2023-06968. Medicare Program; Inpatient Rehabilitation Facility Prospective Payment System for Federal Fiscal Year 2024 and Updates to the IRF Quality Reporting Program

AGENCY:

Centers for Medicare & Medicaid Services (CMS), HHS.

ACTION:

Proposed rule.

SUMMARY:

This proposed rule proposes updates to the prospective payment rates for inpatient rehabilitation facilities (IRFs) for Federal fiscal year (FY) 2024. As required by statute, this proposed rule includes the proposed classification and weighting factors for the IRF prospective payment system's case-mix groups and a description of the methodologies and data used in computing the proposed prospective payment rates for FY 2024. It also proposes to rebase and revise the IRF market basket to reflect a 2021 base year. It also would modify the regulation regarding when IRF units can become excluded and paid under the IRF PPS. This proposed rule also includes updates for the IRF Quality Reporting Program (QRP).

DATES:

To be assured consideration, comments must be received at one of the addresses provided below, no later than 5 p.m. on June 2, 2023.

ADDRESSES:

In commenting, please refer to file code CMS–1781–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–1781–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–1781–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:

Gwendolyn Johnson, (410) 786–6954, for general information.

Catie Cooksey, (410) 786–0179, for information about the IRF payment policies and payment rates.

Kim Schwartz, (410) 786–2571, and Gwendolyn Johnson, (410) 786–6954, for information about the IRF coverage policies.

Ariel Cress, (410) 786–8571, for information about the IRF quality reporting program.

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 Information Through the Internet on the CMS Website

The IRF prospective payment system (IRF PPS) Addenda along with other supporting documents and tables referenced in this proposed rule are available through the internet on the CMS website at https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​InpatientRehabFacPPS.

We note that prior to 2020, each rule or notice issued under the IRF PPS has included a detailed reiteration of the various regulatory provisions that have affected the IRF PPS over the years. That discussion, along with detailed background information for various other aspects of the IRF PPS, is now available on the CMS website at https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​InpatientRehabFacPPS.

I. Executive Summary

A. Purpose

This rulemaking proposes updates to the prospective payment rates for IRFs for FY 2024 (that is, for discharges occurring on or after October 1, 2023, and on or before September 30, 2024) as required under section 1886(j)(3)(C) of the Social Security Act (the Act). As required by section 1886(j)(5) of the Act, this proposed rule includes the classification and weighting factors for the IRF PPS's case-mix groups (CMGs) and a description of the methodologies and data used in computing the prospective payment rates for FY 2024. It also proposes to rebase and revise the IRF market basket to reflect a 2021 base year. It also proposes to modify the regulation governing when an IRF unit can be excluded and paid under the IRF PPS. This proposed rule includes IRF QRP proposals for the FY 2025 IRF QRP and FY 2026 IRF QRP. This proposed rule would add two new measures to the IRF QRP, remove three measures from the IRF QRP, and modify one measure in the IRF QRP. This proposed rule also proposes to begin public reporting of four measures. In addition, this proposed rule includes an update on the Centers for Medicare and Medicaid Services' (CMS') efforts to close the health equity gap and requests information on principles CMS would use to select and prioritize IRF QRP quality measures in future years.

B. Summary of Major Provisions

In this proposed rule, we use the methods described in the FY 2023 IRF PPS final rule (87 FR 47038) to update the prospective payment rates for FY 2024 using updated FY 2022 IRF claims and the most recent available IRF cost report data, which is FY 2021 IRF cost report data. It also proposes to rebase and revise the IRF market basket to reflect a 2021 base year. It also proposes to modify the regulation governing when an IRF unit can be excluded and paid under the IRF PPS.

Beginning with the FY 2025 IRF QRP, we propose to modify the COVID–19 Vaccination Coverage among Healthcare Personnel measure, adopt the Discharge Function Score measure, and 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 measure, the IRF Functional Outcome Measure: Change in Self-Care Score for Medical Rehabilitation Patients (NQF #2633) and the Functional Outcome Measure: Change in Mobility Score for Medical Rehabilitation Patients (NQF #2634) measures. Beginning with the FY 2026 IRF QRP, we propose to adopt the COVID–19 Vaccine: Percent of Patients/Residents Who Are Up to Date measure. This proposed rule also proposes to begin public reporting of the Transfer of Health Information to the Patient-Post-Acute Care (PAC) and Transfer of Health Information to the Provider-PAC measures, the Discharge Function Score measure, and the COVID–19 Vaccine: Percent of Patients/Residents Who Are Up to Date measure. Finally, we are seeking input from interested parties on principles for selecting and prioritizing IRF QRP quality measures and concepts, and we provide an update on our continued efforts to close the health equity gap.

C. Summary of Impact

Table 1—Cost and Benefit

Provision description	Transfers/costs
FY 2024 IRF PPS payment rate update	The overall economic impact of this final rule is an estimated $335 million in increased payments from the Federal Government to IRFs during FY 2024.
FY 2025 through FY 2026 IRF QRP changes	The overall economic impact of this final rule is an estimated increase in cost to IRFs of $31,412.56 beginning with the FY 2025 IRF QRP.

II. Background

A. Statutory Basis and Scope for IRF PPS Provisions

Section 1886(j) of the Act provides for the implementation of a per-discharge PPS for inpatient rehabilitation hospitals and inpatient rehabilitation units of a hospital (collectively, hereinafter referred to as IRFs). Payments under the IRF PPS encompass inpatient operating and capital costs of furnishing covered rehabilitation services (that is, routine, ancillary, and capital costs), but not direct graduate medical education costs, costs of approved nursing and allied health education activities, bad debts, and other services or items outside the scope of the IRF PPS. A complete discussion of the IRF PPS provisions appears in the original FY 2002 IRF PPS final rule (66 FR 41316) and the FY 2006 IRF PPS final rule (70 FR 47880) and we provided a general description of the IRF PPS for FYs 2007 through 2019 in the FY 2020 IRF PPS final rule (84 FR 39055 through 39057). A general description of the IRF PPS for FYs 2020 through 2022, along with detailed background information for various other aspects of the IRF PPS, is now available on the CMS website at https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​InpatientRehabFacPPS.

Under the IRF PPS from FY 2002 through FY 2005, the prospective payment rates were computed across 100 distinct CMGs, as described in the FY 2002 IRF PPS final rule (66 FR 41316). We constructed 95 CMGs using rehabilitation impairment categories (RICs), functional status (both motor and cognitive), and age (in some cases, cognitive status and age may not be a factor in defining a CMG). In addition, we constructed five special CMGs to account for very short stays and for patients who expire in the IRF.

For each of the CMGs, we developed relative weighting factors to account for a patient's clinical characteristics and expected resource needs. Thus, the weighting factors accounted for the relative difference in resource use across all CMGs. Within each CMG, we created tiers based on the estimated effects that certain comorbidities would have on resource use.

We established the Federal PPS rates using a standardized payment conversion factor (formerly referred to as the budget-neutral conversion factor). For a detailed discussion of the budget-neutral conversion factor, please refer to our FY 2004 IRF PPS final rule (68 FR 45684 through 45685). In the FY 2006 IRF PPS final rule (70 FR 47880), we discussed in detail the methodology for determining the standard payment conversion factor.

We applied the relative weighting factors to the standard payment conversion factor to compute the unadjusted prospective payment rates under the IRF PPS from FYs 2002 through 2005. Within the structure of the payment system, we then made adjustments to account for interrupted stays, transfers, short stays, and deaths. Finally, we applied the applicable adjustments to account for geographic variations in wages (wage index), the percentage of low-income patients, location in a rural area (if applicable), and outlier payments (if applicable) to the IRFs' unadjusted prospective payment rates.

For cost reporting periods that began on or after January 1, 2002, and before October 1, 2002, we determined the final prospective payment amounts using the transition methodology prescribed in section 1886(j)(1) of the Act. Under this provision, IRFs transitioning into the PPS were paid a blend of the Federal IRF PPS rate and the payment that the IRFs would have received had the IRF PPS not been implemented. This provision also allowed IRFs to elect to bypass this blended payment and immediately be paid 100 percent of the Federal IRF PPS rate. The transition methodology expired as of cost reporting periods beginning on or after October 1, 2002 (FY 2003), and payments for all IRFs now consist of 100 percent of the Federal IRF PPS rate.

Section 1886(j) of the Act confers broad statutory authority upon the Secretary to propose refinements to the IRF PPS. In the FY 2006 IRF PPS final rule (70 FR 47880) and in correcting amendments to the FY 2006 IRF PPS final rule (70 FR 57166), we finalized a number of refinements to the IRF PPS case-mix classification system (the CMGs and the corresponding relative weights) and the case-level and facility-level adjustments. These refinements included the adoption of the Office of Management and Budget's (OMB's) Core-Based Statistical Area (CBSA) market definitions; modifications to the CMGs, tier comorbidities; and CMG relative weights, implementation of a new teaching status adjustment for IRFs; rebasing and revising the market basket used to update IRF payments, and updates to the rural, low-income percentage (LIP), and high-cost outlier adjustments. Beginning with the FY 2006 IRF PPS final rule (70 FR 47908 through 47917), the market basket used to update IRF payments was a market basket reflecting the operating and capital cost structures for freestanding IRFs, freestanding inpatient psychiatric facilities (IPFs), and long-term care hospitals (LTCHs) (hereinafter referred to as the rehabilitation, psychiatric, and long-term care (RPL) market basket). Any reference to the FY 2006 IRF PPS final rule in this final rule also includes the provisions effective in the correcting amendments. For a detailed discussion of the final key policy changes for FY 2006, please refer to the FY 2006 IRF PPS final rule.

The regulatory history previously included in each rule or notice issued under the IRF PPS, including a general description of the IRF PPS for FYs 2007 through 2020, is available on the CMS website at https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​InpatientRehabFacPPS.

In late 2019,^[1] the United States began responding to an outbreak of a virus named “SARS-CoV–2” and the disease it causes, which is named “coronavirus disease 2019” (abbreviated “COVID–19”). Due to our prioritizing efforts in support of containing and combatting the Public Health Emergency (PHE) for COVID–19, and devoting significant resources to that end, we published two interim final rules with comment period affecting IRF payment and conditions for participation. The interim final rule with comment period (IFC) entitled, “Medicare and Medicaid Programs; Policy and Regulatory Revisions in Response to the COVID–19 Public Health Emergency,” published on April 6, 2020 (85 FR 19230) (hereinafter referred to as the April 6, 2020 IFC), included certain changes to the IRF PPS medical supervision requirements at 42 CFR 412.622(a)(3)(iv) and 412.29(e) during the PHE for COVID–19. In addition, in the April 6, 2020 IFC, we removed the post-admission physician evaluation requirement at § 412.622(a)(4)(ii) for all IRFs during the PHE for COVID–19. In the FY 2021 IRF PPS final rule, to ease documentation and administrative burden, we also removed the post-admission physician evaluation documentation requirement at 42 CFR 412.622(a)(4)(ii) permanently beginning in FY 2021.

A second IFC entitled, “Medicare and Medicaid Programs, Basic Health Program, and Exchanges; Additional Policy and Regulatory Revisions in Response to the COVID–19 Public Health Emergency and Delay of Certain Reporting Requirements for the Skilled Nursing Facility Quality Reporting Program” was published on May 8, 2020 (85 FR 27550) (hereinafter referred to as the May 8, 2020 IFC). Among other changes, the May 8, 2020 IFC included a waiver of the “3-hour rule” at § 412.622(a)(3)(ii) to reflect the waiver required by section 3711(a) of the Coronavirus Aid, Relief, and Economic Security Act (CARES Act) (Pub. L. 116–136, enacted on March 27, 2020). In the May 8, 2020 IFC, we also modified certain IRF coverage and classification requirements for freestanding IRF hospitals to relieve acute care hospital capacity concerns in States (or regions, as applicable) experiencing a surge during the PHE for COVID–19. In addition to the policies adopted in our IFCs, we responded to the PHE with numerous blanket waivers ^[2] and other flexibilities,^[3] some of which are applicable to the IRF PPS. CMS finalized these policies in the Calendar Year 2023 Hospital Outpatient Prospective Payment and Ambulatory Surgical Center Payment Systems final rule with comment period (87 FR 71748).

B. Provisions of the Patient Protection and the Affordable Care Act and the Medicare Access and CHIP Reauthorization Act of 2015 (MACRA) Affecting the IRF PPS in FY 2012 and Beyond

The Patient Protection and the Affordable Care Act (the Affordable Care Act or ACA) (Pub. L. 111–148) was enacted on March 23, 2010. The Health Care and Education Reconciliation Act of 2010 (Pub. L. 111–152), which amended and revised several provisions of the Patient Protection and Affordable Care Act, was enacted on March 30, 2010. In this proposed rule, we refer to the two statutes collectively as the “Patient Protection and Affordable Care Act” or “ACA”.

The ACA included several provisions that affect the IRF PPS in FYs 2012 and beyond. In addition to what was previously discussed, section 3401(d) of the ACA also added section 1886(j)(3)(C)(ii)(I) of the Act (providing for a “productivity adjustment” for FY 2012 and each subsequent FY). The productivity adjustment for FY 2024 is discussed in section V.D. of this proposed rule. Section 1886(j)(3)(C)(ii)(II) of the Act provides that the application of the productivity adjustment to the market basket update may result in an update that is less than 0.0 for a FY and in payment rates for a FY being less than such payment rates for the preceding FY.

Sections 3004(b) of the ACA and section 411(b) of the MACRA (Pub. L. 114–10, enacted on April 16, 2015) also addressed the IRF PPS. Section 3004(b) of ACA reassigned the previously designated section 1886(j)(7) of the Act to section 1886(j)(8) of the Act and inserted a new section 1886(j)(7) of the Act, which contains requirements for the Secretary to establish a QRP for IRFs. Under that program, data must be submitted in a form and manner and at a time specified by the Secretary. Beginning in FY 2014, section 1886(j)(7)(A)(i) of the Act requires the application of a 2-percentage point reduction to the market basket increase factor otherwise applicable to an IRF (after application of paragraphs (C)(iii) and (D) of section 1886(j)(3) of the Act) for a FY if the IRF does not comply with the requirements of the IRF QRP for that FY. Application of the 2-percentage point reduction may result in an update that is less than 0.0 for a FY and in payment rates for a FY being less than such payment rates for the preceding FY. Reporting-based reductions to the market basket increase factor are not cumulative; they only apply for the FY involved. Section 411(b) of the MACRA amended section 1886(j)(3)(C) of the Act by adding paragraph (iii), which required us to apply for FY 2018, after the application of section 1886(j)(3)(C)(ii) of the Act, an increase factor of 1.0 percent to update the IRF prospective payment rates.

C. Operational Overview of the Current IRF PPS

As described in the FY 2002 IRF PPS final rule (66 FR 41316), upon the admission and discharge of a Medicare Part A fee-for-service (FFS) patient, the IRF is required to complete the appropriate sections of a Patient Assessment Instrument (PAI), designated as the IRF–PAI. In addition, beginning with IRF discharges occurring on or after October 1, 2009, the IRF is also required to complete the appropriate sections of the IRF–PAI upon the admission and discharge of each Medicare Advantage (MA) patient, as described in the FY 2010 IRF PPS final rule (74 FR 39762 and 74 FR 50712). All required data must be electronically encoded into the IRF–PAI software product. Generally, the software product includes patient classification programming called the Grouper software. The Grouper software uses specific IRF–PAI data elements to classify (or group) patients into distinct CMGs and account for the existence of any relevant comorbidities.

The Grouper software produces a five-character CMG number. The first character is an alphabetic character that indicates the comorbidity tier. The last four characters are numeric characters that represent the distinct CMG number. A free download of the Grouper software is available on the CMS website at http://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​InpatientRehabFacPPS/​Software.html. The Grouper software is also embedded in the internet Quality Improvement and Evaluation System (iQIES) User tool available in iQIES at https://www.cms.gov/​medicare/​quality-safety-oversight-general-information/​iqies.

Once a Medicare Part A FFS patient is discharged, the IRF submits a Medicare claim as a Health Insurance Portability and Accountability Act of 1996 (HIPAA) (Pub. L. 104–191, enacted on August 21, 1996)—compliant electronic claim or, if the Administrative Simplification Compliance Act of 2002 (ASCA) (Pub. L. 107–105, enacted on December 27, 2002) permits, a paper claim (a UB–04 or a CMS–1450 as appropriate) using the five-character CMG number and sends it to the appropriate Medicare Administrative Contractor (MAC). In addition, once a MA patient is discharged, in accordance with the Medicare Claims Processing Manual, chapter 3, section 20.3 (Pub. 100–04), hospitals (including IRFs) must submit an informational-only bill (type of bill (TOB) 111), which includes Condition Code 04 to their MAC. This will ensure that the MA days are included in the hospital's Supplemental Security Income (SSI) ratio (used in calculating the IRF LIP adjustment) for FY 2007 and beyond. Claims submitted to Medicare must comply with both ASCA and HIPAA.

Section 3 of the ASCA amended section 1862(a) of the Act by adding paragraph (22), which requires the Medicare program, subject to section 1862(h) of the Act, to deny payment under Part A or Part B for any expenses for items or services for which a claim is submitted other than in an electronic form specified by the Secretary. Section 1862(h) of the Act, in turn, provides that the Secretary shall waive such denial in situations in which there is no method available for the submission of claims in an electronic form or the entity submitting the claim is a small provider. In addition, the Secretary also has the authority to waive such denial in such unusual cases as the Secretary finds appropriate. For more information, see the “Medicare Program; Electronic Submission of Medicare Claims” final rule (70 FR 71008). Our instructions for the limited number of Medicare claims submitted on paper are available at http://www.cms.gov/​manuals/​downloads/​clm104c25.pdf.

Section 3 of the ASCA operates in the context of the administrative simplification provisions of HIPAA, which include, among others, the requirements for transaction standards and code sets codified in 45 CFR part 160 and part 162, subparts A and I through R (generally known as the Transactions Rule). The Transactions Rule requires covered entities, including covered healthcare providers, to conduct covered electronic transactions according to the applicable transaction standards. (See the CMS program claim memoranda at http://www.cms.gov/​ElectronicBillingEDITrans/​ and listed in the addenda to the Medicare Intermediary Manual, Part 3, section 3600).

The MAC processes the claim through its software system. This software system includes pricing programming called the “Pricer” software. The Pricer software uses the CMG number, along with other specific claim data elements and provider-specific data, to adjust the IRF's prospective payment for interrupted stays, transfers, short stays, and deaths, and then applies the applicable adjustments to account for the IRF's wage index, percentage of low-income patients, rural location, and outlier payments. For discharges occurring on or after October 1, 2005, the IRF PPS payment also reflects the teaching status adjustment that became effective as of FY 2006, as discussed in the FY 2006 IRF PPS final rule (70 FR 47880).

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.^[4 5] 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.^[6] 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).^[7] 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.^[8] 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.^[9] 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) (Pub. L. 114–255, enacted December 13, 2016) required HHS and ONC to take steps to promote adoption and use of electronic health record (EHR) technology.^[10] 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 ^[11] and Common Agreement Version 1.^[12] 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.^[13] On February 13, 2023, HHS marked a new milestone during an event at HHS headquarters,^[14] 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.^[15] 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 IRFs.

III. Summary of Provisions of the Proposed Rule

In this proposed rule, we are proposing to update the IRF PPS for FY 2024 and the IRF QRP for FY 2025 and FY 2026.

The proposed policy changes and updates to the IRF prospective payment rates for FY 2024 are as follows:

• Update the CMG relative weights and average length of stay values for FY 2024, in a budget neutral manner, as discussed in section IV. of this proposed rule.
• Update the IRF PPS payment rates for FY 2024 by the market basket increase factor, based upon the most current data available, with a productivity adjustment required by section 1886(j)(3)(C)(ii)(I) of the Act, as described in section V. of this proposed rule.
• Rebase and revise the IRF market basket to reflect a 2021 base year, as discussed in section V. of this proposed rule.
• Update the FY 2024 IRF PPS payment rates by the FY 2024 wage index and the labor-related share in a budget-neutral manner, as discussed in section V. of this proposed rule.
• Describe the calculation of the IRF standard payment conversion factor for FY 2024, as discussed in section V. of this proposed rule.
• Update the outlier threshold amount for FY 2024, as discussed in section VI. of this proposed rule.
• Update the cost-to-charge ratio (CCR) ceiling and urban/rural average CCRs for FY 2024, as discussed in section VI. of this proposed rule.
• Describe the proposed modification to the regulation for IRF units to become excluded and paid under the IRF PPS as discussed in section VII. of this proposed rule.

We also propose updates to the IRF QRP and request information in section VIII. of the proposed rule as follows:

• Modify the COVID–19 Vaccination Coverage among Healthcare Personnel measure beginning with the FY 2025 IRF QRP.
• Adopt the Discharge Function Score measure beginning with the FY 2025 IRF QRP.
• 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 measure beginning with the FY 2025 IRF QRP.
• Remove the IRF Functional Outcome Measure: Change in Self-Care Score for Medical Rehabilitation Patients (NQF #2633) measure beginning with the FY 2025 IRF QRP.
• Remove the IRF Functional Outcome Measure: Change in Mobility Score for Medical Rehabilitation Patients (NQF #2634) measure beginning with the FY 2025 IRF QRP.
• Adopt the COVID–19 Vaccine: Percent of Patients/Residents Who Are Up to Date measure beginning with the FY 2026 IRF QRP.
• Request information on principles for selecting and prioritizing IRF QRP quality measures and concepts.
• Provide an update on our continued efforts to close the health equity gap.

IV. Proposed Update to the Case-Mix Group (CMG) Relative Weights and Average Length of Stay (ALOS) Values for FY 2024

As specified in § 412.620(b)(1), we calculate a relative weight for each CMG that is proportional to the resources needed by an average inpatient rehabilitation case in that CMG. For example, cases in a CMG with a relative weight of 2, on average, will cost twice as much as cases in a CMG with a relative weight of 1. Relative weights account for the variance in cost per discharge due to the variance in resource utilization among the payment groups, and their use helps to ensure that IRF PPS payments support beneficiary access to care, as well as provider efficiency.

In this proposed rule, we propose to update the CMG relative weights and ALOS values for FY 2024. Typically, we use the most recent available data to update the CMG relative weights and average lengths of stay. For FY 2024, we are proposing to use the FY 2022 IRF claims and FY 2021 IRF cost report data. These data are the most current and complete data available at this time. Currently, only a small portion of the FY 2022 IRF cost report data are available for analysis, but the majority of the FY 2022 IRF claims data are available for analysis. We are proposing that if more recent data became available after the publication of this proposed rule and before the publication of the final rule, we would use such data to determine the FY 2024 CMG relative weights and ALOS values in the final rule.

We are proposing to apply these data using the same methodologies that we have used to update the CMG relative weights and ALOS values each FY since we implemented an update to the methodology. The detailed CCR data from the cost reports of IRF provider units of primary acute care hospitals is used for this methodology, instead of CCR data from the associated primary care hospitals, to calculate IRFs' average costs per case, as discussed in the FY 2009 IRF PPS final rule (73 FR 46372). In calculating the CMG relative weights, we use a hospital-specific relative value method to estimate operating (routine and ancillary services) and capital costs of IRFs. The process to calculate the CMG relative weights for this proposed rule is as follows:

Step 1. We estimate the effects that comorbidities have on costs.

Step 2. We adjust the cost of each Medicare discharge (case) to reflect the effects found in the first step.

Step 3. We use the adjusted costs from the second step to calculate CMG relative weights, using the hospital-specific relative value method.

Step 4. We normalize the FY 2024 CMG relative weights to the same average CMG relative weight from the CMG relative weights implemented in the FY 2023 IRF PPS final rule (87 FR 47038).

Consistent with the methodology that we have used to update the IRF classification system in each instance in the past, we are proposing to update the CMG relative weights for FY 2024 in such a way that total estimated aggregate payments to IRFs for FY 2024 are the same with or without the changes (that is, in a budget-neutral manner) by applying a budget neutrality factor to the standard payment amount. To calculate the appropriate budget neutrality factor for use in updating the FY 2024 CMG relative weights, we use the following steps:

Step 1. Calculate the estimated total amount of IRF PPS payments for FY 2024 (with no changes to the CMG relative weights).

Step 2. Calculate the estimated total amount of IRF PPS payments for FY 2024 by applying the proposed changes to the CMG relative weights (as discussed in this proposed rule).

Step 3. Divide the amount calculated in step 1 by the amount calculated in step 2 to determine the budget neutrality factor of 0.9999 that would maintain the same total estimated aggregate payments in FY 2024 with and without the proposed changes to the CMG relative weights.

Step 4. Apply the budget neutrality factor from step 3 to the FY 2024 IRF PPS standard payment amount after the application of the budget-neutral wage adjustment factor.

In section V.G. of this proposed rule, we discuss the proposed use of the existing methodology to calculate the proposed standard payment conversion factor for FY 2024.

In Table 2, “Proposed Relative Weights and Average Length of Stay Values for Case-Mix Groups,” we present the proposed CMGs, the comorbidity tiers, the corresponding relative weights, and the ALOS values for each CMG and tier for FY 2024. The ALOS for each CMG is used to determine when an IRF discharge meets the definition of a short-stay transfer, which results in a per diem case level adjustment.

Generally, updates to the CMG relative weights result in some increases and some decreases to the CMG relative weight values. Table 3 shows how we estimate that the application of the proposed revisions for FY 2024 would affect particular CMG relative weight values, which would affect the overall distribution of payments within CMGs and tiers. We note that, because we propose to implement the CMG relative weight revisions in a budget-neutral manner (as previously described), total estimated aggregate payments to IRFs for FY 2024 would not be affected as a result of the proposed CMG relative weight revisions. However, the proposed revisions would affect the distribution of payments within CMGs and tiers.

Table 3—Distributional Effects of the Changes to the CMG Relative Weights

Percentage change in CMG relative weights	Number of cases affected	Percentage of cases affected (percent)
Increased by 15% or more	81	0.0
Increased by between 5% and 15%	1,263	0.3
Changed by less than 5%	375,622	99.4
Decreased by between 5% and 15%	843	0.2
Decreased by 15% or more	0	0.0

As shown in Table 3, 99.4 percent of all IRF cases are in CMGs and tiers that would experience less than a 5 percent change (either increase or decrease) in the CMG relative weight value as a result of the proposed revisions for FY 2024. The proposed changes in the ALOS values for FY 2024, compared with the FY 2023 ALOS values, are small and do not show any particular trends in IRF length of stay patterns.

We invite public comment on our proposed updates to the CMG relative weights and ALOS values for FY 2024.

V. Proposed FY 2024 IRF PPS Payment Update

A. Background

Section 1886(j)(3)(C) of the Act requires the Secretary to establish an increase factor that reflects changes over time in the prices of an appropriate mix of goods and services for which payment is made under the IRF PPS. According to section 1886(j)(3)(A)(i) of the Act, the increase factor shall be used to update the IRF prospective payment rates for each FY. Section 1886(j)(3)(C)(ii)(I) of the Act requires the application of a productivity adjustment described in section 1886(b)(3)(B)(xi)(II) of the Act. Thus, we propose to update the IRF PPS payments for FY 2024 by a market basket increase factor as required by section 1886(j)(3)(C) of the Act based upon the most current data available, with a productivity adjustment as required by section 1886(j)(3)(C)(ii)(I) of the Act.

We have utilized various market baskets through the years in the IRF PPS. For a discussion of these market baskets, we refer readers to the FY 2016 IRF PPS final rule (80 FR 47046).

In FY 2016, we finalized the use of a 2012-based IRF market basket, using Medicare cost report data for both freestanding and hospital-based IRFs (80 FR 47049 through 47068). In FY 2020, we finalized a rebased and revised IRF market basket to reflect a 2016 base year. The FY 2020 IRF PPS final rule (84 FR 39071 through 39086) contains a complete discussion of the development of the 2016-based IRF market basket. Beginning with FY 2024, we are proposing to rebase and revise the IRF market basket to reflect a 2021 base year. In the following discussion, we provide an overview of the proposed market basket and describe the methodologies used to determine the operating and capital portions of the proposed 2021-based IRF market basket.

B. Overview of the Proposed 2021-Based IRF Market Basket

The proposed 2021-based IRF market basket is a fixed-weight, Laspeyres-type price index. A Laspeyres price index measures the change in price, over time, of the same mix of goods and services purchased in the base period. Any changes in the quantity or mix of goods and services (that is, intensity) purchased over time relative to the base period are not measured.

The index itself is constructed in three steps. First, a base period is selected (for the proposed IRF market basket in this proposed rule, we propose to use 2021 as the base period) and total base period costs are estimated for a set of mutually exclusive and exhaustive cost categories. Each category is calculated as a proportion of total costs. These proportions are called cost weights. Second, each cost category is matched to an appropriate price or wage variable, referred to as a price proxy. In almost every instance, these price proxies are derived from publicly available statistical series that are published on a consistent schedule (preferably at least on a quarterly basis). Finally, the cost weight for each cost category is multiplied by the level of its respective price proxy. The sum of these products (that is, the cost weights multiplied by their price index levels) for all cost categories yields the composite index level of the market basket in a given time period. Repeating this step for other periods produces a series of market basket levels over time. Dividing an index level for a given period by an index level for an earlier period produces a rate of growth in the input price index over that timeframe.

As noted, the market basket is described as a fixed-weight index because it represents the change in price over time of a constant mix (quantity and intensity) of goods and services needed to provide IRF services. The effects on total costs resulting from changes in the mix of goods and services purchased subsequent to the base period are not measured. For example, an IRF hiring more nurses after the base period to accommodate the needs of patients would increase the volume of goods and services purchased by the IRF, but would not be factored into the price change measured by a fixed-weight IRF market basket. Only when the index is rebased would changes in the quantity and intensity be captured, with those changes being reflected in the cost weights. Therefore, we rebase the market basket periodically so that the cost weights reflect recent changes in the mix of goods and services that IRFs purchase to furnish inpatient care between base periods.

C. Proposed Rebasing and Revising of the IRF PPS Market Basket

As discussed in the FY 2020 IRF PPS final rule (84 FR 39071 through 39086), the 2016-based IRF market basket cost weights reflect the 2016 Medicare cost report data submitted by both freestanding and hospital-based facilities.

Beginning with FY 2024, we are proposing to rebase and revise the 2016-based IRF market basket cost weights to a 2021 base year reflecting the 2021 Medicare cost report data submitted by both freestanding and hospital-based IRFs. Below we provide a detailed description of our methodology used to develop the proposed 2021-based IRF market basket. This proposed methodology is generally similar to the methodology used to develop the 2016-based IRF market basket.

We invite public comment on our proposed methodology for developing the 2021-based IRF market basket.

1. Development of Cost Categories and Weights for the Proposed 2021-Based IRF Market Basket

a. Use of Medicare Cost Report Data

We are proposing a 2021-based IRF market basket that consists of seven major cost categories and a residual derived from the 2021 Medicare cost reports (CMS Form 2552–10, OMB No. 0938–0050) for freestanding and hospital-based IRFs. The seven major cost categories are Wages and Salaries, Employee Benefits, Contract Labor, Pharmaceuticals, Professional Liability Insurance (PLI), Home Office/Related Organization Contract Labor, and Capital. The residual category reflects all remaining costs not captured in the seven cost categories. The 2021 cost reports include providers whose cost reporting period began on or after October 1, 2020, and before October 1, 2021. As noted previously, the current IRF market basket is based on 2016 Medicare cost reports and, therefore, reflects the 2016 cost structure for IRFs. As described in the FY 2023 IRF PPS final rule (87 FR 47049 through 47050), we received comments on the FY 2023 IRF PPS proposed rule where stakeholders expressed concern that the proposed market basket update was inadequate relative to input price inflation experienced by IRFs, particularly as a result of the COVID–19 PHE. These commenters stated that the PHE, along with inflation, has significantly driven up operating costs. Specifically, some commenters noted changes to the labor markets that led to the use of more contract labor, a trend that we verified in analyzing the Medicare cost reports through 2021. Therefore, we believe it is appropriate to incorporate more recent data to reflect updated cost structures for IRFs and so we are proposing to use 2021 as the base year because we believe that the Medicare cost reports for this year represent the most recent, complete set of Medicare cost report data available for developing the proposed IRF market basket at the time of this rulemaking. Given the potential impact of the PHE on the Medicare cost report data, we will continue to monitor these data going forward and any changes to the IRF market basket will be proposed in future rulemaking.

Since our goal is to establish cost weights that are reflective of case mix and practice patterns associated with the services IRFs provide to Medicare beneficiaries, as we did for the 2016-based IRF market basket, we are proposing to limit the cost reports used to establish the 2021-based IRF market basket to those from facilities that had a Medicare average length of stay (LOS) that was relatively similar to their facility average LOS. We believe that this requirement eliminates statistical outliers and ensures a more accurate market basket that reflects the costs generally incurred during a Medicare-covered stay. The Medicare average LOS for freestanding IRFs is calculated from data reported on line 14 of Worksheet S–3, part I. The Medicare average LOS for hospital-based IRFs is calculated from data reported on line 17 of Worksheet S–3, part I. We propose to include the cost report data from IRFs with a Medicare average LOS within 15 percent (that is, 15 percent higher or lower) of the facility average LOS to establish the sample of providers used to estimate the 2021-based IRF market basket cost weights. We are proposing to apply this LOS edit to the data for IRFs to exclude providers that serve a population whose LOS would indicate that the patients served are not consistent with a LOS of a typical Medicare patient. We note that this is the same LOS edit that we applied to develop the 2016-based IRF market basket. This process resulted in the exclusion of about nine percent of the freestanding and hospital-based IRF Medicare cost reports. Of those excluded, about 15 percent were freestanding IRFs and 85 percent were hospital-based IRFs. This ratio is relatively consistent with the universe of freestanding and hospital-based IRF cost reports where freestanding IRFs represent about 30 percent of the total.

We then propose to use the cost reports for IRFs that met this LOS edit requirement to calculate the costs for the seven major cost categories (Wages and Salaries, Employee Benefits, Contract Labor, Professional Liability Insurance, Pharmaceuticals, Home Office/Related Organization Contract Labor, and Capital) for the market basket. These are the same categories used for the 2016-based IRF market basket. Also, as described in section V.C.1.d. of this proposed rule, and as done for the 2016-based IRF market basket, we are also proposing to use the Medicare cost report data to calculate the detailed capital cost weights for the Depreciation, Interest, Lease, and Other Capital-related cost categories. We note that we are proposing to rename the Home Office Contract Labor cost category to the Home Office/Related Organization Contract Labor cost category to be more consistent with the Medicare cost report instructions.

Similar to the 2016-based IRF market basket major cost weights, for the majority of the proposed 2021-based IRF market basket cost weights, we are proposing to divide the 2021 costs for each cost category by the 2021 total Medicare allowable costs (routine, ancillary and capital) that are eligible for reimbursement through the IRF PPS (we note that we use total facility medical care costs as the denominator to derive both the PLI and Home Office/Related Organization Contract Labor cost weights). We next describe our proposed methodology for deriving the cost levels used to derive the proposed 2021-based IRF market basket.

(1) Total Medicare Allowable Costs

For freestanding IRFs, we propose that total Medicare allowable costs would be equal to the sum of total costs for the Medicare allowable cost centers as reported on Worksheet B, part I, column 26, lines 30 through 35, 50 through 76 (excluding 52 and 75), 90 through 91, and 93.

For hospital-based IRFs, we propose that total Medicare allowable costs would be equal to the total costs for the IRF inpatient unit after the allocation of overhead costs (Worksheet B, part I, column 26, line 41) and a proportion of total ancillary costs reported on Worksheet B, part I, column 26, lines 50 through 76 (excluding 52 and 75), 90 through 91, and 93.

We propose to calculate total ancillary costs attributable to the hospital-based IRF by first deriving an “IRF ancillary ratio” for each ancillary cost center. The IRF ancillary ratio is defined as the ratio of IRF Medicare ancillary costs for the cost center (as reported on Worksheet D–3, column 3 for hospital-based IRFs) to total Medicare ancillary costs for the cost center (equal to the sum of Worksheet D–3, column 3 for all relevant PPSs [that is, inpatient prospective payment system (IPPS), IRF, IPF and skilled nursing facility (SNF)]). For example, if hospital-based IRF Medicare physical therapy costs represent about 30 percent of the total Medicare physical therapy costs for the entire facility, then the IRF ancillary ratio for physical therapy costs would be 30 percent. We believe it is appropriate to use only a portion of the ancillary costs in the market basket cost weight calculations since the hospital-based IRF only utilizes a portion of the facility's ancillary services. We believe the ratio of reported IRF Medicare costs to reported total Medicare costs provides a reasonable estimate of the ancillary services utilized, and costs incurred, by the hospital-based IRF. We propose that this IRF ancillary ratio for each cost center is also used to calculate Wages and Salaries and Capital costs as described below.

Then for each ancillary cost center, we propose to multiply the IRF ancillary ratio for the given cost center by the total facility ancillary costs for that specific cost center (as reported on Worksheet B, part I, column 26) to derive IRF ancillary costs. For example, the 30 percent IRF ancillary ratio for physical therapy cost center would be multiplied by the total ancillary costs for physical therapy (Worksheet B, part I, column 26, line 66). The IRF ancillary costs for each cost center are then added to total costs for the IRF inpatient unit after the allocation of overhead costs (Worksheet B, part I, column 26, line 41) to derive total Medicare allowable costs.

We propose to use these methods to derive levels of total Medicare allowable costs for IRF providers. This is the same methodology used for the 2016-based IRF market basket. We propose that these total Medicare allowable costs for the IRF will be the denominator for the cost weight calculations for the Wages and Salaries, Employee Benefits, Contract Labor, Pharmaceuticals, and Capital cost weights. With this work complete, we then set about deriving cost levels for the seven major cost categories and then derive a residual cost weight reflecting all other costs not classified.

(2) Wages and Salaries Costs

For freestanding IRFs, we are proposing to derive Wages and Salaries costs as the sum of routine inpatient salaries (Worksheet A, column 1, lines 30 through 35), ancillary salaries (Worksheet A, column 1, lines 50 through 76 (excluding 52 and 75), 90 through 91, and 93), and a proportion of overhead (or general service cost centers in the Medicare cost reports) salaries. Since overhead salary costs are attributable to the entire IRF, we only include the proportion attributable to the Medicare allowable cost centers. We are proposing to estimate the proportion of overhead salaries that are attributed to Medicare allowable costs centers by multiplying the ratio of Medicare allowable area salaries (Worksheet A, column 1, lines 30 through 35, 50 through 76 (excluding 52 and 75), 90 through 91, and 93) to total non-overhead salaries (Worksheet A, column 1, line 200 less Worksheet A, column 1, lines 4 through 18) times total overhead salaries (Worksheet A, column 1, lines 4 through 18). This is a similar methodology as used in the 2016-based IRF market basket.

For hospital-based IRFs, we are proposing to derive Wages and Salaries costs as the sum of the following salaries attributable to the hospital-based IRF: inpatient routine salary costs (Worksheet A, column 1, line 41); overhead salary costs; ancillary salary costs; and a portion of overhead salary costs attributable to the ancillary departments.

(a) Overhead Salary Costs

We are proposing to calculate the portion of overhead salary costs attributable to hospital-based IRFs by first calculating an IRF overhead salary ratio, which is equal to the ratio of total facility overhead salaries (as reported on Worksheet A, column 1, lines 4–18) to total facility noncapital overhead costs (as reported on Worksheet A, column 1 and 2, lines 4–18). We then are proposing to multiply this IRF overhead salary ratio by total noncapital overhead costs (sum of Worksheet B, part I, columns 4 through 18, line 41, less Worksheet B, part II, columns 4 through 18, line 41). This methodology assumes the proportion of total costs related to salaries for the overhead cost center is similar for all inpatient units (that is, acute inpatient or inpatient rehabilitation).

(b) Ancillary Salary Costs

We are proposing to calculate hospital-based IRF ancillary salary costs for a specific cost center (Worksheet A, column 1, lines 50 through 76 (excluding 52 and 75), 90 through 91, and 93) as salary costs from Worksheet A, column 1, multiplied by the IRF ancillary ratio for each cost center as described in section V.C.1.a.(1) of this proposed rule. The sum of these costs represents hospital-based IRF ancillary salary costs.

(c) Overhead Salary Costs for Ancillary Cost Centers

We are proposing to calculate the portion of overhead salaries attributable to each ancillary department (lines 50 through 76 (excluding 52 and 75), 90 through 91, and 93) by first calculating total noncapital overhead costs attributable to each specific ancillary department (sum of Worksheet B, part I, columns 4–18 less, Worksheet B, part II, column 26). We then identify the portion of these total noncapital overhead costs for each ancillary department that is attributable to the hospital-based IRF by multiplying these costs by the IRF ancillary ratio as described in section V.C.1.a.(1) of this proposed rule. We then sum these estimated IRF Medicare allowable noncapital overhead costs for all ancillary departments (cost centers 50 through 76, 90 through 91, and 93). Finally, we then identify the portion of these IRF Medicare allowable noncapital overhead costs that are attributable to Wages and Salaries by multiplying these costs by the IRF overhead salary ratio as described in section V.C.1.a.(2)(a) of this proposed rule. This is the same methodology used to derive the 2016-based IRF market basket.

(3) Employee Benefits Costs

Effective with the implementation of CMS Form 2552–10, we began collecting Employee Benefits and Contract Labor data on Worksheet S–3, part V.

For the 2021 Medicare cost report data, 54 percent of providers reported Employee Benefits data on Worksheet S–3, part V; particularly, approximately 57 percent of freestanding IRFs and 53 percent of hospital-based IRFs reported Employee Benefits data on Worksheet S–3, part V. For comparison, for 2016, about 45 percent of providers reported Employee Benefits data on Worksheet S–3, part V. Again, we continue to encourage all providers to report these data on the Medicare cost report.

For freestanding IRFs, we are proposing Employee Benefits costs would be equal to the data reported on Worksheet S–3, part V, column 2, line 2. We note that while not required to do so, freestanding IRFs also may report Employee Benefits data on Worksheet S–3, part II, which is applicable to only IPPS providers. Similar to the method for the 2016-based IRF market basket, for those freestanding IRFs that report Worksheet S–3, part II, data, but not Worksheet S–3, part V, we are proposing to use the sum of Worksheet S–3, part II, lines 17, 18, 20, and 22, to derive Employee Benefits costs.

For hospital-based IRFs, we are proposing to calculate total benefit costs as the sum of inpatient unit benefit costs, a portion of ancillary departments benefit costs, and a portion of overhead benefits attributable to both the routine inpatient unit and the ancillary departments. For those hospital-based IRFs that report Worksheet S–3, part V data, we are proposing inpatient unit benefit costs be equal to Worksheet S–3, part V, column 2, line 4. Given the limited reporting on Worksheet S–3, part V, we are proposing that for those hospital-based IRFs that do not report these data, we calculate inpatient unit benefits costs using a portion of benefits costs reported for Excluded areas on Worksheet S–3, part II. We are proposing to calculate the ratio of inpatient unit salaries (Worksheet A, column 1, line 41) to total excluded area salaries (sum of Worksheet A, column 1, lines 20, 23, 40 through 42, 44, 45, 46, 94, 95, 98 through 101, 105 through 112, 114, 115 through 117, 190 through 194). We then propose to apply this ratio to Excluded area benefits (Worksheet S–3, part II, column 4, line 19) to derive inpatient unit benefits costs for those providers that do not report benefit costs on Worksheet S–3, part V.

We are proposing the ancillary departments benefits and overhead benefits (attributable to both the inpatient unit and ancillary departments) costs are derived by first calculating the sum of hospital-based IRF overhead salaries as described in section V.C.1.a.(2)(a) of this proposed rule, hospital-based IRF ancillary salaries as described in section V.C.1.a.(2)(b) of this proposed rule and hospital-based IRF overhead salaries for ancillary cost centers as described in section V.C.1.a.(2)(c) of this proposed rule. This sum is then multiplied by the ratio of total facility benefits to total facility salaries, where total facility benefits is equal to the sum of Worksheet S–3, part II, column 4, lines 17–25, and total facility salaries is equal to Worksheet S–3, part II, column 4, line 1.

(4) Contract Labor Costs

Contract Labor costs are primarily associated with direct patient care services. Contract labor costs for other services such as accounting, billing, and legal are calculated separately using other government data sources as described in section V.C.1.c. of this proposed rule. To derive contract labor costs using Worksheet S–3, part V, data, for freestanding IRFs, we are proposing Contract Labor costs be equal to Worksheet S–3, part V, column 1, line 2. As we noted for Employee Benefits, freestanding IRFs also may report Contract Labor data on Worksheet S–3, part II, which is applicable to only IPPS providers. For those freestanding IRFs that report Worksheet S–3, part II data, but not Worksheet S–3, part V, we are proposing to use the sum of Worksheet S–3, part II, column 4, lines 11 and 13, to derive Contract Labor costs.

For hospital-based IRFs, we are proposing that Contract Labor costs would be equal to Worksheet S–3, part V, column 1, line 4. For 2021 Medicare cost report data, 30 percent of providers reported Contract Labor data on Worksheet S–3, part V; particularly, approximately 56 percent of freestanding IRFs and 18 percent of hospital-based IRFs reported data on Worksheet S–3, part V. For comparison, for the 2016-based IRF market basket, about 26 percent of providers reported Contract Labor data on Worksheet S–3, part V. We continue to encourage all providers to report these data on the Medicare cost report.

Given the limited reporting on Worksheet S–3, part V, we are proposing that for those hospital-based IRFs that do not report these data, we calculate Contract Labor costs using a portion of contract labor costs reported on Worksheet S–3, part II. We are proposing to calculate the ratio of contract labor costs (Worksheet S–3, part II, column 4, lines 11 and 13) to PPS salaries (Worksheet S–3, part II, column 4, line 1 less the sum of Worksheet S–3, part II, column 4, lines 3, 401, 5, 6, 7, 701, 8, 9, 10 less Worksheet A, column 1, line 20 and 23). We then propose to apply this ratio to total inpatient routine salary costs (Worksheet A, column 1, line 41) to derive contract labor costs for those providers that do not report contract labor costs on Worksheet S–3, part V.

(5) Pharmaceuticals Costs

For freestanding IRFs, we are proposing to calculate pharmaceuticals costs using non-salary costs reported on Worksheet A, column 7, less Worksheet A, column 1, for the pharmacy cost center (line 15) and drugs charged to patients cost center (line 73).

For hospital-based IRFs, we are proposing to calculate pharmaceuticals costs as the sum of a portion of the non-salary pharmacy costs and a portion of the non-salary drugs charged to patient costs reported for the total facility. We propose that non-salary pharmacy costs attributable to the hospital-based IRF would be calculated by multiplying total pharmacy costs attributable to the hospital-based IRF (as reported on Worksheet B, part I, column 15, line 41) by the ratio of total non-salary pharmacy costs (Worksheet A, column 2, line 15) to total pharmacy costs (sum of Worksheet A, columns 1 and 2 for line 15) for the total facility. We propose that non-salary drugs charged to patient costs attributable to the hospital-based IRF would be calculated by multiplying total non-salary drugs charged to patient costs (Worksheet B, part I, column 0, line 73 plus Worksheet B, part I, column 15, line 73 less Worksheet A, column 1, line 73) for the total facility by the ratio of Medicare drugs charged to patient ancillary costs for the IRF unit (as reported on Worksheet D–3 for hospital-based IRFs, column 3, line 73) to total Medicare drugs charged to patient ancillary costs for the total facility (equal to the sum of Worksheet D–3, column 3, line 73 for all relevant PPS (that is, IPPS, IRF, IPF and SNF).

(6) Professional Liability Insurance Costs

For freestanding and hospital-based IRFs, we are proposing that Professional Liability Insurance (PLI) costs (often referred to as malpractice costs) would be equal to premiums, paid losses and self-insurance costs reported on Worksheet S–2, columns 1 through 3, line 118—the same data used for the 2016-based IRF market basket. For hospital-based IRFs, we are proposing to assume that the PLI weight for the total facility is similar to the hospital-based IRF unit since the only data reported on this worksheet is for the entire facility, as we currently have no means to identify the proportion of total PLI costs that are only attributable to the hospital-based IRF. However, when we derive the cost weight for PLI for both hospital-based and freestanding IRFs, we use the total facility medical care costs as the denominator as opposed to total Medicare allowable costs. For freestanding IRFs and hospital-based IRFs, we are proposing to derive total facility medical care costs as the sum of total costs (Worksheet B, part I, column 26, line 202) less non-reimbursable costs (Worksheet B, part I, column 26, lines 190 through 201).

(7) Home Office/Related Organization Contract Labor Costs

For freestanding and hospital-based IRFs, we are proposing to calculate the home office/related organization contract labor costs using data reported on Worksheet S–3, part II, column 4, lines 1401, 1402, 2550, and 2551. Similar to the PLI costs, these costs are for the entire facility. Therefore, when we derive the cost weight for Home Office/Related Organization Contract Labor costs, we use the total facility medical care costs as the denominator (reflecting the total facility costs less the non-reimbursable costs reported on lines 190 through 201). Our assumption is that the same proportion of expenses are used among each unit of the hospital.

(8) Capital Costs

For freestanding IRFs, we are proposing that capital costs would be equal to Medicare allowable capital costs as reported on Worksheet B, part II, column 26, lines 30 through 35, 50 through 76 (excluding 52 and 75), 90 through 91, and 93.

For hospital-based IRFs, we are proposing that capital costs would be equal to IRF inpatient capital costs (as reported on Worksheet B, part II, column 26, line 41) and a portion of IRF ancillary capital costs. We calculate the portion of ancillary capital costs attributable to the hospital-based IRF for a given cost center by multiplying total facility ancillary capital costs for the specific ancillary cost center (as reported on Worksheet B, part II, column 26) by the IRF ancillary ratio as described in section V.C.1.a.(1) of this proposed rule. For example, if hospital-based IRF Medicare physical therapy costs represent 30 percent of the total Medicare physical therapy costs for the entire facility, then 30 percent of total facility physical therapy capital costs (as reported in Worksheet B, part II, column 26, line 66) would be attributable to the hospital-based IRF.

b. Final Major Cost Category Computation

After we derive costs for each of the major cost categories and total Medicare allowable costs for each provider using the Medicare cost report data as previously described, we propose to address data outliers using the following steps. First, for the Wages and Salaries, Employee Benefits, Contract Labor, Pharmaceuticals, and Capital cost weights, we first divide the costs for each of these five categories by total Medicare allowable costs calculated for the provider to obtain cost weights for the universe of IRF providers. We then propose to trim the data to remove outliers (a standard statistical process) by: (1) requiring that major expenses (such as Wages and Salaries costs) and total Medicare allowable operating costs be greater than zero; and (2) excluding the top and bottom five percent of the major cost weight (for example, Wages and Salaries costs as a percent of total Medicare allowable operating costs). We note that missing values are assumed to be zero consistent with the methodology for how missing values were treated in the 2016-based IRF market basket. After these outliers have been excluded, we sum the costs for each category across all remaining providers. We then divide this by the sum of total Medicare allowable costs across all remaining providers to obtain a cost weight for the proposed 2021-based IRF market basket for the given category.

The proposed trimming methodology for the Home Office/Related Organization Contract Labor and PLI cost weights is slightly different than the proposed trimming methodology for the other five cost categories as described above. For these cost weights, since we are using total facility medical care costs rather than Medicare allowable costs associated with IRF services, we are proposing to trim the freestanding and hospital-based IRF cost weights separately.

For the PLI cost weight, for each of the providers, we first divide the PLI costs by total facility medical care costs to obtain a PLI cost weight for the universe of IRF providers. We then propose to trim the data to remove outliers by: (1) requiring that PLI costs are greater than zero and are less than total facility medical care costs; and (2) excluding the top and bottom five percent of the major cost weight trimming freestanding and hospital-based providers separately. After removing these outliers, we are left with a trimmed data set for both freestanding and hospital-based providers. We are then proposing to separately sum the costs for each category (freestanding and hospital-based) across all remaining providers. We next divide this by the sum of total facility medical care costs across all remaining providers to obtain both a freestanding cost weight and hospital-based cost weight. Lastly, we are proposing to weight these two cost weights together using the Medicare allowable costs from the sample of freestanding and hospital-based IRFs that passed the PLI trim (59 percent for hospital-based and 41 percent for freestanding IRFs) to derive a PLI cost weight for the proposed 2021-based IRF market basket.

For the Home Office/Related Organization Contract Labor cost weight, for each of the providers, we first divide the home office/related organization contract labor costs by total facility medical care costs to obtain a Home Office/Related Organization Contract Labor cost weight for the universe of IRF providers. We are then proposing to trim only the top 1 percent of providers to exclude outliers while also allowing providers who have reported zero home office costs to remain in the Home Office/Related Organization Contract Labor cost weight calculations as not all providers will incur home office/relation organization contract labor costs. After removing these outliers, we are left with a trimmed data set for both freestanding and hospital-based providers. We are then proposing to separately sum the costs for each category (freestanding and hospital-based) across all remaining providers. We next divide this by the sum of total facility medical care costs across all remaining providers to obtain a freestanding cost weight and hospital-based cost weight. Lastly, we are proposing to weight these two cost weights together using the Medicare allowable costs from the sample of freestanding and hospital-based IRFs that passed the Home Office/Related Organization Contract Labor cost weight trim (68 percent for hospital-based and 32 percent for freestanding IRFs) to derive a Home Office/Related Organization Contract Labor cost weight for the proposed 2021-based IRF market basket.

Finally, we propose to calculate the residual “All Other” cost weight that reflects all remaining costs that are not captured in the seven cost categories listed. See Table 4 for the resulting cost weights for these major cost categories that we obtain from the Medicare cost reports.

Table 4—Major Cost Categories as Derived From Medicare Cost Reports

Major cost categories	Proposed 2021-based IRF market basket (percent)	2016-based IRF market basket (percent)
Wages and Salaries	46.6	47.1
Employee Benefits	11.6	11.3
Contract Labor	2.0	1.0
Professional Liability Insurance (Malpractice)	0.8	0.7
Pharmaceuticals	4.7	5.1
Home Office/Related Organization Contract Labor	5.4	3.7
Capital	8.6	9.0
All Other	20.4	22.2
* Total may not sum to 100 due to rounding.

As we did for the 2016-based IRF market basket, we are proposing to allocate the Contract Labor cost weight to the Wages and Salaries and Employee Benefits cost weights based on their relative proportions under the assumption that contract labor costs are comprised of both wages and salaries and employee benefits. The Contract Labor allocation proportion for Wages and Salaries is equal to the Wages and Salaries cost weight as a percent of the sum of the Wages and Salaries cost weight and the Employee Benefits cost weight. For this proposed rule, this rounded percentage is 80 percent; therefore, we are proposing to allocate 80 percent of the Contract Labor cost weight to the Wages and Salaries cost weight and 20 percent to the Employee Benefits cost weight. This allocation was 81/19 in the 2016-based IRF market basket (84 FR 39076). Table 5 shows the Wages and Salaries and Employee Benefit cost weights after Contract Labor cost weight allocation for both the proposed 2021-based IRF market basket and 2016-based IRF market basket.

Table 5—Wages and Salaries and Employee Benefits Cost Weights After Contract Labor Allocation

Major cost categories	Proposed 2021-based IRF market basket	2016-based IRF market basket
Wages and Salaries	48.2	47.9
Employee Benefits	11.9	11.4

c. Derivation of the Detailed Operating Cost Weights

To further divide the “All Other” residual cost weight estimated from the 2021 Medicare cost report data into more detailed cost categories, we propose to use the 2012 Benchmark Input-Output (I–O) “Use Tables/Before Redefinitions/Purchaser Value” for North American Industry Classification System (NAICS) 622000, Hospitals, published by the Bureau of Economic Analysis (BEA). This data is publicly available at http://www.bea.gov/​industry/​io_​annual.htm. For the 2016-based IRF market basket, we also used the 2012 Benchmark I–O data, the most recent data available at the time (84 FR 39076).

The BEA Benchmark I–O data are scheduled for publication every 5 years with the most recent data available for 2012. The 2012 Benchmark I–O data are derived from the 2012 Economic Census and are the building blocks for BEA's economic accounts. Thus, they represent the most comprehensive and complete set of data on the economic processes or mechanisms by which output is produced and distributed.^[16] BEA also produces Annual I–O estimates; however, while based on a similar methodology, these estimates reflect less comprehensive and less detailed data sources and are subject to revision when benchmark data becomes available. Instead of using the less detailed Annual I–O data, we propose to inflate the 2012 Benchmark I–O data forward to 2021 by applying the annual price changes from the respective price proxies to the appropriate market basket cost categories that are obtained from the 2012 Benchmark I–O data. We repeat this practice for each year. We then propose to calculate the cost shares that each cost category represents of the inflated 2012 data. These resulting 2021 cost shares are applied to the All Other residual cost weight to obtain the detailed cost weights for the proposed 2021-based IRF market basket. For example, the cost for Food: Direct Purchases represents 5.0 percent of the sum of the “All Other” 2012 Benchmark I–O Hospital Expenditures inflated to 2021; therefore, the Food: Direct Purchases cost weight represents 5.0 percent of the 2021-based IRF market basket's “All Other” cost category (20.4 percent), yielding a “final” Food: Direct Purchases cost weight of 1.0 percent in the proposed 2021-based IRF market basket (0.05 * 20.4 percent = 1.0 percent).

Using this methodology, we propose to derive seventeen detailed IRF market basket cost category weights from the proposed 2021-based IRF market basket residual cost weight (20.4 percent). These categories are: (1) Electricity and Other Non-Fuel Utilities, (2) Fuel: Oil and Gas (3) Food: Direct Purchases, (4) Food: Contract Services, (5) Chemicals, (6) Medical Instruments, (7) Rubber and Plastics, (8) Paper and Printing Products, (9) Miscellaneous Products, (10) Professional Fees: Labor-related, (11) Administrative and Facilities Support Services, (12) Installation, Maintenance, and Repair Services, (13) All Other Labor-related Services, (14) Professional Fees: Nonlabor-related, (15) Financial Services, (16) Telephone Services, and (17) All Other Nonlabor-related Services.

d. Derivation of the Detailed Capital Cost Weights

As described in section V.C.1.b. of this proposed rule, we are proposing a Capital-Related cost weight of 8.6 percent as obtained from the 2021 Medicare cost reports for freestanding and hospital-based IRF providers. We are proposing to then separate this total Capital-Related cost weight into more detailed cost categories.

Using 2021 Medicare cost reports, we are able to group Capital-Related costs into the following categories: Depreciation, Interest, Lease, and Other Capital-Related costs. For each of these categories, we are proposing to determine separately for hospital-based IRFs and freestanding IRFs what proportion of total capital-related costs the category represents.

For freestanding IRFs, using Medicare cost report data on Worksheet A–7 part III, we are proposing to derive the proportions for Depreciation (column 9), Interest (column 11), Lease (column 10), and Other Capital-related costs (column 12 through 14), which is similar to the methodology used for the 2016-based IRF market basket.

For hospital-based IRFs, data for these four categories are not reported separately for the hospital-based IRF; therefore, we are proposing to derive these proportions using data reported on Worksheet A–7 for the total facility. We are assuming the cost shares for the overall hospital are representative for the hospital-based IRF unit. For example, if depreciation costs make up 60 percent of total capital costs for the entire facility, we believe it is reasonable to assume that the hospital-based IRF would also have a 60 percent proportion because it is a unit contained within the total facility. This is the same methodology used for the 2016-based IRF market basket (84 FR 39077).

To combine each detailed capital cost weight for freestanding and hospital-based IRFs into a single capital cost weight for the proposed 2021-based IRF market basket, we are proposing to weight together the shares for each of the categories (Depreciation, Interest, Lease, and Other Capital-related costs) based on the share of total capital costs each provider type represents of the total capital costs for all IRFs for 2021. Applying this methodology results in proportions of total capital-related costs for Depreciation, Interest, Lease and Other Capital-related costs that are representative of the universe of IRF providers. This is the same methodology used for the 2016-based IRF market basket (84 FR 39077).

Lease costs are unique in that they are not broken out as a separate cost category in the proposed 2021-based IRF market basket. Rather, we are proposing to proportionally distribute these costs among the cost categories of Depreciation, Interest, and Other Capital-Related costs, reflecting the assumption that the underlying cost structure of leases is similar to that of capital-related costs in general. As was done under the 2016-based IRF market basket, we are proposing to assume that 10 percent of the lease costs as a proportion of total capital-related costs represents overhead and assign those costs to the Other Capital-Related cost category accordingly. We propose to distribute the remaining lease costs proportionally across the three cost categories (Depreciation, Interest, and Other Capital-Related) based on the proportion that these categories comprise of the sum of the Depreciation, Interest, and Other Capital-related cost categories (excluding lease expenses). This would result in three primary capital-related cost categories in the proposed 2021-based IRF market basket: Depreciation, Interest, and Other Capital-Related costs. This is the same methodology used for the 2016-based IRF market basket (84 FR 39077). The allocation of these lease expenses is shown in Table 6.

Finally, we are proposing to further divide the Depreciation and Interest cost categories. We are proposing to separate Depreciation into the following two categories: (1) Building and Fixed Equipment and (2) Movable Equipment. We are proposing to separate Interest into the following two categories: (1) Government/Nonprofit and (2) For-profit.

To disaggregate the Depreciation cost weight, we need to determine the percent of total Depreciation costs for IRFs that is attributable to Building and Fixed Equipment, which we hereafter refer to as the “fixed percentage.” For the proposed 2021-based IRF market basket, we are proposing to use slightly different methods to obtain the fixed percentages for hospital-based IRFs compared to freestanding IRFs.

For freestanding IRFs, we are proposing to use depreciation data from Worksheet A–7 of the 2021 Medicare cost reports. However, for hospital-based IRFs, we determined that the fixed percentage for the entire facility may not be representative of the hospital-based IRF unit due to the entire facility likely employing more sophisticated movable assets that are not utilized by the hospital-based IRF. Therefore, for hospital-based IRFs, we are proposing to calculate a fixed percentage using: (1) building and fixture capital costs allocated to the hospital-based IRF unit as reported on Worksheet B, part I, column 1, line 41, and (2) building and fixture capital costs for the top five ancillary cost centers utilized by hospital-based IRFs accounting for 78 percent of hospital-based IRF ancillary total costs: Physical Therapy (Worksheet B, part I, column 1, line 66), Drugs Charged to Patients (Worksheet B, part I, column 1, line 73), Occupational Therapy (Worksheet B, part I, column 1, line 67), Laboratory (Worksheet B, part I, column 1, line 60) and Clinic (Worksheet B, part I, column 1, line 90). We propose to weight these two fixed percentages (inpatient and ancillary) using the proportion that each capital cost type represents of total capital costs in the proposed 2021-based IRF market basket. We are proposing to then weight the fixed percentages for hospital-based and freestanding IRFs together using the proportion of total capital costs each provider type represents. For both freestanding and hospital-based IRFs, this is the same methodology used for the 2016-based IRF market basket (84 FR 39077).

To disaggregate the Interest cost weight, we determined the percent of total interest costs for IRFs that are attributable to government and nonprofit facilities, which is hereafter referred to as the “nonprofit percentage,” as price pressures associated with these types of interest costs tend to differ from those for for-profit facilities. For the 2021-based IRF market basket, we are proposing to use interest costs data from Worksheet A–7 of the 2021 Medicare cost reports for both freestanding and hospital-based IRFs. We are proposing to determine the percent of total interest costs that are attributed to government and nonprofit IRFs separately for hospital-based and freestanding IRFs. We then are proposing to weight the nonprofit percentages for hospital-based and freestanding IRFs together using the proportion of total capital costs that each provider type represents.

Table 6 provides the proposed detailed capital cost share composition estimated from the 2021 IRF Medicare cost reports. These detailed capital cost share composition percentages are applied to the total Capital-Related cost weight of 8.6 percent calculated using the methodology described in section V.C.1.a.(8) of this proposed rule.

Table 6—Capital Cost Share Composition for the Proposed 2021-Based IRF Market Basket

	Capital cost share composition before lease expense allocation (percent)	Capital cost share composition after lease expense allocation (percent)
Depreciation	48	70
Building and Fixed Equipment	30	44
Movable Equipment	18	26
Interest	10	14
Government/Nonprofit	5	7
For Profit	5	7
Lease	34
Other Capital-related costs	8	16
* Detail may not add to total due to rounding.

e. Proposed 2021-Based IRF Market Basket Cost Categories and Weights

Table 7 compares the cost categories and weights for the proposed 2021-based IRF market basket compared to the 2016-based IRF market basket.

2. Selection of Price Proxies

After developing the cost weights for the proposed 2021-based IRF market basket, we select the most appropriate wage and price proxies currently available to represent the rate of price change for each expenditure category. For the majority of the cost weights, we base the price proxies on U.S. Bureau of Labor Statistics (BLS) data and group them into one of the following BLS categories:

• Employment Cost Indexes. Employment Cost Indexes (ECIs) measure the rate of change in employment wage rates and employer costs for employee benefits per hour worked. These indexes are fixed-weight indexes and strictly measure the change in wage rates and employee benefits per hour. ECIs are superior to Average Hourly Earnings (AHE) as price proxies for input price indexes because they are not affected by shifts in occupation or industry mix, and because they measure pure price change and are available by both occupational group and by industry. The industry ECIs are based on the NAICS and the occupational ECIs are based on the Standard Occupational Classification System (SOC).

• Producer Price Indexes. Producer Price Indexes (PPIs) measure the average change over time in the selling prices received by domestic producers for their output. The prices included in the PPI are from the first commercial transaction for many products and some services ( https://www.bls.gov/​ppi/​).

• Consumer Price Indexes. Consumer Price Indexes (CPIs) measure the average change over time in the prices paid by urban consumers for a market basket of consumer goods and services ( https://www.bls.gov/​cpi/​). CPIs are only used when the purchases are similar to those of retail consumers rather than purchases at the producer level, or if no appropriate PPIs are available.

We evaluate the price proxies using the criteria of reliability, timeliness, availability, and relevance:

• Reliability. Reliability indicates that the index is based on valid statistical methods and has low sampling variability. Widely accepted statistical methods ensure that the data were collected and aggregated in a way that can be replicated. Low sampling variability is desirable because it indicates that the sample reflects the typical members of the population. (Sampling variability is variation that occurs by chance because only a sample was surveyed rather than the entire population.)

• Timeliness. Timeliness implies that the proxy is published regularly, preferably at least once a quarter. The market baskets are updated quarterly, and therefore, it is important for the underlying price proxies to be up-to-date, reflecting the most recent data available. We believe that using proxies that are published regularly (at least quarterly, whenever possible) helps to ensure that we are using the most recent data available to update the market basket. We strive to use publications that are disseminated frequently, because we believe that this is an optimal way to stay abreast of the most current data available.

• Availability. Availability means that the proxy is publicly available. We prefer that our proxies are publicly available because this will help ensure that our market basket updates are as transparent to the public as possible. In addition, this enables the public to be able to obtain the price proxy data on a regular basis.

• Relevance. Relevance means that the proxy is applicable and representative of the cost category weight to which it is applied. The CPIs, PPIs, and ECIs that we have selected to propose in this regulation meet these criteria. Therefore, we believe that they continue to be the best measure of price changes for the cost categories to which they would be applied.

Table 11 lists all price proxies that we propose to use for the proposed 2021-based IRF market basket. Below is a detailed explanation of the price proxies we are proposing for each cost category weight.

a. Price Proxies for the Operating Portion of the Proposed 2021-Based IRF Market Basket

(1) Wages and Salaries

We are proposing to continue to use the ECI for Wages and Salaries for All Civilian workers in Hospitals (BLS series code CIU1026220000000I) to measure the wage rate growth of this cost category. This is the same price proxy used in the 2016-based IRF market basket (84 FR 39080).

(2) Benefits

We are proposing to continue to use the ECI for Total Benefits for All Civilian workers in Hospitals to measure price growth of this category. This ECI is calculated using the ECI for Total Compensation for All Civilian workers in Hospitals (BLS series code CIU1016220000000I) and the relative importance of wages and salaries within total compensation. This is the same price proxy used in the 2016-based IRF market basket (84 FR 39080).

(3) Electricity and Other Non-Fuel Utilities

We are proposing to continue to use the PPI Commodity Index for Commercial Electric Power (BLS series code WPU0542) to measure the price growth of this cost category (which we are proposing to rename from Electricity to Electricity and Other Non-Fuel Utilities). This is the same price proxy used in the 2016-based IRF market basket (84 FR 39080).

(4) Fuel: Oil and Gas

Similar to the 2016-based IRF market basket, for the 2021-based IRF market basket, we are proposing to use a blend of the PPI for Petroleum Refineries and the PPI Commodity for Natural Gas. Our analysis of the Bureau of Economic Analysis' 2012 Benchmark Input-Output data (use table before redefinitions, purchaser's value for NAICS 622000 [Hospitals]), shows that Petroleum Refineries expenses account for approximately 90 percent and Natural Gas expenses account for approximately 10 percent of Hospitals' (NAICS 622000) total Fuel: Oil and Gas expenses. Therefore, we propose to use a blend of 90 percent of the PPI for Petroleum Refineries (BLS series code PCU324110324110) and 10 percent of the PPI Commodity Index for Natural Gas (BLS series code WPU0531) as the price proxy for this cost category. This is the same blend that was used for the 2016-based IRF market basket (84 FR 39080).

(5) Professional Liability Insurance

We are proposing to continue to use the CMS Hospital Professional Liability Index to measure changes in PLI premiums. To generate this index, we collect commercial insurance premiums for a fixed level of coverage while holding non-price factors constant (such as a change in the level of coverage). This is the same proxy used in the 2016-based IRF market basket (84 FR 39080).

(6) Pharmaceuticals

We are proposing to continue to use the PPI for Pharmaceuticals for Human Use, Prescription (BLS series code WPUSI07003) to measure the price growth of this cost category. This is the same proxy used in the 2016-based IRF market basket (84 FR 39080).

(7) Food: Direct Purchases

We are proposing to continue to use the PPI for Processed Foods and Feeds (BLS series code WPU02) to measure the price growth of this cost category. This is the same proxy used in the 2016-based IRF market basket (84 FR 39080).

(8) Food: Contract Purchases

We are proposing to continue to use the CPI for Food Away From Home (BLS series code CUUR0000SEFV) to measure the price growth of this cost category. This is the same proxy used in the 2016-based IRF market basket (84 FR 39080).

(9) Chemicals

Similar to the 2016-based IRF market basket, we are proposing to use a four-part blended PPI as the proxy for the chemical cost category in the proposed 2021-based IRF market basket. The proposed blend is composed of the PPI for Industrial Gas Manufacturing, Primary Products (BLS series code PCU325120325120P), the PPI for Other Basic Inorganic Chemical Manufacturing (BLS series code PCU32518–32518–), the PPI for Other Basic Organic Chemical Manufacturing (BLS series code PCU32519–32519–), and the PPI for Other Miscellaneous Chemical Product Manufacturing (BLS series code PCU325998325998). For the proposed 2021-based IRF market basket, we are proposing to derive the weights for the PPIs using the 2012 Benchmark I–O data.

Table 8 shows the weights for each of the four PPIs used to create the proposed blended Chemical proxy for the proposed 2021 IRF market basket. This is the same blend that was used for the 2016-based IRF market basket (84 FR 39080).

Table 8—Blended Chemical PPI Weights

Name	Proposed 2021-based IRF weights (percent)	NAICS
PPI for Industrial Gas Manufacturing	19	325120
PPI for Other Basic Inorganic Chemical Manufacturing	13	325180
PPI for Other Basic Organic Chemical Manufacturing	60	325190
PPI for Other Miscellaneous Chemical Product Manufacturing	8	325998

(10) Medical Instruments

We are proposing to use a blended price proxy for the Medical Instruments category, as shown in Table 9. The 2012 Benchmark I–O data shows the majority of medical instruments and supply costs are for NAICS 339112—Surgical and medical instrument manufacturing costs (approximately 56 percent) and NAICS 339113—Surgical appliance and supplies manufacturing costs (approximately 43 percent). Therefore, we are proposing to use a blend of these two price proxies. To proxy the price changes associated with NAICS 339112, we are proposing using the PPI for Surgical and medical instruments (BLS series code WPU1562). This is the same price proxy we used in the 2016-based IRF market basket. To proxy the price changes associated with NAICS 339113, we are proposing to use a 50/50 blend of the PPI for Medical and surgical appliances and supplies (BLS series code WPU1563) and the PPI for Miscellaneous products, Personal safety equipment and clothing (BLS series code WPU1571). We are proposing to include the latter price proxy as it would reflect personal protective equipment including but not limited to face shields and protective clothing. The 2012 Benchmark I–O data does not provide specific expenses for these products; however, we recognize that this category reflects costs faced by IRFs.

Table 9—Blended Medical Instruments PPI Weights

Name	Proposed 2021-based IRF weights (percent)	NAICS
PPI—Commodity—Surgical and medical instruments	56	339112
PPI—Commodity—Medical and surgical appliances and supplies	22	339113
PPI—Commodity—Miscellaneous products-Personal safety equipment and clothing	22

(11) Rubber and Plastics

We are proposing to continue to use the PPI for Rubber and Plastic Products (BLS series code WPU07) to measure price growth of this cost category. This is the same proxy used in the 2016-based IRF market basket (84 FR 39081).

(12) Paper and Printing Products

We are proposing to continue to use the PPI for Converted Paper and Paperboard Products (BLS series code WPU0915) to measure the price growth of this cost category. This is the same proxy used in the 2016-based IRF market basket (84 FR 39081).

(13) Miscellaneous Products

We are proposing to continue to use the PPI for Finished Goods Less Food and Energy (BLS series code WPUFD4131) to measure the price growth of this cost category. This is the same proxy used in the 2016-based IRF market basket (84 FR 39081).

(14) Professional Fees: Labor-Related

We are proposing to continue to use the ECI for Total Compensation for Private Industry workers in Professional and Related (BLS series code CIU2010000120000I) to measure the price growth of this category. This is the same proxy used in the 2016-based IRF market basket (84 FR 39081).

(15) Administrative and Facilities Support Services

We are proposing to continue to use the ECI for Total Compensation for Private Industry workers in Office and Administrative Support (BLS series code CIU2010000220000I) to measure the price growth of this category. This is the same proxy used in the 2016-based IRF market basket (84 FR 39081).

(16) Installation, Maintenance, and Repair Services

We are proposing to continue to use the ECI for Total Compensation for Civilian workers in Installation, Maintenance, and Repair (BLS series code CIU1010000430000I) to measure the price growth of this cost category. This is the same proxy used in the 2016-based IRF market basket (84 FR 39081).

(17) All Other: Labor-Related Services

We are proposing to continue to use the ECI for Total Compensation for Private Industry workers in Service Occupations (BLS series code CIU2010000300000I) to measure the price growth of this cost category. This is the same proxy used in the 2016-based IRF market basket (84 FR 39081).

(18) Professional Fees: Nonlabor-Related

We are proposing to continue to use the ECI for Total Compensation for Private Industry workers in Professional and Related (BLS series code CIU2010000120000I) to measure the price growth of this category. This is the same proxy used in the 2016-based IRF market basket (84 FR 39081).

(19) Financial Services

We are proposing to continue to use the ECI for Total Compensation for Private Industry workers in Financial Activities (BLS series code CIU201520A000000I) to measure the price growth of this cost category. This is the same proxy used in the 2016-based IRF market basket (84 FR 39081).

(20) Telephone Services

We are proposing to continue to use the CPI for Telephone Services (BLS series code CUUR0000SEED) to measure the price growth of this cost category. This is the same proxy used in the 2016-based IRF market basket (84 FR 39081).

(21) All Other: Nonlabor-Related Services

We are proposing to continue to use the CPI for All Items Less Food and Energy (BLS series code CUUR0000SA0L1E) to measure the price growth of this cost category. This is the same proxy used in the 2016-based IRF market basket (84 FR 39081).

b. Price Proxies for the Capital Portion of the Proposed 2021-Based IRF Market Basket

(1) Capital Price Proxies Prior to Vintage Weighting

We are proposing to continue to use the same price proxies for the capital-related cost categories in the proposed 2021-based IRF market basket as were used in the 2016-based IRF market basket, which are provided in Table 11 and described below. Specifically, we are proposing to proxy:

• Depreciation: Building and Fixed Equipment cost category by BEA's Chained Price Index for Nonresidential Construction for Hospitals and Special Care Facilities (BEA Table 5.4.4. Price Indexes for Private Fixed Investment in Structures by Type).
• Depreciation: Movable Equipment cost category by the PPI for Machinery and Equipment (BLS series code WPU11).
• Nonprofit Interest cost category by the average yield on domestic municipal bonds (Bond Buyer 20-bond index).
• For-profit Interest cost category by the iBoxx AAA Corporate Bond Yield index.
• Other Capital-Related cost category by the CPI–U for Rent of Primary Residence (BLS series code CUUS0000SEHA).

We believe these are the most appropriate proxies for IRF capital-related costs that meet our selection criteria of relevance, timeliness, availability, and reliability. We are also proposing to continue to vintage weight the capital price proxies for Depreciation and Interest to capture the long-term consumption of capital. This vintage weighting method is similar to the method used for the 2016-based IRF market basket (84 FR 39082) and is described below.

(2) Vintage Weights for Price Proxies

Because capital is acquired and paid for over time, capital-related expenses in any given year are determined by both past and present purchases of physical and financial capital. The vintage-weighted capital-related portion of the proposed 2021-based IRF market basket is intended to capture the long-term consumption of capital, using vintage weights for depreciation (physical capital) and interest (financial capital). These vintage weights reflect the proportion of capital-related purchases attributable to each year of the expected life of building and fixed equipment, movable equipment, and interest. We are proposing to use vintage weights to compute vintage-weighted price changes associated with depreciation and interest expenses.

Capital-related costs are inherently complicated and are determined by complex capital-related purchasing decisions, over time, based on such factors as interest rates and debt financing. In addition, capital is depreciated over time instead of being consumed in the same period it is purchased. By accounting for the vintage nature of capital, we are able to provide an accurate and stable annual measure of price changes. Annual non-vintage price changes for capital are unstable due to the volatility of interest rate changes, and therefore, do not reflect the actual annual price changes for IRF capital-related costs. The capital-related component of the proposed 2021-based IRF market basket reflects the underlying stability of the capital-related acquisition process.

The methodology used to calculate the vintage weights for the proposed 2021-based IRF market basket is the same as that used for the 2016-based IRF market basket (84 FR 39082 through 39083) with the only difference being the inclusion of more recent data. To calculate the vintage weights for depreciation and interest expenses, we first need a time series of capital-related purchases for building and fixed equipment and movable equipment. We found no single source that provides an appropriate time series of capital-related purchases by hospitals for all of the above components of capital purchases. The early Medicare cost reports did not have sufficient capital-related data to meet this need. Data we obtained from the American Hospital Association (AHA) do not include annual capital-related purchases. However, we are able to obtain data on total expenses back to 1963 from the AHA. Consequently, we are proposing to use data from the AHA Panel Survey and the AHA Annual Survey to obtain a time series of total expenses for hospitals. We are then proposing to use data from the AHA Panel Survey supplemented with the ratio of depreciation to total hospital expenses obtained from the Medicare cost reports to derive a trend of annual depreciation expenses for 1963 through 2020, which is the latest year of AHA data available. We propose to separate these depreciation expenses into annual amounts of building and fixed equipment depreciation and movable equipment depreciation as determined earlier. From these annual depreciation amounts, we derive annual end-of-year book values for building and fixed equipment and movable equipment using the expected life for each type of asset category. While data is not available that is specific to IRFs, we believe this information for all hospitals serves as a reasonable alternative for the pattern of depreciation for IRFs.

To continue to calculate the vintage weights for depreciation and interest expenses, we also need to account for the expected lives for Building and Fixed Equipment, Movable Equipment, and Interest for the proposed 2021-based IRF market basket. We are proposing to calculate the expected lives using Medicare cost report data from Worksheet A–7 part III for freestanding and hospital-based IRFs. The expected life of any asset can be determined by dividing the value of the asset (excluding fully depreciated assets) by its current year depreciation amount. This calculation yields the estimated expected life of an asset if the rates of depreciation were to continue at current year levels, assuming straight-line depreciation. We are proposing to determine the expected life of building and fixed equipment separately for hospital-based IRFs and freestanding IRFs, and then weight these expected lives using the percent of total capital costs each provider type represents. We are proposing to apply a similar method for movable equipment. Using these proposed methods, we determined the average expected life of building and fixed equipment to be equal to 25 years, and the average expected life of movable equipment to be equal to 12 years. For the expected life of interest, we believe vintage weights for interest should represent the average expected life of building and fixed equipment because, based on previous research described in the FY 1997 IPPS final rule (61 FR 46198), the expected life of hospital debt instruments and the expected life of buildings and fixed equipment are similar. We note that for the 2016-based IRF market basket, the expected life of building and fixed equipment is 22 years, and the expected life of movable equipment is 11 years (84 FR 39082) using the 2016 Medicare cost report data for freestanding and hospital-based IRFs.

Multiplying these expected lives by the annual depreciation amounts results in annual year-end asset costs for building and fixed equipment and movable equipment. We then calculate a time series, beginning in 1964, of annual capital purchases by subtracting the previous year's asset costs from the current year's asset costs.

For the building and fixed equipment and movable equipment vintage weights, we are proposing to use the real annual capital-related purchase amounts for each asset type to capture the actual amount of the physical acquisition, net of the effect of price inflation. These real annual capital-related purchase amounts are produced by deflating the nominal annual purchase amount by the associated price proxy as provided earlier in this proposed rule. For the interest vintage weights, we are proposing to use the total nominal annual capital-related purchase amounts to capture the value of the debt instrument (including, but not limited to, mortgages and bonds). Using these capital-related purchase time series specific to each asset type, we are proposing to calculate the vintage weights for building and fixed equipment, for movable equipment, and for interest.

The vintage weights for each asset type are deemed to represent the average purchase pattern of the asset over its expected life (in the case of building and fixed equipment and interest, 25 years, and in the case of movable equipment, 12 years). For each asset type, we used the time series of annual capital-related purchase amounts available from 2020 back to 1964. These data allow us to derive thirty-three 25-year periods of capital-related purchases for building and fixed equipment and interest, and forty-six 12-year periods of capital-related purchases for movable equipment. For each 25-year period for building and fixed equipment and interest, or 12-year period for movable equipment, we calculate annual vintage weights by dividing the capital-related purchase amount in any given year by the total amount of purchases over the entire 25-year or 12-year period. This calculation is done for each year in the 25-year or 12-year period and for each of the periods for which we have data. We then calculate the average vintage weight for a given year of the expected life by taking the average of these vintage weights across the multiple periods of data. The vintage weights for the capital-related portion of the proposed 2021-based IRF market basket and the 2016-based IRF market basket are presented in Table 10.

The process of creating vintage-weighted price proxies requires applying the vintage weights to the price proxy index where the last applied vintage weight in Table 10 is applied to the most recent data point. We have provided on the CMS website an example of how the vintage weighting price proxies are calculated, using example vintage weights and example price indices. The example can be found at http://www.cms.gov/​Research-Statistics-Data-and-Systems/​Statistics-Trends-and-Reports/​MedicareProgramRatesStats/​MarketBasketResearch.html in the zip file titled “Weight Calculations as described in the IPPS FY 2010 Proposed Rule.”

c. Summary of Price Proxies of the Proposed 2021-Based IRF Market Basket

Table 11 shows both the operating and capital price proxies for the proposed 2021-based IRF market base.

We invite public comment on our proposal to rebase and revise the IRF market basket to reflect a 2021 base year.

D. Proposed FY 2024 Market Basket Update and Productivity Adjustment

1. Proposed FY 2024 Market Basket Update

For FY 2024 (that is, beginning October 1, 2023 and ending September 30, 2024), we are proposing to use an estimate of the proposed 2021-based IRF market basket increase factor to update the IRF PPS base payment rate as required by section 1886(j)(3)(C)(i) of the Act. Consistent with historical practice, we are proposing to estimate the market basket update for the IRF PPS based on IHS Global Inc.'s (IGI's) forecast using the most recent available data. IGI is a nationally recognized economic and financial forecasting firm with which CMS contracts to forecast the components of the market baskets.

Based on IGI's fourth quarter 2022 forecast with historical data through the third quarter of 2022, the proposed 2021-based IRF market basket increase factor for FY 2024 is 3.2 percent. Therefore, consistent with our historical practice of estimating market basket increases based on the best available data, we are proposing a market basket increase factor of 3.2 percent for FY 2024. We are also proposing that if more recent data are subsequently available (for example, a more recent estimate of the market basket) we would use such data, if appropriate, to determine the FY 2024 update in the final rule. For comparison, the current 2016-based IRF market basket is also projected to increase by 3.2 percent in FY 2024 based on IGI's fourth quarter 2022 forecast. Table 12 compares the proposed 2021-based IRF market basket and the 2016-based IRF market basket percent changes. On average, the two indexes produce similar updates to one another, with the 4-year average historical growth rates (for FY 2019–FY 2022) of the proposed 2021-based IRF market basket being equal to 3.2 percent compared to the 2016-based IRF market basket with 3.1 percent.

Table 12—Proposed 2021-Based IRF Market Basket and 2016-Based IRF Market Basket Percent Changes, FY 2019 Through FY 2026

Fiscal year (FY)	Proposed 2021-based IRF market basket index percent change	2016-based IRF market basket index percent change
Historical data
FY 2019	2.4	2.3
FY 2020	2.1	2.1
FY 2021	2.8	2.7
FY 2022	5.3	5.3
Average 2019–2022	3.2	3.1
Forecast
FY 2023	4.6	4.6
FY 2024	3.2	3.2
FY 2025	2.9	2.9
FY 2026	2.8	2.8
Average 2023–2026	3.4	3.4
Note that these market basket percent changes do not include any further adjustments as may be statutorily required.
Source: IHS Global Inc. 4th quarter 2022 forecast.

2. Proposed Productivity Adjustment

According to section 1886(j)(3)(C)(i) of the Act, the Secretary shall establish an increase factor based on an appropriate percentage increase in a market basket of goods and services. Section 1886(j)(3)(C)(ii) of the Act then requires that, after establishing the increase factor for a FY, the Secretary shall reduce such increase factor for FY 2012 and each subsequent FY, 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 sets forth the definition of this productivity adjustment. The statute defines the productivity adjustment to be equal to the 10-year moving average of changes in annual economy-wide, private nonfarm business multifactor productivity (as projected by the Secretary for the 10-year period ending with the applicable FY, year, cost reporting period, or other annual period) (the “productivity adjustment”). The U.S. Department of Labor's Bureau of Labor Statistics (BLS) publishes the official measures of productivity for the U.S. economy. We note that previously the productivity measure referenced in 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 multifactor productivity (MFP) with total factor productivity (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) is now published by BLS as private nonfarm business total factor productivity. However, as mentioned above, the data and methods are unchanged. Please see www.bls.gov for the BLS historical published TFP data. A complete description of IGI's TFP projection methodology is available on the CMS website at https://www.cms.gov/​Research-Statistics-Dataand-Systems/​Statistics-Trends-andReports/​MedicareProgramRatesStats/​MarketBasketResearch. In addition, in the FY 2022 IRF final rule (86 FR 42374), we noted that effective with FY 2022 and forward, CMS changed the name of this adjustment to refer to it as the productivity adjustment rather than the MFP adjustment.

Using IGI's fourth quarter 2022 forecast, the 10-year moving average growth of TFP for FY 2024 is projected to be 0.2 percent. Thus, in accordance with section 1886(j)(3)(C) of the Act, we are proposing to calculate the FY 2024 market basket update, which is used to determine the applicable percentage increase for the IRF payments, using IGI's fourth quarter 2022 forecast of the proposed 2021-based IRF market basket. We are proposing to then reduce this percentage increase by the estimated productivity adjustment for FY 2024 of 0.2 percentage point (the 10-year moving average growth of TFP for the period ending FY 2024 based on IGI's fourth quarter 2022 forecast). Therefore, the proposed FY 2024 IRF update is equal to 3.0 percent (3.2 percent market basket update reduced by the 0.2 percentage point productivity adjustment). Furthermore, we are proposing that if more recent data become available after the publication of the proposed rule and before the publication of the final rule (for example, a more recent estimate of the market basket and/or productivity adjustment), we would use such data, if appropriate, to determine the FY 2024 market basket update and productivity adjustment in the final rule.

For FY 2024, the Medicare Payment Advisory Commission (MedPAC) recommends that we reduce IRF PPS payment rates by 5 percent. As discussed, and in accordance with sections 1886(j)(3)(C) and 1886(j)(3)(D) of the Act, the Secretary is proposing to update the IRF PPS payment rates for FY 2024 by a productivity-adjusted IRF market basket increase factor of 3.0 percent. Section 1886(j)(3)(C) of the Act does not provide the Secretary with the authority to apply a different update factor to IRF PPS payment rates for FY 2024.

We invite public comment on our proposals for the FY 2024 market basket update and productivity adjustment.

E. Proposed Labor-Related Share for FY 2024

Section 1886(j)(6) of the Act specifies that the Secretary is to adjust the proportion (as estimated by the Secretary from time to time) of inpatient rehabilitation facilities' costs that are attributable to wages and wage-related costs, of the prospective payment rates computed under section 1886(j)(3) of the Act for area differences in wage levels by a factor (established by the Secretary) reflecting the relative hospital wage level in the geographic area of the rehabilitation facility compared to the national average wage level for such facilities. The labor-related share is determined by identifying the national average proportion of total costs that are related to, influenced by, or vary with the local labor market. We propose to continue to classify a cost category as labor-related if the costs are labor-intensive and vary with the local labor market. As stated in the FY 2020 IRF PPS final rule (84 FR 39087), the labor-related share was defined as the sum of the relative importance of Wages and Salaries, Employee Benefits, Professional Fees: Labor-related Services, Administrative and Facilities Support Services, Installation, Maintenance, and Repair Services, All Other: Labor-related Services, and a portion of the Capital Costs from the 2016-based IRF market basket.

Based on our definition of the labor-related share and the cost categories in the proposed 2021-based IRF market basket, we are proposing to include in the labor-related share for FY 2024 the sum of the FY 2024 relative importance of 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 the Capital-Related cost weight from the proposed 2021-based IRF market basket.

Similar to the 2016-based IRF market basket (84 FR 39087), the proposed 2021-based IRF market basket includes two cost categories for nonmedical Professional Fees (including, but not limited to, expenses for legal, accounting, and engineering services). These are Professional Fees: Labor-related and Professional Fees: Nonlabor-related. For the proposed 2021-based IRF market basket, we propose to estimate the labor-related percentage of non-medical professional fees (and assign these expenses to the Professional Fees: Labor-related services cost category) based on the same method that was used to determine the labor-related percentage of professional fees in the 2016-based IRF market basket.

As was done in the 2016-based IRF market basket (84 FR 39087), we propose to determine the proportion of legal, accounting and auditing, engineering, and management consulting services that meet our definition of labor-related services based on a survey of hospitals conducted by us in 2008, a discussion of which can be found in the FY 2010 IPPS/LTCH PPS final rule (74 FR 43850 through 43856). Based on the weighted results of the survey, we determined that hospitals purchase, on average, the following portions of contracted professional services outside of their local labor market:

• 34 percent of accounting and auditing services.
• 30 percent of engineering services.
• 33 percent of legal services.
• 42 percent of management consulting services.

We are proposing to apply each of these percentages to the respective Benchmark I–O cost category underlying the professional fees cost category to determine the Professional Fees: Nonlabor-related costs. The Professional Fees: Labor-related costs were determined to be the difference between the total costs for each Benchmark I–O category and the Professional Fees: Nonlabor-related costs. This is the same methodology that we used to separate the 2016-based IRF market basket professional fees category into Professional Fees: Labor-related and Professional Fees: Nonlabor-related cost categories (84 FR 39087).

Effective for transmittal 18 ( https://www.cms.gov/​Regulations-and-Guidance/​Guidance/​Transmittals/​Transmittals/​r18p240i), the hospital Medicare Cost Report (CMS Form 2552–10, OMB No. 0938–0050) is collecting information on whether a hospital purchased professional services (for example, legal, accounting, tax preparation, bookkeeping, payroll, advertising, and/or management/consulting services) from an unrelated organization and if the majority of these expenses were purchased from unrelated organizations located outside of the main hospital's local area labor market. We encourage all providers to provide this information so we can potentially use in future rulemaking to determine the labor-related share.

In the proposed 2021-based IRF market basket, nonmedical professional fees that are subject to allocation based on these survey results represent 4.0 percent of total costs (and are limited to those fees related to Accounting & Auditing, Legal, Engineering, and Management Consulting services). Based on our survey results, we propose to apportion approximately 2.6 percentage points of the 4.0 percentage point figure into the Professional Fees: Labor-related share cost category and designate the remaining 1.4 percentage point into the Professional Fees: Nonlabor-related cost category.

In addition to the professional services listed, for the 2021-based IRF market basket, we are proposing to allocate a proportion of the Home Office/Related Organization Contract Labor cost weight, calculated using the Medicare cost reports as stated above, into the Professional Fees: Labor-related and Professional Fees: Nonlabor-related cost categories. We are proposing to classify these expenses as labor-related and nonlabor-related as many facilities are not located in the same geographic area as their home office, and therefore, do not meet our definition for the labor-related share that requires the services to be purchased in the local labor market.

Similar to the 2016-based IRF market basket, we are proposing for the 2021-based IRF market basket to use the Medicare cost reports for both freestanding IRF providers and hospital-based IRF providers to determine the home office labor-related percentages. The Medicare cost report requires a hospital to report information regarding their home office provider. For the proposed 2021-based IRF market basket, we are proposing to start with the sample of IRF providers that passed the top 1 percent trim used to derive the Home Office/Related Organization Contract Labor cost weight as described in section V.C.1.b. of this proposed rule. Using information on the Medicare cost report, for freestanding and hospital-based providers separately, we first compare the location of the IRF with the location of the IRF's home office and classify an IRF based on whether their home office is located in the hospital facility's same Metropolitan Statistical Area. For both freestanding and hospital-based providers, we are proposing to multiply each provider's Home Office/Related Organization Contract Labor cost weight (calculated using data from the total facility) by Medicare allowable total costs. We then calculate the proportion of Medicare allowable home office compensation costs that these IRFs represent of total Medicare allowable home office compensation costs. We propose to multiply this percentage (45 percent) by the Home Office/Related Organization Contract Labor cost weight (5.4 percent) to determine the proportion of costs that should be allocated to the labor-related share. Therefore, we are allocating 2.4 percentage points of the Home Office/Related Organization Contract Labor cost weight (5.4 percent times 45 percent) to the Professional Fees: Labor-related cost weight and 3.0 percentage points of the Home Office/Related Organization Contract Labor cost weight to the Professional Fees: Nonlabor-related cost weight (5.4 percent times 55 percent). For the 2016-based IRF market basket, we used a similar methodology (84 FR 39088) and determined that 42 percent of the 2016-based Home Office/Related Organization Contract Labor cost weight should be allocated to the labor-related share.

In summary, we apportioned 2.6 percentage points of the non-medical professional fees and 2.4 percentage points of the Home Office/Related Organization Contract Labor cost weight into the Professional Fees: Labor-related cost category. This amount was added to the portion of professional fees that was identified to be labor-related using the I–O data such as contracted advertising and marketing costs (approximately 0.6 percentage point of total costs) resulting in a Professional Fees: Labor-related cost weight of 5.6 percent.

As stated previously, we are proposing to include in the labor-related share the sum of the relative importance of 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 the Capital-Related cost weight from the proposed 2021-based IRF market basket. The relative importance reflects the different rates of price change for these cost categories between the base year (2021) and FY 2024. Based on IGI's fourth quarter 2022 forecast for the proposed 2021-based IRF market basket, the sum of the FY 2024 relative importance for Wages and Salaries, Employee Benefits, Professional Fees: Labor-related, Administrative and Facilities Support Services, Installation Maintenance & Repair Services, and All Other: Labor-related Services is 70.3 percent. The portion of Capital costs that is influenced by the local labor market is estimated to be 46 percent, which is the same percentage applied to the 2016-based IRF market basket (84 FR 39088 through 39089). Since the relative importance for Capital is 8.2 percent of the proposed 2021-based IRF market basket in FY 2024, we took 46 percent of 8.2 percent to determine the proposed labor-related share of Capital for FY 2024 of 3.8 percent. Therefore, we are proposing a total labor-related share for FY 2024 of 74.1 percent (the sum of 70.3 percent for the operating costs and 3.8 percent for the labor-related share of Capital). Table 13 shows the FY 2024 labor-related share using the proposed 2021-based IRF market basket relative importance and the FY 2023 labor-related share using the 2016-based IRF market basket relative importance.

Table 13—Proposed FY 2024 IRF Labor-Related Share and FY 2023 IRF Labor-Related Share

	FY 2024 proposed labor-related share 1	FY 2023 final labor related share 2
Wages and Salaries	48.9	48.7
Employee Benefits	11.9	11.3
Professional Fees: Labor-related 3	5.5	4.9
Administrative and Facilities Support Services	0.7	0.8
Installation, Maintenance, and Repair Services	1.5	1.6
All Other: Labor-related Services	1.8	1.9
Subtotal	70.3	69.2
Labor-related portion of capital (46%)	3.8	3.7
Total Labor-Related Share	74.1	72.9
1  Based on the proposed 2021-based IRF Market Basket, IHS Global, Inc. 4th quarter 2022 forecast.
2  Based on the 2016-based IRF market basket as published in the Federal Register (87 FR 47052).
3  Includes all contract advertising and marketing costs and a portion of accounting, architectural, engineering, legal, management consulting, and home office/related organization contract labor costs.

The FY 2024 labor-related share using the proposed 2021-based IRF market basket is 1.2 percentage point higher than the FY 2023 labor-related share using the 2016-based IRF market basket. This higher labor-related share is primarily due to the incorporation of the 2021 Medicare cost report data, which increased the Compensation cost weight by approximately 0.8 percentage point compared to the 2016-based IRF market basket as shown in Table 4 and Table 5 in section V.C.1.b. of this proposed rule.

We invite public comment on the proposed labor-related share for FY 2024.

F. Proposed Wage Adjustment for FY 2024

1. Background

Section 1886(j)(6) of the Act requires the Secretary to adjust the proportion of rehabilitation facilities' costs attributable to wages and wage-related costs (as estimated by the Secretary from time to time) by a factor (established by the Secretary) reflecting the relative hospital wage level in the geographic area of the rehabilitation facility compared to the national average wage level for those facilities. The Secretary is required to update the IRF PPS wage index on the basis of information available to the Secretary on the wages and wage-related costs to furnish rehabilitation services. Any adjustment or updates made under section 1886(j)(6) of the Act for a FY are made in a budget-neutral manner.

In the FY 2023 IRF PPS final rule (87 FR 47054 through 47056) we finalized a policy to apply a 5-percent cap on any decrease 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 IRF 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 IRF would not have a wage index in the prior FY. Also, in the FY 2023 IRF PPS final rule, we amended the regulations at § 412.624(e)(1)(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 IRF PPS final rule.

For FY 2024, we propose to maintain the policies and methodologies described in the FY 2023 IRF PPS final rule (87 FR 47038) related to the labor market area definitions and the wage index methodology for areas with wage data. Thus, we propose to use the core based statistical areas (CBSAs) labor market area definitions and the FY 2024 pre-reclassification and pre-floor hospital wage index data. In accordance with section 1886(d)(3)(E) of the Act, the FY 2024 pre-reclassification and pre-floor hospital wage index is based on data submitted for hospital cost reporting periods beginning on or after October 1, 2019, and before October 1, 2020 (that is, FY 2020 cost report data).

The labor market designations made by the OMB include some geographic areas where there are no hospitals and, thus, no hospital wage index data on which to base the calculation of the IRF PPS wage index. We propose to continue to use the same methodology discussed in the FY 2008 IRF PPS final rule (72 FR 44299) to address those geographic areas where there are no hospitals and, thus, no hospital wage index data on which to base the calculation for the FY 2024 IRF PPS wage index.

We invite public comment on our proposals regarding the Wage Adjustment for FY 2024.

2. Core-Based Statistical Areas (CBSAs) for the FY 2024 IRF Wage Index

The wage index used for the IRF PPS is calculated using the pre-reclassification and pre-floor inpatient PPS (IPPS) wage index data and is assigned to the IRF on the basis of the labor market area in which the IRF is geographically located. IRF labor market areas are delineated based on the CBSAs established by the OMB. The CBSA delineations (which were implemented for the IRF PPS beginning with FY 2016) are based on revised OMB delineations issued on February 28, 2013, in OMB Bulletin No. 13–01. 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). We refer readers to the FY 2016 IRF PPS final rule (80 FR 47068 through 47076) for a full discussion of our implementation of the OMB labor market area delineations beginning with the FY 2016 wage index.

Generally, OMB issues major revisions to statistical areas every 10 years, based on the results of the decennial census. Additionally, OMB occasionally issues updates and revisions to the statistical areas in between decennial censuses to reflect the recognition of new areas or the addition of counties to existing areas. In some instances, these updates merge formerly separate areas, transfer components of an area from one area to another, or drop components from an area. On July 15, 2015, OMB issued OMB Bulletin No. 15–01, which provides minor updates to and supersedes OMB Bulletin No. 13–01 that was issued on February 28, 2013. The attachment to OMB Bulletin No. 15–01 provides detailed information on the update to statistical areas since February 28, 2013. The updates provided in OMB Bulletin No. 15–01 are 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.

In the FY 2018 IRF PPS final rule (82 FR 36250 through 36251), we adopted the updates set forth in OMB Bulletin No. 15–01 effective October 1, 2017, beginning with the FY 2018 IRF wage index. For a complete discussion of the adoption of the updates set forth in OMB Bulletin No. 15–01, we refer readers to the FY 2018 IRF PPS final rule. In the FY 2019 IRF PPS final rule (83 FR 38527), we continued to use the OMB delineations that were adopted beginning with FY 2016 to calculate the area wage indexes, with updates set forth in OMB Bulletin No. 15–01 that we adopted beginning with the FY 2018 wage index.

On August 15, 2017, OMB issued OMB Bulletin No. 17–01, which provided updates to and superseded OMB Bulletin No. 15–01 that was issued on July 15, 2015. The attachments to OMB Bulletin No. 17–01 provide detailed information on the update to statistical areas since July 15, 2015, and are based on the application of the 2010 Standards for Delineating Metropolitan and Micropolitan Statistical Areas to Census Bureau population estimates for July 1, 2014 and July 1, 2015. In the FY 2020 IRF PPS final rule (84 FR 39090 through 39091), we adopted the updates set forth in OMB Bulletin No. 17–01 effective October 1, 2019, beginning with the FY 2020 IRF wage index.

On April 10, 2018, OMB issued OMB Bulletin No. 18–03, which superseded the August 15, 2017 OMB Bulletin No. 17–01, and on September 14, 2018, OMB issued OMB Bulletin No. 18–04, which superseded the April 10, 2018 OMB Bulletin No. 18–03. These bulletins established revised delineations for Metropolitan Statistical Areas, Micropolitan Statistical Areas, and Combined Statistical Areas, and provided guidance on the use of the delineations of these statistical areas. A copy of this bulletin may be obtained at https://www.whitehouse.gov/​wp-content/​uploads/​2018/​09/​Bulletin-18-04.pdf.

To this end, as discussed in the FY 2021 IRF PPS proposed (85 FR 22075 through 22079) and final (85 FR 48434 through 48440) 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) beginning October 1, 2020, including a 1-year transition for FY 2021 under which we applied a 5 percent cap on any decrease in an IRF'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 IRF PPS. 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.

3. IRF Budget-Neutral Wage Adjustment Factor Methodology

To calculate the wage-adjusted facility payment for the payment rates set forth in this proposed rule, we multiply the proposed unadjusted Federal payment rate for IRFs by the FY 2024 labor-related share based on the proposed 2021-based IRF market basket relative importance (74.1 percent) to determine the labor-related portion of the standard payment amount. A full discussion of the calculation of the labor-related share is located in section V.E. of this proposed rule. We would then multiply the labor-related portion by the applicable IRF wage index. The wage index tables are available on the CMS website at https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​InpatientRehabFacPPS/​IRF-Rules-and-Related-Files.html.

Adjustments or updates to the IRF wage index made under section 1886(j)(6) of the Act must be made in a budget-neutral manner. We propose to calculate a budget-neutral wage adjustment factor as established in the FY 2004 IRF PPS final rule (68 FR 45689) and codified at § 412.624(e)(1), as described in the steps below. We propose to use the listed steps to ensure that the FY 2024 IRF standard payment conversion factor reflects the proposed update to the wage indexes (based on the FY 2020 hospital cost report data) and the proposed update to the labor-related share, in a budget-neutral manner:

Step 1. Calculate the total amount of estimated IRF PPS payments using the labor-related share and the wage indexes from FY 2023 (as published in the FY 2023 IRF PPS final rule (87 FR 47038)).

Step 2. Calculate the total amount of estimated IRF PPS payments using the FY 2024 wage index values (based on updated hospital wage data and considering the permanent cap on wage index decreases policy) and the proposed FY 2024 labor-related share of 74.1 percent.

Step 3. Divide the amount calculated in step 1 by the amount calculated in step 2. The resulting quotient is the proposed FY 2024 budget-neutral wage adjustment factor of 1.0032.

Step 4. Apply the budget neutrality factor from step 3 to the FY 2024 IRF PPS standard payment amount after the application of the increase factor to determine the proposed FY 2024 standard payment conversion factor.

We discuss the calculation of the standard payment conversion factor for FY 2024 in section V.G. of this proposed rule.

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

G. Description of the Proposed IRF Standard Payment Conversion Factor and Payment Rates for FY 2024

To calculate the proposed standard payment conversion factor for FY 2024, as illustrated in Table 14, we begin by applying the proposed increase factor for FY 2024, as adjusted in accordance with sections 1886(j)(3)(C) of the Act, to the standard payment conversion factor for FY 2023 ($17,878). Applying the proposed 3.0 percent increase factor for FY 2024 to the standard payment conversion factor for FY 2023 of $17,878 yields a standard payment amount of $18,414. Then, we apply the proposed budget neutrality factor for the FY 2024 wage index (taking into account the permanent cap on wage index decreases policy), and labor-related share of 1.0032, which results in a standard payment amount of $18,473. We next apply the proposed budget neutrality factor for the CMG relative weights of 0.9999, which results in the standard payment conversion factor of $18,471 for FY 2024.

We invite public comment on the proposed FY 2024 standard payment conversion factor.

Table 14—Calculations To Determine the Proposed FY 2024 Standard Payment Conversion Factor

Explanation for adjustment	Calculations
Standard Payment Conversion Factor for FY 2023	$17,878
Proposed Market Basket Increase Factor for FY 2024 (3.2%), reduced by 0.2 percentage point for the productivity adjustment as required by section 1886(j)(3)(C)(ii)(I) of the Act	× 1.030
Budget Neutrality Factor for the Updates to the Wage Index and Labor-Related Share	× 1.0032
Budget Neutrality Factor for the Revisions to the CMG Relative Weights	× 0.9999
Proposed FY 2024 Standard Payment Conversion Factor	= 18,471

After the application of the proposed CMG relative weights described in section IV. of this proposed rule to the FY 2024 standard payment conversion factor ($18,471), the resulting unadjusted IRF prospective payment rates for FY 2024 are shown in Table 15.

H. Example of the Methodology for Adjusting the Proposed Prospective Payment Rates

Table 16 illustrates the methodology for adjusting the proposed prospective payments (as described in section V. of this proposed rule). The following examples are based on two hypothetical Medicare beneficiaries, both classified into CMG 0104 (without comorbidities). The proposed unadjusted prospective payment rate for CMG 0104 (without comorbidities) appears in Table 16.

Example: One beneficiary is in Facility A, an IRF located in rural Spencer County, Indiana, and another beneficiary is in Facility B, an IRF located in urban Harrison County, Indiana. Facility A, a rural non-teaching hospital has a Disproportionate Share Hospital (DSH) percentage of 5 percent (which would result in a LIP adjustment of 1.0156), a wage index of 0.8353, and a rural adjustment of 14.9 percent. Facility B, an urban teaching hospital, has a DSH percentage of 15 percent (which would result in a LIP adjustment of 1.0454 percent), a wage index of 0.8804, and a teaching status adjustment of 0.0784.

To calculate each IRF's labor and non-labor portion of the proposed prospective payment, we begin by taking the unadjusted prospective payment rate for CMG 0104 (without comorbidities) from Table 16. Then, we multiply the proposed labor-related share for FY 2024 (74.1 percent) described in section V.E. of this proposed rule by the unadjusted prospective payment rate. To determine the non-labor portion of the proposed prospective payment rate, we subtract the labor portion of the Federal payment from the proposed unadjusted prospective payment.

To compute the proposed wage-adjusted prospective payment, we multiply the labor portion of the proposed Federal payment by the appropriate wage index located in the applicable wage index table. This table is available on the CMS website at https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​InpatientRehabFacPPS/​IRF-Rules-and-Related-Files.html.

The resulting figure is the wage-adjusted labor amount. Next, we compute the proposed wage-adjusted Federal payment by adding the wage-adjusted labor amount to the non-labor portion of the proposed Federal payment.

Adjusting the proposed wage-adjusted Federal payment by the facility-level adjustments involves several steps. First, we take the wage-adjusted prospective payment and multiply it by the appropriate rural and LIP adjustments (if applicable). Second, to determine the appropriate amount of additional payment for the teaching status adjustment (if applicable), we multiply the teaching status adjustment (0.0784, in this example) by the wage-adjusted and rural-adjusted amount (if applicable). Finally, we add the additional teaching status payments (if applicable) to the wage, rural, and LIP-adjusted prospective payment rates. Table 16 illustrates the components of the adjusted payment calculation.

Table 16—Example of Computing the FY 2024 IRF Prospective Payment

Steps	Rural Facility A (Spencer Co., IN)		Urban Facility B (Harrison Co., IN)
1 Unadjusted Payment		$28,870.17		$28,870.17
2 Labor-Related Share	×	0.741	×	0.741
3 Labor Portion of Payment	=	$21,392.80	=	$21,392.80
4 CBSA-Based Wage Index	×	0.8353	×	0.8804
5 Wage-Adjusted Amount	=	$17,869.40	=	$18,834.22
6 Non-Labor Amount	+	$7,477.37	+	$7,477.37
7 Wage-Adjusted Payment	=	$25,346.78	=	$26,311.59
8 Rural Adjustment	×	1.149	×	1.000
9 Wage- and Rural-Adjusted Payment	=	$29,123.45	=	$26,311.59
10 LIP Adjustment	×	1.0156	×	1.0454
11 Wage-, Rural- and LIP-Adjusted Payment	=	$29,577.77	=	$27,506.14
12 Wage- and Rural-Adjusted Payment		$29,123.45		$26,311.59
13 Teaching Status Adjustment	×	0	×	0.0784
14 Teaching Status Adjustment Amount	=	$0.00	=	$2,062.83
15 Wage-, Rural-, and LIP-Adjusted Payment	+	$29,577.77	+	$27,506.14
16 Total Adjusted Payment	=	$29,577.77	=	$29,568.97

Thus, the proposed adjusted payment for Facility A would be $29,577.77, and the proposed adjusted payment for Facility B would be $29,568.97.

VI. Proposed Update to Payments for High-Cost Outliers Under the IRF PPS for FY 2024

A. Update to the Outlier Threshold Amount for FY 2024

Section 1886(j)(4) of the Act provides the Secretary with the authority to make payments in addition to the basic IRF prospective payments for cases incurring extraordinarily high costs. A case qualifies for an outlier payment if the estimated cost of the case exceeds the adjusted outlier threshold. We calculate the adjusted outlier threshold by adding the IRF PPS payment for the case (that is, the CMG payment adjusted by all of the relevant facility-level adjustments) and the adjusted threshold amount (also adjusted by all of the relevant facility-level adjustments). Then, we calculate the estimated cost of a case by multiplying the IRF's overall CCR by the Medicare allowable covered charge. If the estimated cost of the case is higher than the adjusted outlier threshold, we make an outlier payment for the case equal to 80 percent of the difference between the estimated cost of the case and the outlier threshold.

In the FY 2002 IRF PPS final rule (66 FR 41362 through 41363), we discussed our rationale for setting the outlier threshold amount for the IRF PPS so that estimated outlier payments would equal 3 percent of total estimated payments. For the FY 2002 IRF PPS final rule, we analyzed various outlier policies using 3, 4, and 5 percent of the total estimated payments, and we concluded that an outlier policy set at 3 percent of total estimated payments would optimize the extent to which we could reduce the financial risk to IRFs of caring for high-cost patients, while still providing for adequate payments for all other (non-high cost outlier) cases.

Subsequently, we updated the IRF outlier threshold amount in the FYs 2006 through 2023 IRF PPS final rules and the FY 2011 and FY 2013 notices (70 FR 47880, 71 FR 48354, 72 FR 44284, 73 FR 46370, 74 FR 39762, 75 FR 42836, 76 FR 47836, 76 FR 59256, 77 FR 44618, 78 FR 47860, 79 FR 45872, 80 FR 47036, 81 FR 52056, 82 FR 36238, 83 FR 38514, 84 FR 39054, 85 FR 48444, 86 FR 42362, and 87 FR 47038, respectively) to maintain estimated outlier payments at 3 percent of total estimated payments. We also stated in the FY 2009 final rule (73 FR 46370 at 46385) that we would continue to analyze the estimated outlier payments for subsequent years and adjust the outlier threshold amount as appropriate to maintain the 3 percent target.

To update the IRF outlier threshold amount for FY 2024, we propose to use FY 2022 claims data and the same methodology that we used to set the initial outlier threshold amount in the FY 2002 IRF PPS final rule (66 FR 41362 through 41363), which is also the same methodology that we used to update the outlier threshold amounts for FYs 2006 through 2023. The outlier threshold is calculated by simulating aggregate payments and using an iterative process to determine a threshold that results in outlier payments being equal to 3 percent of total payments under the simulation. To determine the outlier threshold for FY 2024, we estimated the amount of FY 2024 IRF PPS aggregate and outlier payments using the most recent claims available (FY 2022) and the proposed FY 2024 standard payment conversion factor, labor-related share, and wage indexes, incorporating any applicable budget-neutrality adjustment factors. The outlier threshold is adjusted either up or down in this simulation until the estimated outlier payments equal 3 percent of the estimated aggregate payments. Based on an analysis of the preliminary data used for the proposed rule, we estimated that IRF outlier payments as a percentage of total estimated payments would be approximately 2.3 percent in FY 2023. Therefore, we propose to update the outlier threshold amount from $12,526 for FY 2023 to $9,690 for FY 2024 to maintain estimated outlier payments at approximately 3 percent of total estimated aggregate IRF payments for FY 2024. Furthermore, we are proposing that if more recent data become available after the publication of the proposed rule and before the publication of the final rule, we would use such data, if appropriate, to determine the FY 2024 outlier threshold amount in the final rule.

B. Proposed Update to the IRF Cost-to-Charge Ratio Ceiling and Urban/Rural Averages for FY 2024

CCRs are used to adjust charges from Medicare claims to costs and are computed annually from facility-specific data obtained from MCRs. IRF specific CCRs are used in the development of the CMG relative weights and the calculation of outlier payments under the IRF PPS. In accordance with the methodology stated in the FY 2004 IRF PPS final rule (68 FR45692 through 45694), we propose to apply a ceiling to IRFs' CCRs. Using the methodology described in that final rule, we propose to update the national urban and rural CCRs for IRFs, as well as the national CCR ceiling for FY 2024, based on analysis of the most recent data available. We apply the national urban and rural CCRs in the following situations:

• New IRFs that have not yet submitted their first MCR.
• IRFs whose overall CCR is in excess of the national CCR ceiling for FY 2024, as discussed below in this section.
• Other IRFs for which accurate data to calculate an overall CCR are not available.

Specifically, for FY 2024, we propose to estimate a national average CCR of 0.487 for rural IRFs, which we calculated by taking an average of the CCRs for all rural IRFs using their most recently submitted cost report data. Similarly, we propose to estimate a national average CCR of 0.398 for urban IRFs, which we calculated by taking an average of the CCRs for all urban IRFs using their most recently submitted cost report data. We apply weights to both of these averages using the IRFs' estimated costs, meaning that the CCRs of IRFs with higher total costs factor more heavily into the averages than the CCRs of IRFs with lower total costs. For this proposed rule, we have used the most recent available cost report data (FY 2021). This includes all IRFs whose cost reporting periods begin on or after October 1, 2020, and before October 1, 2021. If, for any IRF, the FY 2021 cost report was missing or had an “as submitted” status, we used data from a previous FY's (that is, FY 2004 through FY 2020) settled cost report for that IRF. We do not use cost report data from before FY 2004 for any IRF because changes in IRF utilization since FY 2004 resulting from the 60 percent rule and IRF medical review activities suggest that these older data do not adequately reflect the current cost of care. Using updated FY 2021 cost report data for this proposed rule, we estimate a national average CCR of 0.487 for rural IRFs, and a national average CCR of 0.398 for urban IRFs.

In accordance with past practice, we propose to set the national CCR ceiling at 3 standard deviations above the mean CCR. Using this method, we propose a national CCR ceiling of 1.45 for FY 2024. This means that, if an individual IRF's CCR were to exceed this ceiling of 1.45 for FY 2024, we will replace the IRF's CCR with the appropriate proposed national average CCR (either rural or urban, depending on the geographic location of the IRF). We calculated the proposed national CCR ceiling by:

Step 1. Taking the national average CCR (weighted by each IRF's total costs, as previously discussed) of all IRFs for which we have sufficient cost report data (both rural and urban IRFs combined).

Step 2. Estimating the standard deviation of the national average CCR computed in step 1.

Step 3. Multiplying the standard deviation of the national average CCR computed in step 2 by a factor of 3 to compute a statistically significant reliable ceiling.

Step 4. Adding the result from step 3 to the national average CCR of all IRFs for which we have sufficient cost report data, from step 1.

We are also proposing that if more recent data become available after the publication of this proposed rule and before the publication of the final rule, we would use such data to determine the FY 2024 national average rural and urban CCRs and the national CCR ceiling in the final rule.

We invite public comment on the proposed update to the IRF CCR ceiling and the urban/rural averages for FY 2024.

VII. Proposed Modification to the Regulation for Excluded Inpatient Rehabilitation Facility Units Paid Under the IRF PPS

A. Background

Under current regulation, to be excluded from the IPPS, and to be paid under the IRF PPS or the IPF PPS, an IRF or IPF unit of a hospital must meet a number of requirements under § 412.25. Both this regulation and the policies applying to excluded units (which include excluded IRF units and excluded IPF units) have been in effect since before both the IRF PPS and IPF PPS were established, as discussed in the following paragraphs of this section. Before the IRF PPS and the IPF PPS were established, excluded units were paid based on their costs, as reported on their Medicare cost reports, subject to certain facility-specific cost limits. These cost-based payments were determined separately for operating and capital costs. Thus, under cost-based payments, the process of allocating costs to an IRF or IPF unit for reimbursement created significant administrative complexity. This administrative complexity necessitated strict regulations that allowed hospitals to open a new IPPS-excluded unit only at the start of a cost reporting period.

In the January 3, 1984 final rule (49 FR 235), CMS (then known as the Health Care Financing Administration) established policies and regulations for hospitals and units subject to and excluded from the IPPS. In that rule, we explained that section 1886(d) of the Act requires that the prospective payment system apply to inpatient hospital services furnished by all hospitals participating in the Medicare program except those hospitals or units specifically excluded by the law. We further explained our expectation that a hospital's status (that is, whether it is subject to, or excluded from, the prospective payment system) would generally be determined at the beginning of each cost reporting period. We also stated that this status would continue throughout the period, which is normally 1 year. Accordingly, we stated that changes in a hospital's (or unit's) status that result from meeting or failing to meet the criteria for exclusion would be implemented only at the start of a cost reporting period. However, we also acknowledged that under some circumstances involving factors external to the hospital, status changes could be made at times other than the beginning of the cost reporting period. For example, a change in status could occur if a hospital is first included under the prospective payment system and, after the start of its cost reporting period, is excluded because of its participation in an approved demonstration project or State reimbursement control program that begins after the hospital's cost reporting period has begun.

In the FY 1993 IPPS final rule (57 FR 39798 through 39799), we codified our longstanding policies regarding when a hospital unit can change its status from not excluded to excluded. We explained in that final rule that since the inception of the prospective payment system for operating costs of hospital inpatient services in October 1983, certain types of specialty-care hospitals and hospital units have been excluded from that system under section 1888(d)(1)(B) of the Act. We noted that these currently include psychiatric and rehabilitation hospitals and distinct part units, children's hospitals, and long-term care hospitals. We further explained that section 6004(a)(1) of the Omnibus Budget Reconciliation Act of 1989, (Pub. L. 101–239, enacted December 19, 1989) amended section 1886(d)(1)(B) of the Act to provide that certain cancer hospitals are also excluded. We noted that the preamble to the January 3,1984 final rule implementing the prospective payment system for operating costs (49 FR 235) stated that the status of a hospital or unit (that is, whether it is subject to, or excluded from, the prospective payment system) will be determined at the beginning of each cost reporting period. We noted that that same 1984 final rule also provided that changes in a hospital's or unit's status that result from meeting or failing to meet the criteria for exclusion will be implemented prospectively only at the start of a cost reporting period, that is, starting with the beginning date of the next cost reporting period (49 FR 243). However, we noted that this policy was not set forth in the regulations. In the FY 1993 final rule, we stated that we proposed revising §§ 412.22 and 412.25 to specify that changes in the status of each hospital or hospital unit would be recognized only at the start of a cost reporting period. We stated that except in the case of retroactive payment adjustments for excluded rehabilitation units described in § 412.30(c), any change in a hospital's or unit's compliance with the exclusion criteria that occurs after the start of a cost reporting period would not be considered until the start of the following period. We noted that this policy would also apply to any unit that is added to a hospital during the hospital's cost reporting period. We also stated that we proposed revising § 412.25(a) to specify that as a requirement for exclusion, a hospital unit must be fully equipped and staffed, and be capable of providing inpatient psychiatric or rehabilitation care, as of the first day of the first cost reporting period for which all other exclusion requirements are met. We explained that a unit that meets this requirement would be considered open regardless of whether there are any inpatients in the unit.

In the same FY 1993 IPPS final rule, we responded to commenters who objected to this policy, stating that it unnecessarily penalizes hospitals for factors beyond their control, such as construction delays, that it discourages hospitals from making changes in their programs to meet community needs, or that it can place undue workload demands on regulatory agencies during certain time periods. In response, we explained that we believed that regulatory agencies, hospitals, and the public generally would benefit from policies that are clearly stated, can be easily understood by both hospitals and intermediaries, and can be simply administered. We stated that recognizing changes in status only at the beginning of cost reporting periods is consistent with these goals, while recognizing changes in the middle of cost reporting periods would introduce added complexity to the administration of the exclusion provisions. Therefore, we did not revise the proposed changes based on these comments.

In the FY 2000 IPPS final rule (64 FR 41531 through 41532), we amended the regulations at § 412.25(c) to allow a hospital unit to change from excluded to not excluded at any time during the cost reporting period. We explained the statutory basis and rationale for this change in the FY 2000 IPPS proposed rule (64 FR 24740), and noted that a number of hospitals suggested that we consider a change in our policy to recognize, for purposes of exclusion from the IPPS, reductions in number of beds in, or entire closure of, units at any time during a cost reporting period. In that FY 2000 IPPS proposed rule, we explained that hospitals indicated that the bed capacity made available as a result of these changes could be used, as they need them, to provide additional services to meet patient needs in the acute care part of the hospital that is paid under the IPPS. We further explained that we evaluated the concerns of the hospitals and the effect on the administration of the Medicare program and the health care of beneficiaries of making these payment changes. As a result of that evaluation, we stated that we believed it was reasonable to adopt a more flexible policy in recognition of hospitals' changes in the use of their facilities. However, we noted that whenever a hospital establishes an excluded unit within the hospital, our Medicare fiscal intermediary would need to be able to determine costs of the unit separately from costs of the part of the hospital paid under the prospective payment system. At that time, we stated that the proper determination of costs ensured that the hospital was paid the correct amount for services in each part of the facility, and that payments under the IPPS did not duplicate payments made under the rules that were applicable to excluded hospitals and units, or vice versa. For this reason, we stated that we did not believe it would be appropriate to recognize, for purposes of exclusion from the IPPS, changes in the bed size or status of an excluded unit that are so frequent that they interfere with the ability of the intermediary to accurately determine costs. Moreover, we explained that section 1886(d)(1)(B) of the Act authorizes exclusion from the IPPS of specific types of hospitals and units, but not of specific admissions or stays, such as admissions for rehabilitation or psychiatric care, in a hospital paid under the IPPS. We stated that without limits on the frequency of changes in excluded units for purposes of proper Medicare payment, there was the potential for some hospitals to adjust the status or size of their excluded units so frequently that the units would no longer be distinct entities and the exclusion would effectively apply only to certain types of care.

In the FY 2012 IRF PPS final rule (76 FR 47870), we began further efforts to increase flexibilities for excluded IPF and IRF units. In that rule, we explained that cost-based reimbursement methodologies that were in place before the IPF PPS and IRF PPS meant that the facilities' capital costs were determined, in part, by their bed size and square footage. Changes in the bed size and square footage would complicate the facilities' capital cost allocation. Thus, the regulations at § 412.25 limited the situations under which an IRF or IPF could change its bed size and square footage. In the FY 2012 IRF PPS final rule, we revised § 412.25(b) to enable IRFs and IPFs to more easily adjust to beneficiary changes in demand for IRF or IPF services, and improve beneficiary access to these services. We believed that the first requirement (that beds can only be added at the start of a cost reporting period) was difficult, and potentially costly, for IRFs and IPFs that were expanding through new construction because the exact timing of the end of a construction project is often difficult to predict.

In that same FY 2012 IRF PPS final rule, commenters suggested that CMS allow new IRF units or new IPF units to open and begin being paid under their respective IRF PPS or IPF PPS at any time during a cost reporting period, rather than requiring that they could only begin being paid under the IRF PPS or the IPF PPS at the start of a cost reporting period. In response, we stated that we believed that this suggestion was outside the scope of the FY 2012 IRF PPS proposed rule (76 FR 24214) because we did not propose any changes to the regulations in § 412.25(c). However, we stated that we would consider this suggestion for possible inclusion in future rulemaking. Within the FY 2018 IRF PPS proposed rule (82 FR 20690, 20742 through 20743), CMS published a request for information (RFI) on ways to reduce burden for hospitals, physicians, and patients; improve the quality of care; decrease costs; and ensure that patients and their providers and physicians are making the best health care choices possible. In response to the RFI, we received comments from IRF industry associations, state and national hospital associations, industry groups representing hospitals, and individual IRF providers. One of the comments we received in response to the RFI suggested allowing new IRF units to become excluded and be paid under the IRF PPS at any time during the cost reporting period, rather than only at the start of a cost reporting period, which the commenter believed would increase flexibility and eliminate a policy that may impose higher costs for providers while harmonizing an IRF payment system versus the IPPS payment system across all new IRF units.

B. Current Challenges Related To Excluded Hospital Units (§ 412.25(c)(1) and (c)(2))

Currently, under § 412.25(c)(1), a hospital can only start being paid under the IRF PPS or the IPF PPS for services provided in an excluded unit at the start of a cost reporting period. Specifically, § 412.25(c) limits when the status of hospital units may change for purposes of exclusion from the IPPS, as specified in § 412.25(c)(1) and § 412.25(c)(2). Section 412.25(c)(1) states that the status of a hospital unit may be changed from not excluded to excluded only at the start of the cost reporting period. If a unit is added to a hospital after the start of a cost reporting period, it cannot be excluded from the IPPS before the start of a hospital's next cost reporting period. Under § 412.25(c)(2), the status of a hospital unit may be changed from excluded to not excluded at any time during a cost reporting period, but only if the hospital notifies the fiscal intermediary and the CMS Regional Office in writing of the change at least 30 days before the date of the change, and maintains the information needed to accurately determine costs that are or are not attributable to the excluded unit. A change in the status of a unit from excluded to not excluded that is made during a cost reporting period must remain in effect for the rest of that cost reporting period.

In recent years, interested parties, such as hospitals, have written to CMS to express concerns about what they see as the unnecessary restrictiveness of the requirements of § 412.25(c). Based on this feedback, we continued to explore opportunities to reduce burden for providers and clinicians, while keeping patient-centered care a priority. For instance, we considered whether this regulation might create unnecessary burden for hospitals and could potentially delay necessary rehabilitation beds from opening and being paid under the IRF PPS. As we continued to review and reconsider regulations to identify ways to improve policy, we recognized that the requirement at § 412.25(c)(1) that hospital units can only be excluded at the start of a cost reporting period, may be challenging to meet and potentially costly for facilities under some circumstances, for example, those that are expanding through new construction. Hospitals have indicated it is often difficult to predict the exact timing of the end of a construction project and construction delays may hamper a hospital's ability to have the construction of an excluded unit completed exactly at the start of a cost reporting period, which hospitals said can lead to significant revenue loss if they are unable to be paid under the IRF PPS or IPF PPS until the start of the next cost reporting period.

As discussed, the requirements of § 412.25(c) were established to manage the administrative complexity associated with cost-based reimbursement for excluded IRF and IPF units. Today, however, because IRF units are paid under the IRF PPS, and IPF units are paid under the IPF PPS, cost allocation is not used for payment purposes. Because advancements in technology since the inception of the IRF PPS and IPF PPS have simplified the cost reporting process and enhanced communication between providers, CMS, and Medicare contractors, we are reconsidering whether it is necessary to continue to allow hospital units to become excluded only at the start of a cost reporting period.

C. Proposed Changes To Excluded Hospital Units (§ 412.25(c)(1) and (c)(2))

We are committed to continuing to transform the health care delivery system—and the Medicare program—by putting additional focus on patient-centered care and working with providers, physicians, and patients to improve outcomes, while meeting relevant health care priorities and reducing burden.

In response to the need for availability of inpatient rehabilitation beds we are proposing changes to § 412.25(c) to allow greater flexibility for hospitals to open excluded units, while minimizing the amount of effort Medicare contractors would need to spend administering the regulatory requirements. Although we are cognizant that there is a need for rehabilitative health services and support for providers along a continuum of care, including a robust investment in community-based rehabilitative services, this rule is focused on inpatient rehabilitation facility settings.

We note that § 412.25(c) applies to both IRFs and IPFs; therefore, revisions to § 412.25(c) would also affect IPFs in similar ways. Readers should refer to the FY 2024 IPF PPS proposed rule for discussion of proposed revisions to § 412.25(c) and unique considerations applicable to IPF units.

As discussed, the current requirements of § 412.25(c)(1) were originally established to manage the administrative complexity associated with cost-based reimbursement for excluded IPF and IRF units. Because IPF and IRF units are no longer paid under cost-based reimbursement, but rather under the IPF PPS and IRF PPS respectively, we believe that the restriction that limits an IPF or IRF unit to being excluded only at the start of a cost reporting period is no longer necessary.

We amended our regulations in the FY 2012 IRF PPS final rule to address a regulation that similarly was previously necessary for cost-based reimbursement, but was not material to payment under the IRF PPS and IPF PPS. In that final rule, we explained that under cost-based payments, the facilities' capital costs were determined, in part, by their bed size and square footage. Changes in the bed size and square footage would complicate the facilities' capital cost allocation. We explained that under the IRF PPS and IPF PPS, however, a facility's bed size and square footage were not relevant for determining the individual facility's Medicare payment. Therefore, we believed it was appropriate to modify some of the restrictions on a facility's ability to change its bed size and square footage. Accordingly, we relaxed the restrictions on a facility's ability to increase its bed size and square footage. Under the revised requirements that we adopted in the FY 2012, IRF PPS final rule in § 412.25(b), an IRF or IPF can change (either increase or decrease) its bed size or square footage one time at any point in a given cost reporting period as long as it notifies the CMS RO at least 30 days before the date of the proposed change, and maintains the information needed to accurately determine costs that are attributable to the excluded units.

Similarly, in the case of the establishment of a new excluded IPF and IRF units, we do not believe that the timing of the establishment of the new unit is material for determining the individual facility's level of Medicare payment under the IRF PPS or IPF PPS. We believe it would be appropriate to allow a unit to become excluded at any time in the cost reporting year. However, we also believe it is important to minimize the potential administrative complexity associated with units changing their excluded status.

Accordingly, we propose to amend the requirements currently in regulation at § 412.25(c)(1) to allow a hospital to open a new IRF unit anytime within the cost reporting year, as long as the hospital notifies the CMS Regional Office and Medicare Administrative Contractor (MAC) in writing of the change at least 30 days before the date of the change. Additionally, we are proposing that if a unit becomes excluded during a cost reporting year, this change would remain in effect for the rest of that cost reporting year. We also propose to maintain the current requirements of § 412.25(c)(2), which specify that, if an excluded unit becomes not excluded during a cost reporting year, the hospital must notify the MAC and the CMS Regional Office in writing of the change at least 30 days before the change, and this change would remain in effect for the rest of that cost reporting year. Finally, we propose to consolidate the requirements for § 412.25(c)(1) and § 412.25(c)(2) into a new § 412.25(c)(1) that would apply to IRF units and specify the requirements for an IRF unit to become excluded or not excluded.

We believe this proposal would provide IRFs greater flexibility when establishing an excluded unit at a time other than the start of a cost reporting period.

As noted, we are proposing an identical policy for inpatient psychiatric units of hospitals in § 412.25(c)(2) in the FY 2024 IPF PPS proposed rule.

We are proposing discrete regulation text for each of the hospital unit types (that is, IRF units and IPF units) to solicit comment on issues that might affect one hospital unit type and not the other. However, we may consider adopting one consolidated regulation text for both IRF and IPF units in either the IRF or IPF final rules for both unit types if we finalize both of our proposals. We request public comments on finalizing a consolidated provision that would pertain to both IRF and IPF units.

VIII. Inpatient Rehabilitation Facility (IRF) Quality Reporting Program (QRP)

A. Background and Statutory Authority

The Inpatient Rehabilitation Facility Quality Reporting Program (IRF QRP) is authorized by section 1886(j)(7) of the Act, and it applies to freestanding IRFs, as well as inpatient rehabilitation units of hospitals or Critical Access Hospitals (CAHs) paid by Medicare under the IRF PPS. Section 1886(j)(7)(A)(i) of the Act requires the Secretary to reduce by 2 percentage points the annual increase factor for discharges occurring during a fiscal year (FY) for any IRF that does not submit data in accordance with the IRF QRP requirements set forth in subparagraphs (C) and (F) of section 1886(j)(7) of the Act. 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 of the Act, to solicit input from certain groups regarding he selection of quality and efficiency measures for the IRF QRP. We have codified our program requirements in our regulations at § 412.634.

In this proposed rule, we are proposing to adopt two 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 IRF QRP quality measures in future years. Third, we are providing an update on our efforts to close the health equity gap. 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 IRF QRP

For a detailed discussion of the considerations we use for the selection of IRF QRP quality, resource use, or other measures, we refer readers to the FY 2016 IRF PPS final rule (80 FR 47083 through 47084).

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

The IRF QRP currently has 18 measures for the FY 2024 IRF QRP, which are listed in Table 17. For a discussion of the factors used to evaluate whether a measure should be removed from the IRF QRP, we refer readers to § 412.634(b)(2).

C. Overview of IRF QRP Quality Measure Proposals

In this proposed rule, we propose to adopt two new measures, remove three existing measures, and modify one existing measure for the FY 2025 IRF QRP and the FY 2026 IRF QRP. Beginning with the FY 2025 IRF QRP we are proposing to (1) modify the COVID–19 Vaccination Coverage among Healthcare Personnel (HCP) measure, (2) adopt the Discharge Function Score measure,^[17] which we are specifying under sections 1886(j)(7)(F) and 1899B(c)(1) 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) IRF Functional Outcome Measure: Change in Self-Care Score for Medical Rehabilitation Patients measure, and (iii) IRF Functional Outcome Measure: Change in Mobility Score for Medical Rehabilitation Patients measure.

We are proposing to add one new measure beginning with the FY 2026 IRF QRP, the COVID–19 Vaccine: Percent of Patients/Residents Who Are Up to Date measure which we are specifying under sections 1886(j)(7)(F) and 1899B(d)(1) of the Act.

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

a. Proposed Modification of the COVID–19 Vaccination Coverage Among Healthcare Personnel (HCP) Measure Beginning With the FY 2025 IRF 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 “coronavirus disease 2019” (COVID–19).^[18] Subsequently, in the FY 2022 IRF PPS final rule (86 FR 42385 through 42396), we adopted the COVID–19 Vaccination Coverage among Healthcare Personnel (HCP COVID–19 Vaccine) measure for the IRF QRP. The HCP COVID–19 Vaccine measure requires each IRF to submit data on the number of healthcare personnel (HCP) eligible to work in the IRF for at least one day during the reporting period, excluding persons with contraindications to the COVID–19 vaccine, who have received a complete vaccination course against SARS–CoV–2 (86 FR 42389 through 42396).

Since that time, COVID–19 has continued to spread domestically and around the world with more than 103.8 million cases and 1.1 million deaths in the United States as of March 21, 2023.^[19] 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.^[20] 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 combatting the virus, including through vaccination efforts.^[21]

In the FY 2022 IRF PPS final rule (86 FR 42386 through 42396) and in the Guidance for Staff Vaccination Requirements,^[22] 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 IRFs through quality measurement in order to protect health care workers, patients, and caregivers, and to help sustain the ability of IRFs to continue serving their communities throughout the PHE and beyond. At the time we issued the FY 2022 IRF PPS final rule, the Food and Drug Administration (FDA) had issued emergency use authorizations (EUAs) for COVID–19 vaccines manufactured by Pfizer-BioNTech,^[23] Moderna,^[24] and Janssen.^[25] On August 23, 2021, the FDA issued an approval for the Pfizer-BioNTech vaccine, marketed as Comirnaty.^[26] The FDA issued approval for the Moderna vaccine, marketed as Spikevax, on January 31, 2022 ^[27] and an EUA for the Novavax vaccine, on July 13, 2022.^[28] The FDA also issued EUAs for single booster doses of the then authorized COVID–19 vaccines. As of November 19,2021,^{[29 30 31 ]} 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.^[32] FDA first authorized the use of a booster dose of bivalent or “updated” COVID–19 vaccines from Pfizer-BioNTech and Moderna in August 2022.^[33]

(a) Measure Importance

In the FY2022 IRF PPS final rule (86 FR 42401), we acknowledged that we were still learning how effective the vaccines were against new variants of the virus that cause COVID–19. While the impact of COVID–19 vaccines on asymptomatic infection and transmission is not yet fully known, there are now robust data available across multiple populations on COVID–19 vaccine effectiveness 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.^[34] 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.^[35] 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.^[36] 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.^[37] 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 IRF PPS final rule, we stated that the need for booster doses of COVID–19 vaccines had not been established and no additional doses had been recommended (86 FR 42390). 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 42390). Since we adopted the HCP COVID–19 Vaccine measure in the FY 2022 IRF 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.^[38] 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.^[39] 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.^[40] The FDA issued EUAs for booster doses of two bivalent COVID–19 vaccines, one from Pfizer-BioNTech ^[41] and one from Moderna ^[42] 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.^[43] 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 HCP who received booster doses of the COVID–19 vaccine.^[44 45 ]

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 most recent guidance that explicitly specifies 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 patients, beneficiaries, and their caregivers with information to support informed decision making. 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 IRF QRP.

(b) Measure Testing

The CDC conducted beta testing of the proposed 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 recommendations. Feasibility was assessed by calculating the proportion of facilities that reported booster doses of the COVID–19 vaccine. The assessment was conducted in various facility types, including IRFs, 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 booster doses of vaccine is evident by the fact that 63.9 percent of IRFs reported vaccination booster coverage data to the NHSN for the first quarter of 2022.^[46] Additionally, HCP COVID–19 Vaccine measure scores calculated using January 1—March 31, 2022 data had a median of 20.3 percent and an interquartile range of 8.9 to 37.7 percent, indicating a measure performance gap as there are clinically significant differences in booster/additional dose vaccination coverage rates among IRFs.^[47]

(2) Competing and Related Measures

Section 1886(j)(7)(D)(i) of the Act and section 1899B(e)(2)(A) of the Act requires that, absent an exception under section 1886(j)(7)(D)(i) and section 1899B(e)(2)(B) of the Act, measures specified under section 1899B of the Act must be endorsed by a consensus-based entity (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 1886(j)(7)(D)(i) of the Act and section 1899B(e)(2)(B) of the Act permit 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.^[48] However, this measure received endorsement based on its specifications depicted in the FY 2022 IRF PPS final rule (86 FR 42386 through 42396), 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 IRFs 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 IRF QRP. The CDC, the measure developer, is pursuing CBE endorsement for the modified version of the measure and is considering an expedited review process as the current version of the measure has already received endorsement.

(3) Measure Application Partnership (MAP) Review

We refer readers to the FY 2022 IRF PPS final rule (86 FR 42387 through 42388) for more information on the initial review of the HCP COVID–19 Vaccine measure by the Measure Application Partnership (MAP).

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, including our quality reporting programs. This allows interested parties to provide recommendations to the Secretary on the measures included on the list. We included an updated version of the HCP COVID–19 Vaccine measure on the MUC List, entitled “List of Measures under Consideration for December 1, 2022” ^[49] for the 2022–2023 pre-rulemaking cycle for consideration by the MAP. Interested parties submitted three comments during the pre-rulemaking process on the proposed modifications of the HCP COVID–19 Vaccine measure, and support was mixed. One commenter noted the importance for HCP to 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, while also noting that the measure would provide valuable information to the government as part of its ongoing response to the pandemic. This commenter also recommended the measure be used for internal quality improvement purposes rather than being publicly reported on Care Compare. Finally, this commenter also suggested that the measure should be stratified by social risk factors. However, two commenters supported less specific criteria for denominator and numerator inclusion. Specifically, one such commenter did not support the inclusion of unpaid volunteers in the measure denominator and found the measure's denominator to be unclear. Two commenters expressed concerns regarding burden of data collection, data lag, staffing challenges, and reportedly “high rates of providers contesting penalties tied to the existing HCP COVID–19 Vaccine measure adopted in the FY 2022 IRF PPS final rule.” One commenter recommended that the measure be recharacterized as a surveillance measure given what they referred to as a tenuous relationship between collected data and quality of care provided by IRFs. Finally, all three commenters raised concern about the difficulty of defining up to date for purposes of the measure.

Shortly after publication of the MUC List, several MAP workgroups met to provide input on the modification we are proposing for the current HCP COVID–19 Vaccine 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 patients 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, and responded that the measure will not be stratified by demographic factors 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 modification we are proposing for the HCP COVID–19 Vaccine measure. The MAP noted that the previous version of the measure received endorsement from the CBE (CBE #3636),^[50] 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 consensus-based entity (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 proposed modification of the HCP COVID–19 Vaccine measure, one of which strongly supported the vaccination of HCP against COVID–19. Although these commenters supported the measure, one commenter recommended seeking NQF endorsement for the updated measure, and encouraged CMS to monitor any unintended consequences from the measure. Two commenters raised concerns with the measure's specifications. Specifically, one noted the denominator included a broad number of HCP, and another recommended a vaccination exclusion or exception for sincerely held religious beliefs. Finally, one commenter raised issues related to the time lag between data collection and public reporting on Care Compare and encouraged CMS 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 proposed 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.^[51]

(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 IRFs. 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.^[52] We believe it is necessary to allow IRFs to include all HCP within the facility in the reporting because all HCP would have access to and may interact with IRF patients. IRFs report the following four categories of HCP to NHSN; the first three are included in the measure denominator:

• Employees: 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 only who are affiliated with the reporting 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. 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 and 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 for this category are not included in the HCP COVID–19 Vaccine measure.

The denominator excludes denominator-eligible individuals with contraindications as defined by the CDC.^[53] 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 quarter, which can be found at https://www.cdc.gov/​nhsn/​pdfs/​hps/​covidvax/​UpToDateGuidance-508.pdf. For the purposes of NHSN surveillance, individuals would have been considered up to date during in the Quarter 4 CY 2022 reporting period (surveillance period September 26, 2022–December 25, 2022) for the IRF QRP if they meet one of the following criteria in place at the time:

1. Individuals who received an updated bivalent ^[54] booster dose, or

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

2b. Individuals who completed their primary series ^[55] less than 2 months ago.

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 IRF QRP compliance, IRFs would report individuals who are up to date beginning in quarter four of CY 2023. Under the data submission and reporting process, IRFs 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 an IRF submits more than 1 week of data in a month, the CDC would use the most recent week's data to calculate the measure. Each quarter, the CDC would calculate a single quarterly COVID–19 HCP vaccination coverage rate for each IRF, which would be calculated by taking the average of the data from the three weekly rates submitted by the IRF for that quarter. Beginning with the FY 2026 IRF QRP, we propose that IRFs 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 by the September 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 IRF QRP.

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

(1) Background

IRFs provide rehabilitation therapy in a resource-intensive inpatient hospital environment to patients with complex nursing, medical management, and rehabilitation needs, who require and can reasonably be expected to benefit from the multidisciplinary care provided in an IRF. Patients tend to have neurological conditions such as stroke, spinal cord injury, and brain injury; degenerative conditions including multiple sclerosis; congenital deformities; amputations; burns; active inflammatory conditions; severe or advanced osteoarthritis; or knee and hip joint replacements.^[56] In 2019, the most common condition treated by IRFs was stroke, which accounted for about one-fifth of IRF cases.^[57] For stroke patients, rehabilitation has been shown to be the most effective way to reduce stroke-associated motor impairments. Addressing these impairments is crucial as functional deficits affect patients' mobility, their capabilities in daily life activities, and their participation in society, which can lead to a lower quality of life.^[58]

Section 1886(j)(7)(F)(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 post-acute care (PAC) settings, including IRFs. To satisfy this requirement, we adopted 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 for the IRF QRP in the FY 2016 IRF PPS final rule (80 FR 47100 through 47111). 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 ^[59] and are proposing to remove it in section VIII.C.1.c. of this proposed rule. While there are other outcome measures addressing functional status ^[60] that can reliably distinguish performance among providers in the IRF 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.^[61] 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 patient to the community from post-acute care.^{[62 63 64]} Nonetheless, evidence suggests that physical functional abilities, including mobility and self-care, are modifiable predictors of patient outcomes across PAC settings, including functional recovery or decline after post-acute care,^{[65 66 67 68]}

rehospitalization rates,^{[69 70 71]} discharge to community,^[72 73] and falls.^[74]

The implementation of interventions that improve patients' functional outcomes and reduce the risks of associated undesirable outcomes as a part of a patient-centered care plan is essential to maximizing functional improvement. For many people, the overall goals of IRF care may include optimizing functional improvement, returning to a previous level of independence, or avoiding institutionalization. Several studies have reported that IRF care can improve patients' motor function at discharge for patients with various diagnoses, including traumatic brain injury and stroke.^{[75 76 77 78]} While patients generally improve in all functional domains at IRF discharge, evidence has shown that a significant number of patients continue to exhibit deficits in the domains of fall risk, gait speed, and cognition, suggesting the need for ongoing treatment. Assessing functional status as a health outcome in IRFs can provide valuable information in determining treatment decisions throughout the care continuum, such as the need for rehabilitation services and discharge planning,^{[79 80 81 82]} as well as provide information to consumers about the effectiveness of rehabilitation and other IRF 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 an IRF's quality of care.^[83 84]

We are proposing to adopt the Discharge Function Score (DC Function) measure ^[85] in the IRF QRP beginning with the FY 2025 IRF QRP. This assessment-based outcome measure evaluates functional status by calculating the percentage of IRF patients who meet or exceed an expected discharge function score. We are proposing that this measure would replace the topped-out Application of Functional Assessment/Care Plan cross-setting process measure. Like the Application of Functional Assessment/Care Plan cross-setting process measure, the proposed DC Function measure is calculated using standardized patient assessment data from the IRF Patient Assessment Instrument (IRF–PAI).

The DC Function measure supports our current priorities. Specifically, the measure aligns with the Streamline Quality Measurement domain in CMS's Meaningful Measures 2.0 Framework in two ways. First, the proposed outcome measure could further CMS's objective to prioritize outcome measures by replacing the current cross-setting process measure (see section VIII.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 IRF–PAI that IRFs 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 endorsed by the CBE, with some modifications.^[86] Specifically, the measure (1) considers two dimensions of function ^[87] (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 patient characteristics to produce an unbiased estimate of the score on each item with a missing value. In contrast, the current approach treats patients with missing values and patients who were coded to the lowest functional status similarly, despite evidence suggesting varying measure performance between the two groups, which can to lead less accurate measure performances.

(b) Measure Testing

The measure development contractor used FY 2019 data to conduct testing 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 VIII.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 IRF quality measures. Results indicated that the proposed DC Function measure captures the intended outcome based on the directionalities and strengths of correlation coefficients and are further detailed below in Table 18.

Table 18—Spearman's Rank Correlation Results of DC Function Measure With Publicly Reported IRF Quality Measures

Measure—long name	Measure—short name	ρ
Discharge to Community—PAC IRF QRP	Discharge to Community	0.25
IRF Functional Outcome Measure: Change in Self-Care Score for Medical Rehabilitation Patients	Change in Self-Care Score	0.82
IRF Functional Outcome Measure: Change in Mobility Score for Medical Rehabilitation Patients	Change in Mobility Score	0.86
IRF Functional Outcome Measure: Discharge Self-Care Score for Medical Rehabilitation Patients	Discharge Self-Care Score	0.85
IRF Functional Outcome Measure: Discharge Mobility Score for Medical Rehabilitation Patients	Discharge Mobility Score	0.88

Validity testing of the risk adjustment model showed good model discrimination as the measure model has the predictive ability to distinguish patients with low expected functional capabilities from those with high expected functional capabilities.^[88] 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 patient-family feedback showed strong support for the face validity and importance of the proposed measure as an indicator of quality of care (see section VIII.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 IRF QRP functional outcome measures, specifically the IRF Functional Outcome Measure: Change in Self-Care Score for Medical Rehabilitation Patients measure (Change in Self-Care Score), the IRF Functional Outcome Measure: Change in Mobility Score for Medical Rehabilitation Patients measure (Change in Mobility Score), the IRF Functional Outcome Measure: Discharge Self-Care Score for Medical Rehabilitation Patients measure (Discharge Self-Care Score), and the IRF Functional Outcome Measure: Discharge Mobility Score for Medical Rehabilitation Patients measure (Discharge Mobility Score).

Reliability and reportability testing also yielded results that support the proposed DC Function measure's scientific acceptability. Split-half testing revealed the proposed measure's excellent reliability, indicated by an intraclass correlation coefficient value of 0.95. Reportability testing indicated high reportability (98 percent) of IRFs 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 Inpatient Rehabilitation Facilities (IRFs) Technical Report.^[89]

(2) Competing and Related Measures

Section 1886(j)(7)(D)(i) of the Act and section 1899B(e)(2)(A) of the Act require that, absent an exception under section 1886(j)(7)(D)(i) and 1899B(e)(2)(B) of the Act, measures specified under section 1886(j)(7)(D)(i) of the Act and section 1899B of the Act must be endorsed by the 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 1886(j)(7)(D)(ii) of the Act and section 1899B(e)(2)(B) of the Act permit 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 IRFs and (2) satisfy the requirement of the Act to develop and implement standardized quality measures from the quality measure domain of 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 current cross-setting process measure is not endorsed by a CBE and the performance on the Application of Functional Assessment/Care Plan measure among IRFs is so high and unvarying that this current measure does not offer meaningful distinctions in performance. Additionally, after review of other CBE endorsed measures, we were unable to identify any CBE endorsed measures for IRFs that meet the aforementioned requirements. While the IRF QRP includes CBE endorsed outcome measures addressing functional status, ⁹⁰ 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 IRF 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 patient and family/caregiver advocates (PFA) focus group, two TEPs, and public comments through a request for information (RFI). First, the measure development contractor convened a PFA focus group, during which patients 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 a strong interest in metrics assessing the number of patients 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 IRF QRP. The TEPs consisted of interested parties with a diverse range of expertise, including IRF and PAC subject matter knowledge, clinical expertise, patient 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 measure and recommended moving forward with utilizing the Discharge Mobility Score and Discharge Self-Care Score measure concepts for the development of the 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 patient 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 function 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 the TEP's recommendations for developing a cross-setting function measure, 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) ^[91] and Technical Expert Panel (TEP) for Cross-Setting Function Measure Development Summary Report (January 2022 TEP) ^[92] 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 IRFs through an RFI in the FY 2023 IRF PPS proposed rule (87 FR 20244). 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 47070).

(4) Measure Applications Partnership (MAP) Review

Our pre-rulemaking process includes making publicly available a list of quality and efficiency measures, called the MUC List, that the Secretary is considering adopting for use in the Medicare program, including our quality reporting programs. This allows multi-interested parties to provide recommendations to the Secretary on the measures included on the list.

We included the DC Function measure under the IRF QRP in the publicly available MUC List for December 1, 2022.^[93] After the MUC List was published, the CBE convened MAP received four comments from interested parties in the industry on the 2022 MUC List. Two commenters were supportive of the measure and two were not. Among the commenters in support of the measure, one commenter stated that function scores are the most meaningful outcome measure in the IRF setting, as they not only assess patient 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 supported including the measure in the IRF QRP measures we propose through rulemaking.

Commenters not in support of the measure raised the following concerns: the need for more detailed measure specifications, the complexity of calculating the expected discharge score, the measure's validity and usability, and the differences in denominator populations across PAC settings. We were able to address these concerns during the MAP PAC/LTC workgroup meeting held on December 12, 2022. Specifically, we clarified that the technical reports include detailed measure specifications, and that expected discharge scores are calculated by risk-adjusting the observed discharge scores (see section VIII.C.1.b.(5) of this proposed rule). We also noted that the measure exhibits good validity (see section VIII.C.1.b(1)(b) of this proposed rule) and clarified that the wide range of expected scores does not indicate poor validity and is consistent with the range of observed scores. We also pointed out that the measure is highly usable since it is similar in design and complexity to existing function measures and its data elements are already in use. Lastly, we explained that the denominator population in each measure setting represents the assessed population within the setting and the measure satisfies the requirement of the Act for a cross-setting measure in the functional status domain.

Shortly after, several CBE convened MAP workgroups met to provide input on the proposed 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 asked for clarification regarding measure specifications from the measure steward. The MAP Rural Health Advisory Group met on December 8–9, 2022, during which two of its members provided support for the DC Function measure and other MAP Rural Health Advisory Group members did not express rural health concerns regarding the measure.

The MAP PAC/LTC workgroup met on December 12, 2022 and provided input on the proposed 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 VIII.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 IRF–PAI submitted by IRFs. Lastly, we clarified that the DC Function measure is intended to supplement, rather than replace, existing IRF 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 proposed measure more valid and harder to game.

The MAP PAC/LTC workgroup went on to discuss several 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 patients 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 1886(j)(7) 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 patient met or exceeded their expected discharge score, it accounts for patients 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 measure exhibits good validity and clarified that the wide range of expected scores does not indicate poor validity and is consistent with the range of observed scores. The PAC/LTC workgroup voted to support the staff recommendation of conditional support for rulemaking, with the condition that we seek CBE endorsement.

In response to the MAP PAC/LTC workgroup's preliminary recommendation, the CBE received two comments in support of the MAP PAC/LTC workgroup's preliminary recommendation of conditional support for rulemaking. One commenter recommended the DC Function measure under the condition that the measure be reviewed and refined such that its implementation supports patient autonomy and results in care that aligns with patients' personal functional goals. The second commenter provided support for the DC Function measure under the condition that it produces statistically meaningful information that can inform improvements in care processes, while also expressing concern that the measure is not truly cross-setting because: (1) the measure utilizes different patient populations in each setting-specific denominator, (2) the risk-adjustment models use setting-specific covariates, and (3) using a single set of cross-setting Section GG self-care and mobility function items in our standardized patient assessment instruments is not appropriate since the items may not be relevant given the differences in each PAC resident/patient population.

Finally, the MAP Coordinating Committee workgroup convened on January 24–25, 2023. At this meeting, one interested party indicated their lack of support for the PAC/LTC workgroup's preliminary recommendation. The commenter expressed concern that the proposed DC Function measure competes with existing self-care and mobility measures in the IRF QRP. We noted that we monitor measures to determine whether they meet any measure removal factors, set forth in 42 CFR 413.360(b)(2), and when identified, we may remove such measures through the rulemaking process. We noted again that the TEP had reviewed the item set and determined that all the self-care and mobility items were suitable for all settings. The MAP Coordinating Committee members expressed support for our review of existing measures for potential removal, as well as for the proposed DC Function measure, favoring the implementation of a single, standardized function measure across PAC settings. The Coordinating Committee unanimously upheld the workgroup recommendation of conditional support for rulemaking. We refer readers to the final MAP recommendations titled, 2022–2023 MAP Final Recommendations.^[94]

(5) Quality Measure Calculation

The proposed DC Function measure is an outcome measure that estimates the percentage of IRF patients who meet or exceed an expected discharge score during the reporting period. The proposed measure's numerator is the number of IRF 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 item values at discharge. The expected discharge function score is computed by risk-adjusting the observed discharge function score for each IRF stay. Risk adjustment controls for patient characteristics such as admission function score, age, and clinical conditions. The denominator is the total number of IRF stays with an IRF–PAI 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 Inpatient Rehabilitation Facilities (IRFs) Technical Report.^[95]

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 IRF patients. Currently, functional outcome measures in the IRF 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 (that is, 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 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 Inpatient Rehabilitation Facilities (IRFs) Technical Report  ^[96] for measure specifications and additional details.

We invite public comment on our proposal to adopt the DC Function measure, beginning with the FY 2025 IRF 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 IRF 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 IRF QRP beginning with the FY 2025 IRF QRP. Section 412.634(b)(2) of our regulations specifies eight factors we consider for measure removal from the IRF 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 IRFs is so high and unvarying that meaningful distinctions in improvements in performance can no longer be made.^[97] Second, this measure meets the conditions for measure removal factor six: there is an available measure that is more strongly associated with desired patient functional outcomes. We believe the proposed DC Function measure discussed in section VIII.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, with average performance rates reaching nearly 100 percent over the past 3 years (ranging from 99.8 percent to 99.9 percent during CYs 2019–2021).^{[98]  [99]  [100]} For the 12-month period of third quarter of CY 2020 through second quarter of CY 2021 (July 1, 2020 through June 30, 2021), IRFs had an average score for this measure of 99.8 percent, with nearly 80 percent of IRFs scoring 100 percent,^[101] and for CY 2021, IRFs had an average score of 99.9 percent, with nearly 78 percent of IRFs scoring 100 percent.^[102] 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 IRFs.

In regard to measure removal factor six, the DC Function measure is more strongly associated with desired patient functional outcomes than this current process measure, the Application of Functional Assessment/Care Plan measure. As described in section VIII.C.b.(1)(b) of this proposed rule, the DC Function measure has the predictive ability to distinguish patients with low expected functional capabilities from those with high expected functional capabilities.^[103] 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 statutory requirements 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 IRF's outcome of care on a patient'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 IRF QRP beginning with the FY 2025 IRF QRP. We are also proposing that public reporting of the Application of Functional Assessment/Care Plan measure would end by the September 2024 Care Compare refresh or as soon as technically feasible when public reporting of the proposed DC Function measure would begin (see section VIII.G.3. of this proposed rule).

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

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

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

We are proposing to remove the IRF Functional Outcome Measure: Change in Self-Care Score for Medical Rehabilitation Patients (Change in Self-Care Score) and the IRF Functional Outcome Measure: Change in Mobility Score for Medical Rehabilitation Patients (Change in Mobility Score) measures from the IRF QRP beginning with the FY 2025 IRF QRP. Section 412.634(b)(2) of our regulations specifies eight factors we consider for measure removal from the IRF QRP. We propose removal of these measures because they satisfy 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 measures. On this basis, we believe these measures should be removed for two reasons. First, the costs to IRFs associated with tracking similar or duplicative measures in the IRF QRP outweigh any benefit that might be associated with the measures. Second, the costs to CMS 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 2016 IRF PPS final rule (80 FR 47112 through 47118) 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. Given that the primary goal of rehabilitation is improvement in functional status, IRF clinicians have traditionally assessed and documented individual patients' functional status at admission and discharge to evaluate the effectiveness of the rehabilitation care provided.

We are proposing to remove the Change in Self-Care Score and Change in Mobility Score measures because we believe the IRF costs associated with tracking duplicative measures outweigh any benefit that might be associated with the measures. Since the adoption of these measures in 2016, 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 IRF settings (0.97).^[104] 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 IRF settings (0.98).^[105] 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 IRFs 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 VIII.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 is necessary. Of those nine respondents, six preferred retaining the “Discharge Score” measures over the “Change in Score” measures.^[106]

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, IRFs, 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 IRFs and consumers as the Discharge Self-Care Score and Discharge Mobility Score measures, the costs to CMS 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 IRF QRP beginning with the FY 2025 IRF QRP. We are also proposing that public reporting of the Change in Self-Care Score and the Change in Mobility Score measure would end by the September 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 Change in Mobility Score measures from the IRF QRP beginning with the FY 2025 IRF QRP.

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

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

(1) Background

COVID–19 has been and continues to be a major challenge for PAC facilities, including IRFs. 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.^[107] 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, with those over age 80 dying at five times the average rate.^[108] Older adults, in general, are prone to both acute and chronic infections owing to reduced immunity, and are a high-risk population.^[109] Adults age 65 and older comprise over 75 percent of total COVID–19 deaths despite representing 13.4 percent of reported cases.^[110] 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.^[111]

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.^[112] 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 hospitalization among adults age 65 and older was 91 percent for those who were fully vaccinated with an mRNA vaccine (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 hospitalization while those who were partially vaccinated had a 64 percent reduction in risk.^[113] Further, after the emergence of the Delta variant, vaccine effectiveness against COVID–19-associated hospitalization for adults who were fully vaccinated was 76 percent among adults age 75 and older.^[114]

More recently, since the emergence of the Omicron variants and 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 only receiving the primary series.^{[115]  [116]  [117]} 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.^[118] Additionally, a second vaccine booster dose has been shown to reduce risk of severe outcomes related to COVID–19, such as hospitalization or death.^[119] 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.^{[120]  [121]}

(a) Measure Importance

Despite the availability and demonstrated effectiveness of COVID–19 vaccinations,, significant gaps continue to exist in vaccination rates. ^[122] 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).^[123] 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.^[124] Variations are also present when examining vaccination rates by race, gender, and geographic location.^[125] 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 a bivalent booster dose. Among Hispanic populations, 57.1 percent of the population have completed the primary series, and 8.5 percent have received a 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.^[126] Disparities have been found in vaccination rates between rural and urban areas, with lower vaccination rates found in rural areas.^{[127]  [128]} Data shows 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.^[129] Receipt of bivalent booster doses among those eligible has been lower, with 18 percent of urban population having received a booster dose, and 11.5 percent of the rural population having received a booster dose.^[130]

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 IRF QRP beginning with the FY 2026 IRF QRP. This proposed measure has the potential to increase COVID–19 vaccination coverage of patients in IRFs, as well as prevent the spread of COVID–19 within the IRF patient population. The proposed Patient/Resident COVID–19 Vaccine measure would also support the goal of CMS's 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 patients, including those who are at high risk for developing serious complications from COVID–19, and their caregivers, with valuable information they can consider when choosing an IRF. The proposed Patient/Resident COVID–19 Vaccine measure would also facilitate patient care and care coordination during the hospital discharge planning process. For example, a discharging hospital, in collaboration with the patient and family, could use this proposed measure's publicly reported information on Care Compare to coordinate care and ensure patient preferences are considered in the discharge plan. Additionally, the proposed Patient/Resident COVID–19 Vaccine measure would be an indirect measure of IRF action. Since the patient's COVID–19 vaccination status would be reported at discharge from the IRF, if a patient is not up to date with their COVID–19 vaccination per applicable CDC guidance at the time they are admitted, the IRF has the opportunity to educate the patient and provide information on why they should become up to date with their COVID–19 vaccination. IRFs may also choose to administer the vaccine to the patient prior to their discharge from the IRF or coordinate a follow-up visit for the patient to obtain the vaccine at their physician's office or local pharmacy.

(b) Item Testing

The measure development contractor conducted testing of the proposed standardized patient/resident COVID–19 vaccination coverage assessment item for the proposed Patient/Resident COVID–19 Vaccine measure using patient scenarios, draft guidance manual coding instructions, and cognitive interviews to assess IRFs' comprehension of the item and the associated guidance. A team of clinical experts assembled by our measure development contractor developed these patient scenarios to represent the most common scenarios that IRFs would encounter. The results of the item testing demonstrated that IRFs 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 1886(j)(7)(D)(i) of the Act and section 1899B(e)(2)(A) of the Act require that, absent an exception under section 1886(j)(7)(D)(i) and section 1899B(e)(2)(B) of the Act, measures specified under section 1886(j)(7)(D)(i) of the Act and section 1899B of the Act must 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 1886(j)(7)(D)(i) of the Act and section 1899B(e)(2)(B) of the Act permit 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 IRFs focused on capturing COVID–19 vaccination coverage of IRF patients. We found only one related measure addressing COVID–19 vaccination, the COVID–19 Vaccination Coverage among Healthcare Personnel measure, adopted for the FY 2023 IRF QRP (86 FR 42385 through 42396), which captures the percentage of HCP who receive a complete COVID–19 primary vaccination course.

Therefore, after consideration of other available measures that assess COVID– 19 vaccination rates among IRF patients, we believe the exception under section 1899B(e)(2)(B) of the Act applies. We intend to submit the proposed measure for consideration of endorsement by a CBE 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 felt a measure capturing raw vaccination rate, irrespective of IRF action, would be most helpful in patient and family/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 an IRF 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 is available on the CMS MMS Hub.^[131]

To seek input on the importance, relevance, and applicability of a patient/resident COVID–19 vaccination coverage measure, we also solicited public comments in an RFI for publication in the FY 2023 IRF PPS proposed rule (87 FR 47038).^[132] Comments were generally positive on the concept of a measure addressing COVID–19 vaccination coverage among IRF patients. Some commenters included caveats with their support and requested further details regarding measure specifications and CBE endorsement. In addition, commenters voiced concerns regarding the evolving recommendations related to boosters and the definition of “up to date,” as well as whether an IRF length of stay would allow for meaningful distinctions among IRFs (87 FR 47071).

(4) Measure Applications Partnership (MAP) Review

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 IRF QRP.^[133]

After the MUC List was published, the MAP received five comments from interested parties. Commenters were mostly supportive of the measure and recognized the importance of patients' 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 noted that patient engagement is critical at this stage of the pandemic, while another noted the criteria for inclusion in the numerator and denominator provide flexibility for the measure to remain relevant to current circumstances. Another commenter anticipated minimal implementation challenges, since healthcare providers are already asking for patients' COVID–19 vaccination status at intake. Commenters who were not supportive of the measure raised several issues, including that the measure does not capture quality of care, concern about the evolving definition of the term “up to date,” that data collection would be burdensome, that administering the vaccine could impact the IRF treatment plan, and that a measure only covering one quarter may not be meaningful.

Subsequently, several MAP workgroups met to provide input on the proposed 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.^[134] Similarly, 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.^[135] Next, the MAP PAC/LTC workgroup met on December 12, 2022. The MAP PAC/LTC workgroup's voting members raised concerns brought up in public comments, such as provider actionability, lack of denominator exclusions, requirements for assessing patient vaccination status, evolving COVID–19 vaccination recommendations, and data reporting frequency for this measure. Additionally, MAP PAC/LTC workgroup members noted the potential inability of IRFs to administer the vaccine due to the shorter average length of stay as compared to other PAC settings. In response to workgroup member feedback, we noted that the intent of the Patient/Resident COVID–19 Vaccine measure would be to promote transparency of data for patients to make informed decisions regarding care, and is not intended to be a measure of IRF action. We also explained that this measure does not have exclusions for patient refusal since this measure was intended to report raw rates of vaccination, and this information is important for consumer choice. Additionally, we believe that PAC providers, including IRFs, are in a unique position to leverage their care processes to increase vaccination coverage in their settings to protect patients and prevent negative outcomes. We also noted that collection of these data will not require additional documentation or proof of vaccination. We clarified that the Patient/Resident COVID–19 Vaccine measure would include the definition of up to date, so the measure would consider future changes in the CDC guidance regarding COVID–19 vaccination. We also clarified that the measure would continue to be a quarterly measure similar to the existing HCP COVID–19 Vaccine measure, as CDC has not determined whether COVID–19 is, or will be, a seasonal disease like influenza. Finally, we noted that the average 12-day length of stay at IRFs is generally longer than patient stays at acute care hospitals. Given that health care is a continuum and every contact along the continuum provides an opportunity to encourage vaccination, IRFs have sufficient time to act on the patient's vaccination status. However, the MAP PAC/LTC workgroup reached a 60 percent consensus on the vote of “Do not support for rulemaking” for this measure.^[136]

The MAP received four comments from industry commenters in response to the MAP PAC/LTC workgroup's recommendations. Interested parties generally understood the importance of COVID–19 vaccinations in preventing the spread of COVID–19, although a majority of commenters did not recommend the inclusion of the proposed Patient/Resident COVID–19 Vaccine measure for the IRF QRP and raised several concerns. Specifically, commenters were concerned about vaccine hesitancy and providers' inability to influence results based on factors outside of their control. Commenters also noted that the measure has not been fully tested and encouraged CMS to monitor the measure for unintended consequences and ensure that the measure has meaningful results. One commenter raised concerns on whether patients' vaccination information would be easily available to IRFs as well as potential limitations with patients recounting vaccination status. One commenter was in support of the measure and provided recommendations for CMS to consider adding an exclusion for medical contraindications and submitting the measure for CBE endorsement.

Finally, the MAP Coordinating Committee convened on January 24, 2023, and noted concerns which were previously discussed in the MAP PAC/LTC workgroup, such as potential disruption to patient therapy due to vaccination and acuity of patients in the IRF setting. However, a MAP Coordinating Committee member noted that a patient's potential inability to complete rehabilitation was not a valid reason to withhold support of this measure, and that, because these patients have a high acuity, they are more vulnerable to COVID–19, further emphasizing the need to vaccinate them. MAP Coordinating Committee members also raised concerns discussed previously during the MAP PAC/LTC workgroup, including the shorter IRF length of stay and excluding medical contraindications from the denominator.

The MAP Coordinating Committee recommended three mitigation strategies for the Patient/Resident COVID–19 Vaccine measure: (i) reconsider exclusions for medical contraindications, (ii) complete reliability and validity measure testing, and (iii) seek CBE endorsement. The MAP Coordinating Committee ultimately reached 81 percent consensus on its voted recommendation of `Do not support with potential for mitigation.' Despite the MAP Coordinating Committee's vote, we believe it is still important to propose the Patient/Resident COVID–19 Vaccine measure for the IRF QRP. As we stated in section VIII.C.2.a.(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 .^[137]

(5) Quality Measure Calculation

The proposed Patient/Resident COVID–19 Vaccine measure is an assessment-based process measure that reports the percent of stays in which patients in an IRF are up to date on their COVID–19 vaccinations per the CDC's latest guidance.^[138] This measure has no exclusions, and is not risk adjusted.

The numerator for the proposed measure would be the total number of IRF stays in the denominator in which patients are up to date with their COVID–19 vaccination per CDC's latest guidance. The denominator for the proposed measure would be the total number of IRF stays discharged during the reporting period.

The data source for the proposed Patient/Resident COVID–19 Vaccine measure is the IRF–PAI for IRF patients. For more information about the proposed data submission requirements, we refer readers to section VIII.F.3. 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 .^[139] available on the IRF QRP Measures and Technical Information web page.

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

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

1. Background

We have established a National Quality Strategy (NQS) ^[140] for quality programs which support a resilient, high-value health care 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” ^[141] 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 IRF 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 IRF QRP measures and to solicit public comment on fully developed IRF measures that are not part of the IRF QRP, fully developed quality measures in other programs that may be appropriate for the IRF QRP, and measurement concepts that could be developed into IRF QRP measures, to fill these measurement gaps in the IRF QRP. While we will not be responding to specific comments submitted in response to this RFI in the FY 2024 IRF 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 CMS could use to identify future IRF QRP measures. The second section draws from an environmental scan conducted to identify measurement gaps in the current IRF 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 IRF 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 IRF QRP.

2. Guiding Principles for Selecting and Prioritizing Measures

We have identified a set of principles to guide future IRF 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 IRFs, align with our PAC program goals, and can be readily operationalized. Specifically, measures incorporated into the IRF QRP should meet the following four objectives:

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

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

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

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

3. Gaps in IRF 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, patient experience and patient 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 1886(j)(7) of the Act requires IRFs 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 IRF QRP.

Under the IRF QRP, IRFs currently collect and report to CMS data on cognitive function using the Brief Interview for Mental Status (BIMS) and Confusion Assessment Method (CAM©).^[142] Both the BIMS and CAM© have been incorporated into the IRF–PAI as standardized patient assessment data elements. Scored by IRFs 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 IRF–PAI, these items have not been developed into specific quality measures for the IRF 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.^[143 144] Developed and tested with a broad range of patient populations, PROMIS Cognitive Function assesses cognitive functioning using items related to patient 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 patients with neurological conditions, assesses patient 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 assessment 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 IRF QRP.

Through this RFI, we are requesting comment on the availability of cognitive functioning measures outside of the IRF QRP that may be available for immediate use in the IRF QRP, or that may be adapted or developed for use in the IRF QRP, using the BIMS, CAM©, PROMIS Cognitive Function 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 an IRF stay, which typically averages less than 15 days; ^[145] the cognitive skills (for example, executive functions) that are more likely to improve during an IRF 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.^[146] 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.^[147] In some instances, such as following a knee replacement or stroke, patients may develop depression, anxiety, and/or SUDs. In other instances, patients may have been dealing with mental or behavioral health or SUD issues long before their post-acute admission. Left unmanaged, however, these conditions could make it difficult for affected patients 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 PAC settings is limited, and the 2021 National Impact Assessment of the CMS Quality Measures Report ^[148] identified PAC program measurement gaps in the areas of behavioral and mental health. Among the mental health quality measures in current use by other quality reporting programs, one Home Health QRP measure assesses the extent to which patients have been screened for depression and, if, positive, a follow-up plan is documented.^[149] Although it may be possible to adapt this depression screening 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 or SUDs in PAC settings include the Consumer Assessment of Healthcare Providers and Systems (CAHPS) Experience of Care and Health Outcomes Survey (ECHO), which consists of a series of questions that may be used to understand patients' perspectives concerning mental health services received; ^[150] the PROMIS ^[151] 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,^[152] 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 other mental health issues, SUDs have been under studied in the IRF and other PAC settings, even though they are among the fastest growing disorders in the community dwelling older adult population.^[153 154] 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.^[155]

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

c. Patient Experience and Patient Satisfaction

Patient experience measures focus on how patients experienced or perceived selected aspects of their care, whereas patient satisfaction measures focus on whether a patient's expectations were met. Information on patient experience of care is typically collected via a number of instruments that rely on patient self-reported data. The most prominent among these is the CAHPS suite of surveys, although CAHPS instruments have not been developed for use in IRFs. However, we have developed the IRF Experience of Care Survey,^[156] which measures patient experience in terms of goal setting, communications with staff, respect and privacy received, ability to obtain assistance when needed, cleanliness of the facility, and other domains.

One patient satisfaction measure that has been developed for use by SNFs and potentially could be adapted for use by IRFs is the CoreQ: Short Stay Discharge (CoreQ: SS DC) measure. The CoreQ: SS DC measure, which underwent 2017–2018 pre-rulemaking for the SNF QRP,^[157] assesses the level of satisfaction among SNF short-stay (less than 100 days) patients.

We seek comment on the feasibility and challenges of adapting existing patient experience and patient satisfaction measures and instruments, such as the CMS IRF Experience of Care Survey and the CoreQ: SS DC measure, for use in the IRF QRP. We seek input on the extent to which patient experience measures offer IRFs sufficient information to assist in quality improvement, and the challenges of collecting and reporting patient experience and patient satisfaction data.

d. Chronic Conditions and Pain Management

Despite the availability of measures focused on IRF clinical care, existing IRF QRP measures do not directly address aspects of care rendered to populations with chronic conditions or IRFs' management of patients' 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 IRF performance in treatment or management of patients' chronic respiratory conditions, such as chronic obstructive pulmonary disease (COPD) or asthma.

Existing IRF QRP measures also fail to capture concisely IRFs' actions with respect to patients' 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 IRFs' 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, 2022, IRFs began collecting new standardized patient assessment data elements under the IRF QRP, including items that assess pain interference with (1) daily activities, (2) sleep, and (3) participation in therapy. The collection of this data may provide an opportunity to develop more concise measures of provider performance related to pain management in IRF patients (87 FR 39109 through 39161).

Through this RFI, we are seeking input on measures of chronic condition and pain management for patients that may be used to assess IRF performance. Additionally, we seek general comment on the feasibility and challenges of measuring and reporting IRF performance on existing QRP measures, such as Discharge Self-Care Score and Discharge Mobility Score measures, for subgroups of patients defined by type of chronic condition. As examples, measures could assess discharge outcomes for IRF patients with a stroke diagnosis or for patients admitted with a diagnosis of multiple sclerosis.

4. Solicitation of Comments

We invite general comments on the principles for identifying IRF QRP measures, as well as additional comments 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?

• IRF QRP Measurement Gaps

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

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

• Measures and Measure Concepts Recommended for Use in the IRF QRP

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

CMS also seeks 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 IRF PPS proposed rule (87 FR 20247 through 20254), 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.” ^[158] 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 enrollees need to thrive. Our goals outlined in the CMS Framework for Health Equity 2022–2023  ^[159] are in line with Executive Order 13985, “Advancing Racial Equity and Support for Underserved Communities Through the Federal Government.” ^[160] 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 health care 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).^[161] The NQS identifies a wide range of potential quality levers that can support our advancement of equity, including: (1) establishing a standardized approach for patient-reported data and stratification; (2) employing quality and value-based programs to address closing equity gaps; and (3) developing equity-focused data collections, 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 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.^[162] 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.^[163] 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 IRF PPS final rule (87 FR 47072 through 47073) for a summary of the public comments and suggestions CMS 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 IRF 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.^[164] 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.^[165] 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 IRFs with their results; educate IRFs and offer the opportunity to ask questions; and solicit feedback from IRFs 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,^[166] a measure capturing and addressing SDOH could encourage IRFs to identify patients' 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 IRF. 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 IRF QRP statutory authority. This would further the NQS to align quality measures across our programs as part of the Universal Foundation.^[167]

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 IRF QRP

1. Background

We refer readers to the regulatory text at § 412.634(b)(1) for information regarding the current policies for reporting IRF QRP data.

2. Proposed Reporting Schedule for the IRF–PAI Assessment Data for the Discharge Function Score Measure Beginning With the FY 2025 IRF

As discussed in section VIII.C.1.b. of this proposed rule, we are proposing to adopt the Discharge Function Score (DC Function) measure beginning with the FY 2025 IRF QRP. We are proposing that IRFs would be required to report these IRF–PAI assessment data related to the DC Function measure beginning with patients discharged on October 1, 2023, for purposes of the FY 2025 IRF QRP. Starting in CY 2024, IRFs would be required to submit data for the entire calendar year beginning with the FY 2026 IRF QRP. Because the DC Function measure is calculated based on data that are currently submitted to the Medicare program in the IRF–PAI, there would be no new burden associated with data collection for this measure.

We invite public comments on our proposal.

3. Proposed Reporting Schedule for the Data Submission of IRF–PAI Assessment Data for the COVID–19 Vaccine: Percent of Patients/Residents Who Are Up to Date Quality Measure Beginning With the FY 2026 IRF QRP

As discussed in section VIII.C.2.a. of this proposed rule, we are proposing 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 IRF QRP. We are proposing that IRFs would be required to report the IRF–PAI assessment data related to the Patient/Resident COVID–19 Vaccine measure beginning with patients discharged on October 1, 2024 for purposes of the FY 2026 IRF QRP. Starting in CY 2025, IRFs would be required to submit data for the entire CY beginning with the FY 2027 IRF QRP.

We are also proposing to add a new item to the IRF–PAI in order for IRFs to report this measure. Specifically, a new item would be added to the IRF–PAI discharge assessment to collect information on whether a patient is up to date with their COVID–19 vaccine at the time of discharge from the IRF. 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.^[168]

We invite public comments on our proposal.

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

1. Background

Section 1886(j)(7)(E) of the Act requires the Secretary to establish procedures for making the IRF QRP data available to the public after ensuring that IRFs have the opportunity to review their data prior to public display. For a more detailed discussion about our policies regarding public display of IRF QRP measure data and procedures for the IRF's opportunity to review and correct data and information, we refer readers to the FY 2017 IRF PPS final rule (81 FR 52045 through 52048).

2. Proposed Public Reporting of the Transfer of Health (TOH) Information to the Provider—Post-Acute Care (PAC) Measure and TOH Information to the Patient—PAC Measure Measures Beginning With the FY 2025 IRF QRP

We are proposing to begin publicly displaying data for the measures, TOH Information to the Provider—PAC Measure (TOH—Provider) and TOH Information to the—Patient PAC Measure (TOH—Patient) beginning with the September 2024 Care Compare refresh or as soon as technically feasible.

We adopted these measures in the FY 2020 IRF PPS final rule (84 FR 39099 through 39107). In response to the COVID–19 PHE, we issued an interim final rule (85 FR 27595 through 27596) which delayed the compliance date for the collection and reporting of the TOH—Provider and TOH—Patient measures to October 1st of the year that is at least one full FY after the end of the COVID–19 PHE. Subsequently, the CY 2022 Home Health PPS Rate Update final rule (86 FR 62381 through 62386) revised the compliance date for the collection and reporting of the TOH—Provider and TOH—Patient measures under the IRF QRP to October 1, 2022. Data collection for these two assessment-based measures in the IRF QRP began with patients discharged on or after October 1, 2022.

We are proposing to publicly display four rolling quarters of the data we receive for these two assessment-based measures, initially using data on discharges from January 1, 2023, through December 31, 2023 (Quarter 1 2023 through Quarter 4 2023); and to begin publicly reporting data on these measures with the September 2024 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 an IRF's performance on a measure if the IRF had fewer than 20 eligible cases in any four consecutive rolling quarters for that measure. IRFs that have fewer than 20 eligible cases would be distinguished with a footnote that states, “The number of cases/patient stays is too small to publicly report.”

We invite public comment on our proposal for the public display of the TOH—Provider and TOH—Patient assessment-based measures.

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

We are proposing to begin publicly displaying data for the Discharge Function Score (DC Function) measure beginning with the September 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). We are proposing that an IRF's DC Function measure score would be displayed based on four quarters of data. Provider preview reports would be distributed to IRFs in June 2024, or as soon as technically feasible. Thereafter, an IRF's DC Function measure 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 an IRF's performance on the measure if the IRF had fewer than 20 eligible cases in any quarter. IRFs that have fewer than 20 eligible cases would be distinguished with a footnote that states: “The number of cases/patient stays is too small to report.”

We invite public comment on the proposal for the public display of the DC Function assessment-based measure beginning with the September 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 IRF QRP

We are proposing to begin publicly displaying data for the COVID–19 Vaccine: Percent of Patients/Residents Who are Up to Date (Patient/Resident COVID–19 Vaccine) measure beginning with the September 2025 refresh of Care Compare, or as soon as technically feasible, using data collected for Q4 2024 (October 1, 2024 through December 31, 2024). We are proposing that an IRF's percent of patients who are up to date, as reported under the Patient/Resident COVID–19 Vaccine measure, would be displayed based on one quarter of data. Provider preview reports would be distributed to IRFs in June 2025 for data collected in Q4 2024, or as soon as technically feasible. Thereafter, the percent of IRF patients 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 an IRF's performance on the measure if the IRF had fewer than 20 eligible cases in any quarter. IRFs that have fewer than 20 eligible cases would be distinguished with a footnote that states: “The number of cases/patient stays is too small to report.”

We invite public comment on the proposal for the public display of the Patient/Resident COVID–19 Vaccine measure beginning with the September 2025 refresh of Care Compare, or as soon as technically feasible.

IX. Collection of Information Requirements

Under the Paperwork Reduction Act of 1995, 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. In order to fairly evaluate whether an information collection should be approved by OMB, section 3506(c)(2)(A) of the Paperwork Reduction Act of 1995 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.

This proposed rule refers to associated information collections that are not discussed in the regulation text contained in this document.

A. Requirements for Updates Related to the IRF QRP Beginning With the FY 2025 IRF QRP

An IRF that does not meet the requirements of the IRF QRP for a fiscal year would receive a 2-percentage point reduction to its otherwise applicable annual increase factor for that fiscal year.

We believe that the burden associated with the IRF QRP is the time and effort associated with complying with the requirements of the IRF QRP. In section VIII.C. of this proposed rule, we are proposing to modify one measure, adopt three new measures, and remove three measures from the IRF QRP.

As stated in section VIII.C.1.a. of this proposed rule, we propose that IRFs submit data on one modified quality measure, the COVID–19 Vaccination Coverage among Healthcare Personnel (HCP) (HCP COVID–19 Vaccine) measure beginning with the FY 2025 IRF QRP. The data is collected through the Centers for Disease Control and Prevention (CDC's) National Health Safety Network (NHSN). IRFs currently utilize the NHSN for purposes of meeting other IRF QRP requirements, including the current HCP COVID–19 Vaccine measure. IRFs would continue to submit the HCP COVID–19 Vaccine measure data to CMS through the NHSN. The burden associated with the HCP COVID–19 Vaccine measure is accounted for under the CDC's information collection request currently approved under OMB control number 0920–1317 (expiration date: January 31, 2024). Because we are not proposing any updates to the form, manner, and timing of data submission for this HCP COVID–19 Vaccine measure, there would be no increase in burden associated with the proposal, and refer readers to the FY 2022 IRF PPS final rule (86 FR 42399 through 42400) for these policies.

In section VIII.C.1.b. of this proposed rule, we propose to adopt the Discharge Function Score (DC Function) measure beginning with the FY 2025 IRF QRP. This assessment-based quality measure would be calculated using data from the IRF Patient Assessment Instrument (IRF–PAI) that are already reported to CMS for payment and quality reporting purposes, and the burden is accounted for in the information collection request currently approved under OMB control number 0938–0842 (expiration date: August 31, 2025). There would be no additional burden for IRFs associated with this proposed DC Function measure since it does not require collection of new data elements.

In section VIII.C.1.c. of this proposed rule, we also propose 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 beginning with the FY 2025 IRF QRP. We believe that the removal of the Application of Functional Assessment/Care Plan measure would result in a decrease of 18 seconds (0.3 minutes or 0.005 hours) of clinical staff time at admission beginning with the FY 2025 IRF QRP. We believe the IRF–PAI item affected by 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 item based on past IRF burden calculations in conjunction with expert opinion. Our assumptions for staff type were based on the categories generally necessary to perform an assessment. Individual providers determine the staffing resources necessary. Therefore, we averaged the national average for these labor types and established a composite cost estimate. This composite estimate was calculated by weighting each salary based on the following breakdown regarding provider types most likely to collect this data: OT 45 percent; PT 45 percent; RN 5 percent; LVN 2.5 percent; SLP 2.5 percent. For the purposes of calculating the costs associated with the collection of information requirements, we obtained mean hourly wages for these staff from the U.S. Bureau of Labor Statistics' (BLS) May 2021 National Occupational Employment and Wage Estimates.^[169] To account for overhead and fringe benefits, we have doubled the hourly wage. These amounts are detailed in Table 19.

Table 19—U.S. Bureau of Labor and Statistics' May 2021 National Occupational Employment and Wage Estimates

Occupation title	Occupation code	Mean hourly wage ($/hr)	Overhead and fringe benefit ($/hr)	Adjusted hourly wage ($/hr)
Registered Nurse (RN)	29–1141	$39.78	$39.78	$79.56
Licensed Vocational Nurse (LVN)	29–2061	24.93	24.93	49.86
Speech Language Pathologist (SLP)	29–1127	41.26	41.26	82.52
Physical Therapist (PT)	29–1123	44.67	44.67	89.34
Occupational Therapist (OT)	29–1122	43.02	43.02	86.04

As a result of this proposal, the estimated burden and cost for IRFs for complying with requirements of the FY 2025 IRF QRP would decrease. Specifically, we believe that there would be a 0.005 hour decrease in clinical staff time to report data for each IRF–PAI completed at admission. Using data from calendar year 2021, we estimate 511,938 admission assessments from 1,128 IRFs annually. This equates to a decrease of 2,560 hours in burden at admission for all IRFs (0.005 hour × 511,938 admissions). Given 0.135 minutes of occupational therapist time at $86.04 per hour, 0.135 minutes of physical therapist time at $89.34 per hour, 0.015 minutes registered nurse time at $79.56 per hour, 0.0075 minutes of licensed vocational nurse time at $49.86 per hour, and 0.0075 minutes of speech language pathologist time at $82.52 per hour to complete an average of 454 IRF–PAI admission assessments per IRF per year, we estimate the total cost would be decreased by $195.65 ($220,697.60 total reduction/1,128 IRFs) per IRF annually, or $220,697.60 for all IRFs annually based on the proposed removal of the Application of Functional Assessment/Care Plan measure.

In section VIII.C.1.d. of this proposed rule, we propose to remove the IRF Functional Outcome Measure: Change in Self-Care Score for Medical Rehabilitation Patients (Change in Self-Care Score) and the IRF Functional Outcome Measure: Change in Mobility Score for Medical Rehabilitation Patients (Change in Mobility Score) measures beginning with the FY 2025 IRF QRP. While these assessment-based quality measures are proposed for removal, the data elements used to calculate the measures would still be collected by IRFs for payment and quality reporting purposes, specifically for other quality measures under the IRF QRP. Therefore, we believe that the proposal to remove the Change in Self-Care Score and Change in Mobility Score measures would not decrease burden for IRFs.

In section VIII.C.2.a. of this proposed 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 IRF QRP. The proposed measure would be collected using the IRF–PAI. One data element would need to be added to the IRF–PAI at discharge in order to allow for collection of the Patient/Resident COVID–19 Vaccine measure, and we believe would result in an increase of 0.3 minutes of clinical staff time at discharge. We believe that the additional Patient/Resident COVID–19 Vaccine measure's data element would be completed equally by registered nurses and licensed vocational nurses. Mean hourly wages for these staff are detailed in Table 19. However, individual IRFs determine the staffing resources necessary. Using data from CY 2021, we estimate a total of 779,274 discharges on all patients regardless of payer from 1,128 IRFs annually. This equates to an increase of 3,896 hours in burden for all IRFs (0.005 hour × 779,274 admissions). Given 0.15 minutes of registered nurse time at $79.56 per hour and 0.15 minutes of licensed vocational nurse time at $49.86 per hour to complete an average of 691 IRF–PAI discharge assessments per IRF per year, we estimate that the total cost of complying with the IRF QRP requirements would be increased by $223.50 [($64.71/hr × 3,896 hours)/1,128 IRFs) per IRF annually, or $252,110.16 ($64.71/hr × 3,896 hours) for all IRFs annually based on the proposed adoption of the Patient/Resident COVID–19 Vaccine measure. The information collection request approved under OMB control number 0938–0842 (expiration date: August 31, 2025) will be revised and sent to OMB for approval.

In summary, under OMB control number (0938–0842), if the proposals for the IRF QRP are adopted as proposed, we estimate that there would be a cost increase of $27.85 per IRF ($31,412.56/1,128 IRFs). The total cost increase related to this information collection is approximately $31,412.56 and is summarized in Table 20.

Table 20—Proposals Associated With OMB Control Number 0938–0842

Proposal	Per IRF		All IRFs
	Change in annual burden hours	Change in annual cost	Change in annual burden hours	Change in annual cost
Change in Burden associated with proposed removal of the Application of Functional Assessment/Care Plan measure beginning with the FY 2025 IRF QRP	−2.3	−$195.65	−2,560	−$220,697.60
Change in Burden associated with proposed Patient/Resident COVID–19 Vaccine measure beginning with the FY 2026 IRF QRP	+3.5	+223.50	+3,896	+252,110.16
Total Change in burden for the IRF QRP associated with 0938–0842	1.2	27.85	1,336	31,412.56

We invite public comments on the proposed information collection requirements.

If you comment on these information collection, that is, reporting, recordkeeping or third-party disclosure requirements, please submit your comments electronically as specified in the ADDRESSES section of this proposed rule.

Comments must be received on/by June 2, 2023.

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. Regulatory Impact Analysis

A. Statement of Need

This proposed rule would update the IRF prospective payment rates for FY 2024 as required under section 1886(j)(3)(C) of the Act and in accordance with section 1886(j)(5) of the Act, which requires the Secretary to publish in the Federal Register on or before August 1 before each FY, the classification and weighting factors for CMGs used under the IRF PPS for such FY and a description of the methodology and data used in computing the prospective payment rates under the IRF PPS for that FY. This proposed rule would also implement section 1886(j)(3)(C) of the Act, which requires the Secretary to apply a productivity adjustment to the market basket increase factor for FY 2012 and subsequent years.

Furthermore, this proposed rule proposes to adopt policy changes to the IRF QRP under the statutory discretion afforded to the Secretary under section 1886(j)(7) of the Act. This rule proposes updates to the IRF QRP requirements beginning with the FY 2025 IRF QRP and FY 2026 IRF QRP. We propose a modification to a current measure in the IRF 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 propose adoption of two new measures: one measure to maintain compliance with the requirements of section 1899B of the Act and replace the current cross-setting process measure with a measure that is more strongly associated with desired patient functional outcomes; and a second measure that supports the goals of CMS Meaningful Measures Initiative 2.0 to empower consumers with tools and information as they make healthcare choices as well as assist IRFs leverage their care processes to increase vaccination coverage in their settings to protect residents and prevent negative outcomes. We propose the removal of three measures from the IRF QRP as they meet the criteria specified at § 412.634(b)(2) for measure removal.

B. Overall Impact

We have examined the impacts of this 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 Social Security Act, section 202 of the Unfunded Mandates Reform Act of 1995 (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). Section 3(f) of Executive Order 12866 defines a “significant regulatory action” as an action that is likely to result in a rule: (1) having an annual effect on the economy of $100 million or more in any 1 year, or adversely and materially affecting a sector of the economy, productivity, competition, jobs, the environment, public health or safety, or State, local or tribal governments or communities (2) creating a serious inconsistency or otherwise interfering with an action taken or planned by another agency; (3) materially altering the budgetary impacts of entitlement grants, user fees, or loan programs or the rights and obligations of recipients thereof; or (4) raising novel legal or policy issues arising out of legal mandates, the President's priorities, or the principles set forth in Executive Order 12866.

Section (6)(a) of Executive Order 12866 provides that a regulatory impact analysis (RIA) must be prepared for major rules with significant effects as per section 3(f)(1) Executive Order 12866 ($100 million or more in any 1 year). We estimate the total impact of the policy updates described in this proposed rule by comparing the estimated payments in FY 2024 with those in FY 2023. This analysis results in an estimated $335 million increase for FY 2024 IRF PPS payments. Additionally, we estimate that costs associated with the proposal to update the reporting requirements under the IRF QRP result in an estimated $31,783,532.15 additional cost in FY 2026 for IRFs. Based on our estimates OMB's Office of Information and Regulatory Affairs has reviewed and determined that this rulemaking is “significant” as per section 3(f)(1) of Executive Order 12866. Accordingly, we have prepared an RIA that, to the best of our ability, presents the costs and benefits of the rulemaking.

C. Anticipated Effects

1. Effects on IRFs

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, nonprofit organizations, and small governmental jurisdictions. Most IRFs and most other providers and suppliers are small entities, either by having revenues of $8.0 million to $41.5 million or less in any 1 year depending on industry classification, or by being nonprofit organizations that are not dominant in their markets. (For details, see the Small Business Administration's final rule that set forth size standards for health care industries, at 65 FR 69432 at https://www.sba.gov/​sites/​default/​files/​2019-08/​SBA%20Table%20of%20Size%20Standards_​Effective%20Aug%2019%2C%202019_​Rev.pdf, effective January 1, 2017 and updated on August 19, 2019.) Because we lack data on individual hospital receipts, we cannot determine the number of small proprietary IRFs or the proportion of IRFs' revenue that is derived from Medicare payments. Therefore, we assume that all IRFs (an approximate total of 1,128 IRFs, of which approximately 51 percent are nonprofit facilities) are considered small entities and that Medicare payment constitutes the majority of their revenues. HHS generally uses a revenue impact of 3 to 5 percent as a significance threshold under the RFA. As shown in Table 21, we estimate that the net revenue impact of the final rule on all IRFs is to increase estimated payments by approximately 3.7 percent. The rates and policies set forth in this proposed rule will not have a significant impact (not greater than 4 percent) on a substantial number of small entities. The estimated impact on small entities is shown in Table 21. MACs are not considered to be small entities. Individuals and States are not included in the definition of a small entity.

In addition, section 1102(b) of the Act requires us to prepare an RIA 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 a Metropolitan Statistical Area and has fewer than 100 beds. As shown in Table 21, we estimate that the net revenue impact of this proposed rule on rural IRFs is to increase estimated payments by approximately 3.2 percent based on the data of the 134 rural units and 12 rural hospitals in our database of 1,128 IRFs for which data were available. We estimate an overall impact for rural IRFs in all areas between 1.3 percent and 5.1 percent. As a result, we anticipate that this proposed rule will not have a significant impact on a substantial number of small entities.

Section 202 of the Unfunded Mandates Reform Act of 1995 (Pub. L. 104–04, enacted March 22, 1995) (UMRA) 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 does not mandate any requirements for State, local, or tribal governments, or for the private sector.

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. As stated, this proposed rule would not have a substantial effect on State and local governments, preempt State law, or otherwise have a federalism implication.

2. Detailed Economic Analysis

This proposed rule would update the IRF PPS rates contained in the FY 2023 IRF PPS final rule (87 FR 47038). Specifically, this proposed rule would update the CMG relative weights and ALOS values, the wage index, and the outlier threshold for high-cost cases. This proposed rule would apply a productivity adjustment to the FY 2024 IRF market basket increase factor in accordance with section 1886(j)(3)(C)(ii)(I) of the Act. Further, this proposed rule proposes to rebase and revise the IRF market basket to reflect a 2021 base year. We are also proposing to modify the regulation governing when IRF units can be excluded and paid under the IRF PPS.

We estimate that the impact of the changes and updates described in this proposed rule would be a net estimated increase of $335 million in payments to IRFs. The impact analysis in Table 21 of this proposed rule represents the projected effects of the updates to IRF PPS payments for FY 2024 compared with the estimated IRF PPS payments in FY 2023. We determine the effects by estimating payments while holding all other payment variables constant. We use the best data available, but we do not attempt to predict behavioral responses to these changes, and we do not make adjustments for future changes in such variables as number of discharges or case-mix.

We note that certain events may combine to limit the scope or accuracy of our impact analysis, because such an analysis is future-oriented and, thus, susceptible to forecasting errors because of other changes in the forecasted impact time period. Some examples could be legislative changes made by the Congress to the Medicare program that would impact program funding, or changes specifically related to IRFs. Although some of these changes may not necessarily be specific to the IRF PPS, the nature of the Medicare program is such that the changes may interact, and the complexity of the interaction of these changes could make it difficult to predict accurately the full scope of the impact upon IRFs.

In updating the rates for FY 2024, we are proposing the standard annual revisions described in this proposed rule (for example, the update to the wage index and market basket increase factor used to adjust the Federal rates). We are also reducing the FY 2024 IRF market basket increase factor by a productivity adjustment in accordance with section 1886(j)(3)(C)(ii)(I) of the Act. We estimate the total increase in payments to IRFs in FY 2024, relative to FY 2023, would be approximately $335 million.

This estimate is derived from the application of the proposed FY 2024 IRF market basket increase factor, as reduced by a productivity adjustment in accordance with section 1886(j)(3)(C)(ii)(I) of the Act, which yields an estimated increase in aggregate payments to IRFs of $270 million. However, there is an estimated $65 million increase in aggregate payments to IRFs due to the proposed update to the outlier threshold amount. Therefore, we estimate that these updates would result in a net increase in estimated payments of $335 million from FY 2023 to FY 2024.

The effects of the proposed updates that impact IRF PPS payment rates are shown in Table 21. The following proposed updates that affect the IRF PPS payment rates are discussed separately below:

• The effects of the proposed update to the outlier threshold amount, from approximately 2.3 percent to 3.0 percent of total estimated payments for FY 2024, consistent with section 1886(j)(4) of the Act.
• The effects of the proposed annual market basket update (using the proposed 2021-based IRF market basket) to IRF PPS payment rates, as required by sections 1886(j)(3)(A)(i) and (j)(3)(C) of the Act, including a productivity adjustment in accordance with section 1886(j)(3)(C)(ii)(I) of the Act.
• The effects of applying the proposed budget-neutral labor-related share and wage index adjustment, as required under section 1886(j)(6) of the Act, accounting for the permanent cap on wage index decreases when applicable.
• The effects of the proposed budget-neutral changes to the CMG relative weights and ALOS values under the authority of section 1886(j)(2)(C)(i) of the Act.
• The total change in estimated payments based on the FY 2024 payment changes relative to the estimated FY 2023 payments.

3. Description of Table 21

Table 21 shows the overall impact on the 1,128 IRFs included in the analysis.

The next 12 rows of Table 21 contain IRFs categorized according to their geographic location, designation as either a freestanding hospital or a unit of a hospital, and by type of ownership; all urban, which is further divided into urban units of a hospital, urban freestanding hospitals, and by type of ownership; and all rural, which is further divided into rural units of a hospital, rural freestanding hospitals, and by type of ownership. There are 982 IRFs located in urban areas included in our analysis. Among these, there are 645 IRF units of hospitals located in urban areas and 337 freestanding IRF hospitals located in urban areas. There are 146 IRFs located in rural areas included in our analysis. Among these, there are 134 IRF units of hospitals located in rural areas and 12 freestanding IRF hospitals located in rural areas. There are 455 for-profit IRFs. Among these, there are 420 IRFs in urban areas and 35 IRFs in rural areas. There are 570 non-profit IRFs. Among these, there are 480 urban IRFs and 90 rural IRFs. There are 103 government-owned IRFs. Among these, there are 82 urban IRFs and 21 rural IRFs.

The remaining four parts of Table 21 show IRFs grouped by their geographic location within a region, by teaching status, and by DSH patient percentage (PP). First, IRFs located in urban areas are categorized for their location within a particular one of the nine Census geographic regions. Second, IRFs located in rural areas are categorized for their location within a particular one of the nine Census geographic regions. In some cases, especially for rural IRFs located in the New England, Mountain, and Pacific regions, the number of IRFs represented is small. IRFs are then grouped by teaching status, including non-teaching IRFs, IRFs with an intern and resident to average daily census (ADC) ratio less than 10 percent, IRFs with an intern and resident to ADC ratio greater than or equal to 10 percent and less than or equal to 19 percent, and IRFs with an intern and resident to ADC ratio greater than 19 percent. Finally, IRFs are grouped by DSH PP, including IRFs with zero DSH PP, IRFs with a DSH PP less than 5 percent, IRFs with a DSH PP between 5 and less than 10 percent, IRFs with a DSH PP between 10 and 20 percent, and IRFs with a DSH PP greater than 20 percent.

The estimated impacts of each policy described in this rule to the facility categories listed are shown in the columns of Table 21. The description of each column is as follows:

• Column (1) shows the facility classification categories.
• Column (2) shows the number of IRFs in each category in our FY 2024 analysis file.
• Column (3) shows the number of cases in each category in our FY 2024 analysis file.
• Column (4) shows the estimated effect of the proposed adjustment to the outlier threshold amount.
• Column (5) shows the estimated effect of the proposed update to the IRF labor-related share and wage index, in a budget-neutral manner.
• Column (6) shows the estimated effect of the proposed update to the CMG relative weights and ALOS values, in a budget-neutral manner.
• Column (7) compares our estimates of the payments per discharge, incorporating all of the policies reflected in this proposed rule for FY 2024 to our estimates of payments per discharge in FY 2023.

The average estimated increase for all IRFs is approximately 3.7 percent. This estimated net increase includes the effects of the proposed IRF market basket update for FY 2024 of 3.0 percent, which is based on a proposed IRF market basket increase factor of 3.2 percent, less a 0.2 percentage point productivity adjustment, as required by section 1886(j)(3)(C)(ii)(I) of the Act. It also includes the approximate 0.7 percent overall increase in estimated IRF outlier payments from the proposed update to the outlier threshold amount. Since we are making the proposed updates to the IRF wage index, labor-related share and the CMG relative weights in a budget-neutral manner, they would not be expected to affect total estimated IRF payments in the aggregate. However, as described in more detail in each section, they would be expected to affect the estimated distribution of payments among providers.

4. Impact of the Proposed Update to the Outlier Threshold Amount

The estimated effects of the proposed update to the outlier threshold adjustment are presented in column 4 of Table 21.

For this proposed rule, we are using preliminary FY 2022 IRF claims data and, based on that preliminary analysis, we estimated that IRF outlier payments as a percentage of total estimated IRF payments would be 2.3 percent in FY 2023. Thus, we propose to adjust the outlier threshold amount in this proposed rule to maintain total estimated outlier payments equal to 3 percent of total estimated payments in FY 2024. The estimated change in total IRF payments for FY 2024, therefore, includes an approximate 0.7 percentage point increase in payments because the estimated outlier portion of total payments is estimated to increase from approximately 2.3 percent to 3.0 percent.

The impact of this proposed outlier adjustment update (as shown in column 4 of Table 21) is to increase estimated overall payments to IRFs by 0.7 percentage point.

5. Impact of the Proposed Wage Index, Labor-Related Share, and Wage Index Cap

In column 5 of Table 21, we present the effects of the proposed budget-neutral update of the wage index and labor-related share, taking into account the permanent 5 percent cap on wage index decreases, when applicable. The proposed changes to the wage index and the labor-related share are discussed together because the wage index is applied to the labor-related share portion of payments, so the proposed changes in the two have a combined effect on payments to providers. As discussed in section V.E. of this proposed rule, we are proposing to update the FY 2024 labor-related share from 72.9 percent in FY 2023 to 74.1 percent in FY 2024. In aggregate, we do not estimate that these proposed updates will affect overall estimated payments to IRFs. However, we do expect these updates to have small distributional effects. We estimate the largest decrease in payment from the update to the CBSA wage index and labor-related share to be a 2.5 percent decrease for IRFs in the Rural New England region and the largest increase in payment to be a 0.6 percent increase for IRFs in the Urban Middle Atlantic Region.

6. Impact of the Proposed Update to the CMG Relative Weights and ALOS Values

In column 6 of Table 21, we present the effects of the proposed budget-neutral update of the CMG relative weights and ALOS values. In the aggregate, we do not estimate that these proposed updates will affect overall estimated payments of IRFs. However, we do expect these updates to have small distributional effects, with the largest effect being an increase in payments of 0.3 percent to IRFs in the Rural New England region.

7. Effects of Proposed Modification of the Regulation for Excluded IRF Units Paid Under the IRF PPS

As discussed in section VII. of this proposed rule, we are proposing to amend the regulation text at § 412.25(c)(1) in this proposed rule.

We do not anticipate a financial impact associated with the proposed modification of the regulation for excluded IRF units paid under the IRF PPS. In response to the need for availability of inpatient rehabilitation beds we are proposing changes to § 412.25(c) to allow greater flexibility for hospitals to open excluded units, while minimizing the amount of effort that Medicare contractors would need to spend administering the regulatory requirements. We believe this proposal would provide IRFs greater flexibility when establishing an excluded unit at a time other than the start of a cost reporting period.

8. Effects of Requirements for the IRF QRP Beginning With FY 2025

In accordance with section 1886(j)(7)(A) of the Act, the Secretary must reduce by 2 percentage points the annual market basket increase factor otherwise applicable to an IRF for a fiscal year if the IRF does not comply with the requirements of the IRF QRP for that fiscal year. In section VIII.A. of the proposed rule, we discuss the method for applying the 2 percentage point reduction to IRFs that fail to meet the IRF QRP requirements.

As discussed in section VIII.C.1.a. of this proposed rule, we propose to modify one measure in the IRF QRP beginning with the FY 2025 IRF QRP, the HCP COVID–19 Vaccine measure. We believe that the burden associated with the IRF QRP is the time and effort associated with complying with the non-claims-based measures requirements of the IRF 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 0920–1317 (expiration August 1, 2025).

As discussed in section VIII.C.1.b. of this proposed rule, we propose that IRFs would collect data on one new quality measure, the DC Function measure, beginning with assessments completed on October 1, 2023. However, the measure utilizes data items that IRFs 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 0920–0842 (expiration August 31, 2025).

As discussed in section VIII.C.1.c. of this proposed rule, we propose to remove the Application of Functional Assessment/Care Plan measure, from the IRF QRP and this proposal would result in a decrease of 0.3 minutes of clinical staff time 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 (0938–0842), we are providing impact information. We believe the data element for this quality measure is completed by occupational therapists (45 percent of the time or 0.135 minutes), physical therapists (45 percent of the time or 0.135 minutes), registered nurses (5 percent of the time or 0.015 minutes), licensed practical and vocational nurses (2.5 percent of the time or 0.0075 minutes), or by speech-language pathologists (2.5 percent of the time or 0.0075 minutes). For the purposes of calculating the costs associated with the collection of information requirements, we obtained mean hourly wages for these staff from the U.S. Bureau of Labor Statistics' (BLS) May 2021 National Occupational Employment and Wage Estimates.^[170] To account for overhead and fringe benefits, we have doubled the hourly wage. These amounts are detailed in Table 22.

Table 22—U.S. Bureau of Labor and Statistics' May 2021 National Occupational Employment and Wage Estimates

Occupation title	Occupation code	Mean hourly wage ($/hr)	Overhead and fringe benefit ($/hr)	Adjusted hourly wage ($/hr)
Registered Nurse (RN)	29–1141	$39.78	$39.78	$79.56
Licensed Vocational Nurse (LVN)	29–2061	24.93	24.93	49.86
Speech Language Pathologist (SLP)	29–1127	41.26	41.26	82.52
Physical Therapist (PT)	29–1123	44.67	44.67	89.34
Occupational Therapist (OT)	29–1122	43.02	43.02	86.04

With 511,938 admissions from 1,128 IRFs annually, we estimate an annual burden decrease of 2,560 fewer hours (511,938 admissions × .005 hours) and a decrease of $220,697.60 [2,560 hours × $86.21/hr]. For each IRF we estimate an annual burden decrease of 2.3 hours (2,560 hours/1,128 IRFs) at a savings of $195.65 ($220,697.60/1,128 IRFs).

As discussed in section VIII.C.1.d. of this proposed rule, we propose to remove two additional measures from the IRF QRP, the Change in Self-Care and Change in Mobility measures, beginning with assessments completed on October 1, 2023. However, the data items used in the calculation of this measure are used for other payment and quality reporting purposes, and therefore there is no change in burden associated with this proposal.

9. Effects of Requirements for the IRF QRP Beginning With FY 2026

As discussed in section VIII.C.2.a. of this proposed rule, we propose to adopt a measure, the Patient/Resident COVID–19 Vaccine measure, beginning with the FY 2026 IRF QRP and this proposal would result in an increase of 0.3 minutes 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 (0938–0842), we are providing impact information. We estimate the data element for this quality measure would be completed by registered nurses (50 percent of the time or 0.15 minutes) or by licensed practical and vocational nurses (50 percent of the time or 0.15 minutes). For the purposes of calculating the costs associated with the collection of information requirements, we obtained mean hourly wages for these staff from the U.S. Bureau of Labor Statistics' (BLS) May 2021 National Occupational Employment and Wage Estimates.^[171] To account for overhead and fringe benefits, we have doubled the hourly wage. These amounts are detailed in Table 22. With 779,274 discharges on all patients regardless of payer from 1,128 IRFs annually, we estimate an annual burden increase of 3,896 hours (779,274 discharges × 0.005 hours) and an increase of $252,110.16 ($64.71/hr × 3,896 hours). For each IRF we estimate an annual burden increase of 3.5 hours (3,896 hours/1,128 IRFs) at an additional cost of $223.50 ($252,110.16/1,128 IRFs).

In summary, under OMB control number (0938–0842), if the proposals associated with the IRF QRP are adopted as proposed, we estimate an increase in programmatic impact for 1,128 IRFs. The total burden reduction is approximately $31,412.56 and is summarized in Table 23.

Table 23—Estimated IRF QRP Program Impacts for FY 2025 and FY 2026

Proposal	Per IRF		All IRFs
	Change in annual burden hours	Change in annual cost	Change in annual burden hours	Change in annual cost
Change in Burden associated with proposed removal of the Application of Functional Assessment/Care Plan measure beginning with the FY 2025 IRF QRP	−2.3	−$195.65	−2,560	−$220,697.60
Change in Burden associated with proposed Patient/Resident COVID–19 Vaccine measure beginning with the FY 2026 IRF QRP	+3.5	+223.50	+3,896	+252,110.16
Total increase in burden for the IRF QRP proposals associated with this proposed rule	1.2	27.85	1,336	31,412.56

We invite public comments on the overall impact of the IRF QRP proposals for FY 2025 and FY 2026.

D. Alternatives Considered

The following is a discussion of the alternatives considered for the IRF PPS updates contained in this proposed rule.

Section 1886(j)(3)(C) of the Act requires the Secretary to update the IRF PPS payment rates by an increase factor that reflects changes over time in the prices of an appropriate mix of goods and services included in the covered IRF services.

We are proposing to adopt a market basket increase factor for FY 2024 that is based on a rebased and revised market basket reflecting a 2021 base year. We considered the alternative of continuing to use the IRF market basket without rebasing to determine the market basket increase factor for FY 2024. However, we typically rebase and revise the market baskets for the various PPS every 4 to 5 years so that the cost weights and price proxies reflect more recent data. Therefore, we believe it is more technically appropriate to use a 2021-based IRF market basket since it allows for the FY 2024 market basket increase factor to reflect a more up-to-date cost structure experienced by IRFs.

As noted previously in this proposed rule, section 1886(j)(3)(C) of the Act requires the Secretary to update the IRF PPS payment rates by an increase factor that reflects changes over time in the prices of an appropriate mix of goods and services included in the covered IRF services and section 1886(j)(3)(C)(ii)(I) of the Act requires the Secretary to apply a productivity adjustment to the market basket increase factor for FY 2024. Thus, in accordance with section 1886(j)(3)(C) of the Act, we propose to update the IRF prospective payments in this proposed rule by 3.0 percent (which equals the 3.2 percent estimated IRF market basket increase factor for FY 2024 reduced by a 0.2 percentage point productivity adjustment as determined under section 1886(b)(3)(B)(xi)(II) of the Act (as required by section 1886(j)(3)(C)(ii)(I) of the Act)).

We considered maintaining the existing CMG relative weights and average length of stay values for FY 2024. However, in light of recently available data and our desire to ensure that the CMG relative weights and average length of stay values are as reflective as possible of recent changes in IRF utilization and case mix, we believe that it is appropriate to propose to update the CMG relative weights and average length of stay values at this time to ensure that IRF PPS payments continue to reflect as accurately as possible the current costs of care in IRFs.

We considered maintaining the existing outlier threshold amount for FY 2024. However, analysis of updated FY 2023 data indicates that estimated outlier payments would be less than 3 percent of total estimated payments for FY 2024, by approximately 0.7 percent, unless we updated the outlier threshold amount. Consequently, we propose adjusting the outlier threshold amount in this proposed rule to reflect a 0.7 percent increase thereby setting the total outlier payments equal to 3 percent, instead of 2.3 percent, of aggregate estimated payments in FY 2024.

We considered not modifying the regulation governing when IRF units can be excluded and paid under the IRF PPS. However, we believe that amending the regulation would provide hospitals greater flexibility when establishing an IRF.

With regard to the proposal to modify the HCP COVID–19 Vaccine measure and to add the Patient/Resident COVID–19 Vaccine measure to the IRF QRP Program, the COVID–19 pandemic has exposed the importance of implementing infection prevention strategies, including the promotion of COVID–19 vaccination for HCP and patients/residents. We believe these measures would encourage healthcare personnel to get up to date with the COVID–19 vaccine and increase vaccine uptake in patients/residents resulting in fewer cases, less hospitalizations, and lower mortality associated with the SARS-CoV–2 virus, but we were unable to identify any alternative methods for collecting the data. An overwhelming public need exists to target quality improvement among IRFs as well as provide data to patients and caregivers through transparency of data. Therefore, these proposed measures have the potential to generate actionable data on COVID–19 vaccination rates.

The proposal to replace the topped-out Application of Functional Assessment/Care Plan process measure with the proposed DC Function measure, which has strong scientific acceptability, satisfies the requirement that there be at least one cross-setting function measure in the PAC QRPs, including the IRF QRP, that uses standardized functional assessment data elements from standardized patient assessment instruments. We considered the alternative of delaying the proposal of adopting the DC Function measure. However, given the proposed DC Function measure's strong scientific acceptability, the fact that it provides an opportunity to replace the current cross-setting process measure (that is, the Application of Functional Assessment/Care Plan measure) with an outcome measure, and uses standardized functional assessment data elements that are already collected, we believe further delay of the DC Function measure is unwarranted. Further, the proposed removal of the Application of Functional Assessment/Care Plan measure meets measure removal factors one and six, and no longer provides meaningful distinctions in improvements in performance. Finally, the proposal to remove the Change in Self-Care Score and Change in Mobility Score measures meets measure removal factor eight, and the costs associated with a measure outweigh the benefits of its use in the program. Therefore, no alternatives were considered.

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 the FY 2024 IRF PPS 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 proposed rule. It is possible that not all commenters reviewed the FY 2023 IRF PPS proposed rule in detail, and it is also possible that some reviewers chose not to comment on the FY 2023 proposed rule. For these reasons, we thought that the number of commenters would be a fair estimate of the number of reviewers of this 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 for Occupational Employment Statistics (OES) 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 3 hours for the staff to review half of this proposed rule. For each reviewer of the rule, the estimated cost is $345.66 (3 hours × $115.22). Therefore, we estimate that the total cost of reviewing this regulation is $21,085.26 ($345.66 × 61 reviewers).

F. Accounting Statement and Table

As required by OMB Circular A–4 (available at https://www.whitehouse.gov/​wp-content/​uploads/​legacy_​drupal_​files/​omb/​circulars/​A4/​a-4.pdf), in Table 24 we have prepared an accounting statement showing the classification of the expenditures associated with the provisions of this proposed rule. Table 24 provides our best estimate of the increase in Medicare payments under the IRF PPS as a result of the proposed updates presented in this proposed rule based on the data for 1,128 IRFs in our database.

Table 24—Accounting Statement: Classification of Estimated Expenditure

	Category	Transfers
Change in Estimated Transfers from FY 2023 IRF PPS to FY 2024 IRF PPS	Annualized Monetized Transfers	$335 million.
	From Whom to Whom?	Federal Government to IRF Medicare Providers.
Estimated Costs Associated with the FY 2025 and FY 2026 IRF QRP	Annualized monetized cost in FY 2025 and FY 2026 for IRFs due to new quality reporting program requirements	$31,412.56.
Estimated Costs Associated with Review Cost for FY 2024 IRF PPS	Cost associated with regulatory review cost	$21,085.26.

G. Conclusion

Overall, the estimated payments per discharge for IRFs in FY 2024 are projected to increase by 3.7 percent, compared with the estimated payments in FY 2023, as reflected in column 7 of Table 21.

IRF payments per discharge are estimated to increase by 3.8 percent in urban areas and 3.2 percent in rural areas, compared with estimated FY 2023 payments. Payments per discharge to rehabilitation units are estimated to increase 4.4 percent in urban areas and 3.5 percent in rural areas. Payments per discharge to freestanding rehabilitation hospitals are estimated to increase 3.4 percent in urban areas and 2.3 percent in rural areas.

Overall, IRFs are estimated to experience a net increase in payments as a result of the proposed policies in this proposed rule. The largest payment increase is estimated to be a 5.1 percent increase for IRFs located in the Rural Mountain region. The analysis above, together with the remainder of this preamble, provides an RIA.

In accordance with the provisions of Executive Order 12866, this regulation was reviewed by OMB.

Chiquita Brooks-LaSure, Administrator of the Centers for Medicare & Medicaid Services, approved this document March 30, 2023.

List of Subjects 42 CFR 412

• Administrative practice and procedure
• Health facilities
• Medicare
• Puerto Rico
• 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 412—PROSPECTIVE PAYMENT SYSTEMS FOR INPATIENT HOSPITAL SERVICES

1. The authority citation for part 412 continues to read as follows:

Authority: 42 U.S.C. 1302 and 1395hh.

2. Amend § 412.25 by revising paragraph (c)(1) to read as follows:

§ 412.25

Excluded hospital units: Common requirements.

* * * * *

(c) * * *

(1) The status of an IRF unit may be changed from not excluded to excluded or excluded to not excluded at any time during a cost reporting period, but only if the hospital notifies the Medicare Administrative Contractor and the CMS Regional Office in writing of the change at least 30 days before the date of the change, and maintains the information needed to accurately determine costs that are or are not attributable to the IRF unit. A change in the status of an IRF unit from not excluded to excluded or excluded to not excluded that is made during a cost reporting period must remain in effect for the rest of that cost reporting period.

* * * * *

Dated: March 30, 2023.

Xavier Becerra,

Secretary, Department of Health and Human Services.

Footnotes

1.  Patel A, Jernigan DB. Initial Public Health Response and Interim Clinical Guidance for the 2019 Novel Coronavirus Outbreak—United States, December 31, 2019–February 4, 2020. MMWR Morb Mortal Wkly Rep 2020;69:140–146. DOI http://dx.doi.org/​10.15585/​mmwr.mm6905e1.

2.  CMS, “COVID–19 Emergency Declaration Blanket Waivers for Health Care Providers,” (updated Feb. 19 2021) (available at https://www.cms.gov/​files/​document/​summary-covid-19-emergency-declaration-waivers.pdf).

3.  CMS, “COVID–19 Frequently Asked Questions (FAQs) on Medicare Fee-for-Service (FFS) Billing,” (updated March 5, 2021) (available at https://www.cms.gov/​files/​document/​03092020-covid-19-faqs-508.pdf).

4.  HL7 FHIR Release 4. Available at https://www.hl7.org/​fhir/​.

5.  HL7 FHIR. PACIO Functional Status Implementation Guide. Available at https://paciowg.github.io/​functional-status-ig/​.

6.  PACIO Project. Available at http://pacioproject.org/​about/​.

7.  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.

8.  USCDI. Available at https://www.healthit.gov/​isa/​united-states-core-data-interoperability-uscdi.

9.  USCDI+. Available at https://www.healthit.gov/​topic/​interoperability/​uscdi-plus.

10.  Sections 4001 through 4008 of Public Law 114–255. Available at https://www.govinfo.gov/​content/​pkg/​PLAW-114publ255/​html/​PLAW-114publ255.htm.

11.  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.

12.  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.

13.  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.

14.  “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.

15.  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.

16.   http://www.bea.gov/​papers/​pdf/​IOmanual_​092906.pdf.

17.  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.

18.  U.S. Department of Health and Human Services, Office of the Assistant Secretary for Preparedness and Response. Determination that a Public Health Emergency Exists. Available at https://aspr.hhs.gov/​legal/​PHE/​Pages/​2019-nCoV.aspx.

19.  Centers for Disease Control and Prevention. COVID Data Tracker. March 21, 2023. https://covid.cdc.gov/​covid-data-tracker/​#datatracker-home.

20.  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.

21.  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.

22.  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.

23.  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.

24.  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.

25.  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.

26.  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.

27.  Food and Drug Administration. Coronavirus (COVID–19) Update: FDA Takes Key Action by Approving Second COVID–19 Vaccine. January 21, 2022. https://www.fda.gov/​news-events/​press-announcements/​coronavirus-covid-19-update-fda-takes-key-action-approving-second-covid-19-vaccine.

28.  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.

29.  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.

30.  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.

31.  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.

32.  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.

33.  Food and Drug Administration. (August 2022). Coronavirus (COVID–19) Update: FDA Authorizes Moderna, Pfizer-BioNTech Bivalent COVID–19 Vaccines for Use as a Booster Dose. Available at https://www.fda.gov/​news-events/​press-announcements/​coronavirus-covid-19-update-fda-authorizes-moderna-pfizer-biontech-bivalent-covid-19-vaccines-use.

34.  Centers for Disease Control and Prevention. (September 24, 2021). 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. Available at https://cdc.gov/​mmwr/​volumes/​70/​wr/​mm7038e1.htm?​s_​cid=​mm7038e1_​w.

35.  Centers for Disease Control and Prevention. (September 10, 2021). 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. Available at https://www.cdc.gov/​mmwr/​volumes/​70/​wr/​mm7037e1.htm.

36.  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://www.cdc.gov/​mmwr/​volumes/​70/​wr/​mm7034e4.htm.

37.  Pilishivi, T. et al. Effectiveness of mRNA COVID–19 Vaccine among U.S. Health Care Personnel. New England Journal of Medicine. 2021 Dec 16;385(25):e90. December 16, 2022. https://pubmed.ncbi.nlm.nih.gov/​34551224/​.

38.  Centers for Disease Control and Prevention. Variants of the Virus. https://www.cdc.gov/​coronavirus/​2019-ncov/​variants/​index.html.

39.  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.

40.  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.

41.  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.

42.  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.

43.  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.

44.  Oster Y, Benenson S, Nir-Paz R, Buda I, Cohen MJ. 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. Available online at https://pubmed.ncbi.nlm.nih.gov/​35143997/​.

45.  Prasad N et al. (May 2022). 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: 10.1016/j.cmi.2022.01.019. PMID: 35143997; PMCID: PMC8820100.

46.  Centers for Medicare & Medicaid Services. Measure Application Partnership (MAP) Post-Acute Care/Long-Term Care: 2022–2023 Measures Under Consideration (MUC) Cycle Measure Specifications. December 1, 2022. https://mmshub.cms.gov/​sites/​default/​files/​map-pac-muc-measure-specifications-2022-2023.pdf.

47.  Centers for Medicare & Medicaid Services. Measure Application Partnership (MAP) Post-Acute Care/Long-Term Care: 2022–2023 Measures Under Consideration (MUC) Cycle Measure Specifications. December 1, 2022. https://mmshub.cms.gov/​sites/​default/​files/​map-pac-muc-measure-specifications-2022-2023.pdf.

48.  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.

49.  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.

50.  National Quality Forum. 3636 Quarterly Reporting of COVID–19 Vaccination Coverage among Healthcare Personnel. Accessed February 6, 2023. https://www.qualityforum.org/​QPS/​3636.

51.  2022–2023 MAP Final Recommendations. https://mmshub.cms.gov/​sites/​default/​files/​2022-2023-MAP-Final-Recommendations-508.xlsx.

52.  Centers for Disease Control and Prevention. Contraindications and precautions. https://www.cdc.gov/​vaccines/​covid-19/​clinical-considerations/​interim-considerations-us.html#contraindications.

53.  Centers for Disease Control and Prevention. Contraindications and precautions. https://www.cdc.gov/​vaccines/​covid-19/​clinical-considerations/​interim-considerations-us.html#contraindications.

54.  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.

55.  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.

56.  42 CFR 412.29.

57.  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.

58.  Hatem SM, Saussez G, Della Faille M, Prist V, Zhang X, Dispa D, Bleyenheuft Y. Rehabilitation of Motor Function After Stroke: A Multiple Systematic Review Focused on Techniques to Stimulate Upper Extremity Recovery. Front Hum Neurosci. 2016 Sep 13;10:442. doi: 10.3389/fnhum.2016.00442. PMID: 27679565; PMCID: PMC5020059.

59.  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.

60.  The measures include: Change in Self-Care Score for Medical Rehabilitation Patients (Change in Mobility for Medical Rehabilitation Patients, Discharge Self-Care Score for Medical Rehabilitation Patients), Discharge Mobility Score for Medical Rehabilitation Patients.

61.  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.

62.  Clouston SA, Brewster P, Kuh D, Richards M, Cooper R, Hardy R, Rubin MS, Hofer SM. 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.

63.  Michael YL, Colditz GA, 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.

64.  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.

65.  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.

66.  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.

67.  Alcusky M, Ulbricht CM, Lapane KL. 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.

68.  Chu CH, Quan AML, McGilton KS. 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.

69.  Li CY, Haas A, Pritchard KT, Karmarkar A, Kuo YF, Hreha K, Ottenbacher KJ. 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.

70.  Middleton A, Graham JE, Lin YL, Goodwin JS, Bettger JP, Deutsch A, Ottenbacher KJ. 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.

71.  Gustavson AM, Malone DJ, Boxer RS, Forster JE, Stevens-Lapsley JE. 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.

72.  Minor M, Jaywant A, Toglia J, Campo M, O'Dell MW. 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.

73.  Dubin R, Veith JM, Grippi MA, McPeake J, Harhay MO, Mikkelsen ME. 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.

74.  Hoffman GJ, Liu H, Alexander NB, Tinetti M, Braun TM, Min LC. 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.

75.  Evans E, Krebill C, Gutman R, Resnik L, Zonfrillo MR, Lueckel SN, Zhang W, Kumar RG, Dams-O'Connor K, Thomas KS. Functional Motor Improvement during Inpatient Rehabilitation among Older Adults with Traumatic Brain Injury. PM R. 2022 Apr;14(4):417–427. doi: 10.1002/pmrj.12644. PMID: 34018693; PMCID: PMC8606011.

76.  Kowalski RG, Hammond FM, Weintraub AH, Nakase-Richardson R, Zafonte RD, Whyte J, Giacino JT. Recovery of Consciousness and Functional Outcome in Moderate and Severe Traumatic Brain Injury. JAMA Neurol. 2021;78(5):548–557. doi: 10.1001/jamaneurol.2021.0084. PMID: 33646273; PMCID: PMC7922241.

77.  Li CY, Karmarkar A, Kuo YF, Haas A, Ottenbacher KJ. Impact of Self-Care and Mobility on One or More Post-Acute Care Transitions. J Aging Health. 2020;32(10):1325–1334. doi: 10.1177/0898264320925259. PMID: 32501126; PMCID: PMC7718286.

78.  O'Dell MW, Jaywant A, Frantz M, Patel R, Kwong E, Wen K, Taub M, Campo M, Toglia J. Changes in the Activity Measure for Post-Acute Care Domains in Persons With Stroke During the First Year After Discharge From Inpatient Rehabilitation. Arch Phys Med Rehabil. 2021 Apr;102(4):645–655. doi: 10.1016/j.apmr.2020.11.020. PMID: 33440132.

79.  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.

80.  Chang FH, Lin YN, Liou TH, Lin JC, Yang CH, Cheng HL. Predicting Admission to Post-Acute Inpatient Rehabilitation in Patients with Acute Stroke. J Rehabil Med. 2020 Sep 28;52(9):jrm00105. doi: 10.2340/16501977–2739. PMID: 32924065.

81.  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.

82.  Covert S, Johnson JK, Stilphen M, Passek S, Thompson NR, 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.

83.  Criss MG, Wingood M, Staples WH, Southard V, Miller KL, Norris TL, Avers D, Ciolek CH, Lewis CB, Strunk ER. APTA Geriatrics' Guiding Principles for Best Practices in Geriatric Physical Therapy: An Executive Summary. J Geriatr Phys Ther. 2022 Apr–June;45(2):70–75. doi: 10.1519/JPT.0000000000000342. PMID: 35384940.

84.  Cogan AM, Weaver JA, McHarg M, Leland NE, 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.

85.  Discharge Function Score for Inpatient Rehabilitation Facilities (IRFs) Technical Report. https://www.cms.gov/​files/​document/​irf-discharge-function-score-technical-report-february-2023.pdf.

86.  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 measures (Discharge Mobility Score).

87.  Post-Acute Care Payment Reform Demonstration Report to Congress Supplement—Interim Report. May 2011. Available at https://www.cms.gov/​Research-Statistics-Data-and-Systems/​Statistics-Trends-and-Reports/​Reports/​Downloads/​GAGE_​PACPRD_​RTC_​Supp_​Materials_​May_​2011.pdf.

88.  “Expected functional capabilities” is defined as the predicted discharge function score.

89.   Discharge Function Score for Inpatient Rehabilitation Facilities (IRFs) Technical Report. https://www.cms.gov/​files/​document/​irf-discharge-function-score-technical-report-february-2023.pdf.

90.  The measures include: Change in Self-Care Score for Medical Rehabilitation Patients Change in Mobility Score for Medical Rehabilitation Patients, Discharge Self-Care Score for Medical Rehabilitation Patients, and Discharge Mobility Score for Medical Rehabilitation Patients.

91.   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.

92.  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.

93.  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.

94.  2022–2023 MAP Final Recommendations. https://mmshub.cms.gov/​sites/​default/​files/​2022-2023-MAP-Final-Recommendations-508.xlsx.

95.  Discharge Function Score for Inpatient Rehabilitation Facilities (IRFs) Technical Report. https://www.cms.gov/​files/​document/​irf-discharge-function-score-technical-report-february-2023.pdf.

96.   Discharge Function Score for Inpatient Rehabilitation Facilities (IRFs) Technical Report. https://www.cms.gov/​medicare/​quality-initiatives-patient-assessment-instruments/​irf-quality-reporting/​irf-quality-reporting-program-measures-information-.

97.  For more information on the factors CMS uses to base decisions for measure removal, we refer readers to § 412.364(b)(2). https://www.ecfr.gov/​current/​title-42/​chapter-IV/​subchapter-B/​part-412/​subpart-P/​section-412.634.

98.  Centers for Medicare & Medicaid Services. Inpatient Rehabilitation Facilities Data Archive, 2021, Annual Files National Data 07–21. https://data.cms.gov/​provider-data/​archived-data/​inpatient-rehabilitation-facilities.

99.  Centers for Medicare & Medicaid Services. Inpatient Rehabilitation Facilities Data Archive, 2022, Annual Files National Data 04–22. https://data.cms.gov/​provider-data/​archived-data/​inpatient-rehabilitation-facilities.

100.  Centers for Medicare & Medicaid Services. Inpatient Rehabilitation Facilities Data Archive, 2022, Annual Files National Data 09–22. https://data.cms.gov/​provider-data/​archived-data/​inpatient-rehabilitation-facilities.

101.  Centers for Medicare & Medicaid Services. Inpatient Rehabilitation Facilities Data Archive, 2022, Annual Files Provider Data 04–22. https://data.cms.gov/​provider-data/​archived-data/​inpatient-rehabilitation-facilities.

102.  Centers for Medicare & Medicaid Services. Inpatient Rehabilitation Facilities Data Archive, 2022, Annual Files Provider Data 09–22. https://data.cms.gov/​provider-data/​archived-data/​inpatient-rehabilitation-facilities.

103.  “Expected functional capabilities” is defined as the predicted discharge function score.

104.  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.

105.  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.

106.  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.

107.  Centers for Disease Control and Prevention. COVID Data Tracker. https://covid.cdc.gov/​covid-data-tracker/​#cases_​totalcases.

108.  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.

109.  Lekamwasam R, Lekamwasam S. Effects of COVID–19 pandemic on health and wellbeing of older people: a comprehensive review. Ann Geriatr Med Res. 2020 Sep;24(3):166–172.doi: 10.4235/agmr.20.0027. PMID: 32752587; PMCID: PMC7533189.

110.  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.

111.  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.

112.  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.

113.  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.

114.  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. http://dx.doi.org/​10.15585/​mmwr.mm7037e2.

115.  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 .

116.  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 Apr 21;386(16):1532–1546. doi 10.1056/NEJMoa2119451. PMID: 35249272; PMCID: PMC8908811.

117.  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 Sep 1;5(9):e2232760.doi: 10.1001/jamanetworkopen.2022.32760. https://jamanetwork.com/​journals/​jamanetworkopen/​fullarticle/​2796615. PMID: 36136332; PMCID: PMC9500552.

118.  Centers for Disease Control and Prevention. Rates of laboratory-confirmed COVID–19 hospitalizations by vaccination status. COVID Data Tracker. 2023, February 9. Last accessed March 22, 2023. https://covid.cdc.gov/​covid-data-tracker/​#covidnet-hospitalizations-vaccination.

119.  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.

120.  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.

121.  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.

122.  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.

123.  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.

124.  Freed M, Neuman T, Kates J, Cubanski J. Deaths among older adults due to COVID–19 jumped during the summer of 2022 before falling somewhat in September. Kaiser Family Foundation. October 6, 2022. https://www.kff.org/​coronavirus-covid-19/​issue-brief/​deaths-among-older-adults-due-to-covid-19-jumped-during-the-summer-of-2022-before-falling-somewhat-in-september/​.

125.  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 Mar 4;71:335–340. doi: 10.15585/mmwr.mm7109a2. PMID: 35239636; PMCID: PMC8893338.

126.  Centers for Disease Control and Prevention. COVID Data Tracker: Trends in demographic characteristics of people receiving COVID–19 vaccinations in the United States. https://covid.cdc.gov/​covid-data-tracker/​#vaccination-demographics-trends.

127.  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 Mar 4;71:335–340. doi: 10.15585/mmwr.mm7109a2. PMID: 35239636; PMCID: PMC8893338.

128.  Sun Y, Monnat SM. Rural-urban and within-rural differences in COVID–19 vaccination rates. J Rural Health. 2022 Sep;38(4):916–922. doi: 10.1111/jrh.12625. PMID: 34555222; PMCID: PMC8661570.

129.  Centers for Disease Control and Prevention. COVID Data Tracker. Vaccination Equity. https://covid.cdc.gov/​covid-data-tracker/​#vaccination-equity.

130.  Centers for Disease Control and Prevention. Vaccination Equity. COVID Data Tracker; 2023, January 20. Last accessed January 17, 2023. https://covid.cdc.gov/​covid-data-tracker/​#vaccination-equity.

131.   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. https://mmshub.cms.gov/​sites/​default/​files/​COVID19-Patient-Level-Vaccination-TEP-Summary-Report-NovDec2021.pdf.

132.  87 FR 20218 .

133.  Centers for Medicare & Medicaid Services. (2022). Overview of the List of Measures Under Consideration for December 1, 2022. https://mmshub.cms.gov/​sites/​default/​files/​2022-MUC-List-Overview.pdf.

134.  CMS Measures Management System (MMS). Measure Implementation: Pre-rulemaking MUC Lists and MAP reports. Last accessed March 22, 2023. https://mmshub.cms.gov/​measure-lifecycle/​measure-implementation/​pre-rulemaking/​lists-and-reports.

135.  CMS Measures Management System (MMS). Measure Implementation: Pre-rulemaking MUC Lists and MAP reports. Last accessed March 22, 2023. https://mmshub.cms.gov/​measure-lifecycle/​measure-implementation/​pre-rulemaking/​lists-and-reports.

136.  CMS Measures Management System (MMS). Measure Implementation: Pre-rulemaking MUC Lists and MAP reports. https://mmshub.cms.gov/​measure-lifecycle/​measure-implementation/​pre-rulemaking/​lists-and-reports.

137.  2022–2023 MAP Final Recommendations. https://mmshub.cms.gov/​measure-lifecycle/​measure-implementation/​pre-rulemaking/​lists-and-reports.

138.  The definition of “up to date” may change based on CDC's latest guidelines and is available 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 March 2, 2023).

139.  Patient-Resident-COVID-Vaccine-Draft-Specs.pdf. https://www.cms.gov/​medicare/​quality-initiatives-patient-assessment-instruments/​irf-quality-reporting/​irf-quality-reporting-program-measures-information-.

140.  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.

141.  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.

142.  Centers for Medicare & Medicaid Services. Final Inpatient Rehabilitation Facility Patient Assessment Version 4.0. Effective October 1, 2022. https://www.cms.gov/​files/​document/​irf-pai-version-40-eff-10012022-final.pdf.

143.  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.

144.  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.

145.  Medicare Payment Advisory Commission. March 2022 Report to the Congress; Chapter 9. https://www.medpac.gov/​wp-content/​uploads/​2022/​03/​Mar22_​MedPAC_​ReportToCongress_​Ch9_​SEC.pdf.

146.  Figueroa JF, Phelan J, Orav EJ, Patel V, Jha AK. Association of mental health disorders with health care spending in the Medicare population. JAMA Network Open. 2020 Mar 2;3(3):e201210. doi: 10.1001/jamanetworkopen.2020.1210. PMID: 32191329; PMCID: PMC7082719.

147.  Parish WJ, Mark TL, Weber EW, 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.

148.  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.

149.  Centers for Medicare & Medicaid Services. Depression Screening Conducted and Follow-Up Plan Documented. https://cmit.cms.gov/​cmit/​#/​MeasureView?​variantId=​3102&​sectionNumber=​1.

150.  Agency for Healthcare Research and Quality. CAHPS Mental Health Care Surveys. May 2022. https://www.ahrq.gov/​cahps/​surveys-guidance/​echo/​index.html.

151.  HealthMeasures. Intro to PROMIS®. January 10, 2023. https://www.healthmeasures.net/​explore-measurement-systems/​promis/​intro-to-promis.

152.  HealthMeasures. NIH Toolbox. February 9, 2023. https://www.healthmeasures.net/​explore-measurement-systems/​nih-toolbox.

153.  Desai A, Grossberg G. Substance Use Disorders in Postacute and Long-Term Care Settings. Psychiatr Clin North Am. 2022 Sep;45(3):467–482. doi: 10.1016/j.psc.2022.05.005. PMID: 36055733.

154.  Sorrell JM. Substance Use Disorders in Long-Term Care Settings: A Crisis of Care for Older Adults. J Psychosoc Nurs Ment Health Serv. 2017 Jan 1;55(1):24–27. doi: 10.3928/02793695–20170119–08. PMID: 28135388.

155.  Substance Abuse and Mental Health Services Administration. Resources for Screening, Brief Intervention, and Referral to Treatment (SBIRT). April 14, 2022. https://www.samhsa.gov/​sbirt/​resources.

156.  Centers for Medicare & Medicaid Services. Inpatient Rehabilitation Facility (IRF) Experience of Care. October 12, 2022. https://www.cms.gov/​medicare/​quality-initiatives-patient-assessment-instruments/​irf-quality-reporting/​irf-experience-of-care-.

157.  Centers for Medicare & Medicaid Services. List of Measures under Consideration for December 1, 2017. https://www.cms.gov/​files/​document/​2017amuc-listclearancerpt.pdf.

158.  Centers for Medicare and Medicaid Services. Health Equity. https://www.cms.gov/​pillar/​health-equity. October 3, 2022.

159.  Centers for Medicare & Medicaid Services. CMS Framework for Health Equity 2022–2032. https://www.cms.gov/​files/​document/​cms-framework-health-equity-2022.pdf.

160.  The White House. Executive Order on Advancing Racial Equity and Support for Underserved Communities Through the Federal Government. Executive Order 13985, January 20, 2021. 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/​.

161.  Centers for Medicare & Medicaid Services. What Is the CMS National Quality Strategy? https://www.cms.gov/​Medicare/​Quality-Initiatives-Patient-Assessment-Instruments/​Value-Based-Programs/​CMS-Quality-Strategy.

162.  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.

163.  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.

164.  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.

165.  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.

166.  World Health Organization. Social Determinants of Health. https://www.who.int/​health-topics/​social-determinants-of-health#tab=​tab_​1.

167.  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.

168.   COVID–19 Vaccine: Percent of Patients/Residents Who Are Up to Date. Draft Measure Specifications. https://www.cms.gov/​files/​document/​patient-resident-covid-vaccine-draft-specs.pdf.

169.  U.S. Bureau of Labor Statistics' (BLS) May 2021 National Occupational Employment and Wage Estimates. https://www.bls.gov/​oes/​current/​oes_​nat.htm.

170.  U.S. Bureau of Labor Statistics' (BLS) May 2021 National Occupational Employment and Wage Estimates. https://www.bls.gov/​oes/​current/​oes_​nat.htm.

171.  U.S. Bureau of Labor Statistics' (BLS) May 2021 National Occupational Employment and Wage Estimates. https://www.bls.gov/​oes/​current/​oes_​nat.htm.