Annualized Monetized Transfers	$277.27 million.*
From Whom To Whom?	Federal Government to SNF Medicare Providers.
* This estimate does not include the 2 percent reduction to SNFs' Medicare payments (estimated to be $462.12 million) required by statute.

Table 49—Accounting Statement: Civil Money Penalties: Waiver of Hearing, Reduction of Penalty Amount

Category	Transfers/costs
Cost Savings of Constructive Waiver	$4,509,798
* The cost savings of $4.5 million is expected to occur in the first full year and be an ongoing savings for LTC Facilities and the Federal Government.

10. Conclusion

This rule updates the SNF PPS rates contained in the SNF PPS final rule for FY 2023 (87 FR 47502). Based on the above, we estimate that the overall payments for SNFs under the SNF PPS in FY 2024 are projected to increase by approximately $1.2 billion, or 3.7 percent, compared with those in FY 2023. We estimate that in FY 2024, SNFs in urban and rural areas would experience, on average, a 3.8 percent increase and 3.0 percent increase, respectively, in estimated payments compared with FY 2023. Providers in the urban Middle Atlantic region would experience the largest estimated increase in payments of approximately 5.1 percent. Providers in the urban Outlying region would experience the smallest estimated increase in payments of 1.4 percent.

B. Regulatory Flexibility Act Analysis

The RFA requires agencies to analyze options for regulatory relief of small entities, if a rule has a significant impact on a substantial number of small entities. For purposes of the RFA, small entities include small businesses, non-profit organizations, and small governmental jurisdictions. Most SNFs and most other providers and suppliers are small entities, either by reason of their non-profit status or by having revenues of $30 million or less in any 1 year. We utilized the revenues of individual SNF providers (from recent Medicare Cost Reports) to classify a small business, and not the revenue of a larger firm with which they may be affiliated. As a result, for the purposes of the RFA, we estimate that almost all SNFs are small entities as that term is used in the RFA, according to the Small Business Administration's latest size standards (NAICS 623110), with total revenues of $30 million or less in any 1 year. (For details, see the Small Business Administration's website at https://www.sba.gov/​category/​navigation-structure/​contracting/​contracting-officials/​eligibility-size-standards) In addition, approximately 20 percent of SNFs classified as small entities are non-profit organizations. Finally, individuals and states are not included in the definition of a small entity.

This rule updates the SNF PPS rates contained in the SNF PPS final rule for FY 2023 (87 FR 47502). Based on the above, we estimate that the aggregate impact for FY 2024 will be an increase of $1.2 billion in payments to SNFs, resulting from the proposed SNF market basket update to the payment rates, reduced by the second phase of the parity adjustment recalibration discussed in section III.C. of this proposed rule, using the formula described in section XI.A.4. of this rule. While it is projected in Table 34 that all providers would experience a net increase in payments, we note that some individual providers within the same region or group may experience different impacts on payments than others due to the distributional impact of the FY 2024 wage indexes and the degree of Medicare utilization.

Guidance issued by the Department of Health and Human Services on the proper assessment of the impact on small entities in rulemakings, utilizes a cost or revenue impact of 3 to 5 percent as a significance threshold under the RFA. In their March 2023 Report to Congress (available at https://www.medpac.gov/​wp-content/​uploads/​2023/​03/​Ch7_​Mar23_​MedPAC_​Report_​To_​Congress_​SEC.pdf), MedPAC states that Medicare covers approximately 10 percent of total patient days in freestanding facilities and 16 percent of facility revenue (March 2023 MedPAC Report to Congress, 207). As indicated in Table 34, the effect on facilities is projected to be an aggregate positive impact of 3.7 percent for FY 2024. As the overall impact on the industry as a whole, and thus on small entities specifically, exceeds the 3 to 5 percent threshold discussed previously, the Secretary has determined that this proposed rule will have a significant impact on a substantial number of small entities for FY 2024.

In addition, section 1102(b) of the Act requires us to prepare a regulatory impact analysis if a rule may have a significant impact on the operations of a substantial number of small rural hospitals. This analysis must conform to the provisions of section 603 of the RFA. For purposes of section 1102(b) of the Act, we define a small rural hospital as a hospital that is located outside of an MSA and has fewer than 100 beds. This proposed rule will affect small rural hospitals that: (1) furnish SNF services under a swing-bed agreement or (2) have a hospital-based SNF. We anticipate that the impact on small rural hospitals would be similar to the impact on SNF providers overall. Moreover, as noted in previous SNF PPS final rules (most recently, the one for FY 2023 (87 FR 47502)), the category of small rural hospitals is included within the analysis of the impact of this proposed rule on small entities in general. As indicated in Table 19, the effect on facilities for FY 2024 is projected to be an aggregate positive impact of 3.7 percent. As the overall impact on the industry as a whole exceeds the 3 to 5 percent threshold discussed above, the Secretary has determined that this proposed rule will have a significant impact on a substantial number of small rural hospitals for FY 2024.

C. Unfunded Mandates Reform Act Analysis

Section 202 of the Unfunded Mandates Reform Act of 1995 also requires that agencies assess anticipated costs and benefits before issuing any rule whose mandates require spending in any 1 year of $100 million in 1995 dollars, updated annually for inflation. In 2023, that threshold is approximately $177 million. This proposed rule will impose no mandates on State, local, or Tribal governments or on the private sector.

D. Federalism Analysis

Executive Order 13132 establishes certain requirements that an agency must meet when it issues a proposed rule (and subsequent final rule) that imposes substantial direct requirement costs on State and local governments, preempts State law, or otherwise has federalism implications. This proposed rule will have no substantial direct effect on State and local governments, preempt State law, or otherwise have federalism implications.

E. Regulatory Review Costs

If regulations impose administrative costs on private entities, such as the time needed to read and interpret this proposed rule, we should estimate the cost associated with regulatory review. Due to the uncertainty involved with accurately quantifying the number of entities that will review the rule, we assume that the total number of unique commenters on this year's proposed rule will be the number of reviewers of last year's proposed rule. We acknowledge that this assumption may understate or overstate the costs of reviewing this rule. It is possible that not all commenters reviewed this year's proposed rule in detail, and it is also possible that some reviewers chose not to comment on that proposed rule. For these reasons, we believe that the number of commenters on this year's proposed rule is a fair estimate of the number of reviewers of this year's proposed rule.

We also recognize that different types of entities are in many cases affected by mutually exclusive sections of this proposed rule, and therefore, for the purposes of our estimate we assume that each reviewer reads approximately 50 percent of the rule.

Using the national mean hourly wage data from the May 2021 BLS Occupational Employment and Wage Statistics (OEWS) for medical and health service managers (SOC 11–9111), we estimate that the cost of reviewing this rule is $115.22 per hour, including overhead and fringe benefits https://www.bls.gov/​oes/​current/​oes_​nat.htm. Assuming an average reading speed, we estimate that it would take approximately 4 hours for the staff to review half of the proposed rule. For each SNF that reviews the rule, the estimated cost is $460.88 (4 hours × $115.22). Therefore, we estimate that the total cost of reviewing this regulation is $3,129,719.04 ($460.88 × 6,849 reviewers).

In accordance with the provisions of Executive Order 12866, this proposed rule was reviewed by the Office of Management and Budget.

Chiquita Brooks-LaSure, Administrator of the Centers for Medicare & Medicaid Services, approved this document on March 29, 2023.

List of Subjects

42 CFR Part 411

• Diseases
• Medicare
• Reporting and recordkeeping requirements

42 CFR Part 413

• Diseases
• Health facilities
• Medicare
• Puerto Rico
• Reporting and recordkeeping

42 CFR Part 488

• Administrative practice and procedure
• Health facilities
• Health professions
• Medicare
• Reporting and recordkeeping requirements

42 CFR Part 489

• Health facilities
• Medicare
• Reporting and recordkeeping requirements

For the reasons set forth in the preamble, the Centers for Medicare & Medicaid Services proposes to amend 42 CFR chapter IV as set forth below:

PART 411—EXCLUSIONS FROM MEDICARE AND LIMITATIONS ON MEDICARE PAYMENT

1. The authority citation for part 411 continues to read as follows:

Authority: 42 U.S.C. 1302, 1395w–101 through 1395w–152, 1395hh, and 1395nn.

2. Amend § 411.15 by—

a. Redesignating paragraphs (p)(2)(vi) through (xviii) as (p)(2)(viii) through (xx); and

b. Adding new paragraphs (p)(2)(vi) and (vii).

The additions read as follows:

§ 411.15

Particular services excluded from coverage.

* * * * *

(p) * * *

(2) * * *

(vi) Services performed by a marriage and family therapist, as defined in section 1861(lll)(2) of the Act.

(vii) Services performed by a mental health counselor, as defined in section 1861(lll)(4) of the Act.

* * * * *

PART 413—PRINCIPLES OF REASONABLE COST REIMBURSEMENT; PAYMENT FOR END-STAGE RENAL DISEASE SERVICES; PROSPECTIVELY DETERMINED PAYMENT RATES FOR SKILLED NURSING FACILITIES; PAYMENT FOR ACUTE KIDNEY INJURY DIALYSIS

3. The authority citation for part 413 continues to read as follows:

Authority: 42 U.S.C. 1302, 1395d(d), 1395f(b), 1395g, 1395l(a), (i), and (n), 1395m, 1395x(v), 1395x(kkk), 1395hh, 1395rr, 1395tt, and 1395ww.

4. Amend § 413.338 by—

a. Removing the paragraph designations for paragraphs (a)(1) through (17);

b. Adding in paragraph (a) definitions in alphabetical order for “Health equity adjustment bonus points”, “Measure performance scaler”, “Top tier performing SNF”, “Underserved multiplier”, and “Underserved population”;

c. Revising paragraphs (c)(2)(i), (d)(4)(v), and (e)(2) introductory text;

d. Adding paragraph (e)(3);

e. Revising paragraph (j)(1); and

f. Adding paragraphs (j)(2) and (3) and (k).

The additions and revisions read as follows:

§ 413.338

Skilled nursing facility value-based purchasing program.

(a) * * *

Health equity adjustment (HEA) bonus points means the product of the measure performance scaler and the underserved multiplier.

* * * * *

Measure performance scaler means the sum of the points assigned to a SNF for each measure on which the SNF is a top tier performing SNF.

* * * * *

Top tier performing SNF means a SNF whose performance on a measure during the applicable program year meets or exceeds the 66.67th percentile of SNF performance on the measure during the same program year.

Underserved multiplier means, for a SNF, the number representing the SNF's proportion of residents with DES out of its total resident population in the applicable program year, translated using a logistic exchange function.

Underserved population means residents with dual eligibility status (DES).

* * * * *

(c) * * *

(2) * * *

(i) Total amount available for a fiscal year. The total amount available for value-based incentive payments for a fiscal year is at least 60 percent of the total amount of the reduction to the adjusted SNF PPS payments for that fiscal year, as estimated by CMS, and will be increased as appropriate for each fiscal year to account for the assignment of a performance score to low-volume SNFs under paragraph (d)(3) of this section. Beginning with the FY 2023 SNF VBP, the total amount available for value-based incentive payments for a fiscal year is 60 percent of the total amount of the reduction to the adjusted SNF PPS payments for that fiscal year, as estimated by CMS. Beginning with the FY 2027 SNF VBP, the total amount available for value-based incentive payments for a fiscal year is at least 60 percent of the total amount of the reduction to the adjusted SNF PPS payments for that fiscal year, as estimated by CMS, and will be increased as appropriate for each fiscal year to account for the application of the Health Equity Adjustment described at paragraph (k) of this section.

* * * * *

(d) * * *

(4) * * *

(v) CMS will calculate a SNF Performance Score for a fiscal year for a SNF for which it has granted an exception request that does not include its performance on a quality measure during the calendar months affected by the extraordinary circumstance.

* * * * *

(e) * * *

(2) Calculation of the SNF performance score for fiscal year 2026. The SNF performance score for FY 2026 is calculated as follows:

* * * * *

(3) Calculation of the SNF performance score beginning with fiscal year 2027. The SNF performance score for a fiscal year is calculated as follows:

(i) CMS will sum all points awarded to a SNF as described in paragraph (e)(1) of this section for each measure applicable to a fiscal year.

(ii) CMS will normalize the SNF's point total such that the resulting point total is expressed as a number of points earned out of a total of 100.

(iii) CMS will add to the SNF's point total under paragraph (e)(3)(ii) of this section any applicable health equity adjustment bonus points calculated under paragraph (k) of this section such that the resulting point total is the SNF Performance Score for the fiscal year, except that no SNF Performance Score may exceed 100 points.

* * * * *

(j) * * *

(1) Beginning with the FY 2023 Program year, for the SNFRM measure, and beginning with the FY 2026 Program year for all other claims-based measures, the information reported through claims are validated for accuracy by Medicare Administrative Contractors (MACs).

(2) Beginning with the FY 2026 Program year, for all measures that are calculated using Payroll-Based Journal System data, information reported through the Payroll-Based Journal system is validated for accuracy by CMS and its contractors through quarterly audits.

(3) Beginning with the FY 2027 program year, for all measure that are calculated using Minimum Data Set (MDS) information, such information is validated for accuracy by CMS and its contractors through periodic audits not to exceed 1,500 SNFs per calendar year.

(k) Calculation of the Health Equity Adjustment (HEA) bonus points. CMS calculates the number of HEA bonus points that are added to a SNF's point total calculated under paragraph (e)(3)(iii) of this section by:

(1) Determining for each measure whether the SNF is a top tier performing SNF and assigning two points to the SNF for each such measure;

(2) Summing the points calculated under paragraph (k)(1) of this section to calculate the measure performance scaler;

(3) Calculating the underserved multiplier for the SNF; and

(4) Multiplying the measure performance scaler calculated under paragraph (k)(2) of this section by the underserved multiplier calculated under paragraph (k)(3) of this section.

5. Amend § 413.360 by—

a. Redesignating paragraph (b)(2) as paragraph (b)(3),

b. Adding new paragraph (b)(2); and

c. Revising paragraphs (f)(1) and (2);

The addition and revisions read as follows:

§ 413.360

Requirements under the Skilled Nursing Facility (SNF) Quality Reporting Program (QRP).

* * * * *

(b) * * *

(2) Resident satisfaction data. A SNF must submit to CMS data regarding resident satisfaction after a short-stay discharge in the form and manner, and at a time, specified by CMS.

(i) Requirements. A SNF must contract with an independent survey vendor, approved by CMS in accordance with paragraph (b)(2)(ii) of this section, to administer the resident satisfaction questionnaire on its behalf.

(ii) CMS approval of survey vendor. CMS approves an application for an entity to administer the resident satisfaction questionnaire on behalf of one or more SNFs when an applicant has met the resident satisfaction survey's Protocols and Guidelines minimum business requirements that can be found on the official resident satisfaction measure website, and agrees to comply with the current survey administration protocols that can be found on the resident satisfaction measure website. An entity must be a CMS-approved survey vendor in order to administer and submit the resident satisfaction survey data to CMS on behalf of one or more SNFs.

(iii) Compliance with oversight activities. SNFs and CMS-approved survey vendors must fully comply with resident satisfaction measure oversight activities, including allowing CMS to perform site visits at the survey vendors' company locations.

* * * * *

(f) * * *

(1) SNFs must meet or exceed the following data completeness thresholds with respect to a calendar year:

(i) The threshold set at 100 percent completion of measures data and standardized patient assessment data collected using the Minimum Data Set (MDS) on at least 80 percent of the assessments SNFs submit through the CMS designated data submission system for FY 2018 through FY 2025.

(ii) The threshold set at 100 percent completion of measures data and standardized patient assessment data collected using the MDS on at least 90 percent of the assessments SNFs submit through the CMS designated data submission system beginning with the FY 2026 program year.

(iii) The threshold set at 100 percent for measures data collected and submitted through the Centers for Disease Control and Prevention's (CDC) National Healthcare Safety Network (NHSN) for FY 2023 and for all subsequent payment updates.

(iv) The threshold set at 75 percent of the weeks in a reporting year for submission of resident information files and 90 percent completion of the data required in resident information files for the resident satisfaction measure for FY 2026 and for all subsequent payment updates.

(2) These thresholds apply to all measures and standardized patient assessment data requirements adopted into the SNF QRP.

* * * * *

PART 488—SURVEY, CERTIFICATION, AND ENFORCEMENT PROCEDURES

6. The authority citation for part 488 continues to read as follows:

Authority: 42 U.S.C. 1302 and 1395hh.

7. Amend § 488.432 by revising paragraphs (c)(1) and (2) to read as follows:

§ 488.432

Civil money penalties imposed by the State: NF–only.

* * * * *

(c) * * *

(1) If a facility waives its right to a hearing as specified in § 488.436, the State initiates collection of civil money penalty imposed per day of noncompliance after 60 days from the date of the notice imposing the penalty and the State has not received a timely request for a hearing.

(2) If a facility waives its right to a hearing as specified in § 488.436, the State initiates collection of civil money penalty imposed per instance of noncompliance after 60 days from the date of the notice imposing the penalty and the State has not received a timely request for a hearing.

* * * * *

8. Amend § 488.436 by revising paragraph (a) to read as follows:

§ 488.436

Civil money penalties: Waiver of hearing, reduction of penalty amount.

(a) Constructive waiver of a hearing. A facility is deemed to have waived its right to a hearing after 60 days from the date of the notice imposing the civil money penalty if CMS has not received a request for a hearing from the facility.

* * * * *

9. Amend § 488.442 by revising paragraph (a)(2) introductory text to read as follows:

§ 488.442

Civil money penalties: Due date for payment of penalty.

(a) * * *

(2) After the facility waives its right to a hearing in accordance with § 488.436(a). Except as provided for in § 488.431, a civil money penalty is due 75 days after the notice of the penalty in accordance with § 488.436 and a hearing request was not received when:

* * * * *

PART 489—PROVIDER AGREEMENTS AND SUPPLIER APPROVAL

10. The authority citation for part 489 continues to read as follows:

Authority: 42 U.S.C. 1302, 1395i–3, 1395x, 1395aa(m), 1395cc, 1395ff, and 1395hh.

11. Amend § 489.20 by—

a. Redesignating paragraphs (s)(6) through (18) as paragraphs (s)(8) through (20), respectively; and

b. Adding new paragraphs (s)(6) and (7).

The additions read as follows:

§ 489.20

Basis commitments.

* * * * *

(s) * * *

(6) Services performed by a marriage and family therapist, as defined in section 1861(lll)(2) of the Act.

(7) Services performed by a mental health counselor, as defined in section 1861(lll)(4) of the Act.

* * * * *

Dated: March 31, 2023.

Xavier Becerra,

Secretary, Department of Health and Human Services.

Footnotes

1.  HL7 FHIR Release 4. Available at https://www.hl7.org/​fhir/​.

2.  HL7 FHIR. PACIO Functional Status Implementation Guide. Available at https://paciowg.github.io/​functional-status-ig/​.

3.  PACIO Project. Available at http://pacioproject.org/​about/​.

4.  Centers for Medicare & Medicaid Services. Newsroom. Fact sheet: CMS Data Element Library Fact Sheet. June 21, 2018. Available at https://www.cms.gov/​newsroom/​fact-sheets/​cms-data-element-library-fact-sheet.

5.  USCDI. Available at https://www.healthit.gov/​isa/​united-states-core-data-interoperability-uscdi.

6.  USCDI+. Available at https://www.healthit.gov/​topic/​interoperability/​uscdi-plus.

7.  Sections 4001 through 4008 of Public Law 114–255. Available at https://www.govinfo.gov/​content/​ pkg/PLAW-114publ255/html/PLAW-114publ255.htm.

8.  The Trusted Exchange Framework (TEF): Principles for Trusted Exchange (Jan. 2022). Available at https://www.healthit.gov/​sites/​default/​files/​page/​2022-01/​Trusted_​Exchange_​Framework_​0122.pdf.

9.  Common Agreement for Nationwide Health Information Interoperability Version 1 (Jan. 2022). Available at https://www.healthit.gov/​sites/​default/​files/​page/​2022-01/​Common_​Agreement_​for_​Nationwide_​Health_​Information_​Interoperability_​Version_​1.pdf.

10.  The Common Agreement defines Individual Access Services (IAS) as “with respect to the Exchange Purposes definition, the services provided utilizing the Connectivity Services, to the extent consistent with Applicable Law, to an Individual with whom the QHIN, Participant, or Subparticipant has a Direct Relationship to satisfy that Individual's ability to access, inspect, or obtain a copy of that Individual's Required Information that is then maintained by or for any QHIN, Participant, or Subparticipant.” The Common Agreement defines “IAS Provider” as: “Each QHIN, Participant, and Subparticipant that offers Individual Access Services.” See Common Agreement for Nationwide Health Information Interoperability Version 1, at 7 (Jan. 2022), https://www.healthit.gov/​sites/​default/​files/​page/​2022-01/​Common_​Agreement_​for_​Nationwide_​Health_​Information_​Interoperability_​Version_​1.pdf.

11.  “Building TEFCA,” Micky Tripathi and Mariann Yeager, Health IT Buzz Blog. February 13, 2023. https://www.healthit.gov/​buzz-blog/​electronic-health-and-medical-records/​interoperability-electronic-health-and-medical-records/​building-tefca.

12.  The Common Agreement defines a QHIN as “to the extent permitted by applicable SOP(s), a Health Information Network that is a U.S. Entity that has been Designated by the RCE and is a party to the Common Agreement countersigned by the RCE.” See Common Agreement for Nationwide Health Information Interoperability Version 1, at 10 (Jan. 2022), https://www.healthit.gov/​sites/​default/​files/​page/​2022-01/​Common_​Agreement_​for_​Nationwide_​Health_​Information_​Interoperability_​Version_​1.pdf.

13.  This measure was submitted to the Measures Under Consideration (MUC) List as the Cross-Setting Discharge Function Score. Subsequent to the MAP Workgroup meetings, the measure developer modified the name. Discharge Function Score for Skilled Nursing Facilities (SNFs) Technical Report. https://www.cms.gov/​files/​document/​snf-discharge-function-score-technical-report-february-2023.pdf.

14.  U.S. Department of Health and Human Services, Office of the Assistant Secretary for Preparedness and Response. Determination that a Public Health Emergency Exists. January 31, 2020. https://www.phe.gov/​emergency/​news/​healthactions/​phe/​Pages/​2019-nCoV.aspx.

15.  Centers for Disease Control and Prevention. COVID Data Tracker. February 13, 2023. https://covid.cdc.gov/​covid-data-tracker/​#datatracker-home.

16.  U.S. Department of Health and Human Services, Office of the Assistant Secretary for Preparedness and Response. Renewal of Determination that a Public Health Emergency Exists. February 9, 2023. https://aspr.hhs.gov/​legal/​PHE/​Pages/​COVID19-9Feb2023.aspx.

17.  U.S. Department of Health and Human Services. Fact Sheet: COVID–19 Public Health Emergency Transition Roadmap. February 9, 2023. https://www.hhs.gov/​about/​news/​2023/​02/​09/​fact-sheet-covid-19-public-health-emergency-transition-roadmap.html.

18.  Centers for Medicare & Medicaid Services. Revised Guidance for Staff Vaccination Requirements QSO–23–02–ALL. October 26, 2022. https://www.cms.gov/​files/​document/​qs0-23-02-all.pdf.

19.  Food and Drug Administration. FDA Takes Key Action in Fight Against COVID–19 By Issuing Emergency Use Authorization for First COVID–19 Vaccine. December 11, 2020. https://www.fda.gov/​news-events/​press-announcements/​fda-takes-key-action-fight-against-covid-19-issuing-emergency-use-authorization-first-covid-19.

20.  Food and Drug Administration. FDA Takes Additional Action in Fight Against COVID–19 By Issuing Emergency Use Authorization for Second COVID–19 Vaccine. December 18, 2020. https://www.fda.gov/​news-events/​press-announcements/​fda-takes-additional-action-fight-against-covid-19-issuing-emergency-use-authorization-second-covid.

21.  Food and Drug Administration. FDA Issues Emergency Use Authorization for Third COVID–19 Vaccine. February 27, 2021. https://www.fda.gov/​news-events/​press-announcements/​fda-issues-emergency-use-authorization-third-covid-19-vaccine.

22.  Food and Drug Administration. FDA Approves First COVID–19 Vaccine. August 23, 2021. https://www.fda.gov/​news-events/​press-announcements/​fda-approves-first-covid-19-vaccine.

23.  Food and Drug Administration. Coronavirus (COVID–19) Update: FDA Takes Key Action by Approving Second COVID–19 Vaccine. January 31, 2022. https://www.fda.gov/​news-events/​press-announcements/​coronavirus-covid-19-update-fda-takes-key-action-approving-second-covid-19-vaccine.

24.  Food and Drug Administration. Coronavirus (COVID–19) Update: FDA Authorizes Emergency Use of Novavax COVID–19 Vaccine, Adjuvanted. July 13, 2022. https://www.fda.gov/​news-events/​press-announcements/​coronavirus-covid-19-update-fda-authorizes-emergency-use-novavax-covid-19-vaccine-adjuvanted.

25.  Food and Drug Administration. FDA Authorizes Booster Dose of Pfizer-BioNTech COVID–19 Vaccine for Certain Populations. September 22, 2021. https://www.fda.gov/​news-events/​press-announcements/​fda-authorizes-booster-dose-pfizer-biontech-covid-19-vaccine-certain-populations.

26.  Food and Drug Administration. Coronavirus (COVID–19) Update: FDA Takes Additional Actions on the Use of a Booster Dose for COVID–19 Vaccines. October 20, 2021. https://www.fda.gov/​news-events/​press-announcements/​coronavirus-covid-19-update-fda-takes-additional-actions-use-booster-dose-covid-19-vaccines.

27.  Food and Drug Administration. Coronavirus (COVID–19) Update: FDA Expands Eligibility for COVID–19 Vaccine Boosters. November 19, 2021. https://www.fda.gov/​news-events/​press-announcements/​coronavirus-covid-19-update-fda-expands-eligibility-covid-19-vaccine-boosters.

28.  Food and Drug Administration. Coronavirus (COVID–19) Update: FDA Authorizes Second Booster Dose of Two COVID–19 Vaccines for Older and Immunocompromised Individuals. March 29, 2022. https://www.fda.gov/​news-events/​press-announcements/​coronavirus-covid-19-update-fda-authorizes-second-booster-dose-two-covid-19-vaccines-older-and.

29.  Food and Drug Administration. Coronavirus (COVID–19) Update: FDA Authorizes Moderna, Pfizer-BioNTech Bivalent COVID–19 Vaccines for Use as a Booster Dose. August 31, 2022. https://www.fda.gov/​news-events/​press-announcements/​coronavirus-covid-19-update-fda-authorizes-moderna-pfizer-biontech-bivalent-covid-19-vaccines-use.

30.  Centers for Disease Control and Prevention. Morbidity and Mortality Weekly Report (MMWR). Comparative Effectiveness of Moderna, Pfizer-BioNTech, and Janssen (Johnson & Johnson) Vaccines in Preventing COVID–19 Hospitalizations Among Adults Without Immunocompromising Conditions—United States, March–August 2021. September 24, 2021. https://cdc.gov/​mmwr/​volumes/​70/​wr/​mm7038e1.htm?​s_​cid=​mm7038e1_​w.

31.  Centers for Disease Control and Prevention. Morbidity and Mortality Weekly Report (MMWR). Monitoring Incidence of COVID–19 Cases, Hospitalizations, and Deaths, by Vaccination Status—13 U.S. Jurisdictions, April 4–July 17, 2021. September 10, 2021. https://cdc.gov.mmwr/​volumes/​70/​wr/​mm7037e1.htm?​s_​cid=​mm7037e1_​w.

32.  Centers for Disease Control and Prevention. Morbidity and Mortality Weekly Report (MMWR). Effectiveness of COVID–19 Vaccines in Preventing SARS–CoV–2 Infection Among Frontline Workers Before and During B.1.617.2 (Delta) Variant Predominance—Eight U.S. Locations, December 2020–August 2021. August 27, 2021. https://cdc.gov/​mmwr/​volume/​70/​wr/​mm7034e4.htm?​s_​cid=​mm7034e4_​w.

33.  Pilishvili T., Gierke R., Fleming-Dutra K.E., et al. Effectiveness of mRNA Covid–19 Vaccine among U.S. Health Care Personnel. N Engl J Med. 2021 Dec 16;385(25):e90. doi: 10.1056/NEJMoa2106599. PMID: 34551224; PMCID: PMC8482809.

34.  McGarry B.E., Barnett M.L., Grabowski D.C., Gandhi A.D. Nursing Home Staff Vaccination and Covid–19 Outcomes. N Engl J Med. 2022 Jan 27;386(4):397–398. doi: 10.1056/NEJMc2115674. PMID: 34879189; PMCID: PMC8693685.

35.  Centers for Disease Control and Prevention. Variants of the Virus. https://www.cdc.gov/​coronavirus/​2019-ncov/​variants/​index.html.

36.  Food and Drug Administration. COVID–19 Bivalent Vaccine Boosters. https://www.fda.gov/​emergency-preparedness-and-response/​coronavirus-disease-2019-covid-19/​covid-19-bivalent-vaccine-boosters.

37.  Chalkias S., Harper C., Vrbicky K., et al. A Bivalent Omicron-Containing Booster Vaccine Against COVID–19. N Engl J Med. 2022 Oct 6;387(14):1279–1291. doi: 10.1056/NEJMoa2208343. PMID: 36112399; PMCID: PMC9511634.

38.  Food and Drug Administration. Pfizer-BioNTech COVID–19 Vaccines. https://www.fda.gov/​emergency-preparedness-and-response/​coronavirus-disease-2019-covid-19/​pfizer-biontech-covid-19-vaccines.

39.  Food and Drug Administration. Moderna COVID–19 Vaccines. https://www.fda.gov/​emergency-preparedness-and-response/​coronavirus-disease-2019-covid-19/​moderna-covid-19-vaccines.

40.  Food and Drug Administration. Coronavirus (COVID–19) Update: FDA Authorizes Moderna, Pfizer-BioNTech Bivalent COVID–19 Vaccines for Use as a Booster Dose. August 31, 2022. https://www.fda.gov/​news-events/​press-announcements/​coronavirus-covid-19-update-fda-authorizes-moderna-pfizer-biontech-bivalent-covid-19-vaccines-use.

41.  Prasad N., Derado G., Nanduri S.A., et al. Effectiveness of a COVID–19 Additional Primary or Booster Vaccine Dose in Preventing SARS–CoV–2 Infection Among Nursing Home Residents During Widespread Circulation of the Omicron Variant—United States, February 14–March 27, 2022. Morbidity and Mortality Weekly Report (MMWR). 2022 May 6;71(18):633–637. doi: 10.15585/mmwr.mm7118a4. PMID: 35511708; PMCID: PMC9098239.

42.  Oster Y., Benenson S., Nir-Paz R., Buda I., Cohen M.J. The Effect of a Third BNT162b2 Vaccine on Breakthrough Infections in Health Care Workers: a Cohort Analysis. Clin Microbiol Infect. 2022 May;28(5):735.e1–735.e3. doi: 10.1016/j.cmi.2022.01.019. PMID: 35143997; PMCID: PMC8820100.

43.  National Quality Forum. Measure Application Partnership (MAP) Post-Acute Care/Long-Term Care: 2022–2023 Measures Under Consideration (MUC) Cycle Measure Specifications. December 1, 2022. https://www.qualityforum.org/​WorkArea/​linkit.aspx?​LinkIdentifier=​id&​ItemID=​97883.

44.  National Quality Forum. Measure Application Partnership (MAP) Post-Acute Care/Long-Term Care: 2022–2023 Measures Under Consideration (MUC) Cycle Measure Specifications. December 1, 2022. https://www.qualityforum.org/​WorkArea/​linkit.aspx?​LinkIdentifier=​id&​ItemID=​97883.

45.  National Quality Forum. 3636 Quarterly Reporting of COVID–19 Vaccination Coverage among Healthcare Personnel. Accessed February 6, 2023. Available at https://www.qualityforum.org/​QPS/​3636.

46.  Centers for Medicare & Medicaid Services. Overview of the List of Measures Under Consideration for December 1, 2022. https://mmshub.cms.gov/​sites/​default/​files/​2022-MUC-List-Overview.pdf.

47.  National Quality Forum. 3636 Quarterly Reporting of COVID–19 Vaccination Coverage among Healthcare Personnel. Accessed February 6, 2023. https://www.qualityforum.org/​QPS/​3636.

48.  2022–2023 MAP Final Recommendations. https://mmshub.cms.gov/​sites/​default/​files/​2022-2023-MAP-Final-Recommendations-508.xlsx.

49.  Centers for Disease Control and Prevention. Contraindications and precautions. https://www.cdc.gov/​vaccines/​covid-19/​clinical-considerations/​interim-considerations-us.html#contraindications.

50.  For more details on the reporting of other contract personnel, we refer readers to the NHSN COVID–19 Vaccination Protocol, Weekly COVID–19 Vaccination Module for Healthcare Personnel, https://www.cdc.gov/​nhsn/​pdfs/​hps/​covidvax/​protocol-hcp-508.pdf.

51.  Centers for Disease Control and Prevention. Contraindications and precautions. Available at https://www.cdc.gov/​vaccines/​covid-19/​clinical-considerations/​interim-considerations-us.html#contraindications.

52.  The updated (bivalent) Moderna and Pfizer-BioNTech boosters target the most recent Omicron subvariants. The updated (bivalent) boosters were recommended by the CDC on September 2, 2022. As of this date, the original, monovalent mRNA vaccines are no longer authorized as a booster dose for people ages 12 years and older.

53.  Completing a primary series means receiving a two-dose series of a COVID–19 vaccine or a single dose of Janssen/J&J COVID–19 vaccine.

54.  Medicare Payment Advisory Commission. Report to the Congress: Medicare and the Health Care Delivery System. June 2021. https://www.medpac.gov/​wp-content/​uploads/​import_​data/​scrape_​files/​docs/​default-source/​reports/​jun21_​medpac_​report_​to_​congress_​sec.pdf.

55.  Winkler D., Rose N., Freytag A., Sauter W., Spoden M., Schettler A., Wedekind L., Storch J., Ditscheid B., Schlattmann P., Reinhart K., Günster C., Hartog C.S., Fleischmann-Struzek C. The Effect of Post-acute Rehabilitation on Mortality, Chronic Care Dependency, Health Care Use and Costs in Sepsis Survivors. Ann Am Thorac Soc. 2022 Oct 17. doi: 10.1513/AnnalsATS.202203-195OC. Epub ahead of print. PMID: 36251451.

56.  Chao P.W., Shih C.J., Lee Y.J., Tseng C.M., Kuo S.C., Shih Y.N., Chou K.T., Tarng D.C., Li S.Y., Ou S.M., Chen Y.T. Association of Post discharge Rehabilitation with Mortality in Intensive Care Unit Survivors of Sepsis. Am J Respir Crit Care Med. 2014 Nov 1;190(9):1003-11. doi: 10.1164/rccm.201406-1170OC. PMID: 25210792.

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58.  The measures include: IRF Functional Outcome Measure: Change in Self-Care Score for Medical Rehabilitation Patients, IRF Functional Outcome Measure: Change in Mobility Score for Medical Rehabilitation Patients, IRF Functional Outcome Measure: Discharge Self-Care Score for Medical Rehabilitation Patients, IRF Functional Outcome Measure: Discharge Mobility Score for Medical Rehabilitation Patients.

59.  High K.P., Zieman S., Gurwitz J., Hill C., Lai J., Robinson T., Schonberg M., Whitson H. Use of Functional Assessment to Define Therapeutic Goals and Treatment. J Am Geriatr Soc. 2019 Sep;67(9):1782–1790. doi: 10.1111/jgs.15975. Epub 2019 May 13. PMID: 31081938; PMCID: PMC6955596.

60.  Clouston S.A., Brewster P., Kuh D., Richards M., Cooper R., Hardy R., Rubin M.S., Hofer S.M. The dynamic relationship between physical function and cognition in longitudinal aging cohorts. Epidemiol Rev. 2013;35(1):33–50. doi: 10.1093/epirev/mxs004. Epub 2013 Jan 24. PMID: 23349427; PMCID: PMC3578448.

61.  Michael Y.L., Colditz G.A., Coakley E., Kawachi I. Health behaviors, social networks, and healthy aging: cross-sectional evidence from the Nurses' Health Study. Qual Life Res. 1999 Dec;8(8):711–22. doi: 10.1023/a:1008949428041. PMID: 10855345.

62.  High K.P., Zieman S., Gurwitz J., Hill C., Lai J., Robinson T., Schonberg M., Whitson H. Use of Functional Assessment to Define Therapeutic Goals and Treatment. J Am Geriatr Soc. 2019 Sep;67(9):1782–1790. doi: 10.1111/jgs.15975. Epub 2019 May 13. PMID: 31081938; PMCID: PMC6955596.

63.  Deutsch A., Palmer L., Vaughan M., Schwartz C., McMullen T. Inpatient Rehabilitation Facility Patients' Functional Abilities and Validity Evaluation of the Standardized Self-Care and Mobility Data Elements. Arch Phys Med Rehabil. 2022 Feb 11:S0003–9993(22)00205–2. doi: 10.1016/j.apmr.2022.01.147. Epub ahead of print. PMID: 35157893.

64.  Hong I., Goodwin J.S., Reistetter T.A., Kuo Y.F., Mallinson T., Karmarkar A., Lin Y.L., Ottenbacher K.J. Comparison of Functional Status Improvements Among Patients With Stroke Receiving Postacute Care in Inpatient Rehabilitation vs Skilled Nursing Facilities. JAMA Netw Open. 2019 Dec 2;2(12):e1916646. doi: 10.1001/jamanetworkopen.2019.16646. PMID: 31800069; PMCID: PMC6902754.

65.  Alcusky M., Ulbricht C.M., Lapane K.L. Postacute Care Setting, Facility Characteristics, and Poststroke Outcomes: A Systematic Review. Arch Phys Med Rehabil. 2018;99(6):1124–1140.e9. doi:10.1016/j.apmr.2017.09.005. PMID: 28965738; PMCID: PMC5874162.

66.  Chu C.H., Quan A.M.L, McGilton K.S. Depression and Functional Mobility Decline in Long Term Care Home Residents with Dementia: a Prospective Cohort Study. Can Geriatr J. 2021;24(4):325–331. doi:10.5770/cgj.24.511. PMID: 34912487; PMCID: PMC8629506.

67.  Lane N.E., Stukel T.A., Boyd C.M., Wodchis W.P. Long-Term Care Residents' Geriatric Syndromes at Admission and Disablement Over Time: An Observational Cohort Study. J Gerontol A Biol Sci Med Sci. 2019;74(6):917–923. doi:10.1093/gerona/gly151. PMID: 29955879; PMCID: PMC6521919.

68.  Li C.Y., Haas A., Pritchard K.T., Karmarkar A., Kuo Y.F., Hreha K., Ottenbacher K.J. Functional Status Across Post-Acute Settings is Associated With 30-Day and 90-Day Hospital Readmissions. J Am Med Dir Assoc. 2021 Dec;22(12):2447–2453.e5. doi: 10.1016/j.jamda.2021.07.039. Epub 2021 Aug 30. PMID: 34473961; PMCID: PMC8627458.

69.  Middleton A., Graham J.E., Lin Y.L., Goodwin J.S., Bettger J.P., Deutsch A., Ottenbacher K.J. Motor and Cognitive Functional Status Are Associated with 30-day Unplanned Rehospitalization Following Post-Acute Care in Medicare Fee-for-Service Beneficiaries. J Gen Intern Med. 2016 Dec;31(12):1427–1434. doi: 10.1007/s11606–016–3704–4. Epub 2016 Jul 20. PMID: 27439979; PMCID: PMC5130938.

70.  Gustavson A.M., Malone D.J., Boxer R.S., Forster J.E., Stevens-Lapsley J.E. Application of High-Intensity Functional Resistance Training in a Skilled Nursing Facility: An Implementation Study. Phys Ther. 2020;100(10):1746–1758. doi: 10.1093/ptj/pzaa126. PMID: 32750132; PMCID: PMC7530575.

71.  Minor M., Jaywant A., Toglia J., Campo M., O'Dell M.W. Discharge Rehabilitation Measures Predict Activity Limitations in Patients with Stroke Six Months after Inpatient Rehabilitation. Am J Phys Med Rehabil. 2021 Oct 20. doi: 10.1097/PHM.0000000000001908. Epub ahead of print. PMID: 34686630.

72.  Dubin R., Veith J.M., Grippi M.A., McPeake J., Harhay M.O., Mikkelsen M.E. Functional Outcomes, Goals, and Goal Attainment among Chronically Critically Ill Long-Term Acute Care Hospital Patients. Ann Am Thorac Soc. 2021;18(12):2041–2048. doi:10.1513/AnnalsATS.202011–1412OC. PMID: 33984248; PMCID: PMC8641806.

73.  Hoffman G.J., Liu H., Alexander N.B., Tinetti M., Braun T.M., Min L.C. Posthospital Fall Injuries and 30-Day Readmissions in Adults 65 Years and Older. JAMA Netw Open. 2019 May 3;2(5):e194276. doi: 10.1001/jamanetworkopen.2019.4276. PMID: 31125100; PMCID: PMC6632136.

74.  Jette D.U., Warren R.L., Wirtalla C. The Relation Between Therapy Intensity and Outcomes of Rehabilitation in Skilled Nursing Facilities. Archives of Physical Medicine and Rehabilitation. 2005;86(3):373–379. doi: 10.1016/j.apmr.2004.10.018. PMID: 15759214.

75.  Gustavson A.M., Malone D.J., Boxer R.S., Forster J.E., Stevens-Lapsley J.E. Application of High-Intensity Functional Resistance Training in a Skilled Nursing Facility: An Implementation Study. Phys Ther. 2020;100(10):1746–1758. doi: 10.1093/ptj/pzaa126. PMID: 32750132; PMCID: PMC7530575.

76.  Harry M., Woehrle T., Renier C., Furcht M., Enockson M. Predictive Utility of the Activity Measure for Post-Acute Care `6-Clicks' Short Forms on Discharge Disposition and Effect on Readmissions: A Retrospective Observational Cohort Study. BMJ Open 2021;11:e044278. doi: 10.1136/bmjopen–2020–044278. PMID: 33478966; PMCID: PMC7825271.

77.  Warren M., Knecht J., Verheijde J., Tompkins J. Association of AM–PAC “6-Clicks” Basic Mobility and Daily Activity Scores With Discharge Destination. Phys Ther. 2021 Apr;101(4):pzab043. doi: 10.1093/ptj/pzab043. PMID: 33517463.

78.  Covert S., Johnson J.K., Stilphen M., Passek S., Thompson N.R., Katzan I. Use of the Activity Measure for Post-Acute Care “6 Clicks” Basic Mobility Inpatient Short Form and National Institutes of Health Stroke Scale to Predict Hospital Discharge Disposition After Stroke. Phys Ther. 2020 Aug 31;100(9):1423–1433. doi: 10.1093/ptj/pzaa102. PMID: 32494809.

79.  Criss M.G., Wingood M., Staples W., Southard V., Miller K., Norris T.L., Avers D., Ciolek C.H., Lewis C.B., Strunk E.R. APTA Geriatrics' Guiding Principles for Best Practices in Geriatric Physical Therapy: An Executive Summary. J Geriatr Phys Ther. 2022 April/June;45(2):70–75. doi: 10.1519/JPT.0000000000000342. PMID: 35384940.

80.  Cogan A.M., Weaver J.A., McHarg M., Leland N.E., Davidson L., Mallinson T. Association of Length of Stay, Recovery Rate, and Therapy Time per Day With Functional Outcomes After Hip Fracture Surgery. JAMA Netw Open. 2020 Jan 3;3(1):e1919672. doi: 10.1001/jamanetworkopen.2019.19672. PMID: 31977059; PMCID: PMC6991278.

81.  This measure was submitted to the Measures Under Consideration (MUC) List as the Cross-Setting Discharge Function Score. Subsequent to the MAP workgroup meetings, CMS modified the name. For more information, refer to the Discharge Function Score for Skilled Nursing Facilities (SNFs) Technical Report. https://www.cms.gov/​files/​document/​snf-discharge-function-score-technical-report-february-2023.pdf.

82.  The existing measures are the IRF Functional Outcome Measure: Discharge Self-Care Score for Medical Rehabilitation Patients measure (Discharge Self-Care Score), and the Inpatient Rehabilitation Facility (IRF) Functional Outcome Measure: Discharge Mobility Score for Medical Rehabilitation Patients measure (Discharge Mobility Score).

83.  “Expected functional capabilities” is defined as the predicted discharge function score.

84.   Discharge Function Score for Skilled Nursing Facilities (SNFs) Technical Report. https://www.cms.gov/​files/​document/​snf-discharge-function-score-technical-report-february-2023.pdf.

85.  The measures include: Change in Self-Care Score for Medical Rehabilitation Patients (NQF #2633), Change in Mobility for Medical Rehabilitation Patients (NQF #2634), Discharge Self-Care Score for Medical Rehabilitation Patients (NQF #2635), Discharge Mobility Score for Medical Rehabilitation Patients (NQF #2636).

86.   Technical Expert Panel (TEP) for the Refinement of Long-Term Care Hospital (LTCH), Inpatient Rehabilitation Facility (IRF), Skilled Nursing Facility (SNF)/Nursing Facility (NF), and Home Health (HH) Function Measures Summary Report (July 2021 TEP) is available at https://mmshub.cms.gov/​sites/​default/​files/​TEP-Summary-Report-PAC-Function.pdf.

87.   Technical Expert Panel (TEP) for Cross-Setting Function Measure Development Summary Report (January 2022 TEP) is available at https://mmshub.cms.gov/​sites/​default/​files/​PAC-Function-TEP-Summary-Report-Jan2022-508.pdf.

88.  Centers for Medicare & Medicaid Services. Overview of the List of Measures Under Consideration for December 1, 2022. CMS.gov. https://mmshub.cms.gov/​sites/​default/​files/​2022-MUC-List-Overview.pdf.

89.  2022–2023 MAP Final Recommendations. https://mmshub.cms.gov/​sites/​default/​files/​2022-2023-MAP-Final-Recommendations-508.xlsx.

90.   Discharge Function Score for Skilled Nursing Facilities (SNFs) Technical Report. https://www.cms.gov/​files/​document/​snf-discharge-function-score-technical-report-february-2023.pdf.

91.   Discharge Function Score for Skilled Nursing Facilities (SNFs) Technical Report. https://www.cms.gov/​files/​document/​snf-discharge-function-score-technical-report-february-2023.pdf.

92.  For more information on the factors CMS uses to base decisions for measure removal, we refer readers to the Code of Federal Regulations, § 413.360(b)(2). https://www.ecfr.gov/​current/​title-42/​chapter-IV/​subchapter-B/​part-413/​subpart-J/​section-413.360.

93.  Centers for Medicare & Medicaid Services. 2022 Annual Call for Quality Measures Fact Sheet, p. 10. https://www.cms.gov/​files/​document/​mips-call-quality-measures-overview-fact-sheet-2022.pdf.

94.  Centers for Medicare & Medicaid Services. Nursing Homes including Rehab Services Data Archive, 2020. Annual Files National Data 10–20. PQDC, https://data.cms.gov/​provider-data/​archived-data/​nursing-homes.

95.  Centers for Medicare & Medicaid Services. Nursing Homes including Rehab Services Data Archive, 2022. Annual Files National Data 06–22. PQDC, https://data.cms.gov/​provider-data/​archived-data/​nursing-homes.

96.  Centers for Medicare & Medicaid Services. Nursing Homes including Rehab Services Data Archive, 2022. Annual Files National Data 10–22. PQDC, https://data.cms.gov/​provider-data/​archived-data/​nursing-homes.

97.  Centers for Medicare & Medicaid Services. Nursing Homes including Rehab Services Data Archive, 2022. Annual Files Provider Data 05–22. PQDC, https://data.cms.gov/​provider-data/​archived-data/​nursing-homes.

98.  Centers for Medicare & Medicaid Services. Nursing Homes including Rehab Services Data Archive, 2022. Annual Files Provider Data 10–22. PQDC, https://data.cms.gov/​provider-data/​archived-data/​nursing-homes.

99.  “Expected functional capabilities” is defined as the predicted discharge function score.

100.   Federal Register . Medicare Program; Prospective Payment System and Consolidated Billing for Skilled Nursing Facilities for FY 2018. https://www.federalregister.gov/​documents/​2017/​05/​04/​2017-08521/​medicare-program-prospective-payment-system-and-consolidated-billing-for-skilled-nursing-facilities#p-397.

101.  Acumen, LLC and Abt Associates. Technical Expert Panel (TEP) for the Refinement of Long-Term Care Hospital (LTCH), Inpatient Rehabilitation Facility (IRF), Skilled Nursing Facility (SNF)/Nursing Facility (NF), and Home Health (HH) Function Measures, July 14–15, 2021: Summary Report. February 2022. https://mmshub.cms.gov/​sites/​default/​files/​TEP-Summary-Report-PAC-Function.pdf.

102.  Acumen, LLC and Abt Associates. Technical Expert Panel (TEP) for the Refinement of Long-Term Care Hospital (LTCH), Inpatient Rehabilitation Facility (IRF), Skilled Nursing Facility (SNF)/Nursing Facility (NF), and Home Health (HH) Function Measures, July 14–15, 2021: Summary Report. February 2022. https://mmshub.cms.gov/​sites/​default/​files/​TEP-Summary-Report-PAC-Function.pdf.

103.  Acumen, LLC and Abt Associates. Technical Expert Panel (TEP) for the Refinement of Long-Term Care Hospital (LTCH), Inpatient Rehabilitation Facility (IRF), Skilled Nursing Facility (SNF)/Nursing Facility (NF), and Home Health (HH) Function Measures, July 14–15, 2021: Summary Report. February 2022. https://mmshub.cms.gov/​sites/​default/​files/​TEP-Summary-Report-PAC-Function.pdf.

104.  Centers for Medicare & Medicaid Services. Innovation Center. Person-Centered Care. https://innovation.cms.gov/​key-concepts/​person-centered-care.

105.  National Quality Forum. MAP 2018 Considerations for Implementing Measures in Federal Programs—PAC–LTC. MAP 2018 Considerations for Implementing Measures in Federal Programs: Post-Acute Care and Long-Term Care (cms.gov).

106.  Li Y, Li Q, Tang Y. Associations between Family Ratings on Satisfaction with Care and Clinical Quality-of-Care Measures for Nursing Home Residents. Med Care Res Rev. 2016 Feb;73(1):62–84. doi: 10.1177/1077558715596470. Epub 2015 Jul 21. PMID: 26199288; PMCID: PMC4712136.

107.  Boulding W, Glickman SW, Manary MP, Schulman KA, Staelin R. Relationship between Patient Satisfaction with Inpatient Care and Hospital Readmission within 30 days. Am J Manag Care. 2011 Jan;17(1):41–8. PMID: 21348567.

108.  Carter J, Ward C, Wexler D, Donelan K. The Association between Patient Experience Factors and Likelihood of 30-day Readmission: a Prospective Cohort Study. BMJ Qual Saf. 2018;27:683–690. doi: 10.1136/bmjqs-2017–007184. PMID: 29146680.

109.  Anderson PM, Krallman R, Montgomery D, Kline-Rogers E, Bumpus SM. The Relationship Between Patient Satisfaction With Hospitalization and Outcomes Up to 6 Months Post-Discharge in Cardiac Patients. J Patient Exp. 2020;7(6):1685–1692. doi: 10.117712374373520948389. PMID: 33457631 PMCID: PMC7786784.

110.  Barbosa CD, Balp MM, Kulich K, Germain N, Rofail D. A Literature Review to Explore the Link Between Treatment Satisfaction and Adherence, Compliance, and Persistence. Patient Prefer Adherence. 2012;6:39–48. doi: 10.2147/PPA.S24752. Epub 2012 Jan 13. PMID: 22272068; PMCID: PMC3262489.

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112.  Consumer Assessment of Healthcare Providers & Systems (CAHPS). https://cms.gov/​Research-Statistics-Data-and-Systems/​Research/​CAHPS.com.

113.  Care Compare. https://www.medicare.gov/​care-compare/​.

114.  Sangl J, Bernard S, Buchanan J, Keller S, Mitchell N, Castle NG, Cosenza C, Brown J, Sekscenski E, Larwood D. The development of a CAHPS instrument for nursing home residents. J Aging Soc Policy. 2007;19(2):63–82. doi: 10.1300/J031v19n02_04. PMID: 17409047.

115.  The CAHPS consortium included Harvard Medical School, The RAND Corporation, and Research Triangle Institute International.

116.  The CoreQ was developed by Nicholas Castle, Ph.D., the American Health Care Association/National Center for Assisted Living (AHCA/NCAL), and providers with input from customer satisfaction vendors and residents.

117.  What is CoreQ? www.coreq.org.

118.  CoreQ_Short_Stay_Appendix_Final_updated_Jan2020_Corrected_April2020_FinalforSubmission-637229961612228954.docx. Available in the measure's specifications from the Patient Experience and Function Spring Cycle 2020 project. Available at: https://nqfappservicesstorage.blob.core.windows.net/​proddocs/​36/​Spring/​2020/​measures/​2614/​shared/​2614.zip.

119.  Centers for Medicare & Medicaid Services. Meaningful Measures 2.0: Moving from Measure Reduction to Modernization. https://www.cms.gov/​meaningful-measures-20-moving-measure-reduction-modernization.

120.  CoreQ_Short_Stay_Testing_Final_v7.1_Corrected_4_20_20_FinalforSubmission-637229958835088042.docx. Available in the measure's specifications from the Patient Experience and Function Spring Cycle 2020 project. Available at: https://nqfappservicesstorage.blob.core.windows.net/​proddocs/​36/​Spring/​2020/​measures/​2614/​shared/​2614.zip.

121.  CoreQ_Short_Stay_Testing_Final_v7.1_Corrected_4_20_20_FinalforSubmission-637229958835088042.docx. Available in the measure's specifications from the Patient Experience and Function Spring Cycle 2020 project. Available at: https://nqfappservicesstorage.blob.core.windows.net/​proddocs/​36/​Spring/​2020/​measures/​2614/​shared/​2614.zip.

122.  CoreQ_Short_Stay_Testing_Final_v7.1_Corrected_4_20_20_FinalforSubmission-637229958835088042.docx. Available in the measure's specifications from the Patient Experience and Function Spring Cycle 2020 project. Available at: https://nqfappservicesstorage.blob.core.windows.net/​proddocs/​36/​Spring/​2020/​measures/​2614/​shared/​2614.zip.

123.  CoreQ Measure Worksheet-2614-Spring 2020 Cycle. Patient Experience and Function Project. Available at https://www.qualityforum.org/​WorkArea/​linkit.aspx?​LinkIdentifier=​id&​ItemID=​93879.

124.  The Person and Family Centered Care Final Report—Phase 3. https://www.qualityforum.org/​Publications/​2017/​01/​Person_​and_​Family_​Centered_​Care_​Final_​Report_​-_​Phase_​3.aspx.

125.  Centers for Medicare & Medicaid Services. List of Measures under Consideration for December 1, 2017. https://www.cms.gov/​files/​document/​2017amuc-listclearancerpt.pdf.

126.  MAP Post-Acute Care/Long-Term Care Workgroup Project. 2017–2018 Preliminary Recommendations. Available at https://mmshub.cms.gov/​measure-lifecycle/​measure-implementation/​pre-rulemaking/​lists-and-reports.

127.  Draft CoreQ: SS DC Survey Protocols and Guidelines Manual. Chapter VIII. Data Processing and Coding. Available on the SNF QRP Measures and Technical Information web page at https://www.cms.gov/​medicare/​quality-initiatives-patient-assessment-instruments/​nursinghomequalityinits/​skilled-nursing-facility-quality-reporting-program/​snf-quality-reporting-program-measures-and-technical-information.

128.  Patients who have dementia impairment in their ability to answer the questionnaire are defined as having a Brief Interview of Mental Status (BIMS) score on the MDS 3.0 as 7 or lower. https://cmit.cms.gov/​CMIT_​public/​ViewMeasure?​MeasureId=​3436.

129.  The measure developer examined the following SDS categories: age, race, gender, and highest level of education. CoreQ: Short Stay Discharge Measure.

130.  Draft CoreQ: SS DC Survey Protocols and Guidelines Manual. Chapter VIII. Data Processing and Coding. Available on the SNF QRP Measures and Technical Information web page at https://www.cms.gov/​medicare/​quality-initiatives-patient-assessment-instruments/​nursinghomequalityinits/​skilled-nursing-facility-quality-reporting-program/​snf-quality-reporting-program-measures-and-technical-information.

131.  Centers for Disease Control and Prevention. COVID Data Tracker. https://covid.cdc.gov/​covid-data-tracker/​#cases_​totalcases.

132.  United Nations. Policy Brief: The Impact of COVID–19 on Older Persons. May 2020. https://unsdg.un.org/​sites/​default/​files/​2020-05/​Policy-Brief-The-Impact-of-COVID-19-on-Older-Persons.pdf.

133.  Lekamwasam R, Lekamwasam S. Effects of COVID–19 Pandemic on Health and Wellbeing of Older People: a Comprehensive Review. Ann Geriatr Med Res. 2020;24(3):166–172. doi: 10.4235/agmr.20.0027. PMID: 32752587; PMCID: PMC7533189.

134.  Centers for Disease Control and Prevention. Demographic Trends of COVID–19 Cases and Deaths in the US Reported to CDC. COVID Data Tracker. https://covid.cdc.gov/​covid-data-tracker/​#demographics.

135.  United Nations. Policy Brief: The Impact of COVID–19 on Older Persons. May 2020. https://unsdg.un.org/​sites/​default/​files/​2020-05/​Policy-Brief-The-Impact-of-COVID-19-on-Older-Persons.pdf.

136.  Chalkias S, Harper C, Vrbicky K, et al. A Bivalent Omicron-Containing Booster Vaccine Against COVID–19. N Engl J Med. 2022 Oct 6;387(14):1279–1291. doi: 10.1056/NEJMoa2208343. PMID: 36112399; PMCID: PMC9511634.

137.  Centers for Disease Control and Prevention. Fully Vaccinated Adults 65 and Older Are 94% Less Likely to Be Hospitalized with COVID–19. April 28, 2021. https://www.cdc.gov/​media/​releases/​2021/​p0428-vaccinated-adults-less-hospitalized.html.

138.  Interim Estimates of COVID–19 Vaccine Effectiveness Against COVID–19–Associated Emergency Department or Urgent Care Clinic Encounters and Hospitalizations Among Adults During SARS–CoV–2 B.1.617.2 (Delta) Variant Predominance—Nine States, June–August 2021. (Grannis SJ, et al. MMWR Morb Mortal Wkly Rep. 2021;70(37):1291–1293. doi: 10.15585/mmwr.mm7037e2). https://www.cdc.gov/​mmwr/​volumes/​70/​wr/​mm7037e2.htm.

139.  Surie D, Bonnell L, Adams K, et al. Effectiveness of monovalent mRNA vaccines against COVID–19–associated hospitalization among immunocompetent adults during BA.1/BA.2 and BA.4/BA.5 predominant periods of SARS–CoV–2 Omicron variant in the United States—IVY Network, 18 States, December 26, 2021–August 31, 2022. MMWR Morb Mortal Wkly Rep. 2022;71(42):1327–1334. doi: 10.15585/mmwr.mm7142a3.

140.  Andrews N, Stowe J, Kirsebom F, et al. Covid–19 Vaccine Effectiveness against the Omicron (B.1.1.529) Variant. N Engl J Med. 2022;386(16):1532–1546. doi: 10.1056/NEJMoa2119451. PMID: 35249272; PMCID: PMC8908811.

141.  Buchan SA, Chung H, Brown KA, et al. Estimated Effectiveness of COVID–19 Vaccines Against Omicron or Delta Symptomatic Infection and Severe Outcomes. JAMA Netw Open. 2022;5(9):e2232760. doi:10.1001/jamanetworkopen.2022.32760. PMID: 36136332; PMCID: PMC9500552.

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143.  Centers for Disease Control and Prevention. COVID–19 Vaccine Effectiveness Monthly Update. COVID Data Tracker. November 10, 2022. https://covid.cdc.gov/​covid-data-tracker/​#vaccine-effectiveness.

144.  Chalkias S, Harper C, Vrbicky K, et al. A Bivalent Omicron-Containing Booster Vaccine Against COVID–19. N Engl J Med. 2022 Oct 6;387(14):1279–1291. doi: 10.1056/NEJMoa2208343. PMID: 36112399; PMCID: PMC9511634.

145.  Tan, S.T., Kwan, A.T., Rodríguez-Barraquer, I. et al. Infectiousness of SARS–CoV–2 breakthrough infections and reinfections during the Omicron wave. Nat Med 29, 358–365 (2023). https://doi.org/​10.1038/​s41591-022-02138-x.

146.  Centers for Disease Control and Prevention. COVID–19 Vaccinations in the United States. COVID Data Tracker. https://covid.cdc.gov/​covid-data-tracker/​#vaccinations_​vacc-people-booster-percent-pop5.

147.  Centers for Disease Control and Prevention. COVID–19 Vaccination Age and Sex Trends in the United States, National and Jurisdictional. https://data.cdc.gov/​Vaccinations/​COVID-19-Vaccination-Age-and-Sex-Trends-in-the-Uni/​5i5k-6cmh.

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151.  Saelee R, Zell E, Murthy BP, et al. Disparities in COVID–19 Vaccination Coverage Between Urban and Rural Counties—United States, December 14, 2020–January 31, 2022. MMWR Morb Mortal Wkly Rep. 2022;71:335–340. doi: 10.15585/mmwr.mm7109a2.

152.  Sun Y, Monnat SM. Rural-Urban and Within-Rural Differences in COVID–19 Vaccination Rates. J Rural Health. 2022;38(4):916–922. doi: 10.1111/jrh.12625. PMID: 34555222; PMCID: PMC8661570.

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162.  The definition of “up to date” may change based on CDC's latest guidelines and can be found on the CDC web page, “Stay Up to Date with COVID–19 Vaccines Including Boosters,” at https://www.cdc.gov/​coronavirus/​2019-ncov/​vaccines/​stay-up-to-date.html (updated January 9, 2023).

163.   Patient-Resident-COVID-Vaccine-Draft-Specs.pdf. https://www.cms.gov/​medicare/​quality-initiatives-patient-assessment-instruments/​nursinghomequalityinits/​skilled-nursing-facility-quality-reporting-program/​snf-quality-reporting-program-measures-and-technical-information.

164.  Schreiber M, Richards AC, Moody-Williams J, Fleisher LA. The CMS National Quality Strategy: A Person-centered Approach to Improving Quality. Centers for Medicare & Medicaid ServicesBblog. June 6, 2022. https://www.cms.gov/​blog/​cms-national-quality-strategy-person-centered-approach-improving-quality.

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166.  Centers for Medicare & Medicaid Services. Minimum Data Set (MDS) 3.0 Technical Information. Effective October 1, 2020. https://www.cms.gov/​medicare/​quality-initiatives-patient-assessment-instruments/​nursinghomequalityinits/​nhqimds30technicalinformation.

167.  HealthMeasures. List of Adult Measures: Available Neuro-QoL^TM Measures for Adult Self-Report. https://www.healthmeasures.net/​explore-measurement-systems/​neuro-qol/​intro-to-neuro-qol/​list-of-adult-measures.

168.  HealthMeasures. List of Adult Measures: Available PROMIS® Measures for Adults. https://www.healthmeasures.net/​explore-measurement-systems/​promis/​intro-to-promis/​list-of-adult-measures.

169.  Figueroa JF, Phelan J, Orav EJ, Patel V, Jha AK. Association of Mental Health Disorders with Health Care Spending in the Medicare Population. JAMA Netw Open. 2020;3(3):e201210. doi: 10.1001/jamanetworkopen.2020.1210. PMID: 32191329; PMCID: PMC7082719.

170.  Parish WJ, Mark TL, Weber EM, Steinberg DG. Substance Use Disorders Among Medicare Beneficiaries: Prevalence, Mental and Physical Comorbidities, and Treatment Barriers. Am J Prev Med. 2022 Aug;63(2):225–232. doi: 10.1016/j.amepre.2022.01.021. PMID: 35331570.

171.  Centers for Medicare & Medicaid Services. 2021 National Impact Assessment of the Centers for Medicare & Medicaid Services (CMS) Quality Measures Report. June 2021. https://www.cms.gov/​files/​document/​2021-national-impact-assessment-report.pdf.

172.  Depression Screening Conducted and Follow-Up Plan Documented. https://cmit.cms.gov/​cmit/​#/​MeasureView?​variantId=​3102&​sectionNumber=​1.

173.  Agency for Healthcare Research and Quality. CAHPS Mental Health Care Surveys. May 2022. https://www.ahrq.gov/​cahps/​surveys-guidance/​echo/​index.html.

174.  HealthMeasures. Intro to PROMIS®. January 10, 2023. https://www.healthmeasures.net/​explore-measurement-systems/​promis/​intro-to-promis.

175.  HealthMeasures. NIH Toolbox. February 9, 2023. https://www.healthmeasures.net/​explore-measurement-systems/​nih-toolbox.

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178.  Substance Abuse and Mental Health Services Administration. Resources for Screening, Brief Intervention, and Referral to Treatment (SBIRT). Available at https://www.samhsa.gov/​sbirt/​resources.

179.  Agency for Healthcare Research and Quality. CAHPS Nursing Home Surveys. Content last reviewed April 2020. https://www.ahrq.gov/​cahps/​surveys-guidance/​nh/​index.html.

180.  In addition to the Discharged Resident Survey, Nursing Home CAHPS includes two other instruments, a Long-Stay Survey for Residents with a length of stay of 100 days or more, and a Family Member survey.

181.  Centers for Medicare & Medicaid Services. Health Equity. https://www.cms.gov/​pillar/​health-equity. Accessed February 1, 2023.

182.  Centers for Medicare & Medicaid Services. CMS Framework for Health Equity 2022–2032. https://www.cms.gov/​files/​document/​cms-framework-health-equity-2022.pdf.

183.  Executive Order 13985, “Advancing Racial Equity and Support for Underserved Communities Through the Federal Government,” can be found at https://www.whitehouse.gov/​briefing-room/​presidential-actions/​2021/​01/​20/​executive-order-advancing-racial-equity-and-support-for-underserved-communities-through-the-federal-government/​.

184.  Centers for Medicare & Medicaid Services. What Is the CMS Quality Strategy? https://www.cms.gov/​Medicare/​Quality-Initiatives-Patient-Assessment-Instruments/​Value-Based-Programs/​CMS-Quality-Strategy.

185.  Turner A. The Business Case for Racial Equity: A Strategy for Growth. April 24, 2018. W.K. Kellogg Foundation and Altarum. https://altarum.org/​RacialEquity2018.

186.  Agency for Healthcare Research and Quality. 2022 National Healthcare Quality and Disparities Report. Content last reviewed November 2022. https://www.ahrq.gov/​research/​findings/​nhqrdr/​nhqdr22/​index.html.

187.  Agency for Healthcare Research and Quality. 2022 National Healthcare Quality and Disparities Report. November 2022. https://www.ahrq.gov/​research/​findings/​nhqrdr/​nhqdr22/​index.html.

188.  Agency for Healthcare Research and Quality. 2022 National Healthcare Quality and Disparities Report. Content last reviewed November 2022. https://www.ahrq.gov/​research/​findings/​nhqrdr/​nhqdr22/​index.html.

189.  World Health Organization. Social Determinants of Health. https://www.who.int/​westernpacific/​healthtopics/​social-determinants-of-health.

190.  Jacobs DB, Schreiber M, Seshamani M, Tsai D, Fowler E, Fleisher LA. Aligning Quality Measures across CMS—The Universal Foundation. N Engl J Med. 2023 Mar 2;338:776–779. doi: 10.1056/NEJMp2215539. PMID: 36724323.

191.  Draft CoreQ: SS DC Survey Protocols and Guidelines Manual. Chapter III. CoreQ Survey Participation Requirements. Available on the SNF QRP Measures and Technical Information web page at https://www.cms.gov/​medicare/​quality-initiatives-patient-assessment-instruments/​nursinghomequalityinits/​skilled-nursing-facility-quality-reporting-program/​snf-quality-reporting-program-measures-and-technical-information.

192.  Draft CoreQ: SS DC Survey Protocols and Guidelines Manual. Available on the SNF QRP Measures and Technical Information web page at https://www.cms.gov/​medicare/​quality-initiatives-patient-assessment-instruments/​nursinghomequalityinits/​skilled-nursing-facility-quality-reporting-program/​snf-quality-reporting-program-measures-and-technical-information.

193.  There are 26 weeks in the period July 1, 2024 and December 31, 2024. The threshold of a minimum of 75 percent of weekly resident information files is applied first, meaning that a SNF must submit a minimum of 20 resident information files (26 × 0.75 = 19.5, rounded up to 20). The threshold of 90 percent for complete and accurate resident information files is applied second, meaning that a minimum of 18 submitted weekly resident information files must be complete and accurate (20 × 0.9 = 18).

194.  There are 52 weeks in the period January 1, 2025 to December 31, 2025. The threshold of a minimum of 75 percent of weekly resident information files is applied first, meaning that a SNF must submit a minimum of 39 resident information files (52 × 0.75 = 39). The threshold of 90 percent for complete and accurate resident information files is applied second, meaning that a minimum of 35 submitted weekly resident information files must be complete and accurate (39 × 0.9 = 35.1, rounded down).

195.  The SNF QRP Reconsideration and Exception & Extension web page is available at https://www.cms.gov/​Medicare/​Quality-Initiatives-Patient-Assessment-Instruments/​NursingHomeQualityInits/​Skilled-Nursing-Facility-Quality-Reporting-Program/​SNF-QR-Reconsideration-and-Exception-and-Extension.

196.  Draft CoreQ: SS DC Survey Protocols and Guidelines Manual. Chapter X. SNF CoreQ Survey Website Reports. Available on the SNF QRP Measures and Technical Information web page at https://www.cms.gov/​medicare/​quality-initiatives-patient-assessment-instruments/​nursinghomequalityinits/​skilled-nursing-facility-quality-reporting-program/​snf-quality-reporting-program-measures-and-technical-information.

197.   COVID–19 Vaccine: Percent of Patients/Residents Who Are Up to Date Draft Measure Specifications is available at https://www.cms.gov/​files/​document/​patient-resident-covid-vaccine-draft-specs.pdf.

198.  80 FR 22077; 80 FR 46458.

199.  The SNF QRP Measures and Technical Information page is available at https://www.cms.gov/​Medicare/​Quality-Initiatives-Patient-Assessment-Instruments/​NursingHomeQualityInits/​Skilled-Nursing-Facility-Quality-Reporting-Program/​SNF-Quality-Reporting-Program-Measures-and-Technical-Information.

200.  2022 Measures Under Consideration Spreadsheet available at https://mmshub.cms.gov/​sites/​default/​files/​2022-MUC-List.xlsx.

201.  Centers for Medicare and Medicaid Services. 2001 Report to Congress: Appropriateness of Minimum Nurse Staffing Ratios in Nursing Homes, Phase II. Baltimore, MD: Centers for Medicare and Medicaid Services. http://phinational.org/​wp-content/​uploads/​legacy/​clearinghouse/​PhaseIIVolumeIofIII.pdf.

202.  Institute of Medicine. Nursing Staff in Hospitals and Nursing Homes: Is It Adequate? Washington, DC: National Academy Press; 1996.

203.  “To Advance Information on Quality of Care, CMS Makes Nursing Home Staffing Data Available | CMS.” Accessed December 22, 2022. https://www.cms.gov/​newsroom/​press-releases/​advance-information-quality-care-cms-makes-nursing-home-staffing-data-available.

204.  Zheng Q, Williams CS, Shulman ET, White AJ Association between staff turnover and nursing home quality—evidence from payroll-based journal data. Journal of the American Geriatrics Society. May 2022. doi:10.1111/jgs.17843.

205.  Bostick JE, Rantz MJ, Flesner MK, Riggs CJ Systematic review of studies of staffing and quality in nursing homes. J Am Med Dir Assoc. 2006;7:366–376. https://pubmed.ncbi.nlm.nih.gov/​16843237/​.

206.  Backhaus R, Verbeek H, van Rossum E, Capezuti E, Hamer JPH Nursing staffing impact on quality of care in nursing homes: a systemic review of longitudinal studies. J Am Med Dir Assoc. 2014;15(6):383–393. https://pubmed.ncbi.nlm.nih.gov/​24529872/​.

207.  Spilsbury K., Hewitt C., Stirk L., Bowman C. The relationship between nurse staffing and quality of care in nursing homes: a systematic review. Int J Nurs Stud. 2011; 48(6):732–750. https://pubmed.ncbi.nlm.nih.gov/​21397229/​.

208.  Castle N. Nursing home caregiver staffing levels and quality of care: a literature review. J Appl Gerontol. 2008;27:375–405. https://doi.org/​10.1177%2F0733464808321596.

209.  Spilsbury et al.

210.  Castle NG, Engberg J. Staff turnover and quality of care in nursing homes. Med Care. 2005 Jun;43(6):616–26. doi: 10.1097/01.mlr.0000163661.67170.b9. PMID: 15908857.

211.  Zheng, Q, Williams, CS, Shulman, ET, White, AJ Association between staff turnover and nursing home quality—evidence from payroll-based journal data. J Am Geriatr Soc. 2022; 70(9): 2508–2516. doi:10.1111/jgs.17843.

212.  Ibid.

213.  Centers for Medicare and Medicaid Services. 2001 Report to Congress: Appropriateness of Minimum Nurse Staffing Ratios in Nursing Homes, Phase II. Baltimore, MD: Centers for Medicare and Medicaid Services. http://phinational.org/​wp-content/​uploads/​legacy/​clearinghouse/​PhaseIIVolumeIofIII.pdf.

214.  Loomer, L, Grabowski, DC, Yu, H, & Gandhi, A. (2021). Association between nursing home staff turnover and infection control citations. Health Services Research. https://doi.org/​10.1111/​1475-6773.13877.

215.  Loomer, L., Grabowski, D.C., Yu, H., & Gandhi, A. (2021). Association between nursing home staff turnover and infection control citations. Health Services Research. https://doi.org/​10.1111/​1475-6773.13877.

216.  National Academies of Sciences, Engineering, and Medicine. 2022. The National Imperative to Improve Nursing Home Quality: Honoring Our Commitment to Residents, Families, and Staff. Washington, DC: The National Academies Press. https://doi.org/​10.17226/​26526.

217.  National Academies of Sciences, Engineering, and Medicine, 2022.

218.  The White House. (2022, February 28). FACT SHEET: Protecting Seniors by Improving Safety and Quality of Care in the Nation's Nursing Homes. https://www.whitehouse.gov/​briefing-room/​statements-releases/​2022/​02/​28/​fact-sheet-protecting-seniors-and-people-with-disabilities-by-improving-safety-and-quality-of-care-in-the-nations-nursing-homes/​.

219.  The White House. (2021, October 21). FACT SHEET: Biden-Harris Administration Announces New Steps to Improve Quality of Nursing Homes. https://www.whitehouse.gov/​briefing-room/​statements-releases/​2022/​10/​21/​fact-sheet-biden-harris-administration-announces-new-steps-to-improve-quality-of-nursing-homes/​.

220.   https://www.cms.gov/​Medicare/​Provider-Enrollment-and-Certification/​SurveyCertificationGenInfo/​Downloads/​QSO18-17-NH.pdf.

221.  Zheng, Q, Williams, CS, Shulman, ET, White, AJ Association between staff turnover and nursing home quality—evidence from payroll-based journal data. J Am Geriatr Soc. 2022; 70(9): 2508–2516.

222.  2022 Measures Under Consideration Spreadsheet available at https://mmshub.cms.gov/​sites/​default/​files/​2022-MUC-List.xlsx.

223.  The baseline quarter is specific to this measure calculation and not related to the SNF VBP Program's measure baseline period, which is part of the performance standards used to score the measure. The baseline quarter is the quarter prior to the first quarter of either the baseline period or the performance period for a program year.

224.  Burns E, Kakara R. Deaths from Falls Among Persons Aged ≥65 Years—United States, 2007–2016. MMWR Morb Mortal Wkly Rep 2018;67:509–514. DOI: http://dx.doi.org/​10.15585/​mmwr.mm6718a1externalicon.

225.  Ibid.

226.  Ibid.

227.  The Falls Management Program: A Quality Improvement Initiative for Nursing Facilities: Chapter 1. introduction and program overview. Agency for Healthcare Research and Quality. https://www.ahrq.gov/​patient-safety/​settings/​long-term-care/​resource/​injuries/​fallspx/​man1.html. Published December 2017. Accessed December 13, 2022.

228.  The Falls Management Program: A Quality Improvement Initiative for Nursing Facilities: Chapter 1. Introduction and Program Overview. Agency for Healthcare Research and Quality. https://www.ahrq.gov/​patient-safety/​settings/​long-term-care/​resource/​injuries/​fallspx/​man1.html. Published December 2017. Accessed December 13, 2022.

229.  Bastami M, Azadi A. Effects of a Multicomponent Program on Fall Incidence, Fear of Falling, and Quality of Life among Older Adult Nursing Home Residents. Ann Geriatr Med Res. 2020;24(4):252–258. doi:10.4235/agmr.20.0044.

230.  Cost of older adult falls. Centers for Disease Control and Prevention. https://www.cdc.gov/​falls/​data/​fall-cost.html. Published July 9, 2020. Accessed December 13, 2022.

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232.  Quigley PA, Campbell RR, Bulat T, Olney RL, Buerhaus P, Needleman J. Incidence and cost of serious fall-related injuries in nursing homes. Clin Nurs Res. Feb 2012;21(1):10–23.

233.  Morse, JM. Enhancing the safety of hospitalization by reducing patient falls. Am J Infect Control 2002; 30(6): 376–80.

234.  Cost of older adult falls. Centers for Disease Control and Prevention. https://www.cdc.gov/​falls/​data/​fall-cost.html. Published July 9, 2020. Accessed December 13, 2022.

235.  Galik, E, Resnick, B, Hammersla, M, & Brightwater, J (2014). Optimizing function and physical activity among nursing home residents with dementia: testing the impact of function-focused care. Gerontologist 54(6), 930–943. https://doi.org/​10.1093/​geront/​gnt108.

236.  Broe KE, Chen TC, Weinberg J, Bischoff-Ferrari HA, Holick MF, Kiel DP. A higher dose of vitamin d reduces the risk of falls in nursing home residents: a randomized, multiple-dose study. J Am Geriatr Soc. 2007;55(2):234–239. doi:10.1111/j.1532–5415.2007.01048.x.

237.  Zhang N, Lu SF, Zhou Y, Zhang B, Copeland L, Gurwitz JH. Body Mass Index, Falls, and Hip Fractures Among Nursing Home Residents. J Gerontol A Biol Sci Med Sci. 2018;73(10):1403–1409. doi:10.1093/gerona/gly039.

238.  Fernando E, Fraser M, Hendriksen J, Kim CH, Muir-Hunter SW. Risk Factors Associated with Falls in Older Adults with Dementia: A Systematic Review. Physiother Can. 2017;69(2):161–170. doi:10.3138/ptc.2016–14.

239.  Grundstrom AC, Guse CE, Layde PM. Risk factors for falls and fall-related injuries in adults 85 years of age and older. Arch Gerontol Geriatr. 2012;54(3):421–428. doi:10.1016/j.archger.2011.06.008.

240.  Morris JN, Moore T, Jones R, et al. Validation of long-term and post-acute care quality indicators. CMS Contract No: 500–95–0062.

241.  Chen XL, Liu YH, Chan DK, Shen Q, Van Nguyen H. Chin Med J (Engl). Characteristics associated with falls among the elderly within aged care wards in a tertiary hospital: A Retrospective. 2010 Jul; 123(13):1668–72.

242.  Fonad E, Wahlin TB, Winblad B, Emami A, Sandmark H. Falls and fall risk among nursing home residents. J Clin Nurs. 2008 Jan; 17(1):126–34.

243.  Lee JE, Stokic DS. Risk factors for falls during inpatient rehabilitation. Am J Phys Med Rehabil. 2008 May; 87(5):341–50; quiz 351, 422.

244.  Centers for Medicare & Medicaid Services. Meaningful Measures Framework. Available at https://www.cms.gov/​Medicare/​Quality-Initiatives-Patient-Assessment-Instruments/​QualityInitiativesGenInfo/​CMS-Quality-Strategy.

245.  Gulka, HJ, Patel, V, Arora, T, McArthur, C, & Iaboni, A (2020). Efficacy and generalizability of falls prevention interventions in nursing homes: A systematic review and meta-analysis. Journal of the American Medical Directors Association, 21(8), P1024–1035.E4. https://doi.org/​10.1016/​j.jamda.2019.11.012.

246.  Tricco, AC, Thomas, SM, Veroniki, AA, Hamid, JS, Cogo, E, Strifler, L, Khan, PA, Robson, R, Sibley, KM, MacDonald, H, Riva, JJ, Thavorn, K, Wilson, C, Holroyd-Leduc, J, Kerr, GD, Feldman, F, Majumdar, SR, Jaglal, SB, Hui, W, & Straus, SE (2017). Comparisons of interventions for preventing falls in older adults: A systematic review and meta-analysis. Journal of the American Medical Association, 318(17), 1687–1699. https://doi.org/​10.1001/​jama.2017.15006.

247.  Vlaeyen, E, Coussement, J, Leysens, G, Van der Elst, E, Delbaere, K, Cambier, D, Denhaerynck, K, Goemaere, S, Wertelaers, A, Dobbels, F, Dejaeger, E, & Milisen, K (2015). Characteristics and effectiveness of fall prevention programs in nursing homes: A systematic review and meta-analysis of randomized control trials. Journal of the American Geriatrics Society, 6(3), 211–21. https://doi.org/​10.1111/​jgs.13254.

248.  Gulka, HJ, Patel, V, Arora, T, McArthur, C, & Iaboni, A (2020). Efficacy and generalizability of falls prevention interventions in nursing homes: A systematic review and meta-analysis. Journal of the American Medical Directors Association, 21(8), P1024–1035.E4. https://doi.org/​10.1016/​j.jamda.2019.11.012.

249.  Crandall, M, Duncan, T, Mallat, A, Greene, W, Violano, P, & Christmas, B (2016). Prevention of fall-related injuries in the elderly: An eastern association for the surgery of trauma practice management guideline. Journal of Trauma and Acute Care Surgery, 81(1), 196–206. https://doi.org/​10.1097/​TA.0000000000001025.

250.  Vlaeyen, E, Stas, J, Leysens, G, Van der Elst, E, Janssens, E, Dejaeger, E, Dobbels, F, & Milisen, K (2017). Implementation of fall prevention in residential care facilities: A systematic review of barriers and facilitators. International Journal of Nursing Studies, 70, 110–121. https://doi.org/​10.1016/​j.ijnurstu.2017.02.002.

251.  Ibid.

252.  Gulka, HJ, Patel, V, Arora, T, McArthur, C, & Iaboni, A (2020). Efficacy and generalizability of falls prevention interventions in nursing homes: A systematic review and meta-analysis. Journal of the American Medical Directors Association, 21(8), P1024–1035.E4. https://doi.org/​10.1016/​j.jamda.2019.11.012.

253.  Tricco, AC, Thomas, SM, Veroniki, AA, Hamid, JS, Cogo, E, Strifler, L, Khan, PA, Robson, R, Sibley, KM, MacDonald, H, Riva, JJ, Thavorn, K, Wilson, C, Holroyd-Leduc, J, Kerr, GD, Feldman, F, Majumdar, SR, Jaglal, SB, Hui, W, & Straus, SE (2017). Comparisons of interventions for preventing falls in older adults: A systematic review and meta-analysis. Journal of the American Medical Association, 318(17), 1687–1699. https://doi.org/​10.1001/​jama.2017.15006.

254.  2022 Measures Under Consideration Spreadsheet available at https://mmshub.cms.gov/​sites/​default/​files/​2022-MUC-List.xlsx.

255.  This measure was submitted to the Measure Under Consideration (MUC) List as the Cross-Setting Discharge Function Score. Subsequent to the MAP workgroup meetings, the measure developer modified the name.

256.  High KP, Zieman S, Gurwitz J, Hill C, Lai J, Robinson T, Schonberg M, Whitson H. Use of Functional Assessment to Define Therapeutic Goals and Treatment. J Am Geriatr Soc. 2019 Sep;67(9):1782–1790. doi: 10.1111/jgs.15975. Epub 2019 May 13. PMID: 31081938; PMCID: PMC6955596.

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261.  Hong I, Goodwin JS, Reistetter TA, Kuo YF, Mallinson T, Karmarkar A, Lin YL, Ottenbacher KJ. Comparison of Functional Status Improvements Among Patients With Stroke Receiving Postacute Care in Inpatient Rehabilitation vs Skilled Nursing Facilities. JAMA Netw Open. 2019 Dec 2;2(12):e1916646. doi: 10.1001/jamanetworkopen.2019.16646. PMID: 31800069; PMCID: PMC6902754.

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