2022-13376. Medicare Program; Calendar Year (CY) 2023 Home Health Prospective Payment System Rate Update; Home Health Quality Reporting Program Requirements; Home Health Value-Based Purchasing Expanded Model Requirements; and Home Infusion Therapy ...

AGENCY:

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

ACTION:

Proposed rule.

SUMMARY:

This proposed rule would set forth routine updates to the Medicare home health and home infusion therapy services payment rates for calendar year (CY) 2023 in accordance with existing statutory and regulatory requirements. This proposed rule discusses home health utilization; proposes a methodology for determining the difference between assumed versus actual behavior change on estimated aggregate expenditures for home health payments as result of the change in the unit of payment to 30 days and the implementation of the Patient Driven Groupings Model (PDGM) case-mix adjustment methodology; and proposes a temporary retrospective and permanent prospective adjustment to the CY 2023 home health payment rates. This rule proposes reassignment of certain diagnosis codes under the PDGM. and proposes to establish a permanent mitigation policy to smooth the impact of year-to-year changes in home health payments related to changes in the home health wage index. This rule also proposes recalibration of the PDGM case-mix weights and updates the low utilization payment adjustment (LUPA) thresholds, functional impairment levels, comorbidity adjustment subgroups for CY 2023 and the fixed-dollar loss ratio (FDL) used for outlier payments. Additionally, this rule discusses the future collection of data regarding the use of telecommunications technology during a 30-day home health period of care on home health claims. In addition, this rule proposes changes to the Home Health Quality Reporting Program (HH QRP) requirements; changes to the expanded Home Health Value-Based Purchasing (HHVBP) Model; and updates to the home infusion therapy services payment rates for CY 2023.

DATES:

To be assured consideration, comments must be received at one of the addresses provided below, no later than 5 p.m. on August 16, 2022.

ADDRESSES:

In commenting, please refer to file code CMS-1766-P. Because of staff and resource limitations, we cannot accept comments by facsimile (FAX) transmission.

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 https://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-1766-P, P.O. Box 8013, Baltimore, MD 21244-8013.

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-1766-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:

Brian Slater, [phone], for home health and home infusion therapy payment inquiries.

For general information about home infusion payment, send your inquiry via email to [e-mail].

For general information about the Home Health Prospective Payment System (HH PPS), send your inquiry via email to [e-mail].

For information about the Home Health Quality Reporting Program (HH QRP), send your inquiry via email to [e-mail].

For more information about the expanded Home Health Value-Based Purchasing Model, please visit the Expanded HHVBP Model web page at https://innovation.cms.gov/​innovation-models/​expanded-home-health-value-based-purchasing-model.

SUPPLEMENTARY INFORMATION:

I. Executive Summary and Advancing Health Information Exchange

A. Executive Summary

1. Purpose and Legal Authority

a. Home Health Prospective Payment System (HH PPS)

As required under section 1895(b) of the Social Security Act (the Act), this proposed rule would update the payment rates for HHAs for CY 2023. In addition, the rule would: recalibrate the case-mix weights under section 1895(b)(4)(A)(i) and (b)(4)(B) of the Act for 30-day periods of care in CY 2023; determine the impact of differences between assumed behavior changes and actual behavior changes on estimated aggregate expenditures for CYs 2020-2021 in accordance with section 1895(b)(3)(D)(i) of the Act; propose a permanent payment adjustment to the CY 2023 30-day payment rate and solicit comments on a temporary payment adjustment to the 30-day payment rate in accordance with section 1895(b)(3)(D)(ii) and (iii) of the Act; update the LUPA thresholds, functional impairment levels, and comorbidity subgroups for CY 2023; and update the CY 2023 fixed-dollar loss ratio (FDL) for outlier payments (so that outlier payments as a percentage of estimated total payments are not to exceed 2.5 percent, as required by section 1895(b)(5)(A) of the Act). This proposed rule also includes a solicitation of comments on the collection of data on the use of telecommunications technology on home health claims.

b. Home Health (HH) Quality Reporting Program (QRP)

This proposed rule proposes to end the suspension of the collection of Outcome and Assessment Information Set (OASIS) data on non-Medicare and non-Medicaid patients under section 704 of the Medicare Prescription Drug, Improvement, and Modernization Act of 2003, and to require HHAs to report all-payer OASIS data for purposes of the HH QRP, beginning with the CY 2025 program year. We are proposing to amend the regulatory text to make a technical change that consolidates the statutory references to data submission. We also propose to codify in our regulations the factors we adopted in the CY 2019 HH PPS final rule as the factors we will consider when determining whether to remove measures from the HH QRP measure set. Finally, we are requesting feedback on a Request for Information on Health Equity in the HH QRP.

c. Expanded Home Health Value Based Purchasing (HHVBP) Model

In accordance with the statutory authority at section 1115A of the Act, we are proposing updated policies, new definitions and modifying existing definitions, and conforming regulation text changes for the expanded Home Health Value-Based Purchasing (HHVBP) expanded Model and requesting comment on a potential future approach to health equity in the expanded HHVBP Model.

d. Medicare Coverage of Home Infusion Therapy

This proposed rule discusses updates to the home infusion therapy services payment rates for CY 2023 under section 1834(u) of the Act.

2. Summary of the Provisions of This Rule

a. Home Health Prospective Payment System (HH PPS)

In section II.B.1. of this proposed rule, we provide monitoring and data analysis on PDGM utilization for CYs 2020 and 2021. In section II.B.2. of this rule, we propose payment adjustments to reflect the impact of differences between assumed behavior changes and actual behavior changes on estimated aggregate payment expenditures under the HH PPS. In section II.B.3 of this rule, we discuss the proposal to reassign certain ICD-10-CM codes related to the PDGM clinical groups and comorbidity subgroups.

In section II.B.4. of this rule, we are proposing the recalibration of the PDGM case-mix weights, LUPA thresholds, functional levels, and comorbidity adjustment subgroups for CY 2023.

In section II.B.5. of this rule, we propose to update the home health wage index, the CY 2023 national, standardized 30-day period payment rates and the CY 2023 national per-visit payment amounts by the home health payment update percentage. The proposed home health payment update percentage for CY 2023 would be 2.9 percent. This rule also proposes a permanent 5-percent cap on HHA's applicable wage index reductions from their wage index from the prior year, regardless of the circumstances causing the decline. Additionally, this rule proposes the FDL ratio to ensure that aggregate outlier payments do not exceed 2.5 percent of the total aggregate payments, as required by section 1895(b)(5)(A) of the Act.

In section II.B.6. of this proposed rule, we include a comment solicitation on the collection of data on the use of telecommunications technology on home health claims.

b. HH QRP

In section III.D. of this proposed rule, we are proposing to end the temporary suspension of non-Medicare/non-Medicaid data under section 704 of the Medicare Prescription Drug, Improvement, and Modernization Act of 2003 and, in accordance with section 1895(b)(3)(B)(v) of the Act, to require HHAs to report all-payer OASIS data for purposes of the HH QRP, beginning with the CY 2025 program year. In section III.E. of this rule, we are proposing technical changes in § 484.245(b)(1). In section III.F. of this rule, we are proposing to codify in our regulations the factors we adopted in the CY 2019 HH PPS final rule as the factors we will consider when determining whether to remove measures from the HH QRP measure set. Lastly, in section III.G. of this rule, we are requesting feedback on a Request for Information on Health Equity in the HH QRP.

c. Expanded Home Health Value Based Purchasing (HHVBP) Model

In section IV. of this proposed rule, we are proposing to change the HHA baseline year to CY 2022 for all HHAs that were certified prior to January 1, 2022 starting in the CY 2023 performance year. We would make conforming regulation text changes at § 484.350(b) and (c). We are also proposing to amend the Model baseline year from CY 2019 to CY 2022 starting in the CY 2023 performance year to enable CMS to measure competing HHAs performance on benchmarks and achievement thresholds that are more current. We are making conforming amendments to definitions in § 484.345. In section IV.C. of this proposed rule, we have included an RFI related to a potential future approach to health equity in the expanded HHVBP Model.

d. Medicare Coverage of Home Infusion Therapy

In section V. of this proposed rule, we discuss updates to the home infusion therapy services payment rates for CY 2023, under section 1834(u) of the Act.

3. Summary of Costs, Transfers, and Benefits

B. 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 industry stakeholders to develop Health Level Seven International® (HL7) Fast Healthcare Interoperability Resources® (FHIR) standards.^[1] These standards could support the exchange and reuse of patient assessment data derived from 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. 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. We encourage PAC provider and health information technology (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). The DEL furthers CMS' goal of data standardization and interoperability. Standards in the DEL ( https://del.cms.gov/​DELWeb/​pubHome ) can be referenced on the CMS website and in the ONC Interoperability Standards Advisory (ISA). The 2022 ISA is available at https://www.healthit.gov/​isa.

The 21st Century Cures Act (Cures Act) (Pub. L. 114-255, enacted December 13, 2016) required HHS and ONC to take steps to further interoperability for providers in settings across the care continuum. 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 a universal floor of interoperability across the country. On January 18, 2022, ONC announced a significant milestone by releasing the Trusted Exchange Framework ^[2] and Common Agreement Version 1.^[3] 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 ^[4] (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 Trusted Exchange Framework and 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.^[5] For more information, we refer readers to https://www.healthit.gov/​topic/​interoperability/​trusted-exchange-framework-and-common-agreement.

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

II. Home Health Prospective Payment System

A. Overview of the Home Health Prospective Payment System

1. Statutory Background

Section 1895(b)(1) of the Act requires the Secretary to establish a Home Health Prospective Payment System (HH PPS) for all costs of home health services paid under Medicare. Section 1895(b)(2) of the Act requires that, in defining a prospective payment amount, the Secretary will consider an appropriate unit of service and the number, type, and duration of visits provided within that unit, potential changes in the mix of services provided within that unit and their cost, and a general system design that provides for continued access to quality services. In accordance with the statute, as amended by the Balanced Budget Act of 1997 (BBA) (Pub. L. 105-33, enacted August 5, 1997), we published a final rule in the July 3, 2000 Federal Register (65 FR 41128) to implement the HH PPS legislation.

Section 5201(c) of the Deficit Reduction Act of 2005 (DRA) (Pub. L.109-171, enacted February 8, 2006) added new section 1895(b)(3)(B)(v) to the Act, requiring home health agencies (HHAs) to submit data for purposes of measuring health care quality, and linking the quality data submission to the annual applicable payment percentage increase. This data submission requirement is applicable for CY 2007 and each subsequent year. If an HHA does not submit quality data, the home health market basket percentage increase is reduced by 2 percentage points. In the November 9, 2006 Federal Register (71 FR 65935), we published a final rule to implement the pay-for-reporting requirement of the DRA, which was codified at § 484.225(h) and (i) in accordance with the statute. The pay-for-reporting requirement was implemented on January 1, 2007.

Section 51001(a)(1)(B) of the Bipartisan Budget Act of 2018 (BBA of 2018) (Pub. L. 115-123) amended section 1895(b) of the Act to require a change to the home health unit of payment to 30-day periods beginning January 1, 2020. Section 51001(a)(2)(A) of the BBA of 2018 added a new subclause (iv) under section 1895(b)(3)(A) of the Act, requiring the Secretary to calculate a standard prospective payment amount (or amounts) for 30-day units of service furnished that end during the 12-month period beginning January 1, 2020, in a budget neutral manner, such that estimated aggregate expenditures under the HH PPS during CY 2020 are equal to the estimated aggregate expenditures that otherwise would have been made under the HH PPS during CY 2020 in the absence of the change to a 30-day unit of service. Section 1895(b)(3)(A)(iv) of the Act requires that the calculation of the standard prospective payment amount (or amounts) for CY 2020 be made before the application of the annual update to the standard prospective payment amount as required by section 1895(b)(3)(B) of the Act.

Additionally, section 1895(b)(3)(A)(iv) of the Act requires that in calculating the standard prospective payment amount (or amounts), the Secretary must make assumptions about behavior changes that could occur as a result of the implementation of the 30-day unit of service under section 1895(b)(2)(B) of the Act and case-mix adjustment factors established under section 1895(b)(4)(B) of the Act. Section 1895(b)(3)(A)(iv) of the Act further requires the Secretary to provide a description of the behavior assumptions made in notice and comment rulemaking. CMS finalized these behavior assumptions in the CY 2019 HH PPS final rule with comment period (83 FR 56461).

Section 51001(a)(2)(B) of the BBA of 2018 also added a new subparagraph (D) to section 1895(b)(3) of the Act. Section 1895(b)(3)(D)(i) of the Act requires the Secretary to annually determine the impact of differences between assumed behavior changes, as described in section 1895(b)(3)(A)(iv) of the Act, and actual behavior changes on estimated aggregate expenditures under the HH PPS with respect to years beginning with 2020 and ending with 2026. Section 1895(b)(3)(D)(ii) of the Act requires the Secretary, at a time and in a manner determined appropriate, through notice and comment rulemaking, to provide for one or more permanent increases or decreases to the standard prospective payment amount (or amounts) for applicable years, on a prospective basis, to offset for such increases or decreases in estimated aggregate expenditures, as determined under section 1895(b)(3)(D)(i) of the Act. Additionally, 1895(b)(3)(D)(iii) of the Act requires the Secretary, at a time and in a manner determined appropriate, through notice and comment rulemaking, to provide for one or more temporary increases or decreases to the payment amount for a unit of home health services for applicable years, on a prospective basis, to offset for such increases or decreases in estimated aggregate expenditures, as determined under section 1895(b)(3)(D)(i) of the Act. Such a temporary increase or decrease shall apply only with respect to the year for which such temporary increase or decrease is made, and the Secretary shall not take into account such a temporary increase or decrease in computing the payment amount for a unit of home health services for a subsequent year. Finally, section 51001(a)(3) of the BBA of 2018 amends section 1895(b)(4)(B) of the Act by adding a new clause (ii) to require the Secretary to eliminate the use of therapy thresholds in the case-mix system for CY 2020 and subsequent years.

2. Current System for Payment of Home Health Services

For home health periods of care beginning on or after January 1, 2020, Medicare makes payment under the HH PPS on the basis of a national, standardized 30-day period payment rate that is adjusted for case-mix and area wage differences in accordance with section 51001(a)(1)(B) of the BBA of 2018. The national, standardized 30-day period payment rate includes payment for the six home health disciplines (skilled nursing, home health aide, physical therapy, speech-language pathology, occupational therapy, and medical social services). Payment for non-routine supplies (NRS) is also part of the national, standardized 30-day period rate. Durable medical equipment (DME) provided as a home health service, as defined in section 1861(m) of the Act, is paid the fee schedule amount or is paid through the competitive bidding program and such payment is not included in the national, standardized 30-day period payment amount. Additionally, the 30-day period payment rate does not include payment for certain injectable osteoporosis drugs and negative pressure wound therapy (NPWT) using a disposable device, but such drug and services must be billed by the HHA while a patient is under a home health plan of care, as the law requires consolidated billing of osteoporosis drugs and NPWT using a disposable device.

To better align payment with patient care needs and to better ensure that clinically complex and ill beneficiaries have adequate access to home health care, in the CY 2019 HH PPS final rule with comment period (83 FR 56406), we finalized case-mix methodology refinements through the Patient-Driven Groupings Model (PDGM) for home health periods of care beginning on or after January 1, 2020. The PDGM did not change eligibility or coverage criteria for Medicare home health services, and as long as the individual meets the criteria for home health services as described at 42 CFR 409.42, the individual can receive Medicare home health services, including therapy services. For more information about the role of therapy services under the PDGM, we refer readers to the Medicare Learning Network (MLN) Matters article SE2000 available at https://www.cms.gov/​regulations-and-guidanceguidancetransmittals2020-transmittals/​se20005. To adjust for case-mix for 30-day periods of care beginning on and after January 1, 2020, the HH PPS uses a 432-category case-mix classification system to assign patients to a home health resource group (HHRG) using patient characteristics and other clinical information from Medicare claims and the Outcome and Assessment Information Set (OASIS) assessment instrument. These 432 HHRGs represent the different payment groups based on five main case-mix categories under the PDGM, as shown in Figure B1. Each HHRG has an associated case-mix weight that is used in calculating the payment for a 30-day period of care. For periods of care with visits less than the low-utilization payment adjustment (LUPA) threshold for the HHRG, Medicare pays national per-visit rates based on the discipline(s) providing the services. Medicare also adjusts the national standardized 30-day period payment rate for certain intervening events that are subject to a partial payment adjustment (PEP). For certain cases that exceed a specific cost threshold, an outlier adjustment may also be available.

Under this case-mix methodology, case-mix weights are generated for each of the different PDGM payment groups by regressing resource use for each of the five categories (admission source, timing, clinical grouping, functional impairment level, and comorbidity adjustment) using a fixed effects model. A detailed description of each of the case-mix variables under the PDGM have been described previously, and we refer readers to the CY 2021 HH PPS final rule (85 FR 70303 through 70305).

B. Proposed Provisions for CY 2023 Payment Under the HH PPS

1. Monitoring the Effects of the Implementation of PDGM

a. Routine PDGM Monitoring

CMS routinely analyzes Medicare home health benefit utilization, including but not limited to, overall total 30-day periods of care and average periods of care per HHA user; distribution of the type of visits in a 30-day period of care; the percentage of periods that receive the LUPA; estimated costs; the percentage of 30-day periods of care by clinical group, comorbidity adjustment, admission source, timing, and functional impairment level; GG items by response type; and the proportion of 30-day periods of care with and without any therapy visits, nursing visits, and/or aide/social worker visits. For the monitoring included in this rule, we examine simulated CY 2018 and CY 2019 data and actual CY 2020 and CY 2021 data for 30-day periods of care. We provide interpretation of results for CY 2020 and CY 2021. We refer readers to the CY 2022 HH PPS final rule (86 FR 35881) for discussion about simulated data for CYs 2018 and 2019.

(1) Utilization

Table B2 shows the overall utilization of home health and Table B3 shows the average utilization of visits per 30-day period of care by home health discipline. This data indicates the average number of 30-day periods of care per unique HHA user is similar per 30-day period of care between CY 2020 and CY 2021. Table B3 shows utilization of visits per 30-day period of care by home health discipline over time. The data indicates that the number of 30-day periods of care decreased between CY 2018 and CY 2021. Table B4 shows the proportion of 30-day periods of care that are LUPAs and the average number of visits per discipline of those LUPA 30-day periods of care over time.

(2) Analysis of 2020 Cost Report Data for 30-Day Periods of Care

In the CY 2020 HH PPS final rule with comment period (84 FR 60483), we provided a summary of analysis on FY 2017 HHA cost report data and how such data, if used, would impact our estimate of the percentage difference between the CY 2020 30-day payment amount and estimated, average HHA costs for a 30-day period of care. In that rule, we utilized FY 2017 cost reports and CY 2017 home health claims to estimate the costs of both 60-day episodes of care and 30-day periods of care. We then updated the estimated CY 2017 60-day episode costs and 30-day period of care costs by the home health market basket update, reduced by the productivity adjustment for CYs 2018, 2019, and 2020 to calculate the 2020 estimated 60-day episode costs and 30-day period of care costs. As stated in the CY 2020 HH PPS final rule with comment period (84 FR 60485), we estimated that the CY 2020 30-day payment amount was approximately 16 percent higher than the average costs for a 30-day period of care. In MedPAC's March 2020 Report to Congress,^[6] their review of home health payment adequacy found that “access is more than adequate in most areas and that Medicare payments are substantially in excess of costs”.

In this proposed rule, we examined 2020 HHA Medicare cost reports, as this is the most recent and complete cost report data at the time of rulemaking, and CY 2021 home health claims, to estimate 30-day period of care costs. We excluded LUPAs and PEPs in the average number of visits. The 2020 average NRS costs per visit is $4.53. To update the estimated 30-day period of care costs, we begin with the 2020 average costs per visit with NRS for each discipline and multiply that amount by the CY 2021 home health payment update percentage of 2.0 percent. That amount for each discipline is then multiplied by the 2021 average number of visits by discipline to determine the 2021 Estimated 30-day Period Costs. Table B5 shows the estimated average costs for 30-day periods of care by discipline with NRS and the total 30-day period of care costs with NRS for CY 2021.

The CY 2021 national, standardized 30-day period payment rate was $1,901.12, which is approximately 34 percent more than the estimated CY 2021 30-day period average facility cost of $1,420.35. Note that in the CY 2020 HH PPS final rule with comment period (84 FR 60484), the average number of visits for a 30-day period of care in 2017 was estimated to be 10.5 visits for non-LUPA, non-PEP 30-day periods of care. Using actual CY 2021 claims data, the average number of visits in a non-LUPA-non-PEP 30-day period of care was 8.81 visits—a decrease of approximately 16 percent. We recognize that with the COVID-19 public health emergency (PHE), the 2020 data on the Medicare cost reports may not reflect the most recent changes such as increased telecommunications technology costs, increased personal protective equipment (PPE) costs, and hazard pay. In its March 2022 Report to Congress, MedPAC assumed a cost growth of 3.47 percent for both CY 2021 and CY 2027.^[7] Furthermore, MedPAC noted that for more than a decade, payments under the HH PPS have significantly exceeded HHAs' costs primarily due to two factors. First, agencies have reduced the average number of visits per episode to reduce episode costs. Second, cost growth in recent years has been lower than the annual payment updates. As shown in Table B3 in this proposed rule, HHAs have reduced visits under the PDGM in CY 2021.

(3) Clinical Groupings and Comorbidities

Each 30-day period of care is grouped into one of 12 clinical groups, which describe the primary reason for which a patient is receiving home health services under the Medicare home health benefit. The clinical grouping is based on the principal diagnosis reported on the home health claim. Table B6 shows the distribution of the 12 clinical groups over time.

Thirty-day periods of care will receive a comorbidity adjustment category based on the presence of certain secondary diagnoses reported on home health claims. These diagnoses are based on a home health specific list of clinically and statistically significant secondary diagnosis subgroups with similar resource use. We refer readers to section II.B.4.c. of this proposed rule and the CY 2020 final rule with comment period (84 FR 60493) for further information on the comorbidity adjustment categories. Home health 30-day periods of care can receive a low or a high comorbidity adjustment, or no comorbidity adjustment. Table B7 shows the distribution of 30-day periods of care by comorbidity adjustment category for all 30-day periods.

(4) Admission Source and Timing

Each 30-day period of care is classified into one of two admission source categories—community or institutional—depending on what healthcare setting was utilized in the 14 days prior to receiving home health care. Thirty-day periods of care for beneficiaries with any inpatient acute care hospitalizations, inpatient psychiatric facility (IPF) stays, skilled nursing facility (SNF) stays, inpatient rehabilitation facility (IRF) stays, or long-term care hospital (LTCH) stays within 14-days prior to a home health admission will be designated as institutional admissions. The institutional admission source category will also include patients that had an acute care hospital stay during a previous 30-day period of care and within 14 days prior to the subsequent, contiguous 30-day period of care and for which the patient was not discharged from home health and readmitted.

Thirty-day periods of care are classified as “early” or “late” depending on when they occur within a sequence of 30-day periods of care. The first 30-day period of care is classified as early and all subsequent 30-day periods of care in the sequence (second or later) are classified as late. A subsequent 30-day period of care would not be considered early unless there is a gap of more than 60 days between the end of one previous period of care and the start of another. Information regarding the timing of a 30-day period of care comes from Medicare home health claims data and not the OASIS assessment to determine if a 30-day period of care is “early” or “late”. Table B8 shows the distribution of 30-day periods of care by admission source and timing.

(5) Functional Impairment Level

Each 30-day period of care is placed into one of three functional impairment levels (low, medium, or high) based on responses to certain OASIS functional items associated with grooming, bathing, dressing, ambulating, transferring, and risk for hospitalization. The specific OASIS items that are used for the functional impairment level are found in Table B7 in the CY 2020 HH PPS final rule with comment period (84 FR 60490). Responses to these OASIS items are grouped together into response categories with similar resource use and each response category has associated points. A more detailed description as to how these response categories were established can be found in the technical report, “Overview of the Home Health Groupings Model” posted on the HHA web page.^[8] The sum of these points results in a functional impairment score used to group 30-day periods of care into a functional impairment level with similar resource use. The scores associated with the functional impairment levels vary by clinical group to account for differences in resource utilization. A patient's functional impairment level will remain the same for the first and second 30-day periods of care unless there is a significant change in condition that warrants an “other follow-up” assessment prior to the second 30-day period of care. For each 30-day period of care, the Medicare claims processing system will look for occurrence code 50 on the claim to correspond to the M0090 date of the applicable assessment. Table B9 shows the distribution of 30-day periods by functional impairment level.

(6) CY 2023 Discussion and Analysis of GG Items

The Improving Medicare Post-Acute Care Transformation Act of 2014 (IMPACT Act) (Pub. L. 113-185, enacted on October 6, 2014) amended Title XVIII of the Act to include new data reporting requirements for certain post-acute care (PAC) providers, such as HHAs. Section 1899B(b)(1)(A) of the Act requires that HHAs report standardized patient assessment data beginning no later than January 1, 2019. Since the standardized patient assessment data categories included functional status, such as mobility and self-care at admission and discharge, in accordance with section 1899B(b)(1)(B)(i) of the Act, CMS finalized adding the functional items, Section GG, “Functional Abilities and Goals”, to the OASIS data set, effective January 1, 2019, in order to measure functional status across PAC providers. However, for payment purposes under the PDGM, CMS did not have the data to determine the effect, if any, of these newly added items on resource costs during a home health period of care. Therefore, the GG functional items are not currently used to determine the functional impairment level under the PDGM. CMS continues to use the M1800-1860 items to determine functional impairment level for case-mix purposes. As such, the purpose of the following analysis is to explore the relationship between the M1800-1860 items used in the PDGM and the analogous GG items. The analysis of the M1800 functional items and the analogous GG items shows there was a small decline in the percentage of individuals who were associated with the “most independent” responses with a large percentage of the responses using the “Activity not Attempted” (ANA) response option. If the activity was not attempted, there are various codes that explain the reason for this response, such as “Not attempted due to medical or safety concerns,” and “Not applicable.”

To conduct this analysis, we reviewed OASIS data from January 1, 2019, to December 31, 2021, that was linked to 30-day home health periods. Responses for each of the M1800 functional items used in the PDGM functional scores were compared to the responses of the analogous GG items. There is a correlation between the current responses to the M1800-1860 items and the GG items; however, certain information in the M1800 items is collected at follow—up, but is not collected at follow-up for the GG items (for example, the M1800 items associated with upper and lower body dressing are collected at follow up, but the analogous GG item is not collected at follow-up). Additionally, ongoing analysis of the GG items shows a significant amount of ANA responses, making it difficult to map to the corresponding M1800-1860 item responses. Figure B2 demonstrates the frequencies by response type in CY 2021 of the OASIS GG items.

(7) Therapy Visits

Beginning in CY 2020, section 1895(b)(4)(B)(ii) of the Act eliminated the use of therapy thresholds in calculating payments for CY 2020 and subsequent years. Prior to implementation of the PDGM, HHAs could receive an adjustment to payment based on the number of therapy visits provided during a 60-day episode of care. We examined the proportion of actual 30-day periods of care with and without therapy visits. To be covered as skilled therapy, the services must require the skills of a qualified therapist (that is, physical therapy (PT), occupational therapy (OT), or speech-language pathology (SLP)) or qualified therapist assistant and must be reasonable and necessary for the treatment of the patient's illness or injury.^[9] As shown in Table B2, we monitor the number of visits per 30-day period of care by each home health discipline. Any 30-day period of care can include both therapy and non-therapy visits. If any 30-day period of care consisted of only visits for PT, OT, and/or SLP, then this 30-day period of care is considered “therapy only”. If any 30-day period of care consisted of only visits for skilled nursing, home health aide, or social worker, then this 30-day period of care is considered “no therapy”. If any 30-day period of care consisted of at least one therapy visit and one non-therapy, then this 30-day period of care is considered “therapy + non-therapy”. Table B10 shows the proportion of 30-day periods of care with only therapy visits, at least one therapy visit and one non-therapy visit, and no therapy visits. Figure B3 shows the proportion of 30-day periods of care by the number of therapy visits (excluding zero) provided during 30-day periods of care.

Both Table B10 and Figure B3, as previously discussed, indicate there have been changes in the distribution of both therapy and non-therapy visits in CY 2021 compared to CY 2020. For example, the percent of 30-day periods with seven or less therapy visits during a 30-day period increased in CY 2021 compared to CY 2020.

In addition, we also examined the proportion of 30-day periods of care with and without skilled nursing, social work, or home health aide visits. Table B11 shows the number of 30-day periods of care with only skilled nursing visits, at least one skilled nursing visit and one other visit type (therapy or non-therapy), and no skilled nursing visits. Table B12 shows the number of 30-day periods of care with and without home health aide and/or social worker visits.

We will continue to monitor the provision of home health services, including any changes in the number and duration of home health visits, composition of the disciplines providing such services, and overall home health payments to determine if refinements to the case-mix adjustment methodology may be needed in the future.

2. Proposed Methodology for Behavioral Assumptions and Adjustments Under the HH PPS,

a. Background and Comment Solicitation From the CY 2022 HH PPS Proposed Rule

(1) Background

As discussed in section II.A.1. of this rule, starting in CY 2020, the Secretary was statutorily required to change the unit of payment under the HH PPS from a 60-day episode of care to a 30-day period of care. CMS was also required to make assumptions about behavior changes that could occur as a result of the implementation of the 30-day unit of payment and the case-mix adjustment factors that eliminated the use of therapy thresholds, when calculating the standard prospective payment amount for CY 2020. In the CY 2019 HH PPS final rule with comment period (83 FR 56455), we finalized the following three behavior assumptions:

Clinical Group Coding: The clinical group is determined by the principal diagnosis code for the patient as reported by the HHA on the home health claim. This behavior assumption assumes that HHAs will change their documentation and coding practices and put the highest paying diagnosis code as the principal diagnosis code in order to have a 30-day period be placed into a higher-paying clinical group.

Comorbidity Coding: The PDGM further adjusts payments based on patients' secondary diagnoses as reported by the HHA on the home health claim. The OASIS only allows HHAs to designate 1 principal diagnosis and 5 secondary diagnoses while the home health claim allows HHAs to designate 1 principal diagnosis and up to 24 secondary diagnoses. This behavior assumption assumes that by considering additional ICD-10- CM diagnosis codes listed on the home health claim (beyond the 6 allowed on the OASIS), more 30-day periods of care will receive a comorbidity adjustment.

LUPA Threshold: This behavior assumption assumes that for one-third of LUPAs that are 1 to 2 visits away from the LUPA threshold HHAs will provide 1 to 2 extra visits to receive a full 30-day payment.

As described in the CY 2020 final rule with comment period (84 FR 60512), in order to calculate the CY 2020 budget neutral 30-day payment amounts both with and without behavior assumptions, we first calculated the total, aggregate amount of expenditures that would occur under the pre-PDGM case-mix adjustment methodology (60-day episodes under 153 case-mix groups). We then calculated what the 30-day payment amount would need to be set at in order for CMS to pay the same total expenditures in CY 2020 with the application of a 30-day unit of payment under the PDGM.

We initially determined a negative 8.39 percent behavior change adjustment to the base payment rate would be needed in order to ensure that the payment rate in CY 2020 would be budget neutral, as required by law. However, based on the comments received and reconsideration as to the frequency of the assumed behaviors during the first year of the transition to a new unit of payment and case-mix adjustment methodology, we finalized in the CY 2020 HH PPS final rule with comment period (84 FR 60519) a negative 4.36 percent behavior change assumption adjustment (“assumed behaviors”) in order to calculate the 30-day payment rate in a budget-neutral manner for CY 2020. After applying the wage index budget neutrality factor and the home health payment update, the CY 2020 30-day payment rate was set at $1,864.03.

Our data analysis in section II.B.1. of this proposed rule compares the 2018 simulated 30-day periods with behavior assumptions applied and actual 30-day periods. Specifically, Tables B4, B6, and B7 indicate that the three assumed behavior changes did occur as a result of the implementation of the PDGM. Additionally, this monitoring shows that other behaviors, such as changes in the provision of therapy and changes in functional impairment levels also occurred. Overall, the actual 30-day periods are similar to the simulated 30-day periods, which is supporting evidence that HHAs did make behavioral changes. However, we remind readers that by law we are required to ensure that estimated aggregate expenditures under the HH PPS during CY 2020 are equal to the estimated aggregate expenditures that otherwise would have been made under the HH PPS during CY 2020 in the absence of the change to a 30-day unit of payment. Regardless of the magnitude and frequency of individual behavior change (for example, LUPAs, therapy, etc.), the occurrence of any behavior change is captured by the methodology to determine the impact on aggregate expenditures.

We remind readers that in the CY 2020 HH PPS final rule (84 FR 60513), we stated that we interpret actual behavior changes to encompass both behavior changes that were previously outlined as assumed by CMS, and other behavior changes not identified at the time the budget-neutral 30-day payment rate for CY 2020 was established. Subsequently, our analysis resulted in the identification of other behavior changes that occurred after the implementation of the PDGM. For example, Table B10 and Figure B3 in section II.B.1. of this proposed rule indicates the number of therapy visits declined in CYs 2020 and 2021. However, the data, as depicted in Figure B3, also indicates a slight decline in therapy visits began in CY 2019 after the finalization of the removal of therapy thresholds, but prior to implementation of the PDGM. This suggests HHAs were already beginning to decrease their therapy provision. Although not originally one of the three finalized behavior assumptions, the decline in therapy utilization is indicative of an additional behavior change.

Each Health Insurance Prospective Payment System (HIPPS) code is assigned a case-mix weight and the case-mix weight determines the base payment of non-LUPA claims prior to any other adjustments (for example outlier). Prior to the PDGM, the first position of the HIPPS code was a numeric value that represented the interaction of episode timing and number of therapy visits (grouping step). The second, third, and fourth positions of the pre-PDGM HIPPS code reflected clinical severity, functional severity, and service utilization respectively. Therefore, to evaluate how the decrease in therapy visits related to payments, we compared the average case mix weights of CY 2018 actual 60-day episodes and CY 2021 simulated 60-day episodes. Prior to the PDGM, the average case-mix weight for CY 2018 60-day episodes was 1.0176. When we set therapy levels at the pre-PDGM (that is, CY 2018) level and kept the clinical and functional levels at the PDGM levels (that is, CY 2021) the average case-mix weight was 1.0389. After the PDGM, the average case-mix weight for CY 2021 simulated 60-day episodes was 0.9664. When we kept therapy levels at the PDGM (that is, CY 2021) level and set the clinical and functional levels at the pre-PDGM levels (that is, CY 2018) the average case-mix weight was 0.9361. By controlling for therapy levels, we were able to determine the change in 60-day episode case-mix weights were largely driven by therapy utilization. The decrease in therapy visits led to a decrease in case-mix weight, and therefore a decrease in aggregate expenditures under the pre-PDGM HH PPS.

(2) Summary of Comment Solicitation From the CY 2022 Proposed Rule

As required by section 1895(b)(3)(D)(i) of the Act, CMS must annually determine the impact of differences between assumed and actual behavior changes on estimated aggregate expenditures under the HH PPS with respect to years beginning with 2020 and ending with 2026. Section 1895(b)(3)(D)(ii) and (iii) of the Act requires that CMS make permanent and temporary adjustments to the payment rate to offset for such increases or decreases in estimated aggregate expenditures through notice and comment rulemaking. Therefore, to evaluate the impact of assumed versus actual behavior changes for CYs 2020 through 2026, we developed a methodology that uses actual claims data for 30-day periods under the 432-group case-mix model (PDGM claims) to simulate 60-day episodes under the 153-group case-mix model (representing pre-PDGM HH PPS claims) in order to estimate what aggregate expenditures would have been in the absence of the PDGM. This methodology mirrors the initial approach used to calculate the CY 2020 30-day period payment amount for the PDGM, where we used a single year of claims data (that is, CY 2018 claims data for 60-day episodes of care under the 153-group case-mix model) and simulated payments for 30-day periods of care with the application of the PDGM case-mix adjustment methodology. We then compared actual aggregate expenditures under the existing system (that is, 60-day episodes of care under the 153-group case-mix model) to simulated payments under the PDGM for 30-day periods of care with assumed behavior changes, and used the difference between the two amounts to construct the budget neutrality factor. We described this methodology in the CY 2022 HH PPS proposed rule (86 FR 35889 through 35892). For determining the impact of the difference between assumed and actual behavior changes on overall expenditures for CY 2020 and CY 2021, we analyzed a single year of claims data (for example, CY 2020 claims data for 30-day periods of care under the 432-group PDGM case-mix model) and simulated payments for 60-day episodes of care under the 153-group case-mix model. We then compared the actual aggregate expenditures under the PDGM to what aggregate expenditures would have been pre-PDGM.

In the CY 2022 HH PPS proposed rule (86 FR 35892), we solicited comments on this approach (86 FR 35892). Commenters raised concerns about this methodology, most notably about the elimination of therapy thresholds, the onset of the COVID-19 PHE, interpretation of section 1895(b)(3)(D)(i) of the Act, the differing case-mix weight systems (153 vs 432 case-mix groups), and inappropriate data exclusions and assumptions when creating the simulated 60-day episodes.

Commenters stated that there has been a large decrease in therapy utilization since the implementation of the PDGM. Commenters stated several possible reasons for the decrease in therapy utilization, including that the PDGM resulted in significant differences in payment incentives. Specifically, commenters noted that HHAs could have received higher payments if certain therapy volume thresholds were met pre-PDGM; whereas that incentive no longer exists under the PDGM. Therefore, many commenters indicated the estimated aggregate expenditures calculated with simulated 60-day episodes (pre PDGM) is inaccurate because it does not control for the payment incentives which would have been present under the old system. However, we stated in the CY 2019 HH PPS final rule with comment period (83 FR 56481), that the PDGM is not limiting or prohibiting the provision of therapy services or the number of home health periods of care. In addition, we believe that regardless of the case-mix system in place, HHAs should continue to provide the most appropriate care to Medicare home health beneficiaries, in accordance with the home health CoP requirements at § 484.60.

While overall utilization may have decreased in the early months of CY 2020 due to the onset of the COVID-19 PHE, the methodology described in the CY 2022 HH PPS proposed rule used the same claims dataset (for example, CY 2020) to compare aggregate expenditures under the two payment systems. Any effect of the COVID-19 PHE is included in the estimated aggregate expenditures for both simulated 60-day episodes and actual 30-day periods, and therefore this methodology ensures that any differences between the two calculated amounts is not attributable to the COVID-19 PHE. In other words, any potential changes due to the COVID-19 PHE (for example, decreased utilization) in the 30-day periods would also be present in the simulated 60-day episodes, making the two datasets comparable.

However, we recognize that the COVID-19 PHE presented unique challenges for all healthcare settings, including HHAs. For example, we understand elective procedures were cancelled or postponed and some beneficiaries decreased the care in their home, including potentially both the number of care providers furnishing services inside their homes and the frequency of services to avoid exposure to COVID-19. While we believe the proposed methodology presented best controls for the effects of the COVID-19 PHE, we are soliciting comments on how the COVID-19 PHE may have impacted service provision in a manner not reflected in the proposed methodology described above. We expect that such comments will include empirical evidence to support the commenter's position on how the COVID-19 PHE affected provider behavior.

Commenters stated that the statute requires CMS to analyze solely the differences between the three assumed behavior changes (clinical group coding, comorbidity coding, LUPA threshold) that were incorporated into the original CY 2020 rate setting and what the actual behavior change was for just those three assumptions. Commenters stated that any adjustments to the 30-day payment amount must be related to the impact of those three assumed behavior changes and the actual behavior changes for those same three assumptions on estimated aggregate expenditures; rather than other behavior changes that occurred that impacted aggregate expenditures. As such, commenters presented an alternative method that compares aggregate expenditures between the CY 2018 simulated 30-day periods with the three behavior assumptions applied to the CY 2020 actual 30-day periods. As we have stated previously in the CY 2020 HH PPS final rule with comment period and in the CY 2022 HH PPS final rule (84 FR 60513, 86 FR 62248), we interpret actual behavior changes to encompass both behavior changes that were previously outlined, as assumed by CMS, and other behavior changes not identified at the time that the budget neutral 30-day payment amount for CY 2020 was determined. We use claims data to calculate estimated aggregate expenditures under the HH PPS, regardless of methodology. All claims data are products of behavior changes, (whether or not acknowledged in previous rules), as well as interactions between behaviors. Therefore, any behavior changes observed under the PDGM are considered when determining an adjustment.

A few commenters also proposed determining the extent to which nominal case-mix changes affected aggregate expenditures under the PDGM versus the old payment system as an alternative methodology to evaluate the behavior change assumptions. In order to evaluate case-mix changes, CMS previously utilized a regression model that estimated whether changes in case-mix were due to changes in agency coding practices or other nominal factors, versus real changes in patient characteristics or acuity. While changes in nominal case-mix may be supplemental to our findings, the law requires CMS to determine the effect of the difference between assumed versus actual behavioral changes on estimated aggregate expenditures, which are not factored into our calculations of case-mix adjustment authority. Section 1895(b)(3)(B)(iv) of the Act states that CMS has the authority to adjust for case-mix changes that are a result of changes in the coding or classification of different units of services that do not reflect real changes in case mix. Therefore, at this time we do not believe analyses of nominal case-mix change is the most accurate method to evaluate what aggregate expenditures would have been in absence of the PDGM. Upon continued review of what the law requires us to do in regards to determining the difference between assumed versus actual behaviors on estimated aggregate expenditures, we continue to believe that the best reading of the law requires us to retrospectively determine if the 30-day payment amount in CY 2020 resulted in the same estimated aggregate expenditures that would have been made if the change in the unit of payment and the PDGM case-mix adjustment methodology had not been implemented.

Furthermore, if the estimated aggregate expenditures are determined not to be equal, we are required, by law, to make permanent and temporary adjustments to the PDGM payment rate so that the expenditures across the two payments systems would be equal. We believe using the methodology described previously in the CY 2022 HH PPS proposed rule (85 FR 35890 through 35892 and in this proposed rule, best satisfies our interpretation of section 1895(b)(3)(D)(i) of the Act.

Lastly, commenters raised concerns about the differing case-mix weight systems and that the data exclusions and assumptions made when creating the simulated 60-day episodes introduced some level of bias. Commenters stated that each case-mix system are unique to each payment system as they are dependent on the underlying variables used to describe clinical characteristics or resource use. For this reason, commenters had concerns that the two case-mix weight systems (153 vs 432 case-mix groups) are not comparable. We recognize that the underlying variables in the payment regression are different, but a case-mix of 1.0 is interpreted the same way under both systems. For example, a case-mix of 1.000 means the predicted resource use for a particular home health 60-day episode or 30-day period is equal to overall average resource use. Therefore, we disagree with commenters that comparing the two case-mix systems is flawed. We note there may be some selection bias present due to the data exclusions and assumptions described in section II.B.2.b. of this proposed rule, but we believe this is minimal and does not significantly affect the overall calculation of estimated aggregate expenditures. For example, when we dropped fewer claims we got approximately the same results. Therefore, if we did not exclude claims (for example, there was no linked OASIS data available in the CCW VRDC) or make assumptions about which two 30-day periods to combine, we would further introduce informational and analytical bias.

We reiterate that this methodology uses simulated 60-day episodes priced using the pre-PDGM payment system parameters to determine what the estimated aggregate expenditures would have been in the absence of the PDGM and a 30-day unit of payment. The resulting estimated aggregate expenditures from the pre-PDGM payment system are compared to actual aggregate expenditures from the PDGM 30-day periods to determine, if a permanent prospective adjustment and/or a temporary retrospective adjustment are needed to offset the difference in estimated aggregate expenditures. We propose to use this methodology, as described in this section of this rule, for CYs 2020 through 2026. We refer readers to sections II.B.2.d and II.B.2.e of this proposed rule for our preliminary results of our analysis for CYs 2020 and 2021, respectively.

b. Proposed Method To Annually Determine the Impact of Differences Between Assumed Behavior Changes and Actual Behavior Changes on Estimated Aggregate Expenditures

We analyzed data to determine if the CY 2020 30-day payment amount resulted in the same estimated aggregate expenditures that would have been paid if the PDGM and change in the unit of payment had not been implemented. To evaluate if the 30-day budget neutral payment amount for CY 2020 maintained budget neutrality given the change to a 30-day unit of payment and the implementation of a new case-mix adjustment methodology without therapy thresholds was accurate, we used actual CY 2020 30-day period claims data to simulate 60-day episodes, and we determined what CY 2020 payments would have been under the 153-group case-mix system and 60-day unit of payment. To do this, we used the following steps:

The first step in repricing CY 2020 PDGM claims was to calculate estimated aggregate expenditures under the pre-PDGM, 153-group case-mix system and 60-day unit of payment, by determining which PDGM 30-day periods of care could be grouped together to form simulated 60-day episodes of care. To facilitate grouping, we made some exclusions and assumptions as described later in this section prior to pricing out the simulated 60-day episodes of care. We note in the early months of CY 2020, there were 60-day episodes which started in 2019 and ended in 2020 and therefore, some of these exclusions and assumptions may be specific to the first year of the PDGM. We identify, through footnotes, if an exclusion or assumption is specific to CY 2020 only. The following describes the steps in determining the annual estimated aggregate expenditures including the exclusions and assumptions made when simulating 60-day episodes from actual 30-day periods.

(1) Exclusions

• Claims where the claim occurrence code 50 date (OASIS assessment date) occurred on or after October 31 of that year. This exclusion was applied to ensure the simulated 60-day episodes contained both 30-day periods from the same year and would not overlap into the following year (for example, 2021, 2022, 2023). This is done because any 30-day periods with an OASIS assessment date in November or December might be part of a simulated 60-day episode that would continue into the following year and where payment would have been made based on the “through” date. For CYs 2021 through 2026, we also excluded claims with an OASIS assessment date before January 1 of that year.^[10] Again, this is to ensure a simulated 60-day episode (simulated from two 30-day periods) does not overlap years.

• Beneficiaries and all of their claims if they have overlapping claims from the same provider (as identified by CMS Certification Number (CCN)).^[11]

• Beneficiaries and all of their claims if three or more claims from the same provider are linked to the same occurrence code 50 date.^[12]

(2) Assumptions

• If two 30-day periods of care from the same provider reference the same OASIS assessment date (using occurrence code 50), then we assume those two 30-day periods of care would have been billed as a 60-day episode of care under the 153-group system.
• If two 30 day-periods of care reference different OASIS assessment dates and each of those assessment dates is referenced by a single 30-day period of care, and those two 30-day periods of care occur together close in time (that is, the “from” date of the later 30-day period of care is between 0 to 14 days after the “through” date of the earlier 30-day period of care), then we assume those two 30-day periods of care also would have been billed as a 60-day episode of care under the 153-group system.
• For all other 30-day periods of care, we assume that they would not be combined with another 30-day period of care and would have been billed as a single 30-day period.

(3) Calculating Estimated Aggregate Expenditures—Pricing Simulated 60-Day Episode Claims

After application of the exclusions and assumptions described previously we have the simulated the 60-day episode datasets for each year. Starting with CY 2020, we assign each 60-day episode of care as a normal episode, PEP, LUPA, or outlier based on the payment parameters established in the CY 2020 final rule with comment period (84 FR 60478) for 60-day episodes of care. Next, using the October 2019 3M Home Health Grouper (v8219) ^[13] we assign a HIPPS code to each simulated 60-day episode of care using the 153-group methodology. Finally, we price the CY 2020 simulated 60-day episodes of care using the payment parameters described in the CY 2020 final rule with comment period (84 FR 60537) for 60-day episodes of care. For CYs 2021 through 2026, we would adjust the simulated 60-day base payment rate to align with current payments for the analysis year (that is, wage index budget neutrality factor, HH payment update). For example, to calculate the CY 2021 simulated 60-day episode base payment rate, we would start with the final CY 2020 60-day base payment rate ($3,220.79) and multiply by the final CY 2021 wage index budget neutrality factor (0.9999) and the CY 2021 HH payment update (1.020) to get an adjusted 60-day base payment rate ($3,284.88) for CY 2021. We would use the 60-day base payment rate ($3,284.88) to price the CY 2021 simulated 60-day claims under the pre-PDGM HH PPS (60-day episodes under 153 case-mix groups) based on actual behaviors. Once each claim is priced under the pre-PDGM HH PPS, we calculate the estimated aggregate expenditures for all simulated 60-day episodes in CY 2021. This method would be used to reprice claims to simulated 60-day episodes for each subsequent year (that is, through CY 2026).

Next, we calculated the PDGM aggregate expenditures for CY 2020 using those specific 30-day periods that were used to create the simulated 60-day episodes. Therefore, both the actual CY 2020 PDGM expenditures and the simulated pre-PDGM CY 2020 aggregate expenditures are based on the same claims for the permanent adjustment calculation.

c. Calculating Permanent and Temporary Payment Adjustments

To offset for such increases or decreases in estimated aggregate expenditures as a result of the impact of differences between assumed behavior changes and actual behavior changes, in any given year, we calculate a permanent prospective adjustment by determining what the 30 day base payment amount should have been in order to achieve the same estimated aggregate expenditures as obtained from the simulated 60-day episodes. This would be our recalculated base payment rate. The percent change between the actual 30-day base payment rate and the recalculated 30-day base payment rate would be the permanent prospective adjustment.

To calculate a temporary retrospective adjustment for each year we would determine the dollar amount difference between the estimated aggregate expenditures from all 30-day periods using the recalculated 30-day base payment rate, and the aggregate expenditures for all 30-day periods using the actual 30-day base payment rate for the same year. In determining the temporary retrospective dollar amount, we use the full dataset of actual 30-day periods using both the actual and recalculated base payment rates to ensure utilization and distribution of claims are the same. In accordance with section 1895(b)(3)(D)(iii) of the Act, the temporary adjustment is to be applied on a prospective basis and shall apply only with respect to the year for which such temporary increase or decrease is made. Therefore, after we determine the dollar amount to be reconciled in any given year, we calculate a temporary adjustment factor to be applied to the base payment rate. The temporary adjustment factor is based on an estimated number of 30-day periods in the next year using historical data trends, and as applicable, we control for a permanent adjustment factor, case-mix weight recalibration neutrality factor, wage index budget neutrality factor, and the home health payment update. The temporary adjustment factor is applied last.

d. CY 2020 Results

Using the methodology described previously, we simulated 60-day episodes using actual CY 2020 30-day periods to determine what the CY 2020 permanent and temporary payment adjustments should be to offset for such increases or decreases in estimated aggregate expenditures. For CY 2020, we began with 8,423,688 30-day periods and dropped 603,157 30-day periods that had a claim occurrence code 50 date after October 31, 2020. We also eliminated 79,328 30-day periods that didn't appear to group with another 30-day period to form a 60-day episode if the 30-day period had a “from date” before January 15, 2020 or a “through date” after November 30, 2020. This was done to ensure a 30-day period would not have been part of a 60-day episode that would have overlapped into CY 2021. Applying the additional exclusions and assumptions as described previously, an additional 14,062 30-day periods were excluded from this analysis. Additionally, we excluded 66,469 simulated 60-day episodes of care where no OASIS information was available in the CCW VRDC or could not be grouped to a HIPPS due to a missing primary diagnosis or other reason. Our simulated 60-day episodes of care produced a distribution of two 30-day periods of care (70.6 percent) and single 30-day periods of care (29.4 percent). This distribution is similar to what we found when we simulated 30-day periods of care for implementation of the PDGM. After all exclusions and assumptions were applied, the final dataset included 7,618,061 actual 30-day periods of care and 4,463,549 simulated 60-day episodes of care for CY 2020.

Using the final dataset for CY 2020 (7,618,061 actual 30-day periods which made up the 4,463,549 simulated 60-day episodes) we determined the estimated aggregate expenditures under the pre-PDGM HH PPS was lower than the actual estimated aggregate expenditures under the PDGM HH PPS (see Table B13). This indicates that aggregate expenditures under the PDGM were higher than if the 153-group payment system was still in place in CY 2020. As described previously, we recalculated what the CY 2020 30-day base payment rate should have been to equal aggregate expenditures that we calculated using the simulated CY 2020 60-day episodes. The percent change between the two payment rates would be the permanent adjustment. Next, we calculated the difference in aggregate expenditures for all CY 2020 PDGM 30-day claims using the actual and recalculated payment rates. This difference is the retrospective dollar amount needed to offset payment. Our results are shown in Table B13.

As shown in Table B13, a permanent prospective adjustment of −6.52 percent to the CY 2023 30-day payment rate would be required to offset for such increases in estimated aggregate expenditures in future years. Additionally, we determined that our initial estimate of base payment rates required to achieve budget neutrality resulted in excess expenditures of HHAs of approximately $873 million in CY 2020. This would require a temporary adjustment to offset for such increase in estimated aggregate expenditures for CY 2020.

e. CY 2021 Preliminary Results

We will continue the practice of using the most recent complete home health claims data at the time of rulemaking. The CY 2021 analysis presented in this proposed rule is considered preliminary and as more data become available from the latter half of CY 2021, we will update our results in the final rule. Using the methodology described previously, we simulated 60-day episodes using actual CY 2021 30-day periods to determine what the permanent and temporary payment adjustments should be to offset for such increases or decreases in estimated aggregate expenditures as a result of the impact of differences between assumed behavior changes and actual behavior changes. For CY 2021, we began with 8,962,690 30-day periods of care and dropped 478,105 30-day periods of care that had claim occurrence code 50 date after October 31, 2021. We also excluded 968,361 30-day periods of care that had claim occurrence code 50 date before January 1, 2021 to ensure the 30-day period would not be part of a simulated 60-day episode that began in CY 2020. Applying the additional exclusions and assumptions as described previously, an additional 4,853 30-day periods were excluded.

Additionally, we excluded 11,143 simulated 60-day episodes of care where no OASIS information was available in the CCW VRDC or could not be grouped to a HIPPS due to a missing primary diagnosis or other reason. Our simulated 60-day episodes of care produced a distribution of two 30-day periods of care (69.1 percent) and single 30-day periods of care (30.9 percent) that was similar to what we found when we simulated two 30-day periods of care for implementation of the PDGM. After all exclusions and assumptions were applied, the final dataset included 7,494,836 actual 30-day periods of care and 4,431,238 simulated 60-day episodes of care for CY 2021.

Using the final dataset for CY 2021 (7,494,836 actual 30-day periods which made up the 4,431,238 simulated 60-day episodes) we determined the estimated aggregate expenditures under the pre-PDGM HH PPS was lower than the actual estimated aggregate expenditures under the PDGM HH PPS. This indicates that aggregate expenditures under the PDGM were higher than if the 153-group payment system was still in place in CY 2021. As described previously, we recalculated what the CY 2021 30-day base payment rate should have been to equal aggregate expenditures that we calculated using the simulated CY 2021 60-day episodes. We note, the actual CY 2021 base payment rate of $1,901.12 does not account for any adjustments previously made for CY 2020 and therefore to evaluate changes for only CY 2021 we need to control for the −6.52 percent prospective adjustment that we determined for CY 2020. Therefore, using the recalculated CY 2020 base payment rate of $1,742.52, multiplied by the CY 2021 wage index budget neutrality factor (0.9999) and the CY 2021 HH payment update (1.020), the CY 2021 base payment rate for assumed behavior would have been $1,777.19. The percent change between the two payment rates would be the permanent adjustment. Next, we calculated the difference in aggregate expenditures for all CY 2021 PDGM 30-day claims using the actual and recalculated payment rates. This difference is the retrospective dollar amount needed to offset payment. Our results are shown in Table B14.

As shown in Table B14, a permanent prospective adjustment of −1.26 percent and would be required to offset for such increases in estimated aggregate expenditures in future years. Additionally, we determined that our initial estimate of base payment rates required to achieve budget neutrality resulted in excess expenditures of approximately $1.1 billion in CY 2021. This would require a one-time temporary adjustment factor to offset for such increases in estimated aggregate expenditures for CY 2021.

f. Proposed CY 2023 Permanent and Temporary Adjustments

The percent change between the actual CY 2021 base payment rate of $1,901.12 and the CY 2021 recalculated base payment rate of $1,754.88 is the total permanent adjustment for CYs 2020 and 2021, because no previous adjustments were applied to the CY 2020 rate to reset the CY 2021 rate. The summation of the dollar amount for CYs 2020 and 2021 is the amount that represents the temporary payment adjustment to offset for increased aggregate expenditures in both CYs 2020 and 2021. Our results are shown in Table B15 and B16.

To offset the increase in estimated aggregate expenditures for CYs 2020 and 2021 based on the impact of the differences between assumed and actual behavior changes, CMS would need to apply a −7.69 percent permanent adjustment to the CY 2023 base payment rate as well as implement a temporary adjustment of approximately $2.0 billion to reconcile retrospective overpayments in CYs 2020 and 2021. We recognize that applying the full permanent and temporary adjustment immediately would result in a significant negative adjustment in a single year. However, if the PDGM base 30-day payment rate remains higher than it should be, then there would likely be a compounding effect potentially creating the need for a larger reduction in future years. Therefore, we propose initially to apply only the permanent adjustment of −7.69 percent to the CY 2023 base payment rate. We believe this could mitigate the need for a larger permanent adjustment and could reduce the amount of any additional temporary adjustments in future years. We are soliciting comments on the application of only the permanent payment adjustment to the CY 2023 30-day payment rate. Additionally, we solicit comments on how best to collect the temporary payment adjustment of approximately $2.0 billion for CYs 2020 and 2021. As noted previously, we will update these permanent and temporary adjustments in the final rule to reflect more complete claims data for CY 2021.

3. Proposed Reassignment of Specific ICD-10-CM Codes Under the PDGM

a. Background

The 2009 final rule, “HIPAA Administrative Simplification: Modifications to Medical Data Code Set Standards To Adopt ICD-10-CM and ICD-10-PCS” ^[14] (74 FR 3328, January 16, 2009), set October 1, 2013, as the compliance date for all covered entities under the Health Insurance Portability and Accountability Act of 1996 (HIPAA) to use the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) and the International Classification of Diseases, 10th Revision, Procedure Coding System (ICD-10-PCS) medical data code sets. The ICD-10-CM diagnosis codes are granular and specific, and provide HHAs a better opportunity to report codes that best reflect the patient's conditions that support the need for home health services. However, as stated in the CY 2019 HH PPS final rule with comment period (83 FR 56473), because the ICD-10-CM is comprehensive, it also contains many codes that may not support the need for home health services. For example, diagnosis codes that indicate death as the outcome are Medicare covered codes, but are not relevant to home health. In addition, diagnosis and procedure coding guidelines may specify the sequence of ICD-10-CM coding conventions. For example, the underlying condition must be listed first (for example, Parkinson's disease must be listed prior to Dementia if both codes were listed on a claim). Therefore, not all the ICD-10-CM diagnosis codes are appropriate as principal diagnosis codes for grouping home health periods into clinical groups or to be placed into a comorbidity subgroup when listed as a secondary diagnosis. As such, each ICD-10-CM diagnosis code is assigned, including those diagnosis codes designated as “not assigned” (NA), to a clinical group and comorbidity subgroup within the HH PPS grouper software (HHGS). We remind commenters the ICD-10-CM diagnosis code list is updated each fiscal year with an effective date of October 1st and therefore, the HH PPS is generally subject to a minimum of two HHGS releases, one in October and one in January of each year, to ensure that claims are submitted with the most current code set available. Likewise, there may be new ICD-10-CM diagnosis codes created (for example, codes for emergency use) or a new or revised edit in the Medicare Code Editor (MCE) so an update to the HHGS may occur on the first of each quarter (January, April, July, October).

b. Methodology for ICD-10-CM Diagnosis Code Assignments

Although it is not our intent to review all ICD-10-CM diagnosis codes each year, we recognize that occasionally some ICD-10-CM diagnosis codes may require changes to their assigned clinical group and/or comorbidity subgroup. For example, there may be an update to the MCE unacceptable principal diagnosis list, or we receive public comments from interested parties requesting specific changes. Any addition or removal of a specific diagnosis code to the ICD-10-CM code set (for example, three new diagnosis codes, Z28.310, Z28.311 and Z28.39, for reporting COVID-19 vaccination status were effective April 1, 2022) or minor tweaks to a descriptor of an existing ICD-10-CM diagnosis code generally would not require rulemaking, and may occur at any time. However, if an ICD-10-CM diagnosis code is to be reassigned from one clinical group and/or a comorbidity subgroup to another, which may affect payment, then we believe it is appropriate to propose these changes through notice and comment rulemaking.

We rely on the expert opinion of our clinical reviewers (for example, nurse consultants and medical officers) and current ICD-10-CM coding guidelines to determine if the ICD-10-CM diagnosis codes under review for reassignment are significantly similar or different to the existing clinical group and/or comorbidity subgroup assignment. As we stated in the CY 2018 proposed rule (82 FR 35313), the intent of the clinical groups is to reflect the reported principal diagnosis, clinical relevance, and coding guidelines and conventions. Therefore, for the purposes of assignment of ICD-10-CM diagnosis codes into the PDGM clinical groups we would not conduct additional statistical analysis as such decisions are clinically based and the clinical groups are part of the overall case-mix weights.

In the CY 2019 final rule with comment period (83 FR 56486), we stated the home health-specific comorbidity list is based on the principles of patient assessment by body systems and their associated diseases, conditions, and injuries to develop larger categories of conditions that identified clinically relevant relationships associated with increased resource use meaning the diagnoses have at least as high as the median resource use and are reported in more than 0.1 percent of 30-day periods of care. If specific ICD-10-CM diagnosis codes are to be reassigned to a different comorbidity subgroup (including NA), we will first evaluate the clinical characteristics (as discussed previously for clinical groups) and if the ICD-10-CM diagnosis code does not meet the clinical criteria, then no reassignment will occur. However, if an ICD-10-CM diagnosis code does meet the clinical criteria for a comorbidity subgroup reassignment, then we will evaluate the resource consumption associated with the ICD-10-CM diagnosis codes, the current assigned comorbidity subgroup, and the proposed (reassigned) comorbidity subgroup. This analysis is to ensure that any reassignment of an ICD-10-CM diagnosis code (if reported as secondary) in any given year would not significantly alter the overall resource use of a specific comorbidity subgroup. For resource consumption, we use non-LUPA 30-day periods to evaluate the total number of 30-day periods for the comorbidity subgroup(s) and the ICD-10-CM diagnosis code, the average number of visits per 30-day periods for the comorbidity subgroup(s) and the ICD-10-CM diagnosis code, and the average resource use for the comorbidity subgroup(s) and the ICD-10-CM diagnosis code. The average resource use measures the costs associated with visits performed during a home health period, and was previously described in the CY 2019 final rule with comment period (83 FR 56450).

c. Proposed ICD-10-CM Diagnosis Code Reassignments to a PDGM Clinical Group or Comorbidity Subgroup

The following section proposes reassignment of 320 diagnosis codes to a different clinical group when listed as a principal diagnosis, reassignment of 37 diagnosis codes to a different comorbidity subgroup when listed as a secondary diagnosis, and the establishment of a new comorbidity subgroup for certain neurological conditions and disorders. Due to the amount of diagnosis codes proposed for reassignment this year, we have posted the “CY 2023 Proposed Reassignment of ICD-10-CM Diagnosis Codes for HH PDGM Clinical Groups and Comorbidity Subgroups” supplemental file on the Home Health Prospective Payment System Regulations and Notices web page.^[15] The supplemental file can be accessed through the CY 2023 Home Health Prospective Payment System Rate Update; Home Health Quality Reporting Requirements; and Home Infusion Therapy Requirements link. The following tables are included in the supplemental file:

(1) Proposed Clinical Group Reassignment of Certain Unspecified Diagnosis Codes

We remind readers that in the CY 2019 final rule with comment period (83 FR 56473) we stated that whenever possible, the most specific code that describes a medical disease, condition, or injury should be used. Generally, “unspecified” codes are used when there is lack of information about location or severity of medical conditions in the medical record. However, we would expect a provider to use a precise code whenever more specific codes are available. Furthermore, if additional information regarding the diagnosis is needed, we would expect the HHA to follow-up with the referring provider in order to ensure the care plan is sufficient in meeting the needs of the patient. For example, T14.90 “Injury, unspecified” does not provide sufficient information (for example, the type and extent of the injury) that would be necessary in care planning for home health services. The ICD-10-CM code set also includes laterality. We believe a home health clinician should not report an “unspecified” code if that clinician can identify the side or site of a condition. For example, a home health clinician should be able to state whether a fracture of the arm is on the right or left arm. In the FY 2022 Inpatient Prospective Payment System/Long-Term Care Hospital Prospective Payment System (IPPS/LTCH PPS) final rule (86 FR 44940 through 44943), CMS finalized the implementation of a new MCE to expand the list of unacceptable principal diagnoses for “unspecified” ICD-10-CM diagnosis codes when there are other diagnosis codes available in that diagnosis code subcategory that further specify the anatomic site. As such, we reviewed the ICD-10-CM diagnosis codes where “unspecified” is used. We identified 159 ICD-10-CM diagnosis codes currently accepted as a principal diagnosis that have more specific codes available for such medical conditions that would more accurately identify the primary reason for home health services. For example, S59.109A (Unspecified physeal fracture of upper end of radius, unspecified arm, initial encounter for closed fracture) does not specify which arm has the fracture; whereas, S59.101A (Unspecified physeal fracture of upper end of radius, right arm, initial encounter for closed fracture) does indicate the fracture is on the right arm and therefore more accurately identifies the primary reason for home health services. Therefore, in accordance with our expectation that the most precise code be used, we believe these 159 ICD-10 CM diagnosis codes are not acceptable as principal diagnoses and we propose to reassign them to “no clinical group” (NA). We refer readers to Table 1.A of the CY 2023 Proposed Reassignment of ICD-10-CM Diagnosis Codes supplemental file ^[16] for the list of the 159 unspecified diagnosis codes.

We also determined that B78.9 strongyloidiasis, unspecified was assigned to clinical group C (Wounds), and should be reassigned to clinical group K (MMTA—Infectious Disease, Neoplasms, and Blood-Forming Diseases) because it would be consistent with the assignment of the other strongyloidiasis codes. We also identified that N83.201 unspecified ovarian cyst, right side was assigned to clinical group A (MMTA-Other) and should be reassigned to clinical group J (MMTA—Gastrointestinal Tract and Genitourinary System) because it would be consistent with the assignment of other ovarian cyst codes. We propose to reassign these two ICD-10-CM diagnosis codes' clinical groups as shown in Table B17.

(2) Proposed Clinical Group Reassignment of Gout-Related Codes

We identified that certain groups of gout-related ICD-10-CM diagnosis codes, such as idiopathic gout and drug-induced gout, were assigned to clinical group E (musculoskeletal rehabilitation) when listed as a principal diagnosis. However, other groups of gout related ICD-10-CM diagnosis codes, such as gout due to renal impairment, were assigned to “no clinical group” (NA). Therefore, we reviewed all gout-related codes and determined there are 144 gout related codes with an anatomical site specified, not currently assigned to a clinical group that should be moved to clinical group E (musculoskeletal rehabilitation) for consistency with the aforementioned gout codes. In the ICD-10-CM code set, gout codes and osteoarthritis codes are found in chapter 13 Diseases of the Musculoskeletal System and Connective Tissue (M00-M99). Gout and osteoarthritis affect similar joints such as the fingers, toes, and knees and they can initially be treated with medications. However, generally, as a part of a treatment program, once the initial inflammation is reduced, physical therapy can be started to stretch and strengthen the affected joint to restore flexibility and joint function. Because those cases may require therapy, we believe gout codes are more appropriately placed into MS rehab along with other codes affecting the musculoskeletal system. We refer readers to Table 1.B of the CY 2023 Proposed Reassignment of ICD-10-CM Diagnosis Codes supplemental file for the list of the 144 gout related codes. We propose to reassign these 144 gout-related ICD-10-CM diagnosis codes to clinical group E (musculoskeletal rehabilitation).

(3) Proposed Clinical Group Reassignment of Crushing Injury-Related Codes

We identified 12 ICD-10-CM diagnosis codes related to crushing injury of the face, skull, and head that warrant reassignment. These codes are listed in Table B18.

Our clinical advisors reviewed the 12 ICD-10-CM diagnosis codes related to crushing injury of the face, skull, and head and determined that reassignment of these codes to clinical group B (Neurological Rehabilitation) is clinically appropriate because they are consistent with other diagnosis codes in clinical group E that describe injuries requiring neurological rehabilitation. Therefore, we propose to reassign the ICD-10-CM diagnosis codes listed in Table B18 from clinical group A (MMTA-Other) to clinical group B (Neurological Rehabilitation).

(4) Proposed Clinical Group Reassignment of Lymphedema-Related Codes

We received questions from interested parties regarding three lymphedema codes with conflicting clinical group assignments when listed as a principal diagnosis. These codes are listed in Table B19.

Our clinical advisors reviewed the three ICD-10-CM diagnosis codes related to lymphedema and determined that assessing and treating lymphedema is similar to the assessment and staging of wounds. It requires the assessment of pulses, evaluation of the color and amount of drainage, and measurement. In addition, some lymphedema can require compression bandaging, similar to wound care. Because of these similarities, we determined the reassignment of the three ICD-10-CM diagnosis codes related to lymphedema to clinical group C (Wounds) is clinically appropriate. Therefore, we propose to reassign the ICD-10-CM diagnosis codes listed in Table B19 from clinical group E (Musculoskeletal Rehabilitation) and clinical group A (MMTA-Other) to clinical group C (Wounds).

(5) Proposed Behavioral Health Comorbidity Subgroups

Our clinical advisors reviewed the ICD-10-CM diagnosis code F60.5 (obsessive-compulsive personality disorder) which is currently assigned to the comorbidity subgroup behavioral 6 (Schizotypal, Persistent Mood, and Adult Personality Disorders). However, they noted that behavioral 5 (Phobias, Other Anxiety and Obsessive-Compulsive Disorders) contains other obsessive-compulsive disorders (for example, F42.8 and F42.9) and clinically F60.5 should be reassigned to the comorbidity subgroup behavioral 5. In addition, we evaluated resource consumption related to the comorbidity subgroup behavioral 5, the comorbidity subgroup behavioral 6, and F60.5 and found no significant variations negating a reassignment, meaning the reassignment is still in alignment with the actual costs of providing care. Therefore, we propose to reassign diagnosis code F60.5 to behavioral 5 when listed as a secondary diagnosis.

(6) Proposed Circulatory Comorbidity Subgroups

We reviewed Q82.0 (hereditary lymphedema) for clinical group reassignment, as described in section II.B.3.4. of this rule. During this review, we discovered Q82.0 is not currently assigned to a comorbidity subgroup when listed as a secondary diagnosis. The comorbidity subgroup circulatory 10 includes ICD-10-CM diagnosis codes related to varicose veins and lymphedema and our clinical advisors determined that Q82.0 should be assigned to the comorbidity subgroup circulatory 10 similar to other lymphedema diagnosis codes. In addition, we evaluated resource consumption related to the comorbidity subgroup circulatory 10 and Q82.0 and found no significant variations negating a reassignment. Therefore, we propose to assign diagnosis code Q82.0 to circulatory 10 (varicose veins and lymphedema) when listed as a secondary diagnosis.

(7) Proposed Neoplasm Comorbidity Subgroups

(i) Malignant Neoplasm of Upper Respiratory

In response to interested parties' questions regarding upper respiratory malignant neoplasms, we reviewed 14 ICD-10-CM diagnosis codes related to malignant neoplasms of the upper respiratory tract currently assigned to the comorbidity subgroup neoplasm 6 (malignant neoplasms of trachea, bronchus, lung, and mediastinum). These 14 codes are listed in Table B20.

Our clinical advisors reviewed the codes listed in Table B20 and determined that C32.3, C32.8, and C32.9 are currently assigned to the most clinically appropriate neoplasm comorbidity subgroup (neoplasm 6), and therefore no further analysis was conducted for these three ICD-10 CM diagnosis codes. However, upon review of all the neoplasm comorbidity subgroups, they determined that the remaining 11 codes listed in Table B20 should be reassigned to neoplasm 1 (malignant neoplasms of lip, oral cavity, and pharynx, including head and neck cancers) in alignment with clinically similar diagnosis codes already assigned (for example, C11.0 malignant neoplasm of superior wall of nasopharynx). In addition, we evaluated resource consumption related to the comorbidity subgroup, neoplasm 1, as well as diagnosis codes, C30.0, C30.1, C31.0, C31.1, C31.2, C31.3, C31.8, C31.9, C32.0, C32.1, or C32.2 and found no significant variations negating a reassignment.

Therefore, we propose to reassign diagnosis codes C30.0, C30.1, C31.0, C31.1, C31.2, C31.3, C31.8, C31.9, C32.0, C32.1, or C32.2 from neoplasm 6 to neoplasm 1 when listed as a secondary diagnosis.

(ii) Malignant Neoplasm of Unspecified Adrenal Gland

While reviewing unspecified codes for a change in clinical group, we noticed that ICD-10-CM diagnosis codes C74.00 (malignant neoplasm of cortex of unspecified adrenal gland) and C74.90 (malignant neoplasm of unspecified part of unspecified adrenal gland) were coded as “N/A” instead of placed in a comorbidity subgroup. The comorbidity subgroup neoplasm 15 currently includes ICD-10-CM diagnosis codes related to malignant neoplasm of adrenal gland, endocrine glands and related structures; specifically, C74.10 (malignant neoplasm of medulla of unspecified adrenal gland). At this time, we believe that C74.00 and C74.90 should be reassigned to neoplasm 15 based on clinical similarities of other codes currently assigned. In addition, we evaluated resource consumption related to the comorbidity subgroup neoplasm 15, as well as diagnosis codes C74.00, and C74.90 and found no significant variations negating a reassignment. Therefore, we propose to reassign diagnosis codes C74.00 and C74.90 from “NA” to neoplasm 15 (malignant neoplasm of adrenal gland, endocrine glands and related structures) when listed as secondary diagnoses.

(8) Proposed New Neurological Comorbidity Subgroup

In response to a comment received, we discussed in the CY 2022 final rule (86 FR 62263, 62264) our review of ICD-10-CM diagnosis codes related to specified neuropathy or unspecified polyneuropathy. These include specific ICD-10-CM G-codes. We stated that the codes were assigned to the most clinically appropriate subgroup at the time. However, upon further clinical review we believe a new neurological comorbidity subgroup to include ICD-10-CM diagnosis codes related to nondiabetic neuropathy is warranted. We identified 18 ICD-10-CM diagnosis codes for potential reassignment to a proposed new comorbidity subgroup, neurological 12. We refer readers to Table 1.C of the CY 2023 Proposed Reassignment of ICD-10-CM Diagnosis Codes supplemental file for a list of the G-codes related to specified neuropathy or unspecified polyneuropathy. Of the 18 codes, 11 diagnosis codes were not currently assigned a comorbidity group and seven diagnosis codes were assigned to neurological 11 comorbidity subgroup.

Using claims data from the CY 2021 HH PPS analytical file, we identified that the 18 diagnosis G-codes related to specified neuropathy or unspecified polyneuropathy would have sufficient claims (>400,000) for a new comorbidity subgroup. The removal of the seven codes from the neurological 11 comorbidity subgroup, would still allow for sufficient claims (>250,000) and include the remaining 146 diagnosis codes currently listed in the neurological 11 comorbidity subgroup. We evaluated resource consumption related to the comorbidity subgroup neurological 11, the 18 diagnosis G-codes, and the proposed comorbidity subgroup neurological 12 and found no significant variations negating a reassignment. A new neurological comorbidity subgroup allows more clinically similar codes, nondiabetic neuropathy, to be grouped together. Therefore, we propose to reassign the 18 diagnosis codes listed in Table 1.C of the CY 2023 Proposed Reassignment of ICD-10 CM Diagnosis Codes supplemental file, to the new comorbidity subgroup neurological 12 (nondiabetic neuropathy) when listed as secondary diagnoses. In conjunction with the proposed new comorbidity subgroup, we propose to change the description of the current comorbidity subgroup, neurological 11, from “Diabetic Retinopathy and Macular Edema” to “Disease of the Macula and Blindness/Low Vision”.

(9) Proposed Respiratory Comorbidity Subgroups

(i) J18.2 Hypostatic Pneumonia, Unspecified Organism

Our clinical advisors reviewed the ICD-10-CM diagnosis code J18.2 (hypostatic pneumonia, unspecified organism) which is currently assigned to the comorbidity subgroup respiratory 4 (bronchitis, emphysema, and interstitial lung disease). However, respiratory 2 (whooping cough and pneumonia) contains other pneumonia with unspecified organism (for example, J18.1 and J18.8). Clinically, J18.2 is similar to the other pneumonias in respiratory 2 and therefore, should be reassigned from comorbidity subgroup respiratory 4 to comorbidity subgroup respiratory 2. In addition, we evaluated resource consumption related to the comorbidity subgroups respiratory 2 and respiratory 4, and J18.2 and found no significant variations negating a reassignment.

Therefore, we propose to reassign diagnosis code J18.2 (hypostatic pneumonia, unspecified organism) to respiratory 2 when listed as a secondary diagnosis.

(ii) J98.2 Interstitial Emphysema and J98.3 Compensatory Emphysema

Our clinical advisors reviewed the ICD-10-CM diagnosis codes J98.2, interstitial emphysema and J98.3, compensatory emphysema, which are currently assigned to the comorbidity subgroup respiratory 9 (respiratory failure and atelectasis). However, respiratory 4 (bronchitis, emphysema, and interstitial lung disease) contains other emphysema codes (for example, J43.0 through J43.9) and therefore clinically we believe it is appropriate to reassign J98.2 and J98.3 to the comorbidity subgroup respiratory 9. In addition, we evaluated resource consumption related to the comorbidity subgroups respiratory 4 and respiratory 9, as well as diagnosis codes J98.2, and J98.3 and found no significant variations negating a reassignment. Therefore, we propose to reassign diagnosis codes J98.2 and J98.3 to respiratory 4 when listed as a secondary diagnosis.

(iii) U09.9 Post COVID-19 Condition, Unspecified

Our clinical advisors reviewed the ICD-10-CM diagnosis code U09.9 (post COVID-19 condition, unspecified), which is currently assigned to the comorbidity subgroup, respiratory 2 (whooping cough and pneumonia). However, respiratory 10 (2019 novel Coronavirus) contains other COVID-19 codes (for example, U07.1). Therefore, we believe clinically that U09.9 should be reassigned to the comorbidity subgroup, respiratory 10. In addition, we evaluated resource consumption related to the comorbidity subgroups respiratory 2 and respiratory 10, and diagnosis codes U09.9 and found no significant variations negating a reassignment.

Therefore, we propose to reassign diagnosis code U09.9 to respiratory 10 when listed as a secondary diagnosis.

We solicit comments on all of the proposed clinical group and comorbidity subgroup reassignments described in this section.

4. Proposed CY 2023 PDGM LUPA Thresholds and PDGM Case-Mix Weights

a. Proposed CY 2023 PDGM LUPA Thresholds

Under the HH PPS, LUPAs are paid when a certain visit threshold for a payment group during a 30-day period of care is not met. In the CY 2019 HH PPS final rule (83 FR 56492), we finalized that the LUPA thresholds would be set at the 10th percentile of visits or 2 visits, whichever is higher, for each payment group. This means the LUPA threshold for each 30 day period of care varies depending on the PDGM payment group to which it is assigned. If the LUPA threshold for the payment group is met under the PDGM, the 30-day period of care will be paid the full 30-day period case-mix adjusted payment amount (subject to any PEP or outlier adjustments). If a 30-day period of care does not meet the PDGM LUPA visit threshold, then payment will be made using the CY 2023 per-visit payment amounts as described in Section II.B.5.c. of this proposed rule. For example, if the LUPA visit threshold is four, and a 30-day period of care has four or more visits, it is paid the full 30-day period payment amount; if the period of care has three or less visits, payment is made using the per-visit payment amounts.

In the CY 2019 HH PPS final rule with comment period (83 FR 56492), we finalized our policy that the LUPA thresholds for each PDGM payment group would be reevaluated every year based on the most current utilization data available at the time of rulemaking. However, as CY 2020 was the first year of the new case-mix adjustment methodology, we stated in the CY 2021 final rule (85 FR 70305, 70306) that we would maintain the LUPA thresholds that were finalized and shown in Table 17 of the CY 2020 HH PPS final rule with comment period (84 FR 60522) for CY 2021 payment purposes. We stated that at that time, we did not have sufficient CY 2020 data to reevaluate the LUPA thresholds for CY 2021.

In the CY 2022 HH PPS final rule (86 FR 62249), we finalized the proposal to recalibrate the PDGM case-mix weights, functional impairment levels, and comorbidity subgroups while maintaining the LUPA thresholds for CY 2022. We stated that because there are several factors that contribute to how the case-mix weight is set for a particular case-mix group (such as the number of visits, length of visits, types of disciplines providing visits, and non-routine supplies) and the case-mix weight is derived by comparing the average resource use for the case-mix group relative to the average resource use across all groups, we believe the PHE would have impacted utilization within all case-mix groups similarly. Therefore, the impact of any reduction in resource use caused by the PHE on the calculation of the case-mix weight would be minimized since the impact would be accounted for both in the numerator and denominator of the formula used to calculate the case-mix weight. However, in contrast, the LUPA thresholds are based on the number of overall visits in a particular case-mix group (the threshold is the 10th percentile of visits or 2 visits, whichever is greater) instead of a relative value (like what is used to generate the case-mix weight) that would control for the impacts of the PHE. We noted that visit patterns and some of the decrease in overall visits in CY 2020 may not be representative of visit patterns in CY 2022. Therefore, to mitigate any potential future and significant short-term variability in the LUPA thresholds due to the COVID-19 PHE, we finalized the proposal to maintain the LUPA thresholds finalized and displayed in Table 17 in the CY 2020 HH PPS final rule with comment period (84 FR 60522) for CY 2022 payment purposes.

For CY 2023, we are proposing to update the LUPA thresholds using CY 2021 Medicare home health claims (as of March 21, 2022) linked to OASIS assessment data. After reviewing the CY 2021 home health claims utilization data we determined that visit patterns have stabilized. Our data analysis indicates that visits in 2021 were similar to visits in 2020. We believe that CY 2021 data will be more indicative of visit patterns in CY 2023 rather than continuing to use the LUPA thresholds derived from the CY 2018 data pre-PDGM. Therefore, we are proposing to update the LUPA thresholds for CY 2023 using data from CY 2021. In general, there is not much variation in the updated LUPA thresholds; 280 case-mix groups had no change in their LUPA threshold. There are 120 case-mix groups that had their LUPA threshold go down by one visit and 18 case-mix groups that have their LUPA threshold go up by a visit. There are 12 case-mix groups that had their LUPA threshold go down by two visits and 2 case-mix groups that had their LUPA threshold go down by three visits.

The proposed LUPA thresholds for the CY 2023 PDGM payment groups with the corresponding Health Insurance Prospective Payment System (HIPPS) codes and the case-mix weights are listed in Table B26. We solicit public comments on the proposed updates to the LUPA thresholds for CY 2023.

b. CY 2023 Functional Impairment Levels

Under the PDGM, the functional impairment level is determined by responses to certain OASIS items associated with activities of daily living and risk of hospitalization; that is, responses to OASIS items M1800-M1860 and M1033. A home health period of care receives points based on each of the responses associated with these functional OASIS items, which are then converted into a table of points corresponding to increased resource use. The sum of all of these points results in a functional score which is used to group home health periods into a functional level with similar resource use. That is, the higher the points, the higher the response is associated with increased resource use. The sum of all of these points results in a functional impairment score which is used to group home health periods into one of three functional impairment levels with similar resource use. The three functional impairment levels of low, medium, and high were designed so that approximately one-third of home health periods from each of the clinical groups fall within each level. This means home health periods in the low impairment level have responses for the functional OASIS items that are associated with the lowest resource use, on average. Home health periods in the high impairment level have responses for the functional OASIS items that are associated with the highest resource use on average.

For CY 2023, we propose to use CY 2021 claims data to update the functional points and functional impairment levels by clinical group. The CY 2018 HH PPS proposed rule (82 FR 35320) and the technical report from December 2016, posted on the Home Health PPS Archive webpage located at: https://www.cms.gov/​medicare/​home-health-pps/​home-health-pps-archive , provide a more detailed explanation as to the construction of these functional impairment levels using the OASIS items. We are proposing to use this same methodology previously finalized to update the functional impairment levels for CY 2023. The updated OASIS functional points table and the table of functional impairment levels by clinical group for CY 2023 are listed in Tables B21 and B22, respectively. We solicit public comments on the updates to functional points and the functional impairment levels by clinical group.

c. CY 2023 Comorbidity Subgroups

Thirty-day periods of care receive a comorbidity adjustment category based on the presence of certain secondary diagnoses reported on home health claims. These diagnoses are based on a home-health specific list of clinically and statistically significant secondary diagnosis subgroups with similar resource use, meaning the diagnoses have at least as high as the median resource use and are reported in more than 0.1 percent of 30-day periods of care. Home health 30-day periods of care can receive a comorbidity adjustment under the following circumstances:

• Low comorbidity adjustment: There is a reported secondary diagnosis on the home health-specific comorbidity subgroup list that is associated with higher resource use.

• High comorbidity adjustment: There are two or more secondary diagnoses on the home health-specific comorbidity subgroup interaction list that are associated with higher resource use when both are reported together compared to when they are reported separately. That is, the two diagnoses may interact with one another, resulting in higher resource use.

• No comorbidity adjustment: A 30-day period of care receives no comorbidity adjustment if no secondary diagnoses exist or do not meet the criteria for a low or high comorbidity adjustment.

In the CY 2019 HH PPS final rule with comment period (83 FR 56406), we stated that we would continue to examine the relationship of reported comorbidities on resource utilization and make the appropriate payment refinements to help ensure that payment is in alignment with the actual costs of providing care. For CY 2023, we propose to use the same methodology used to establish the comorbidity subgroups to update the comorbidity subgroups using CY 2021 home health data.

For CY 2023, we propose to update the comorbidity subgroups to include 23 low comorbidity adjustment subgroups as identified in Table B23 and 94 high comorbidity adjustment interaction subgroups as identified in Table B24. The proposed 23 low comorbidity adjustment subgroups and 94 high comorbidity adjustment interactions reflect the proposed coding changes detailed in section II.B.3.c. of this proposed rule. The proposed CY 2023 low comorbidity adjustment subgroups and the high comorbidity adjustment interaction subgroups including those diagnoses within each of these comorbidity adjustments will also be posted on the HHA Center webpage at https://www.cms.gov/​Center/​Provider-Type/​Home-Health-Agency-HHA-Center .

We invite comments on the proposed updates to the low comorbidity adjustment subgroups and the high comorbidity adjustment interactions for CY 2023.

d. CY 2023 PDGM Case-Mix Weights

As finalized in the CY 2019 HH PPS final rule with comment period (83 FR 56502), the PDGM places patients into meaningful payment categories based on patient and other characteristics, such as timing, admission source, clinical grouping using the reported principal diagnosis, functional impairment level, and comorbid conditions. The PDGM case-mix methodology results in 432 unique case-mix groups called home health resource groups (HHRGs). We also finalized a policy in the CY 2019 HH PPS final rule with comment period (83 FR 56515) to recalibrate annually the PDGM case-mix weights using a fixed effects model with the most recent and complete utilization data available at the time of annual rulemaking. Annual recalibration of the PDGM case-mix weights ensures that the case-mix weights reflect, as accurately as possible, current home health resource use and changes in utilization patterns. To generate the proposed recalibrated CY 2023 case-mix weights, we used CY 2021 home health claims data with linked OASIS data (as of March 21, 2021). These data are the most current and complete data available at this time. We believe that recalibrating the case-mix weights using data from CY 2021 would be reflective of PDGM utilization and patient resource use for CY 2023. The proposed recalibrated case-mix weights will be updated based on more complete CY 2021 claims data for the final rule.

The claims data provide visit-level data and data on whether non-routine supplies (NRS) were provided during the period and the total charges of NRS. We determine the case-mix weight for each of the 432 different PDGM payment groups by regressing resource use on a series of indicator variables for each of the categories using a fixed effects model as described in the following steps:

Step 1: Estimate a regression model to assign a functional impairment level to each 30-day period. The regression model estimates the relationship between a 30-day period's resource use and the functional status and risk of hospitalization items included in the PDGM, which are obtained from certain OASIS items. We refer readers to Table B21 for further information on the OASIS items used for the functional impairment level under the PDGM. We measure resource use with the cost-per-minute + NRS approach that uses information from 2020 home health cost reports. We use 2020 home health cost report data because it is the most complete cost report data available at the time of rulemaking. Other variables in the regression model include the 30-day period's admission source, clinical group, and 30-day period timing. We also include home health agency level fixed effects in the regression model. After estimating the regression model using 30-day periods, we divide the coefficients that correspond to the functional status and risk of hospitalization items by 10 and round to the nearest whole number. Those rounded numbers are used to compute a functional score for each 30-day period by summing together the rounded numbers for the functional status and risk of hospitalization items that are applicable to each 30-day period. Next, each 30-day period is assigned to a functional impairment level (low, medium, or high) depending on the 30-day period's total functional score. Each clinical group has a separate set of functional thresholds used to assign 30-day periods into a low, medium or high functional impairment level. We set those thresholds so that we assign roughly a third of 30-day periods within each clinical group to each functional impairment level (low, medium, or high).

Step 2: A second regression model estimates the relationship between a 30-day period's resource use and indicator variables for the presence of any of the comorbidities and comorbidity interactions that were originally examined for inclusion in the PDGM. Like the first regression model, this model also includes home health agency level fixed effects and includes control variables for each 30-day period's admission source, clinical group, timing, and functional impairment level. After we estimate the model, we assign comorbidities to the low comorbidity adjustment if any comorbidities have a coefficient that is statistically significant (p-value of 0.05 or less) and which have a coefficient that is larger than the 50th percentile of positive and statistically significant comorbidity coefficients. If two comorbidities in the model and their interaction term have coefficients that sum together to exceed $150 and the interaction term is statistically significant (p-value of 0.05 or less), we assign the two comorbidities together to the high comorbidity adjustment.

Step 3: After Step 2, each 30-day period is assigned to a clinical group, admission source category, episode timing category, functional impairment level, and comorbidity adjustment category. For each combination of those variables (which represent the 432 different payment groups that comprise the PDGM), we then calculate the 10th percentile of visits across all 30-day periods within a particular payment group. If a 30-day period's number of visits is less than the 10th percentile for their payment group, the 30-day period is classified as a Low Utilization Payment Adjustment (LUPA). If a payment group has a 10th percentile of visits that is less than two, we set the LUPA threshold for that payment group to be equal to two. That means if a 30-day period has one visit, it is classified as a LUPA and if it has two or more visits, it is not classified as a LUPA.

Step 4: Take all non-LUPA 30-day periods and regress resource use on the 30-day period's clinical group, admission source category, episode timing category, functional impairment level, and comorbidity adjustment category. The regression includes fixed effects at the level of the home health agency. After we estimate the model, the model coefficients are used to predict each 30-day period's resource use. To create the case-mix weight for each 30-day period, the predicted resource use is divided by the overall resource use of the 30-day periods used to estimate the regression.

The case-mix weight is then used to adjust the base payment rate to determine each 30-day period's payment. Table B25 shows the coefficients of the payment regression used to generate the weights, and the coefficients divided by average resource use.

The case-mix weights proposed for CY 2023 are listed in Table B26 and will also be posted on the HHA Center web-page ^[17] upon display of this proposed rule.

For CY 2023, there are 238 groups that experience a −5% to 0% change in case-mix weights and 183 groups that experience a 0% to +5% change in weights compared to their CY 2022 case-mix weights. There are 10 groups that experience a change between +5% and +10% and one group that experiences a 10% to 12% increase in weights compared to the CY 2022 case-mix weights. Changes to the PDGM case-mix weights are implemented in a budget neutral manner by multiplying the CY 2023 national standardized 30-day period payment rate by a case-mix budget neutrality factor. Typically, the case-mix weight budget neutrality factor is also calculated using the most recent, complete home health claims data available. However, in the CY 2022 HH PPS proposed rule (86 FR 35908), due to the COVID-19 PHE, we discussed using the previous calendar year's home health claims data (CY 2019) to determine if there were significant differences between utilizing CY 2019 and CY 2020 claims data. We noted that CY 2020 was the first year of actual PDGM utilization data, therefore, if we were to use CY 2019 data due to the PHE we would need to simulate 30-day periods from 60-day episodes under the old system. We determined that using CY 2020 utilization data was more appropriate than using CY 2019 utilization data, as it is actual PDGM utilization data. For CY 2023, we will continue the practice of using the most recent complete home health claims data at the time of rulemaking, which is CY 2021 data. The case-mix budget neutrality factor is calculated as the ratio of 30-day base payment rates such that total payments when the CY 2023 PDGM case mix weights (developed using CY 2021 home health claims data) are applied to CY 2021 utilization (claims) data are equal to total payments when CY 2022 PDGM case-mix weights (developed using CY 2020 home health claims data) are applied to CY 2021 utilization data. This produces a case-mix budget neutrality factor for CY 2023 of 0.9895.

We invite comments on the CY 2023 proposed case-mix weights and proposed case-mix weight budget neutrality factor.

5. Proposed CY 2023 Home Health Payment Rate Updates

a. Proposed CY 2023 Home Health Market Basket Update for HHAs

Section 1895(b)(3)(B) of the Act requires that the standard prospective payment amounts for home health be increased by a factor equal to the applicable home health market basket update for those HHAs that submit quality data as required by the Secretary. In the CY 2019 HH PPS final rule with comment period (83 FR 56425), we finalized a rebasing of the home health market basket to reflect 2016 cost report data. A detailed description of how we rebased the HHA market basket is available in the CY 2019 HH PPS final rule with comment period (83 FR 56425 through 56436).

Section 1895(b)(3)(B) of the Act requires that in CY 2015 and in subsequent calendar years, except CY 2018 (under section 411(c) of the Medicare Access and CHIP Reauthorization Act of 2015 (MACRA) (Pub. L. 114-10, enacted April 16, 2015)), and CY 2020 (under section 53110 of the Bipartisan Budget Act of 2018 (BBA) (Pub. L. 115-123, enacted February 9, 2018)), the market basket percentage under the HHA prospective payment system, as described in section 1895(b)(3)(B) of the Act, be annually adjusted by changes in economy-wide productivity. Section 1886(b)(3)(B)(xi)(II) of the Act defines the productivity adjustment to be equal to the 10-year moving average of changes in annual economy-wide private nonfarm business multifactor productivity (MFP) (as projected by the Secretary for the 10-year period ending with the applicable fiscal year, calendar year, cost reporting period, or other annual period). The United States Department of Labor's Bureau of Labor Statistics (BLS) publishes the official measures of productivity for the United States economy. We note that previously the productivity measure referenced in section 1886(b)(3)(B)(xi)(II) 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” 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) of the Act is now published by BLS as “private nonfarm business total factor productivity”. We refer readers to https://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-Data-and-Systems/​Statistics-Trends-and-Reports/​MedicareProgramRatesStats/​MarketBasketResearch.

The proposed home health update percentage for CY 2023 is based on the estimated home health market basket update, specified at section 1895(b)(3)(B)(iii) of the Act, of 3.3 percent (based on IHS Global Inc.'s first-quarter 2022 forecast with historical data through fourth-quarter 2021). The estimated CY 2023 home health market basket update of 3.3 percent is then reduced by a productivity adjustment, as mandated by the section 3401 of the Patient Protection and Affordable Care Act (the Affordable Care Act) (Pub. L. 111-148), currently estimated to be 0.4 percentage point for CY 2023. In effect, the proposed home health payment update percentage for CY 2023 is a 2.9 percent increase. Section 1895(b)(3)(B)(v) of the Act requires that the home health update be decreased by 2 percentage points for those HHAs that do not submit quality data as required by the Secretary. For HHAs that do not submit the required quality data for CY 2023, the home health payment update would be 0.9 percent (2.9 percent minus 2 percentage points). If more recent data become available after the publication of this proposed rule and before the publication of the final rule (for example, more recent estimates of the home health market basket update and productivity adjustment), we would use such data, if appropriate, to determine the home health payment update percentage for CY 2023 in the final rule.

b. CY 2023 Home Health Wage Index

(1) Proposed CY 2023 Home Health Wage Index

Sections 1895(b)(4)(A)(ii) and (b)(4)(C) of the Act require the Secretary to provide appropriate adjustments to the proportion of the payment amount under the HH PPS that account for area wage differences, using adjustment factors that reflect the relative level of wages and wage-related costs applicable to the furnishing of home health services. Since the inception of the HH PPS, we have used inpatient hospital wage data in developing a wage index to be applied to home payments. We propose to continue this practice for CY 2023, as we continue to believe that, in the absence of home health-specific wage data that accounts for area differences, using inpatient hospital wage data is appropriate and reasonable for the HH PPS.

In the CY 2021 HH PPS final rule (85 FR 70298), we finalized our proposal to adopt the revised Office of Management and Budget (OMB) delineations with a 5-percent cap on wage index decreases, where the estimated reduction in a geographic area's wage index would be capped at 5-percent in CY 2021 only, meaning no cap would be applied to wage index decreases for the second year (CY 2022). Therefore, we proposed and finalized the use of the FY 2022 pre-floor, pre reclassified hospital wage index with no 5-percent cap on decreases as the CY 2022 wage adjustment to the labor portion of the HH PPS rates (86 FR 62285). For CY 2023, we propose to base the HH PPS wage index on the FY 2023 hospital pre-floor, pre-reclassified wage index for hospital cost reporting periods beginning on or after October 1, 2018, and before October 1, 2019 (FY 2019 cost report data). The proposed CY 2023 HH PPS wage index would not take into account any geographic reclassification of hospitals, including those in accordance with section 1886(d)(8)(B) or 1886(d)(10) of the Act. We also propose that the CY 2023 HH PPS wage index would include a 5-percent cap on wage index decreases as discussed later in this section. If finalized, we will apply the appropriate wage index value to the labor portion of the HH PPS rates based on the site of service for the beneficiary (defined by section 1861(m) of the Act as the beneficiary's place of residence).

To address those geographic areas in which there are no inpatient hospitals, and thus, no hospital wage data on which to base the calculation of the CY 2023 HH PPS wage index, we propose to continue to use the same methodology discussed in the CY 2007 HH PPS final rule (71 FR 65884) to address those geographic areas in which there are no inpatient hospitals. For rural areas that do not have inpatient hospitals, we propose to use the average wage index from all contiguous Core Based Statistical Areas (CBSAs) as a reasonable proxy. Currently, the only rural area without a hospital from which hospital wage data could be derived is Puerto Rico. However, for rural Puerto Rico, we do not apply this methodology due to the distinct economic circumstances that exist there (for example, due to the close proximity to one another of almost all of Puerto Rico's various urban and non-urban areas, this methodology would produce a wage index for rural Puerto Rico that is higher than that in half of its urban areas). Instead, we propose to continue to use the most recent wage index previously available for that area. The most recent wage index previously available for rural Puerto Rico is 0.4047, which is what we propose to use. For urban areas without inpatient hospitals, we use the average wage index of all urban areas within the State as a reasonable proxy for the wage index for that CBSA. For CY 2023, the only urban area without inpatient hospital wage data is Hinesville, GA (CBSA 25980). Using the average wage index of all urban areas in Georgia as proxy, we propose the CY 2023 wage index value for Hinesville, GA to be 0.8535.

On February 28, 2013, OMB issued Bulletin No. 13-01, announcing revisions to the delineations of MSAs, Micropolitan Statistical Areas, and CBSAs, and guidance on uses of the delineation of these areas. In the CY 2015 HH PPS final rule (79 FR 66085 through 66087), we adopted OMB's area delineations using a 1-year transition.

On August 15, 2017, OMB issued Bulletin No. 17-01 in which it announced that one Micropolitan Statistical Area, Twin Falls, Idaho, now qualifies as a Metropolitan Statistical Area. The new CBSA (46300) comprises the principal city of Twin Falls, Idaho in Jerome County, Idaho and Twin Falls County, Idaho. The CY 2022 HH PPS wage index value for CBSA 46300, Twin Falls, Idaho, will be 0.8803. Bulletin No. 17-01 is available at https://www.whitehouse.gov/​wp-content/​uploads/​legacy_​drupal_​files/​omb/​bulletins/​2017/​b-17-01.pdf.

On April 10, 2018, OMB issued OMB Bulletin No. 18-03, which superseded the August 15, 2017 OMB Bulletin No. 17-01. 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 OMB Bulletin No. 18-04 may be obtained at: https://www.bls.gov/​bls/​omb-bulletin-18-04-revised-delineations-of-metropolitan-statistical-areas.pdf.

On March 6, 2020, OMB issued Bulletin No. 20-01, which provided updates to and superseded OMB Bulletin No. 18-04 that was issued on September 14, 2018. The attachments to OMB Bulletin No. 20-01 provided detailed information on the update to statistical areas since September 14, 2018, and were based on the application of the 2010 Standards for Delineating Metropolitan and Micropolitan Statistical Areas to Census Bureau population estimates for July 1, 2017, and July 1, 2018. (For a copy of this bulletin, we refer readers to https://www.whitehouse.gov/​wp-content/​uploads/​2020/​03/​Bulletin-20-01.pdf .) In OMB Bulletin No. 20-01, OMB announced one new Micropolitan Statistical Area, one new component of an existing Combined Statistical Are and changes to New England City and Town Area (NECTA) delineations. In the CY 2021 HH PPS final rule (85 FR 70298) we stated that if appropriate, we would propose any updates from OMB Bulletin No. 20-01 in future rulemaking. After reviewing OMB Bulletin No. 20-01, we have determined that the changes in Bulletin 20-01 encompassed delineation changes that would not affect the Medicare home health wage index for CY 2022. Specifically, the updates consisted of changes to NECTA delineations and the re-designation of a single rural county into a newly created Micropolitan Statistical Area. The Medicare home health wage index does not utilize NECTA definitions, and, as most recently discussed in the CY 2021 HH PPS final rule (85 FR 70298) we include hospitals located in Micropolitan Statistical areas in each State's rural wage index. In other words, these OMB updates did not affect any geographic areas for purposes of the wage index calculation for CY 2022.

The proposed CY 2023 wage index is available on the CMS website at: https://www.cms.gov/​Center/​Provider-Type/​Home-Health-Agency-HHA-Center.

(2) Proposed Permanent Cap on Wage Index Decreases

As discussed in section II.B.5.b.1 of this proposed rule, we have proposed and finalized temporary transition policies in the past to mitigate significant changes to payments due to changes to the home health wage index. Specifically, in the CY 2015 HH PPS final rule (79 FR 66086), we implemented a 50/50 blend for all geographic areas consisting of the wage index values using the then-current OMB area delineations and the wage index values using OMB's new area delineations based on OMB Bulletin No. 13-01. In the CY 2021 HH PPS final rule (85 FR 73100), we adopted the revised OMB delineations with a 5-percent cap on wage index decreases, where the estimated reduction in a geographic area's wage index would be capped at 5-percent in CY 2021. We explained that we believed the 5-percent cap would provide greater transparency and would be administratively less complex than the prior methodology of applying a 50/50 blended wage index. We noted that this transition approach struck an appropriate balance by providing a transition period to mitigate the resulting short-term instability and negative impacts on providers and time for them to adjust to their new labor market area delineations and wage index values.

In the CY 2022 HH PPS final rule (86 FR 62285), a few commenters stated that providers should be protected against substantial payment reductions due to dramatic reductions in wage index values from one year to the next. Because we did not propose any transition policy in the CY 2022 proposed rule, we did not extend the transition period for CY 2022. In the CY 2022 HH PPS final rule, we stated that we continued to believe that applying the 5-percent cap transition policy in year one provided an adequate safeguard against any significant payment reductions associated with the adoption of the revised CBSA delineations in CY 2021, allowed for sufficient time to make operational changes for future calendar years, and provided a reasonable balance between mitigating some short-term instability in home health payments and improving the accuracy of the payment adjustment for differences in area wage levels. However, we acknowledged that certain changes to wage index policy may significantly affect Medicare payments. In addition, we reiterated that our policy principles with regard to the wage index include generally using the most current data and information available and providing that data and information, as well as any approaches to addressing any significant effects on Medicare payments resulting from these potential scenarios, in notice and comment rulemaking. With these policy principles in mind, we considered for this CY 2023 HH PPS proposed rule how best to address the potential scenarios, which commenters raised concerns; that is, scenarios in which changes to wage index policy may significantly affect Medicare home health payments.

In the past, we have established transition policies of limited duration to phase in significant changes to labor market areas. In taking this approach in the past, we sought to mitigate short-term instability and fluctuations that can negatively impact providers due to wage index changes. Sections 1895(b)(4)(A)(ii) and (b)(4)(C) of the Act requires the Secretary to provide appropriate adjustments to the proportion of the payment amount under the HH PPS that account for area wage differences, using adjustment factors that reflect the relative level of wages and wage-related costs applicable to the furnishing of home health services. We have previously stated that, because the wage index is a relative measure of the value of labor in prescribed labor market areas, we believe it is important to implement new labor market area delineations with as minimal a transition as is reasonably possible. However, we recognize that changes to the wage index have the potential to create instability and significant negative impacts on certain providers even when labor market areas do not change. In addition, year-to-year fluctuations in an area's wage index can occur due to external factors beyond a provider's control, such as the COVID-19 PHE, and for an individual provider, these fluctuations can be difficult to predict. We also recognize that predictability in Medicare payments is important to enable providers to budget and plan their operations.

In light of these considerations, we are proposing a permanent approach to smooth year-to-year changes in providers' wage indexes. We are proposing a policy that increases the predictability of home health payments for providers and mitigates instability and significant negative impacts to providers resulting from changes to the wage index.

As previously discussed, we believe that applying a 5-percent cap on wage index decreases for CY 2021 provided greater transparency and was administratively less complex than prior transition methodologies. In addition, we believe this methodology mitigates short-term instability and fluctuations that can negatively impact providers due to wage index changes. Lastly, we note that we believe the 5-percent cap we applied to all wage index decreases for CY 2021 provided an adequate safeguard against significant payment reductions related to the adoption of the revised CBSAs. However, as discussed earlier in this section of this proposed rule, we recognize there are circumstances that a one-year mitigation policy would not effectively address future years in which providers continue to be negatively affected by significant wage index decreases.

Typical year-to-year variation in the home health wage index has historically been within 5-percent, and we expect this will continue to be the case in future years. Therefore, we believe that applying a 5-percent cap on all wage index decreases in future years, regardless of the reason for the decrease, would effectively mitigate instability in home health payments due to any significant wage index decreases that may affect providers in any year that commenters raised in the CY 2022 HH PPS final rule. Additionally, we believe that applying a 5-percent cap on all wage index decreases would increase the predictability of home health payments for providers, enabling them to more effectively budget and plan their operations. Lastly, we believe that applying a 5-percent cap on all wage index decreases, from the prior year, would have a small overall impact on the labor market area wage index system. As discussed in further detail in section VII.C. of this proposed rule, we estimate that applying a 5-percent cap on all wage index decreases, from the prior year, will have a very small effect on the wage index budget neutrality factors for CY 2023. Because the wage index is a measure of the value of labor (wage and wage-related costs) in a prescribed labor market area relative to the national average, we anticipate that most providers will not experience year-to-year wage index declines greater than 5-percent in any given year. We believe that applying a 5-percent cap on all wage index decreases, from the prior year, would continue to maintain the accuracy of the overall labor market area wage index system.

Therefore, for CY 2023 and subsequent years, we are proposing to apply a permanent 5 percent cap on any decrease to a geographic area's wage index from its wage index in the prior year, regardless of the circumstances causing the decline. That is, we are proposing that a geographic area's wage index for CY 2023 would not be less than 95 percent of its final wage index for CY 2022, regardless of whether the geographic area is part of an updated CBSA, and that for subsequent years, a geographic area's wage index would not be less than 95 percent of its wage index calculated in the prior CY. We further propose that if a geographic area's prior CY wage index is calculated based on the 5-percent cap, then the following year's wage index would not be less than 95 percent of the geographic area's capped wage index. For example, if a geographic area's wage index for CY 2023 is calculated with the application of the 5-percent cap, then its wage index for CY 2024 would not be less than 95 percent of its capped wage index in CY 2023. Likewise, we are proposing to make the corresponding regulations text changes at § 484.220(c) as follows: Beginning on January 1, 2023, CMS will apply a cap on decreases to the home health wage index such that the wage index applied to a geographic area is not less than 95 percent of the wage index applied to that geographic area in the prior CY. This 5-percent cap on negative wage index changes would be implemented in a budget neutral manner through the use of wage index budget neutrality factors.

In section VII.C. of this proposed rule, we estimate the impact to payments for providers in CY 2023 based on this proposed policy. We also note that we would examine the effects of this policy on an ongoing basis in the future in order to assess its appropriateness.

c. CY 2023 Annual Payment Update

(1) Background

The HH PPS has been in effect since October 1, 2000. As set forth in the July 3, 2000 final rule (65 FR 41128), the base unit of payment under the HH PPS was a national, standardized 60-day episode payment rate. As finalized in the CY 2019 HH PPS final rule with comment period (83 FR 56406), and as described in the CY 2020 HH PPS final rule with comment period (84 FR 60478), the unit of home health payment changed from a 60-day episode to a 30-day period effective for those 30- day periods beginning on or after January 1, 2020.

As set forth in § 484.220, we adjust the national, standardized prospective payment rates by a case-mix relative weight and a wage index value based on the site of service for the beneficiary. To provide appropriate adjustments to the proportion of the payment amount under the HH PPS to account for area wage differences, we apply the appropriate wage index value to the labor portion of the HH PPS rates. In the CY 2019 HH PPS final rule with comment period (83 FR 56435), we finalized rebasing the home health market basket to reflect 2016 Medicare cost report data. We also finalized a revision to the labor share to reflect the 2016-based home health market basket compensation (Wages and Salaries plus Benefits) cost weight. We finalized that for CY 2019 and subsequent years, the labor share would be 76.1 percent and the non-labor share would be 23.9 percent. The following are the steps we take to compute the case-mix and wage-adjusted 30-day period payment amount for CY 2023:

• Multiply the national, standardized 30-day period rate by the patient's applicable case mix weight.
• Divide the case-mix adjusted amount into a labor (76.1 percent) and a non labor portion (23.9 percent).
• Multiply the labor portion by the applicable wage index based on the site of service of the beneficiary.
• Add the wage-adjusted portion to the non-labor portion, yielding the case-mix and wage adjusted 30-day period payment amount, subject to any additional applicable adjustments.

We provide annual updates of the HH PPS rate in accordance with section 1895(b)(3)(B) of the Act. Section 484.225 sets forth the specific annual percentage update methodology. In accordance with section 1895(b)(3)(B)(v) of the Act and § 484.225(i), for an HHA that does not submit home health quality data, as specified by the Secretary, the unadjusted national prospective 30-day period rate is equal to the rate for the previous calendar year increased by the applicable home health payment update, minus 2 percentage points. Any reduction of the percentage change would apply only to the calendar year involved and would not be considered in computing the prospective payment amount for a subsequent calendar year.

The final claim that the HHA submits for payment determines the total payment amount for the period and whether we make an applicable adjustment to the 30-day case-mix and wage-adjusted payment amount. The end date of the 30-day period, as reported on the claim, determines which calendar year rates Medicare will use to pay the claim.

We may adjust a 30-day case-mix and wage-adjusted payment based on the information submitted on the claim to reflect the following:

• A LUPA is provided on a per-visit basis as set forth in §§ 484.205(d)(1) and 484.230.
• A PEP adjustment as set forth in §§ 484.205(d)(2) and 484.235.
• An outlier payment as set forth in §§ 484.205(d)(3) and 484.240.

(2) CY 2023 National, Standardized 30-Day Period Payment Amount

Section 1895(b)(3)(A)(i) of the Act requires that the standard prospective payment rate and other applicable amounts be standardized in a manner that eliminates the effects of variations in relative case-mix and area wage adjustments among different home health agencies in a budget-neutral manner. To determine the CY 2023 national, standardized 30-day period payment rate, we apply a permanent behavioral adjustment factor, a case-mix weights recalibration budget neutrality factor, a wage index budget neutrality factor and the home health payment update percentage discussed in section II.C.2. of this proposed rule. As discussed in section II.B.2.f. of this proposed rule, we are implementing a permanent behavior adjustment of −7.69 percent to prevent further overpayments. The permanent behavior adjustment factor is 0.9231 (1−0.0769). As discussed previously, to ensure the changes to the PDGM case-mix weights are implemented in a budget neutral manner, we apply a case-mix weights budget neutrality factor to the CY 2022 national, standardized 30-day period payment rate. The proposed case-mix weights budget neutrality factor for CY 2023 is 0.9895. Additionally, we also apply a wage index budget neutrality to ensure that wage index updates and revisions are implemented in a budget neutral manner. Typically, the wage index budget neutrality factor is calculated using the most recent, complete home health claims data available. However, in the CY 2022 HH PPS final rule due to the COVID-19 PHE, we looked at using the previous calendar year's home health claims data (CY 2019) to determine if there were significant differences between utilizing 2019 and 2020 claims data. Our analysis showed that there was only a small difference between the wage index budget neutrality factors calculated using CY 2019 and CY 2020 home health claims data. Therefore, for CY 2022 we decided to continue our practice of using the most recent, complete home health claims data available; that is, we used CY 2020 claims data for the CY 2022 payment rate updates. For CY 2023 rate setting, we do not anticipate significant differences between using pre COVID-19 PHE data (CY 2019 claims) and the most recent claims data at the time of rulemaking (CY 2021 claims). Therefore, we will continue our practice of using the most recent, complete utilization data at the time of rulemaking; that is, we are using CY 2021 claims data for CY 2023 payment rate updates.

To calculate the wage index budget neutrality factor, we first determine the payment rate needed for non-LUPA 30-day periods using the CY 2023 wage index so those total payments are equivalent to the total payments for non-LUPA 30-day periods using the CY 2022 wage index and the CY 2022 national standardized 30-day period payment rate adjusted by the case-mix weights recalibration neutrality factor. Then, by dividing the payment rate for non-LUPA 30-day periods using the CY 2023 wage index with a 5-percent cap on wage index decreases by the payment rate for non-LUPA 30-day periods using the CY 2022 wage index, we obtain a wage index budget neutrality factor of 0.9975. We then apply the wage index budget neutrality factor of 0.9975 to the 30-day period payment rate.

Next, we would update the 30-day period payment rate by the CY 2023 home health payment update percentage of 2.9 percent. The CY 2023 national, standardized 30-day period payment rate is calculated in Table B27.

The CY 2023 national, standardized 30-day period payment rate for a HHA that does not submit the required quality data is updated by the CY 2023 home health payment update of 2.9 percent minus 2 percentage points and is shown in Table B28.

(3) CY 2023 National Per-Visit Rates for 30-Day Periods of Care

The national per-visit rates are used to pay LUPAs and are also used to compute imputed costs in outlier calculations. The per-visit rates are paid by type of visit or HH discipline. The six HH disciplines are as follows:

• Home health aide (HH aide).
• Medical Social Services (MSS).
• Occupational therapy (OT).
• Physical therapy (PT).
• Skilled nursing (SN).
• Speech-language pathology (SLP).

To calculate the CY 2023 national per-visit rates, we started with the CY 2022 national per-visit rates. Then we applied a wage index budget neutrality factor to ensure budget neutrality for LUPA per-visit payments. We calculated the wage index budget neutrality factor by simulating total payments for LUPA 30-day periods of care using the CY 2023 wage index with a 5-percent cap on wage index decreases and comparing it to simulated total payments for LUPA 30-day periods of care using the CY 2022 wage index (with no 5-percent cap). By dividing the total payments for LUPA 30-day periods of care using the CY 2023 wage index by the total payments for LUPA 30-day periods of care using the CY 2022 wage index, we obtained a wage index budget neutrality factor of 0.9992. We apply the wage index budget neutrality factor in order to calculate the CY 2022 national per visit rates.

The LUPA per-visit rates are not calculated using case-mix weights. Therefore, no case mix weights budget neutrality factor is needed to ensure budget neutrality for LUPA payments. Additionally, we are not applying the permanent adjustment to the per visit payment rates but only the case-mix adjusted payment rate. Lastly, the per-visit rates for each discipline are updated by the CY 2023 home health payment update percentage of 2.9 percent. The national per-visit rates are adjusted by the wage index based on the site of service of the beneficiary. The per-visit payments for LUPAs are separate from the LUPA add-on payment amount, which is paid for episodes that occur as the only episode or initial episode in a sequence of adjacent episodes. The CY 2023 national per visit rates for HHAs that submit the required quality data are updated by the CY 2023 home health payment update percentage of 2.9 percent and are shown in Table B29.

The CY 2023 per-visit payment rates for HHAs that do not submit the required quality data are updated by the CY 2023 home health payment update percentage of 2.9 percent minus 2 percentage points and are shown in Table B30.

(4) LUPA Add-On Factors

Prior to the implementation of the 30-day unit of payment, LUPA episodes were eligible for a LUPA add-on payment if the episode of care was the first or only episode in a sequence of adjacent episodes. As stated in the CY 2008 HH PPS final rule, the average visit lengths in these initial LUPAs are 16 to 18 percent higher than the average visit lengths in initial non-LUPA episodes (72 FR 49848). LUPA episodes that occur as the only episode or as an initial episode in a sequence of adjacent episodes are adjusted by applying an additional amount to the LUPA payment before adjusting for area wage differences. In the CY 2014 HH PPS final rule (78 FR 72305), we changed the methodology for calculating the LUPA add-on amount by finalizing the use of three LUPA add-on factors: 1.8451 for SN; 1.6700 for PT; and 1.6266 for SLP. We multiply the per-visit payment amount for the first SN, PT, or SLP visit in LUPA episodes that occur as the only episode or an initial episode in a sequence of adjacent episodes by the appropriate factor to determine the LUPA add-on payment amount.

In the CY 2019 HH PPS final rule with comment period (83 FR 56440), in addition to finalizing a 30-day unit of payment, we finalized our policy of continuing to multiply the per-visit payment amount for the first skilled nursing, physical therapy, or speech-language pathology visit in LUPA periods that occur as the only period of care or the initial 30-day period of care in a sequence of adjacent 30-day periods of care by the appropriate add-on factor (1.8451 for SN, 1.6700 for PT, and 1.6266 for SLP) to determine the LUPA add-on payment amount for 30-day periods of care under the PDGM. For example, using the proposed CY 2023 per-visit payment rates for HHAs that submit the required quality data, for LUPA periods that occur as the only period or an initial period in a sequence of adjacent periods, if the first skilled visit is SN, the payment for that visit would be $297.65 (1.8451 multiplied by $161.32), subject to area wage adjustment.

(5) Occupational Therapy LUPA Add-On Factor

In order to implement Division CC, section 115, of CAA 2021, CMS finalized changes to regulations at § 484.55(a)(2) and (b)(3) that allowed occupational therapists to conduct initial and comprehensive assessments for all Medicare beneficiaries under the home health benefit when the plan of care does not initially include skilled nursing care, but either PT or SLP (86 FR 62351). This change, led to us establishing a LUPA add-on factor for calculating the LUPA add-on payment amount for the first skilled occupational therapy (OT) visit in LUPA periods that occurs as the only period of care or the initial 30-day period of care in a sequence of adjacent 30-day periods of care.

As stated in the CY 2022 HH PPS final rule with comment period (86 FR 62289) since there was not sufficient data regarding the average excess of minutes for the first visit in LUPA periods when the initial and comprehensive assessments are conducted by occupational therapists we finalized the use of the PT LUPA add-on factor of 1.6700 as a proxy. We also stated that we would use the PT LUPA add-on factor as a proxy until we have CY 2022 data to establish a more accurate OT add-on factor for the LUPA add-on payment amounts (86 FR 62289). Therefore, we continue to believe the similarity in the per-visit payment rates for both PT and OT make the PT LUPA add-on factor the most appropriate proxy until we have CY 2022 data to propose a LUPA add-on factor specific to OT in future rulemaking.

d. Proposed Payments for High-Cost Outliers Under the HH PPS

(1) Background

Section 1895(b)(5) of the Act allows for the provision of an addition or adjustment to the home health payment amount otherwise made in the case of outliers because of unusual variations in the type or amount of medically necessary care. Under the HH PPS and the previous unit of payment (that is, 60-day episodes), outlier payments were made for 60-day episodes whose estimated costs exceed a threshold amount for each HHRG. The episode's estimated cost was established as the sum of the national wage-adjusted per visit payment amounts delivered during the episode. The outlier threshold for each case-mix group or PEP adjustment defined as the 60-day episode payment or PEP adjustment for that group plus a fixed-dollar loss (FDL) amount. For the purposes of the HH PPS, the FDL amount is calculated by multiplying the home health FDL ratio by a case's wage-adjusted national, standardized 60-day episode payment rate, which yields an FDL dollar amount for the case. The outlier threshold amount is the sum of the wage and case-mix adjusted PPS episode amount and wage-adjusted FDL amount. The outlier payment is defined to be a proportion of the wage-adjusted estimated cost that surpasses the wage-adjusted threshold. The proportion of additional costs over the outlier threshold amount paid as outlier payments is referred to as the loss-sharing ratio.

As we noted in the CY 2011 HH PPS final rule (75 FR 70397 through 70399), section 3131(b)(1) of the Affordable Care Act amended section 1895(b)(3)(C) of the Act to require that the Secretary reduce the HH PPS payment rates such that aggregate HH PPS payments were reduced by 5 percent. In addition, section 3131(b)(2) of the Affordable Care Act amended section 1895(b)(5) of the Act by redesignating the existing language as section 1895(b)(5)(A) of the Act and revised the language to state that the total amount of the additional payments or payment adjustments for outlier episodes could not exceed 2.5 percent of the estimated total HH PPS payments for that year. Section 3131(b)(2)(C) of the Affordable Care Act also added section 1895(b)(5)(B) of the Act, which capped outlier payments as a percent of total payments for each HHA for each year at 10 percent.

As such, beginning in CY 2011, we reduced payment rates by 5 percent and targeted up to 2.5 percent of total estimated HH PPS payments to be paid as outliers. To do so, we first returned the 2.5 percent held for the target CY 2010 outlier pool to the national, standardized 60-day episode rates, the national per visit rates, the LUPA add-on payment amount, and the NRS conversion factor for CY 2010. We then reduced the rates by 5 percent as required by section 1895(b)(3)(C) of the Act, as amended by section 3131(b)(1) of the Affordable Care Act. For CY 2011 and subsequent calendar years we targeted up to 2.5 percent of estimated total payments to be paid as outlier payments, and apply a 10 percent agency-level outlier cap.

In the CY 2017 HH PPS proposed and final rules (81 FR 43737 through 43742 and 81 FR 76702), we described our concerns regarding patterns observed in home health outlier episodes. Specifically, we noted the methodology for calculating home health outlier payments may have created a financial incentive for providers to increase the number of visits during an episode of care in order to surpass the outlier threshold; and simultaneously created a disincentive for providers to treat medically complex beneficiaries who require fewer but longer visits. Given these concerns, in the CY 2017 HH PPS final rule (81 FR 76702), we finalized changes to the methodology used to calculate outlier payments, using a cost-per-unit approach rather than a cost-per-visit approach. This change in methodology allows for more accurate payment for outlier episodes, accounting for both the number of visits during an episode of care and the length of the visits provided. Using this approach, we now convert the national per-visit rates into per 15-minute unit rates. These per 15-minute unit rates are used to calculate the estimated cost of an episode to determine whether the claim will receive an outlier payment and the amount of payment for an episode of care. In conjunction with our finalized policy to change to a cost-per-unit approach to estimate episode costs and determine whether an outlier episode should receive outlier payments, in the CY 2017 HH PPS final rule we also finalized the implementation of a cap on the amount of time per day that would be counted toward the estimation of an episode's costs for outlier calculation purposes (81 FR 76725). Specifically, we limit the amount of time per day (summed across the six disciplines of care) to 8 hours (32 units) per day when estimating the cost of an episode for outlier calculation purposes.

In the CY 2017 HH PPS final rule (81 FR 76724), we stated that we did not plan to re-estimate the average minutes per visit by discipline every year. Additionally, the per unit rates used to estimate an episode's cost were updated by the home health update percentage each year, meaning we would start with the national per visit amounts for the same calendar year when calculating the cost-per-unit used to determine the cost of an episode of care (81 FR 76727). We will continue to monitor the visit length by discipline as more recent data becomes available, and may propose to update the rates as needed in the future.

In the CY 2019 HH PPS final rule with comment period (83 FR 56521), we finalized a policy to maintain the current methodology for payment of high-cost outliers upon implementation of PDGM beginning in CY 2020 and calculated payment for high-cost outliers based upon 30-day period of care. Upon implementation of the PDGM and 30-day unit of payment, we finalized the FDL ratio of 0.56 for 30-day periods of care in CY 2020. Given that CY 2020 was the first year of the PDGM and the change to a 30-day unit of payment, we finalized to maintain the same FDL ratio of 0.56 in CY 2021 as we did not have sufficient CY 2020 data at the time of CY 2021 rulemaking to proposed a change to the FDL ratio for CY 2021. In the CY 2022 HH PPS final rule with comment period (86 FR 62292), we estimated that outlier payments would be approximately 1.8 percent of total HH PPS final rule payments if we maintained an FDL of 0.56 in CY 2022. Therefore, in order to pay up to, but no more than, 2.5 percent of total payments as outlier payments we finalized an FDL of 0.40 for CY 2022.

(2) FDL Ratio for CY 2023

For a given level of outlier payments, there is a trade-off between the values selected for the FDL ratio and the loss-sharing ratio. A high FDL ratio reduces the number of periods that can receive outlier payments, but makes it possible to select a higher loss-sharing ratio, and therefore, increase outlier payments for qualifying outlier periods. Alternatively, a lower FDL ratio means that more periods can qualify for outlier payments, but outlier payments per period must be lower.

The FDL ratio and the loss-sharing ratio are selected so that the estimated total outlier payments do not exceed the 2.5 percent aggregate level (as required by section 1895(b)(5)(A) of the Act). Historically, we have used a value of 0.80 for the loss-sharing ratio, which, we believe, preserves incentives for agencies to attempt to provide care efficiently for outlier cases. With a loss-sharing ratio of 0.80, Medicare pays 80 percent of the additional estimated costs that exceed the outlier threshold amount. Using CY 2021 claims data (as of March 21, 2022) and given the statutory requirement that total outlier payments do not exceed 2.5 percent of the total payments estimated to be made under the HH PPS, we are proposing an FDL ratio of 0.44 for CY 2023. CMS will update the FDL, if needed, once we have more complete CY 2021 claims data.

K. Comment Solicitation on the Collection of Data on the Use of Telecommunications Technology Under the Medicare Home Health Benefit

Even prior to the COVID-19 PHE, CMS acknowledged the importance of technology in allowing HHAs the flexibility of furnishing services remotely. In the CY 2019 HH PPS final rule with comment (83 FR 56406), for purposes of the Medicare home health benefit, we finalized the definition of “remote patient monitoring” in regulation at 42 CFR 409.46(e) as the collection of physiologic data (for example, electrocardiogram (ECG), blood pressure, glucose monitoring) digitally stored and/or transmitted by the patient and/or caregiver to the HHA. In the CY 2019 HH PPS final rule with comment, we also finalized in regulation at § 409.46(e) that the costs of remote patient monitoring are considered allowable administrative costs (operating expenses) if remote patient monitoring is used by the HHA to augment the care planning process (83 FR 56527).

With the declaration of the COVID-19 PHE in early 2020, the use of telecommunications technology has become more prominent in the delivery of healthcare in the United States. Anecdotally, many beneficiaries preferred to stay home than go to physician's offices and outpatient centers to seek care, while also limiting the number and frequency of care providers furnishing services inside their homes to avoid exposure to COVID-19. Accordingly, CMS implemented additional policies under the HH PPS to make providing and receiving services via telecommunications technology easier. In the first COVID-19 PHE interim final rule with comment period (IFC) (85 FR 19230), we changed the plan of care requirements at § 409.43(a) on an interim basis, for the purposes of Medicare payment, to state that the plan of care must include any provision of remote patient monitoring or other services furnished via a telecommunications system. The plan of care must also describe how the use of such technology is tied to the patient-specific needs as identified in the comprehensive assessment and will help to achieve the goals outlined on the plan of care. The amended plan of care requirements at § 409.43(a) also state that these services cannot substitute for a home visit ordered as part of the plan of care and cannot be considered a home visit for the purposes of patient eligibility or payment, in accordance with section 1895(e)(1)(A) and (B) of the Act. The CY 2021 HH PPS final rule with comment period (85 FR 70298) finalized these changes on a permanent basis, as well as amended § 409.46(e) to include not only remote patient monitoring, but other communication or monitoring services consistent with the plan of care for the individual, on the home health cost report as allowable administrative costs.

Sections 1895(e)(1)(A) and (B) of the Act specify that telecommunications services cannot substitute for in-person home health services ordered as part of the plan of care certified by a physician and are not considered a home health visit for purposes of eligibility or payment under Medicare. Though the use of telecommunications technology is not to be used as a substitute for in-person home health services, as ordered on the plan of care, and services provided through the use of telecommunications technology (rather than in-person) are not considered a home health visit, anecdotally we have heard that HHAs are using telecommunication services during the course of a 30-day period of care and as a result of the COVID-19 PHE, as described previously. In the first COVID-19 PHE IFC, we provided an example describing a situation where the use of technology is not a substitute for the provision of in-person visits as ordered on the plan of care, rather the plan of care is updated to reflect a change in the frequency of the in-person visits and to include “virtual visits” as part of the management of the home health patient (85 FR 19248).

Currently, the collection of data on the use of telecommunications technology is limited to overall cost data on a broad category of telecommunications services as a part of an HHA's administrative costs on line 5 of the HHA Medicare cost reports.^[18] As we noted in the CY 2019 HH PPS proposed rule, these costs would then be factored into the costs per visit. Factoring the costs associated with telecommunications systems into the costs per visit has important implications for assessing home health costs relevant to payment, including HHA Medicare margin calculations (83 FR 32426). Data on the use of telecommunications technology during a 30-day period of care at the beneficiary level is not currently collected on the home health claim. While the provision of services furnished via a telecommunications system must be included on the patient's plan of care, CMS does not routinely review plans of care to determine the extent to which these services are actually being furnished.

Collecting data on the use of telecommunications technology on home health claims would allow CMS to analyze the characteristics of the beneficiaries utilizing services furnished remotely, and will give us a broader understanding of the social determinants that affect who benefits most from these services, including what barriers may potentially exist for certain subsets of beneficiaries. Furthermore, in their March 2022 Report to the Congress: Medicare's Payment Policy, MedPAC recommended tracking the use of telehealth in the home health care benefit on home health claims in order to improve payment accuracy.^[19] As such, to collect more complete data on the use of telecommunications technology in the provision of home health services, we are soliciting comments on the collection of such data on home health claims, which we aim to begin collecting by January 1, 2023 on a voluntary basis by HHAs, and will begin to require this information be reported on claims by July of 2023. Specifically, we are soliciting comments on the use of three new G-codes identifying when home health services are furnished using synchronous telemedicine rendered via a real-time two-way audio and video telecommunications system; synchronous telemedicine rendered via telephone or other real-time interactive audio-only telecommunications system; and the collection of physiologic data digitally stored and/or transmitted by the patient to the home health agency, that is, remote patient monitoring. We would capture the utilization of remote patient monitoring through the inclusion of the start date of the remote patient monitoring and the number of units indicated on the claim. This may help us understand in general how long remote monitoring is used for individual patients and for which conditions. Although we plan to begin collecting this information beginning with these three G-codes on January 1, 2023, we are interested in comments on whether there are other common uses of telecommunications technology under the home health benefit that would warrant additional G-codes that would be helpful in tracking the use of such technology in the provision of care.

In accordance with section 40.2 in Chapter 10 of the Medicare Claims Processing Manual (Pub. 100-04), we plan to issue instructions that these forthcoming G-codes are to be used to report services in line item detail and each service must be reported as a separate line under the appropriate revenue code (04x—Physical Therapy, 043x—Occupational Therapy, 044x—Speech-Language Pathology, 055x—Skilled Nursing, 056x—Medical Social Services, or 057x—Home Health Aide). While we do not plan on limiting the use of these G-codes to any particular discipline, we would not anticipate use of such technology would be reported under certain revenue codes such as 027x or 0623—Medical Supplies, or revenue code 057x—Home Health Aide. We are interested in comments from the public on our belief that, due to the hands-on nature of home health aide services, the use of telecommunications technology would generally not be appropriate for such services. We remind interested parties that if there is a service that cannot be provided through telecommunications technology (for example, wound care that requires in-person, hands-on care from a skilled nurse), the HHA must make an in-person visit to furnish such services (85 FR 39428). We are also requesting comments regarding the appropriateness of such technology for particular services in order to more clearly delineate when the use of such technology is appropriate. This may help inform how we use this analysis, for instance, connecting how such technology is impacting the provision of care to certain beneficiaries, costs, quality, and outcomes, and determine if further requirements surrounding the use of telecommunications technology are needed.

We are also soliciting comments on future refinement of these G-codes beginning July 1, 2023. Specifically whether the codes should differentiate the type of clinician performing the service via telecommunications technology, such as a therapist versus therapist assistant; and whether new G-codes should differentiate the type of service being performed through the use of telecommunications technology, such as: skilled nursing services performed for care plan oversight (for example, management and evaluation or observation and assessment) versus teaching; or physical therapy services performed for the establishment or performance of a maintenance program versus other restorative physical therapy services.

We will issue program instruction outlining the use of new codes for the purposes of tracking the use of telecommunications technology under the home health benefit with sufficient notice to enable HHAs to make the necessary changes in their electronic health records and billing systems. As stated previously, we will begin collecting this information on home health claims by January 1, 2023, on a voluntary basis by HHAs, and will require this information be reported on home health claims beginning in July, 2023. We would issue further program instruction prior to July 1, 2023, if the G-code description changes between January 1, 2023, and July 1, 2023, based on comments in this proposed rule. However, we reiterate that the collection of information on the use of telecommunications technology does not mean that such services are considered “visits” for purposes of eligibility or payment. In accordance with section 1895(e)(1)(A) and (B) of the Act, such data will not be used or factored into case-mix weights, or count towards outlier payments or the LUPA threshold per payment period.

III. Home Health Quality Reporting Program (HH QRP)

A. Background and Statutory Authority

The HH QRP is authorized by section 1895(b)(3)(B)(v) of the Act. Section 1895(b)(3)(B)(v)(II) of the Act requires that, for 2007 and subsequent years, each home health agency (HHA) submit to the Secretary in a form and manner, and at a time, specified by the Secretary, such data that the Secretary determines are appropriate for the measurement of health care quality. To the extent that an HHA does not submit data in accordance with this clause, the Secretary shall reduce the home health market basket percentage increase applicable to the HHA for such year by 2 percentage points. As provided at section 1895(b)(3)(B)(vi) of the Act, depending on the market basket percentage increase applicable for a particular year, as further reduced by the productivity adjustment (except in 2018 and 2020) described in section 1886(b)(3)(B)(xi)(II) of the Act, the reduction of that increase by 2 percentage points for failure to comply with the requirements of the HH QRP may result in the home health market basket percentage increase being less than 0.0 percent for a year, and may result in payment rates under the Home Health PPS for a year being less than payment rates for the preceding year. The HH QRP regulations can be found at 42 CFR 484.245 and 484.250.

B. General Considerations Used for the Selection of Quality Measures for the HH QRP

For a detailed discussion of the considerations we historically use for measure selection for the HH QRP quality, resource use, and other measures, we refer readers to the CY 2016 HH PPS final rule (80 FR 68695 through 68696). In the CY 2019 HH PPS final rule with comment period (83 FR 56548 through 56550), we finalized the factors we consider for removing previously adopted HH QRP measures.

C. Quality Measures Currently Adopted for the CY 2023 HH QRP

The HH QRP currently includes 20 measures for the CY 2023 program year, as described in Table C1.

D. Proposal To End the Suspension of OASIS Data Collection on Non-Medicare/Medicaid HHA Patients To Require HHAs To Submit All-Payer OASIS Data for Purposes of the HH QRP, Beginning With the CY 2025 Program Year

In 1987, Congress added a new section 1891(d) to the Act (section 4021(b) of Pub. L. 100-203 (December 22, 1987)). The statute required the Secretary to develop a comprehensive assessment for Medicare-participating HHAs. In 1993, CMS (then known as HCFA) developed an assessment instrument that identified each patient's need for home care and that meets the patient's medical, nursing, rehabilitative, social and discharge planning needs. As part of this assessment, Medicare-certified HHAs were required to use a standard core assessment data set, the “Outcome and Assessment Information Set” (“OASIS”). Section 1891(d) of the Act requires, as part of the home health assessment, a survey of the quality of care and services furnished by the agency as measured by indicators of medical, nursing, and rehabilitative care provided by the HHA. OASIS is the designated assessment instrument (or instruments) for use by an HHA in complying with the requirement. In the January 25, 1999, final rule titled, “Medicare and Medicaid Programs: Comprehensive Assessment and Use of the OASIS as Part of the Conditions of Participation for Home Health Agencies,” we also required HHAs to submit the data collected by the OASIS assessment to HCFA as an HHA condition of participation (64 FR 3772).

Early on, privacy concerns were raised by HHAs around the collection of all-payer data and the release of personal health information. As we indicated in the study, any new collection requirements such as this raise concerns and this was no exception. In response to the privacy concerns, CMS took steps to mask the personal health information before the data was transmitted to the Quality Improvement and Evaluation System (QIES). In the study, we collected information from HHAs and the industry including the surveying of Agencies by one of the trade organizations and note that the privacy concerns initially raised were not raised as an ongoing concern. Based upon this feedback, we conclude that the privacy issues raised initially are no longer a concern.

Subsequently, Congress enacted section 704 of the Medicare Prescription Drug, Improvement, and Modernization Act of 2003 (MMA), which suspended the legal authority of the Secretary to require HHAs to report OASIS information on non-Medicare/non-Medicaid patients until at least 2 months after the Secretary published final regulations on CMS's collection and use of those data following the submission of a report to Congress on the study required under section 704(c) of the MMA. This study required the Secretary to examine the use of non-Medicare/non-Medicaid OASIS data by large HHAs, including whether there were unique benefits from the analysis of that information that CMS could not obtain from other sources, and the value of collecting such data by small HHAs versus the administrative burden of collection. In conducting the study, the Secretary was also required to obtain recommendations from quality assessment experts on the use of such information and the necessity of HHAs collecting such information.^[20]

The Secretary conducted the study required under section 704 of the MMA in 2004 to 2005 and submitted it to Congress in December 2006 ( https://www.cms.gov/​files/​document/​cms-oasis-study-all-payer-data-submission-2006.pdf ). The study made the following key findings:

• There are significant differences between private pay and Medicare/Medicaid patients in terms of diagnosis, patient characteristics, and patient outcomes. Within-agency correlation between Medicare/Medicaid and private pay patient outcomes was low, indicating that outcomes based on Medicare/Medicaid patient data cannot be generalized to serve as a proxy for private pay patients.
• Risk adjustment models at the time did not account for all of the sources of variation in outcomes across different payer groups and as a result, measures could produce misleading information.
• Requiring OASIS data collection on private pay patients at Medicare-certified HHAs could increase staff and patient burden and would require CMS to develop a mechanism for these agencies to receive reports from CMS on their private pay patients.
• A change to all-payer assessment data collection would strengthen CMS's ability to assess and report indicators of the quality of care furnished by HHAs to their entire patient population.

After considering the study's findings, the Secretary noted that the suspension of OASIS collection from non-Medicare patients would continue because “it would be unfair to burden the providers with the collection of OASIS at this time since the case mix and outcomes reports are not designed to include private pay patients.” The Secretary also noted that it would be inappropriate for CMS to collect the private pay OASIS data and not use it. The Secretary further stated that “if funding for the development of HHA patient outcome and case mix reports for private pay patients is identified as a priority function, CMS would not hesitate to call for the removal of the suspension of OASIS for private pay patients.”

In the November 9, 2006, final rule, “Medicare Program; Home Health Prospective Payment System Rate Update for Calendar Year 2007 and Deficit Reduction Act of 2005 Changes to Medicare Payment for Oxygen Equipment and Capped Rental Durable Medical Equipment”, we finalized our policy that the agency would continue to suspend collection of OASIS all payer data (71 FR 65883 and 65889).

Since 2006, CMS has laid the groundwork for the resumption of all-payer data submission because we want to represent overall care being provided to all patients in an HHA. CMS implemented the QIES and iQIES provider data reporting systems to securely transfer and manage assessment data across QRPs, including HH. These systems can now support an extensive range of provider reports, including case-mix reports for private pay patients. The HH QRP program expanded quality domains to include patient reported outcome measures and new assessment and claims-based quality measures. We sought and received public comment on several occasions regarding data reporting on all HHA patients, regardless of payer type. In February 2012, the NQF-convened MAP also issued a report that encouraged establishing a data collection and transmission infrastructure for all payers that would work across PAC settings.^[21] In the July 28, 2017, and November 7, 2017, “Home Health Prospective Payment System Rate Update and CY 2018 Case-Mix Adjustment Methodology Refinements; Home Health Value-Based Purchasing Model; and Home Health Quality Reporting Requirements” proposed and final rules (at 82 FR 35372 through 35373 and 82 FR 51736 through 51737, respectively) and in the July 18, 2019, and November 8, 2019, “Medicare and Medicaid Programs; CY 2020 Home Health Prospective Payment System Rate Update” proposed and final rules (at 84 FR 34686 and 84 FR 60478, respectively), we sought and responded to input on whether we should require quality data reporting on all HHA patients, regardless of payer source, to ensure representation of the quality of the services provided to the entire HHA population. In the “CY 2018 Home Health Prospective Payment System Rate Update and CY 2019 Case-Mix Adjustment Methodology Refinements; Home Health Value-Based Purchasing Model; and Home Health Quality Reporting Requirements” final rule, some commenters shared that there would be increased burden from requiring all-payer data submissions (82 FR 51676). A few commenters also raised the issue of whether it would be appropriate to collect and report private pay data, given that private payors may have different care pathways, approval, and authorization processes. In the CY 2020 HH PPS proposed rule, we also sought input on whether collection of quality data used in the HH QRP should include all HHA patients, regardless of their payer source (84 FR 60478). Several commenters supported expanding the HH QRP to include collection of data on all patients regardless of payer. Several commenters noted that this expanded data collection would not be overly burdensome because the majority of HHAs already complete the OASIS on all patients, regardless of payer status. Commenters were concerned that the usefulness of all-payer data collection to CMS's health policy development would not outweigh the additional reporting burden. Several commenters supporting all-payer data collection stated that expansion of the data collection would align the HH QRP's data collection policy with that of Hospices and Long-Term Care Hospitals (LTCHs), as well as the data collection policy under the Merit-based Incentive Payment System. Other reasons cited by commenters who supported the expanded data collection included more accurate representation of the quality of care furnished by HHAs to the entire HH population, the ability of such data to better guide quality improvement activities, and the reduction of current administrative efforts made by HHAs to ensure that only OASIS data for Medicare and Medicaid patients are reported to CMS.

We believe that collecting OASIS data on all HHA patients, regardless of payer, would align our data collection requirements under the HH QRP with the data collection requirements for the LTCH QRP and Hospice QRP. We also believe that the most accurate representation of the quality of care furnished by HHAs is best captured by calculating the assessment-based measures rates using OASIS data submitted on all HHA patients, regardless of payer. New risk adjustment models with all-payer data would better represent the full spectrum of patients receiving skilled care in HHAs. The submission of all-payer OASIS data would also enable us to meaningfully compare performance on quality measures across PAC settings. For example, Changes in Skin Integrity Post-Acute Care is currently reported by different PAC payers on different denominators of payer populations, which greatly inhibits our ability to compare performance on this measure across PAC settings. Standardizing the denominator for cross setting PAC measures to include all patients will enable us to make these comparisons, which we believe will realize our goal of establishing consistent measures of quality across PAC settings.

The concerns raised surrounding privacy outlined above have been mitigated. We take the privacy and security of individually identifiable health information of all patients very seriously. CMS data systems conform to all applicable Federal laws, regulations and standards on information security and data privacy. The systems limit data access to authorized users and monitor such users to help protect against unauthorized data access or disclosures. CMS anticipates updating the current provider data reporting system in iQIES to address the addition of private payer patients.

For these reasons, we are proposing to end the suspension of non-Medicare/Medicaid OASIS data collection and to require HHAs to submit all-payer OASIS data for purposes of the HH QRP beginning with the CY 2025 HH QRP program year. We would use the OASIS data to calculate all measures for which OASIS is a data source. Although the 2006 report recommended that the suspension continue, the subsequent passage of the IMPACT Act (Pub. L. 113-185) in 2014, requiring us to create a uniform quality measurement system which would allow us to compare outcomes across post-acute care providers, requires us to revisit the policy. We have indeed established such a uniform quality measurement system, based on standardized patient assessment data leading us to propose OASIS data collection on Non-Medicare/Non-Medicaid patients. There are now cross-setting quality measures in place that should have consistent reporting parameters but currently do not have consistent reporting parameters because they currently have only Medicare and Medicaid populations. The goal of CMS is to have these measures reported for all patients for all payer sources. The iQIES system utilized by providers is robust enough to make feasible the generation of outcome and case mix reports for private pay patients whereas the 2006 QIES system lacked this functionality. The HH QRP program also has a more robust measure set, including patient reported outcomes, a criteria of importance for CMS to move forward with all-payer collection. We believe that the maturation of the HH QRP as described previously argues for the collection of OASIS all-payer data. It will improve the HH QRP program's ability to assess HHA quality and allow the HH QRP to foster better quality care for patients regardless of payer source. It will also support CMS's ability to compare standardized outcome measures across PAC settings.

Consistent with the two-quarter phase-in that we typically use when adopting new reporting requirements for the HHAs, we are proposing that for the CY 2025 HH QRP, the expanded reporting would be required for patients discharged between January 1, 2024, and June 30, 2024. Beginning with the CY 2026 HH QRP, HHAs would be required to report assessment based quality measure data and standardized patient assessment data on all patients, regardless of payer, for the applicable 12 month performance period (which for the CY 2026 program, would be patients discharged between July 1, 2024, and June 30, 2025).

While we appreciate that submitting OASIS data on all HHA patients regardless of payer source may create additional burden for HHAs, we also note that the current practice of separating and submitting OASIS data on only Medicare beneficiaries has clinical and workflow implications with an associated burden. As noted previously, we also understand that it is common practice for HHAs to collect OASIS data on all patients, regardless of payer source. Requiring HHAs to report OASIS data on all patients will provide CMS with the most robust, accurate reflection of the quality of care delivered to Medicare beneficiaries as compared with non-Medicare patients.

E. Proposed Technical Changes

We are proposing to amend the regulation text in § 484.245(b)(1) as a technical change to consolidate the statutory references to data submission to § 484.245(b)(1)(i) and § 484.245(b)(1)(ii). We are also proposing to modify § 484.245(b)(1)(iii) to describe additional requirements specific to HHCAHPS to make it clear that A through E only apply to HHCAHPS.

In this technical change we specifically propose moving quality data required under section 1895(b)(3)(B)(v)(II) from § 484.245(b)(1)(iii) to § 484.245(b)(1)(i).^[22] Specifically, the proposed § 484.245(b)(1)(i) would state, “Data on measures specified under sections 1895(b)(3)(B)(v)(II), 1899B(c)(1), and 1899B(d)(1) of the Act.” The proposed § 484.245(b)(1)(iii) would state, “For the purposes of this HHCAHPS survey data submission, the following additional requirements apply:”.

We invite public comments on this proposal.

F. Proposed Codification of the HH QRP Measure Removal Factors

In the CY 2019 HH PPS final rule with comment period (83 FR 56548 through 56550), we adopted eight measure removal factors that we consider when determining whether to remove measures from the HH QRP measure set:

• Factor 1. Measure performance among HHAs is so high and unvarying that meaningful distinctions in improvements in performance can no longer be made.
• Factor 2. Performance or improvement on a measure does not result in better patient outcomes.
• Factor 3. A measure does not align with current clinical guidelines or practice.
• Factor 4. A more broadly applicable measure (across settings, populations, or conditions) for the particular topic is available.
• Factor 5. A measure that is more proximal in time to desired patient outcomes for the particular topic is available.
• Factor 6. A measure that is more strongly associated with desired patient outcomes for the particular topic is available.
• Factor 7. Collection or public reporting of a measure leads to negative unintended consequences other than patient harm.
• Factor 8. The costs associated with a measure outweigh the benefit of its continued use in the program. To align the HH QRP with similar quality reporting programs (that is SNF QRP, IRF QRP, and LTCH QRP) we are proposing to amend 42 CFR 484.245 to add eight HH QRP measure removal factors in a new paragraph (b)(3). We welcome comments on this proposal.

G. Request for Information: Health Equity in the HH QRP

CMS defines health equity as the attainment of the highest level of health for all people, where everyone has a fair and just opportunity to attain their optimal health regardless of race, ethnicity, disability, sexual orientation, gender identity, socioeconomic status, geography, preferred language, or other factors that affect access to care and health outcomes.^[23] CMS is working to advance health equity by designing, implementing, and operationalizing policies and programs that support health for all the people served by our programs, eliminating avoidable differences in health outcomes experienced by people who are underserved, and providing the care and support that our enrollees need to thrive.^[24] CMS' goals are in line with Executive Order 13985, on the advancement of racial equity and support for the underserved communities, which can be found at 86 FR 7009 (January 25, 2021) ( https://www.whitehouse.gov/​briefing-room/​presidential-actions/​2021/​06/​25/​executive-order-on-diversity-equity-inclusion-and-accessibility-in-the-federal-workforce/​ ).

Belonging to an underserved community is often associated with worse health outcomes.^{25 26 27 28 29[ 30 31 32 33]} Such disparities in health outcomes are the result of multiple factors. Although not the sole determinants, poor access to care and provision of lower quality health care are important contributors to health disparities notable for CMS programs. Prior research has shown that home health agencies serving higher proportions of Black and low-income older adults furnish lower quality care than those with lower proportions of such patients.^[34] It is unclear why this relationship exists, but some evidence suggests that these outcomes are the result of reduced access to home health agencies with the highest scores for quality and health outcomes measures reported (subsequently referred to as high-quality HHAs).^[35] Research in long term care access has shown that neighborhoods with larger proportions of Black, Hispanic, and low-income residents have lower access to a range of high-quality care including hospitals, primary care physicians, nursing homes, and community-based long-term services.^{[36 37 38]} A recent study found that Black and Hispanic home health patients were less likely to use high quality home health agencies than White patients who lived in the same neighborhoods.^[39] This difference in use of high quality HHAs persisted even after adjusting for patient health status, suggesting disparity in access to higher-quality home health agency was present. Disparities exist within neighborhoods, where Black, Hispanic, and lower-income home health patients that live in a neighborhood with higher-quality home health agencies still have less access to these HHAs.^[40] Disparities also persist across neighborhoods where the researchers found that 40-77 percent of disparities in high-quality agency use was attributable to neighborhood-level factors.^[41] The issue of disparity in access is especially critical to address currently with the COVID-19 public health emergency (PHE). The PHE has increased demand for home health services instead of nursing home care for many patients seeking post-acute care.^[42] Factors outside of neighborhood effects that could affect inequities in home health care and access to care may include a provider's selection of patients with higher socioeconomic status (SES) who are perceived to have a lower likelihood of reducing provider quality ratings ^[43] or a provider's biased perception of a patient's risk behavior and adherence to care plans.^[44] These findings suggest the need to address issues related to care and access when striving to improve health equity.

We are committed to achieving equity in health care outcomes for beneficiaries by supporting providers in quality improvement activities to reduce health disparities, enabling beneficiaries to make more informed decisions, and promoting provider accountability for health care disparities.^[45 46] CMS is committed to closing the equity gap in CMS quality programs.

We thank commenters for previous input to our request for information on closing the health equity gap in home health care in the CY 2022 HH PPS final rule (86 FR 62240). Many commenters shared that relevant data collection and appropriate stratification are very important in addressing any health equity gaps. These commenters noted that CMS should consider potential stratification of health outcomes. Stakeholders, including providers, also shared their strategies for addressing health disparities, noting that this was an important commitment for many health provider organizations. Commenters also shared recommendations for additional social determinants of health (SDOH) data elements that could strengthen their assessment of disparities and issues of health equity. SDOH 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.^[47] Many commenters suggested capturing information related to food insecurity, income, education, transportation, and housing. We will continue to take all comments and suggestions into account as we work to develop policies on this important topic. We appreciate home health agencies and other stakeholders sharing their support and commitment to addressing health disparities and offering meaningful comments for consideration. As we continue to consider health equity within the HH QRP, we are soliciting public comment on the following questions:

• What efforts does your HHA employ to recruit staff, volunteers, and board members from diverse populations to represent and serve underserved populations? How does your HHA attempt to bridge any cultural gaps between your personnel and beneficiaries/clients? How does your HHA measure whether this has an impact on health equity?
• How does your HHA currently identify barriers to access to care in your community or service area?
• What are the barriers to collecting data related to disparities, SDOH, and equity? What steps does your HHA take to address these barriers?
• How does your HHA collect self-reported demographic information such as information on race and ethnicity, disability, sexual orientation, gender identity, veteran status, socioeconomic status, and language preference?
• How is your HHA using collected information such as housing, food security, access to interpreter services, caregiving status, and marital status to inform its health equity initiatives?

In addition, we are considering the adoption of a structural composite measure for the HH QRP, which could include organizational activities to address access to and quality of home health care for underserved populations. The composite structural measure concept could include HHA reported data on HHA activities to address underserved populations' access to home health care. An HHA could receive a point (for a total of three points for the three domains) for each domain where data are submitted to a CMS portal, regardless of the action in that domain.

HHAs could submit information such as documentation, examples, or narratives to qualify for the measure numerator. The domains under consideration for the measure, as well as how an HHA could satisfy each of those domains and earn a point for that domain, are the following:

Domain 1: HHAs' commitment to reducing disparities is strengthened when equity is a key organizational priority. Candidate domain 1 could be satisfied if an HHA submits data on actions it is taking with respect to health equity and community engagement in their strategic plan. HHAs could report data in the reporting year about their actions in each of the following areas, and submission of data for all elements could be required to qualify for the measure numerator.

• HHAs attest to whether their strategic plan includes approaches to address health equity in the reporting year.
• HHAs report community engagement and key stakeholder activities in the reporting year.
• HHAs report on any attempts to measure input they solicit from patients and caregivers about care disparities they may experience as well as recommendations or suggestions for improvement.

Domain 2: Training HHA board members, HHA leaders, and other HHA staff in culturally and linguistically appropriate services (CLAS),^[48] health equity, and implicit bias is an important step the HHA can take to provide quality care to diverse populations. Candidate domain 2 could focus on HHAs' diversity, equity, inclusion training for board members and staff by capturing the following reported actions in the reporting year. Submission of relevant data for all elements could be required to qualify for the measure numerator.

• HHAs attest as to whether their employed staff were trained in culturally sensitive care mindful of (SDOH in the reporting year and report data relevant to this training, such as documentation of specific training programs or training requirements.

• HHAs attest as to whether they provided resources to staff about health equity, SDOH, and equity initiatives in the reporting year and report data such as the materials provided or other documentation of the learning opportunities.

Domain 3: HHA leaders and staff can improve their capacity to address health disparities by demonstrating routine and thorough attention to equity and setting an organizational culture of equity. This candidate domain could capture activities related to organizational inclusion initiatives and capacity to promote health equity. Examples of equity-focused factors include proficiency in languages other than English, experience working with diverse populations in the service area, and experience working with individuals with disabilities. Submission of relevant data for all elements could be required to qualify for the measure numerator.

• HHAs attest as to whether they considered equity-focused factors in the hiring of HHA senior leadership, including chief executives and board of trustees, in the applicable reporting year.
• HHAs attest as to whether equity-focused factors were included in the hiring of direct patient care staff (for example, therapists, nurses, social workers, physicians, or aides) in the applicable reporting year.
• HHAs attest as to whether equity focused factors were included in the hiring of indirect care or support staff (for example, administrative, clerical, or human resources) in the applicable reporting year.

We are interested in developing health equity measures based on information collected by HHAs not currently available on claims, assessments, or other publicly available data sources to support development of future quality measures. We are soliciting public comment on the conceptual domains and quality measures described in this section. Furthermore, we are soliciting public comments on publicly reporting a composite structural health equity quality measure; displaying descriptive information on Care Compare from the data HHAs provide to support health equity measures; and the impact of the domains and quality measure concepts on organizational culture change.

G. 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 industry stakeholders to develop Health Level Seven International® (HL7) Fast Healthcare Interoperability Resources® (FHIR) standards.^[49] These standards could support the exchange and reuse of patient assessment data derived from the Minimum Data Set (MDS), Inpatient Rehabilitation Facility-Patient Assessment Instrument (IRF-PAI), LTCH Continuity Assessment Record and Evaluation (CARE) Data Set (LCDS), Outcome and Assessment Information Set (OASIS), and other sources. 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. 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). The DEL furthers CMS' goal of data standardization and interoperability. Standards in the DEL ( https://www.del.cms.gov/​DELWeb/​pubHome) can be referenced on the CMS website and in the ONC Interoperability Standards Advisory (ISA). The 2022 ISA is available at https://www.healthit.gov/​isa .

The 21st Century Cures Act (Cures Act) (Pub. L. 114-255, enacted December 13, 2016) required HHS and ONC to take steps to further interoperability for providers in settings across the care continuum. 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 a universal floor of interoperability across the country. On January 18, 2022, ONC announced a significant milestone by releasing the Trusted Exchange Framework ^[50] and Common Agreement Version 1.^[51] 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 ^[52] (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 Trusted Exchange Framework and 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.^[53] For more information, we refer readers to https://www.healthit.gov/​topic/​interoperability/​trusted-exchange-framework-and-common-agreement.

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

IV. Expanded Home Health Value-Based Purchasing (HHVBP) Model

A. Background

As authorized by section 1115A of the Act and finalized in the CY 2016 HH PPS final rule (80 FR 68624), the Center for Medicare and Medicaid Innovation (Innovation Center) implemented the Home Health Value-Based Purchasing (HHVBP) Model (“original Model”) in nine states on January 1, 2016. The design of the original HHVBP Model leveraged the successes and lessons learned from other CMS value-based purchasing programs and demonstrations to shift from volume-based payments to a model designed to promote the delivery of higher quality care to Medicare beneficiaries. The specific goals of the original HHVBP Model were to—

• Provide incentives for better quality care with greater efficiency;
• Study new potential quality and efficiency measures for appropriateness in the home health setting; and,
• Enhance the current public reporting process.

The original HHVBP Model resulted in an average 4.6 percent improvement in HHAs' total performance scores (TPS) and an average annual savings of $141 million to Medicare without evidence of adverse risks.^[54] The evaluation of the original model also found reductions in unplanned acute care hospitalizations and skilled nursing facility (SNF) stays, resulting in reductions in inpatient and SNF spending. The U.S. Secretary of Health and Human Services determined that expansion of the original HHVBP Model would further reduce Medicare spending and improve the quality of care. In October 2020, the CMS Chief Actuary certified that expansion of the HHVBP Model would produce Medicare savings if expanded to all states.^[55]

On January 8, 2021, CMS announced the certification of the HHVBP Model for expansion nationwide, as well as the intent to expand the Model through notice and comment rulemaking.^[56]

In the CY 2022 HH PPS final rule (86 FR 62292 through 62336) and codified at 42 CFR part 484, subpart F, we finalized the decision to expand the HHVBP Model to all Medicare certified HHAs in the 50 States, territories, and District of Columbia beginning January 1, 2022. We finalized that the expanded Model will generally use benchmarks, achievement thresholds, and improvement thresholds based on CY 2019 data to assess achievement or improvement of HHA performance on applicable quality measures and that HHAs will compete nationally in their applicable size cohort, smaller-volume HHAs or larger-volume HHAs, as defined by the number of complete unique beneficiary episodes for each HHA in the year prior to the performance year. All HHAs certified to participate in the Medicare program prior to January 1, 2022, will be required to participate and will be eligible to receive an annual Total Performance Score based on their CY 2023 performance.

We finalized the quality measure set for the expanded Model, as well as policies related to the removal, modification, and suspension of applicable measures, and the addition of new measures and the form, manner and timing of the OASIS-based, Home Health Consumer Assessment of Healthcare Providers and Systems (HHCAHPS) survey-based, and claims-based measures submission in the applicable measure set beginning CY 2022 and subsequent years. We also finalized an appeals process, an extraordinary circumstances exception policy, and public reporting of annual performance data under the expanded Model.

Additionally, in the CY 2022 HH PPS proposed rule (86 FR 35929) we solicited comments on the challenges unique to value-based purchasing frameworks in terms of health equity and ways in which we could incorporate health equity goals into the expanded HHVBP Model. We received comments related to the use of stabilization measures to promote access to care for individuals with chronic illness or limited ability to improve; collection of patient level demographic information for existing measures; and stratification of outcome measures by various patient populations to determine how they are affected by social determinants of health (SDOH). In the CY 2022 HHPPS final rule (86 FR 62312) we summarized and responded to these comments received.

In this proposed rule, we are proposing to replace the term baseline year with the terms HHA baseline year and Model baseline year and to change the calendar years associated with each of those baseline years, and soliciting comment on future approaches to health equity in the expanded HHVBP Model.

B. Proposed Changes to the Baseline Years and New Definitions

1. Definitions

a. Background

Benchmarks, achievement thresholds, and improvement thresholds are used to assess achievement or improvement of HHA performance on applicable quality measures. As codified at § 484.345, baseline year means the year against which measure performance in a performance year will be compared. As discussed in the CY 2022 HH PPS final rule (86 FR 62300), we finalized our proposal to use CY 2019 (January 1, 2019, through December 31, 2019) as the baseline year for the expanded HHVBP Model. In that rule, we also codified at § 484.350(b), that for a new HHA that is certified by Medicare on or after January 1, 2019, the baseline year is the first full calendar year of services beginning after the date of Medicare certification, with the exception of HHAs certified on January 1, 2019, through December 31, 2019, for which the baseline year is calendar year (CY) 2021, and the first performance year is the first full calendar year (beginning with CY 2023) following the baseline year.

b. Proposals To Amend Definitions

Since that final rule, it has come to our attention that there could be some confusion and we would like to explain our terminology more clearly by proposing to differentiate between two types of baseline years used in the expanded HHVBP Model. The Model baseline year is used to determine the benchmark and achievement threshold for each measure for all HHAs. For example, as finalized, CY 2019 data is used in the calculation of the achievement thresholds and benchmarks for all applicable measures for both the small cohort and for the large cohort. The HHA baseline year is used to determine the HHA improvement threshold for each measure for each individual competing HHA. For example, if an HHA is certified in CY 2021, CY 2022 data would be used in the calculation of the improvement thresholds for all applicable measures for that HHA.

Therefore, we are proposing to amend § 484.345 to remove the existing baseline year definition: means the year against which measure performance in a performance year will be compared. In its place, we are proposing to define: (1) HHA baseline year as the calendar year used to determine the improvement threshold for each measure for each individual competing HHA, and (2) Model baseline year as the calendar year used to determine the benchmark and achievement threshold for each measure for all competing HHAs. In line with these proposed definitions, we are proposing to make conforming revisions toto the definitions of achievement threshold and benchmark to indicate that they are calculated using the Model baseline year, and the definition of improvement threshold to indicate that it is calculated using the HHA baseline year. Additionally, we are proposing to amend paragraph (a) of § 484.370 to remove the phrase “for the baseline year” because the calculation of the TPS using the applicable benchmarks and achievement thresholds (determined usingusing the Model baseline year) and improvement thresholds (determined using the HHA baseline year) is described at § 484.360.

We invite public comments on these proposals.

2. Proposed Change of HHA Baseline Years

a. Background—New and Existing HHAs Baseline Years

As previously discussed, in the CY 2022 HH PPS final rule (86 FR 62300), we finalized our proposal to use CY 2019 as the baseline year for the expanded HHVBP Model. Our intent was that the Model baseline year used to determine achievement thresholds and benchmarks is CY 2019 for all HHAs and the HHA baseline year used to determine an individual HHA's improvement threshold is 2019 for HHAs certified prior to January 1, 2019. As discussed in the section IV.B.1.b. of this rule, we are proposing to replace the term baseline year with the terms Model baseline year and HHA baseline year to differentiate between two types of baseline years used in the expanded HHVBP Model.

As mentioned earlier, in that same rule (86 FR 62423), we codified at § 484.350(b), that for a new HHA that is certified by Medicare on or after January 1, 2019, the baseline year is the first full calendar year of services beginning after the date of Medicare certification, with the exception of HHAs certified on January 1, 2019, through December 31, 2019, for which the baseline year is calendar year (CY) 2021, and the first performance year is the first full calendar year (beginning with CY 2023) following the baseline year. Table D1 depicts what was finalized in the CY 2022 HH PPS final rule.

b. Proposals To Change the HHA Baseline Year for New and Existing HHAs

As discussed in the CY 2022 final rule, we stated that we may conduct analyses of the impact of using various baseline periods and consider any changes for future rulemaking (86 FR 62300). Due to the continuing effects of the COVID-19 public health emergency (PHE), we conducted a measure-by-measure comparison of performance for CY 2019 to CY 2021 for the expanded HHVBP Model's measure set relative to the historical trends of those measures. We found that, while performance scores on the five applicable HHCAHPS measures and the OASIS-based “Discharged to Community” remained stable from CY 2019 to CY 2021, there was a general trend upwards following historical trends for four of the five applicable OASIS-based measures. These trends were consistent with the historical national data that CMS used to monitor the original HHVBP Model beginning 2015.

In contrast, Figures D1 and D2 that were derived from the archived HH quality data from CMS.data.gov  ^[57] illustrate the trend of average national performance on the Acute Care Hospitalization During the First 60 Days of Home Health Use measure and the Emergency Department Use without Hospitalization During the First 60 Days of Home Health measure deviated significantly, with a drop of 9 percent and 15 percent in CY 2020, respectively, relative to CY 2019 (Table D2) and remained lower in CY 2021 as compared to historic trends that occurred prior to the pandemic. In the five years prior to 2020, both measures demonstrated stable trends, varying +/−5 percent from year to year, which highlights the significance of the change from CY 2019 to CY 2020 compared to CY 2015 to CY 2019.

We note that for HHAs with sufficient data on each of the 12 applicable measures, performance on the two claims-based measures (Acute Care Hospitalization During the First 60 Days of Home Health Use and Emergency Department Use without Hospitalization During the First 60 Days of Home Health) makes up 35 percent of the total performance score used to determine payment adjustments under the Model. While average national performance on these measures in CY 2021 was similar to average national performance in CY 2020, CY 2022 is the first year where the vast majority of beneficiaries are vaccinated; as of January 27, 2022, 95 percent of Americans ages 65 years or older had received at least one dose of vaccine and 88.3 percent were fully vaccinated.^[58] In addition, there were viable treatments available and healthcare providers had nearly 2 years of experience managing COVID-19 patients. We believe that more recent data from the CY 2022 time period is more likely to be aligned with performance years' data under the expanded Model, and provide a more appropriate baseline for assessing HHA improvement for all measures under the Model as compared to both the pre-PHE CY 2019 data, as previously finalized for existing HHAs, and the CY 2021 data, as previously finalized for new HHAs certified between January 1, 2019 and December 31, 2020. Use of CY 2022 data for the HHA baseline year for all measures under the expanded Model would also allow all HHAs certified by Medicare prior to CY 2022 to have the same baseline period, based on the most recent available data, beginning with the CY 2023 performance year. Accordingly, we are proposing to change the HHA baseline year for HHAs certified prior to January 1, 2019, and for HHAs certified during January 1, 2019-December 31, 2021 for all applicable measures used in the expanded Model, from CY 2019 and 2021 respectively, to CY 2022 beginning with the CY 2023 performance year. Additionally, we are also proposing that for any new HHA certified on or after January 1, 2022, the HHA baseline year is the first full calendar year of services beginning after the date of Medicare certification and the first performance year is the first full calendar year following the HHA baseline year.

As discussed in the CY 2022 HH PPS final rule, we understand that HHAs want to have time to examine their baseline data as soon as possible, and we stated that we anticipated making available baseline reports using the CY 2019 baseline year data in advance of the first performance year under the expanded Model (CY 2023). If we were to finalize this proposal to instead use CY 2022 data for the HHA baseline year, we would intend to continue to make these baseline data available as soon as administratively possible, and would anticipate providing HHAs with their final individual improvement thresholds in the summer of CY 2023. We note that this would be consistent with the original HHVBP Model, for which improvement thresholds using CY 2015 data were made available HHAs in the first interim performance report (IPR) in the summer of the first performance year (CY 2016).

This proposal is made in conjunction with our proposal to add the definition of the term HHA baseline year discussed previously. We believe that this proposal would allow all eligible HHAs, starting with the CY 2023 performance year, to compete on a level playing field with all HHA baseline data being after the peak of the pandemic. Accordingly, we are proposing to amend § 484.350(b) to reflect that for a new HHA, specifically an HHA that is certified by Medicare on or after January 1, 2022, the HHA baseline year is the first full calendar year of services beginning after the date of Medicare certification, and to add § 484.350(c) to reflect that for an existing HHA, specifically an HHA that is certified by Medicare before January 1, 2022, the HHA baseline year is CY 2022. Table D3 depicts these proposals.

In developing this proposal, we considered changing the HHA baseline year to CY 2021 for all HHAs for all of the applicable measures or, alternatively, not changing the HHA baseline year for any of the applicable measures. We decided against those alternatives for the reasons explained previously in support of our proposal to change the HHA baseline year to CY 2022. We also considered changing the HHA baseline for only some of the applicable measures. For example, we considered changing the HHA baseline to CY 2022 only for the claims-based measures and using the HHA baseline of CY 2019 or CY 2021 (see Table D1) for applicable HHAs for the OASIS-based and HHCAHPS-based measures. However, for the reasons previously discussed, we are instead proposing to change the HHA baseline year to CY 2022 for all applicable measures used in the expanded HHVBP Model, which would allow all HHAs certified by Medicare prior to CY 2022 to have the same baseline period for all measures, using the most recent available data, for the performance year beginning CY 2023.

We invite public comments on these proposals.

3. Proposal to Change the Model Baseline Year

As mentioned earlier, under the policy finalized in the CY 2022 HH PPS final rule (86 FR 62300), we previously adopted CY 2019 as the Model baseline year for the expanded HHVBP Model for all HHAs. This baseline year is used to determine the benchmarks and achievement threshold for each measure for all HHAs.

Consistent with our proposal to update the HHA baseline year to CY 2022 for all HHAs that are certified by Medicare before January 1, 2022, and in conjunction with our proposal to more clearly define the Model baseline year in previous section IV.B.1.b., we are also proposing to change the Model baseline year from CY 2019 to CY 2022 for the CY 2023 performance year and subsequent years. This would enable us to measure competing HHAs' performance using benchmarks and achievement thresholds that are based on the most recent data available. This would also allow the benchmarks and achievement thresholds to be set using data from after the most acute phase of the COVID-19 PHE, which we believe would provide a more appropriate basis for assessing performance under the expanded Model than the CY 2019 pre-PHE period. As previously discussed, CY 2022 is the first year where the vast majority of beneficiaries are vaccinated, there are viable treatments available and healthcare providers had nearly two years of experience managing COVID-19 patients. We anticipate that this more recent data from the CY 2022 time period would more likely be aligned with performance years' data under the expanded Model. As discussed in connection with our proposal to use CY 2022 data for the HHA baseline year, if we were to finalize this proposal to use CY 2022 rather than CY 2019 data for the Model baseline year, we would anticipate providing HHAs with the final achievement thresholds and benchmarks in the July 2023 IPR in the summer of CY 2023. This would be consistent with the rollout of the original HHVBP Model in which benchmarks and achievement thresholds using 2015 data were made available to HHAs during the summer of the first performance year (CY 2016).

We invite public comments on this proposal.

C. Request for Comment on a Future Approach to Health Equity in the Expanded HHVBP Model

Significant and persistent inequities in healthcare outcomes exist in the United States. Belonging to a racial or ethnic minority group; living with a disability; being a member of the lesbian, gay, bisexual, transgender, and queer (LGBTQ+) community; living in a rural area; being a member of a religious minority; or being near or below the poverty level, is often associated with worse health

outcomes.^{[59 60 61 62 63 64 65 66 67]} In line with Executive Order 13985 of January 20, 2021, “Advancing Racial Equity and Support for Underserved Communities Through the Federal Government”,^[68] CMS defines health equity as the attainment of the highest level of health for all people, where everyone has a fair and just opportunity to attain their optimal health regardless of race, ethnicity, disability, sexual orientation, gender identity, socioeconomic status, geography, preferred language, or other factors that affect access to care and health outcomes.^[69] 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, 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. Over the past decade we have established a suite of programs and policies aimed at reducing health care disparities including the CMS Mapping Medicare Disparities Tool,^[70] the CMS Innovation Center's Accountable Health Communities Model,^[71] the CMS Disparity Methods stratified reporting program,^[72] and efforts to expand social risk factor data collection, such as the collection of Standardized Patient Assessment Data Elements in the post-acute care setting,^[73] and the CMS Framework for Health Equity 2022-2023.^[74]

As we continue to leverage our value-based purchasing initiatives to improve the quality of care furnished across healthcare settings, we are interested in exploring the role of health equity in creating better health outcomes for all populations in our programs and models. As the March 2020 Assistant Secretary for Planning and Evaluation (ASPE) Report to Congress on Social Risk Factors and Performance in Medicare's Value-Based Purchasing Program notes, it is important to implement strategies that cut across all programs and health care settings to create aligned incentives that drive providers to improve health outcomes for all beneficiaries.^[75] We are interested in stakeholder feedback on specific actions the expanded HHVBP Model can take to address healthcare disparities and advance health equity.

As we continue to develop policies for the expanded HHVBP Model, we are requesting public comments on policy changes that we should consider on the topic of health equity. We specifically request comments on whether we should consider incorporating adjustments into the expanded HHVBP Model to reflect the varied patient populations that HHAs serve around the country and tie health equity outcomes to the payment adjustments we make based on HHA performance under the Model. These adjustments could be made at the measure level in forms such as stratification (for example, based on dual status or other metrics), or we could propose to adopt new measures of social determinants of health (SDOH). These adjustments could also be incorporated at the scoring level in forms such as modified benchmarks, points adjustments, or modified payment adjustment percentages (for example, peer comparison groups based on whether the HHA includes a high proportion of dual eligible beneficiaries or other metrics). We request commenters' views on which of these adjustments, if any, would be most effective for the expanded HHVBP Model.

V. Home Infusion Therapy Services: Annual Payment Updates for CY 2023

In accordance with section 1834(u)(3) of the Act and 42 CFR 414.1550, our national home infusion therapy (HIT) services payment rates for the initial and subsequent visits in each of the home infusion therapy payment categories for CY 2023 are required to be the CY 2022 rate adjusted by the percentage increase in the Consumer Price Index (CPI) for all urban consumers (United States city average) for the 12 month period ending with June of the preceding year reduced by a productivity adjustment described in section 1886(b)(3)(B)(xi)(II) of the Act as the 10-year moving average of changes in annual economy-wide private nonfarm business multifactor productivity. Section 1834(u)(3) of the Act further states that the application of the productivity adjustment may result in a percentage being less than 0.0 for a given year, and may result in payment being less than such payment rates for the preceding year. We note that § 414.1550(d) does not permit any exercise of discretion by the Secretary. The single payment amounts are also adjusted for geographic area wage differences using the geographic adjustment factor (GAF). We remind stakeholders that the GAFs are a weighted composite of each Physician Fee Schedule (PFS) localities work, practice expense (PE) and malpractice (MP) expense geographic practice cost indices (GPCIs). The periodic review and adjustment of the GPCIs is mandated by section 1848(e)(1)(C) of the Act. At each update, the proposed GPCIs are published in the PFS proposed rule to provide an opportunity for public comment and further revisions in response to comments prior to implementation. The GPCIs and the GAFs are updated triennially with a 2 year phase in and were last updated in the CY 2020 PFS final rule

(84 FR 62568). The next full update to the GPCIs and the GAFs will be proposed in the CY 2023 PFS proposed rule. The CY 2023 PFS proposed rule and the CY 2023 proposed GAFs will be available on the PFS website at https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​PhysicianFeeSched after publication in the Federal Register .

The updated GAFs, national home infusion therapy payment rates, and locality-adjusted home infusion therapy payment rates will be posted on CMS' Home Infusion Therapy Services web page ^[76] once these rates are finalized. In the future, we will no longer include a section in the HH PPS rule on home infusion therapy if no changes are being proposed to the payment methodology. Instead, the rates will be updated each year in a Change Request and posted on the website. For more in-depth information regarding the finalized policies associated with the scope of the home infusion therapy services benefit and conditions for payment, we refer readers to the CY 2020 HH PPS final rule with comment period (84 FR 60544).

VI. Collection of Information Requirements

A. Statutory Requirement for Solicitation of Comments

Under the Paperwork Reduction Act of 1995, we are required to provide a 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.

In this proposed rule, we are soliciting public comment on each of these issues for the following sections of this document that contain information collection requirements (ICRs).

B. Collection of Information Requirement

1. ICRs for HH QRP

In section III. of this proposed rule, we are proposing to end the suspension of the collection of OASIS data on non-Medicare and non-Medicaid patients and to require HHAs to submit all-payer OASIS data for purposes of the HH QRP, beginning with the CY 2025 program year. We believe that the burden associated with this proposal is the time and effort associated with the submission of non-Medicare and non-Medicaid OASIS data. The submission of OASIS data on HH patients regardless of payor source will ensure that CMS can appropriately assess the quality of care provided to all patients receiving skilled care by all Medicare-certified HHAs that participate in the HH QRP. As of January 1, 2022, there are approximately 11,354 HHAs reporting OASIS data to CMS under the HH QRP.

The OASIS is completed by RNs or PTs, or very occasionally by occupational therapists (OT) or speech language pathologists (SLP/ST). Data from 2020 show that the SOC/ROC OASIS is completed by RNs (approximately 76.50 percent of the time), PTs (approximately 20.78 percent of the time), and other therapists, including OTs and SLP/STs (approximately 2.72 percent of the time). Based on this analysis, we estimated a weighted clinician average hourly wage of $79.41, inclusive of fringe benefits, using the hourly wage data in Table F1. Individual providers determine the staffing resources necessary.

For purposes of calculating the costs associated with the information collection requirements, we obtained mean hourly wages for these from the U.S. Bureau of Labor Statistics' May 2020 National Occupational Employment and Wage Estimates ( https://www.bls.gov/​oes/​current/​oes_​nat.htm ). To account for overhead and fringe benefits (100 percent), we have doubled the hourly wage. These amounts are detailed in Table F1.

We estimate that this proposed new requirement would result in HHAs having to increase by 30 percent the number of assessments they complete at each timepoint, with a corresponding 30 percent increase in their estimated hourly burden and estimated clinical cost.^[77] For purposes of estimating burden, we utilize item-level burden estimates for OASIS-E that will be released January 1, 2023.

Table F2 shows the total number of OASIS assessments that HHAs actually completed in CY 2020, as well as how those numbers would have increased if non-Medicare and non-Medicaid OASIS assessments had been required at that time.

Table F3 summarizes the estimated clinician hourly burden for Medicare only, non Medicare, and all-payer patients receiving HH care for each OASIS assessment type using CY 2020 assessment totals.

The calculations we used to estimate the total all-payer hourly burden with CY 2020 assessment totals and OASIS-E data elements at each time point of OASIS data collection are as follows:

Start of Care

Estimated Time Spent per Each OASIS-E SOC Assessment/Patient = 57.3 Clinician Minutes

203 data elements × 0.15−0.3 minutes per data element = 57.3 minutes of clinical time spent to complete data entry for the OASIS-E SOC assessment.

• 21 DE counted as 0.15 minutes/DE (3.15)
• 9 DE counted as 0.25 minutes/DE (2.25)
• 173 DE counted as 0.30 minutes/DE (51.9)

Clinician Estimated Hourly Burden for All HHAs (11,354) for OASIS-E SOC Assessments = 7,937,363 Hours

57.3 clinician minutes per SOC assessment × 8,311,375 assessments = 476,241,787 minutes/60 minutes per hour = 7,937,363 hours for all HHAs

Resumption of Care

Estimated Time Spent per Each OASIS-D ROC Assessment/Patient = 48 Minutes

172 data elements × 0.15−0.3 minutes per data element = 48 minutes of clinical time spent to complete data entry for the OASIS-D ROC assessment

• 21 DE counted as 0.15 minute/DE (3.15)
• 9 DE counted as 0.25 minute/DE (2.25)
• 142 DE counted as 0.30 minute/DE (42.6)

Clinician Estimated Hourly Burden for All HHAs for OASIS-E ROC Assessments = 968,146 Hours

48 clinician minutes per ROC assessment × 1,210,183 ROC assessments = 58,088,784 minutes/60 minutes = 968,146 hours for all HHAs

Follow Up

Estimated Time Spent per Each OASIS-E FU Assessment/Patient = 11.1 Minutes

37 data elements × 0.3 minutes per data element = 11.1 minutes of clinical time spent to complete data entry for the OASIS-D FU assessment.

• 37 DE counted as 0.30 minutes/DE

Clinician Estimate Hourly Burden for All HHAs for OASIS-E FU Assessments = 878,532 Hours

11.1 clinician minutes for OASIS-E FU assessments × 4,748,822 FU assessments = 52,711,924 minutes/60 minutes = 878,532 hours for all HHAs

Transfer of Care

Estimated Time Spent per Each OASIS-E TOC Assessment/Patient = 6.6 Minutes

22 data elements × 0.15−0.3 minutes per data element = 6.6 minutes of clinical time spent to complete data entry for the OASIS-D TOC assessment

• 22 DE counted as 0.30 minutes/DE

Clinician Estimated Hourly Burden for All HHAs for OASIS-E TOC Assessments = 256,946 Hours

6.6 clinician minutes × 2,335,875 TOC assessments = 15,416,775 minutes/60 minutes = 256,946 hours

Death at Home

Estimated Time Spent per Each OASIS-E DAH Assessment/Patient = 2.7 Minutes

9 data elements × 0.15−0.3 minutes per data element = 2.7 minutes of clinical time spent to complete data entry for the OASIS-E DAH assessment.

• 9 DE counted as 0.30 minutes/DE

Clinician Estimated Hourly Burden for All HHAs for OASIS-E DAH Assessments = 2,953 Hours

2.7 clinician minutes × 65,640 DAH assessments = 177,228 minutes/60 minutes = 2,954 hours

Discharge

Estimated Time Spent per Each OASIS-E DC Assessment/Patient = 40.2 Minutes

146 data elements × 0.15−0.3 minutes per data element = 40.2 minutes of clinical time spent to complete data entry for the OASIS-E DC assessment.

• 21 DE counted as 0.15 minutes/DE
• 9 DE counted as 0.25 minutes/DE
• 116 DE counted as 0.30 minutes/DE

Clinician Estimated Hourly Burden for All HHAs for OASIS-E DC Assessments = 4,534,626 Hours

40.2 clinician minutes × 6,768,099 DC assessments = 272,077,580 minutes/60 minutes = 4,534,626 hours

Table F4 summarizes the estimated clinician costs for the completion of the OASIS-E assessment tool for Medicare only, Non-Medicare, and All-Payer patients receiving HH care for each OASIS assessment type using CY2020 assessment and cost data.

Outlined later are the calculation for estimates used to derive total all-payer costs with OASIS E data elements for each OASIS assessment type using CY2020 assessment and cost data:

Start of Care

Estimated Cost for All HHAs for OASIS-E SOC Assessments = $630,305,995.83 for All HHAs

$79.41/hour × 7,937,363 hours for all HHAs = $630,305,995.83 for all HHAs

Resumption of Care

Estimated Cost for All HHAs for OASIS-E ROC Assessments = $76,880,473.86 for All HHAs

$79.41/hour × 968,146 hours = $76,880,473.86 for all HHAs

Follow Up

Estimated Costs for All HHAs for OASIS-E FU Assessments = $82,962,803.4 for All HHAs

$79.41/hour × 878,532hours = $69,764,226 for all HHAs

Transfer of Care

Estimated costs for All HHAs for All OASIS-E TOC Assessments = $20,404,081.86 for All HHAs

$79.41/hour × 256,946 hours = $20,404,081.86 for All HHAs

Death at Home

Estimated Costs for all HHAs for OASIS-E DAH Assessments = $234,497.73 for All HHAs

$79.41 × 2,953 hours = $234,497.73 for all HHAs

Discharge

Estimated costs for All HHAs for OASIS-E DC Assessments = $360,094,650.66 for all HHAs

$79.41/hour × 4,534,626 hours = $360,094,650.66 for all HHAs

Based on the data in Tables F1 to F3 for the 11,354 active Medicare-certified HHAs, we estimate the total increase in costs associated with the changes in the HH QRP to be approximately 23,529.82 per HHA annually or $267,157,680.3 all HHAs. This corresponds to an estimated increase in clinician burden associated with the changes to the HH QRP of approximately 296.3 hours per HHA or approximately 3,364,285 hours for all HHAs. This additional burden would begin with January 1, 2024 HHA discharges. We have also included a request for information (RFI) related to potentially applying health equity to the expanded HHVBP Model in the future. Section 1115A(d)(3) of the Act exempts Innovation Center model tests and expansions, which include the expanded HHVBP Model, from the provisions of the PRA. Specifically, this section provides that the provisions of the PRA do not apply to the testing and evaluation of Innovation Center models or to the expansion of such models.

C. Submission of PRA-Related Comments

We have submitted a copy of this proposed rule to OMB for its review of the rule's information collection requirements. The requirements are not effective until they have been approved by OMB.

We invite public comments on these information collection requirements. If you wish to comment, please identify the rule (CMS-1766-P) and, where applicable, the preamble section, and the ICR section. See this rule's DATES and ADDRESSES sections for the comment due date and for additional instructions.

VII. Regulatory Impact Analysis

A. Statement of Need

1. HH PPS

Section 1895(b)(1) of the Act requires the Secretary to establish a HH PPS for all costs of home health services paid under Medicare. In addition, section 1895(b) of the Act requires: (1) the computation of a standard prospective payment amount include all costs for home health services covered and paid for on a reasonable cost basis and that such amounts be initially based on the most recent audited cost report data available to the Secretary; (2) the prospective payment amount under the HH PPS to be an appropriate unit of service based on the number, type, and duration of visits provided within that unit; and (3) the standardized prospective payment amount be adjusted to account for the effects of case-mix and wage levels among HHAs. Section 1895(b)(3)(B) of the Act addresses the annual update to the standard prospective payment amounts by the home health applicable percentage increase. Section 1895(b)(4) of the Act governs the payment computation. Sections 1895(b)(4)(A)(i) and (b)(4)(A)(ii) of the Act requires the standard prospective payment amount be adjusted for case-mix and geographic differences in wage levels. Section 1895(b)(4)(B) of the Act requires the establishment of appropriate case-mix adjustment factors for significant variation in costs among different units of services. Lastly, section 1895(b)(4)(C) of the Act requires the establishment of wage adjustment factors that reflect the relative level of wages, and wage-related costs applicable to home health services furnished in a geographic area compared to the applicable national average level.

Section 1895(b)(3)(B)(iv) of the Act provides the Secretary with the authority to implement adjustments to the standard prospective payment amount (or amounts) for subsequent years to eliminate the effect of changes in aggregate payments during a previous year or years that were the result of changes in the coding or classification of different units of services that do not reflect real changes in case-mix. Section 1895(b)(5) of the Act provides the Secretary with the option to make changes to the payment amount otherwise paid in the case of outliers because of unusual variations in the type or amount of medically necessary care. Section 1895(b)(3)(B)(v) of the Act requires HHAs to submit data for purposes of measuring health care quality, and links the quality data submission to the annual applicable percentage increase. Section 50208 of the BBA of 2018 (Pub. L. 115-123) requires the Secretary to implement a new methodology used to determine rural add-on payments for CYs 2019 through 2022.

Sections 1895(b)(2) and 1895(b)(3)(A) of the Act, as amended by section 51001(a)(1) and 51001(a)(2) of the BBA of 2018 respectively, required the Secretary to implement a 30-day unit of service, for 30-day periods beginning on and after January 1, 2020. The HH PPS wage index utilizes the wage adjustment factors used by the Secretary for purposes of sections 1895(b)(4)(A)(ii) and (b)(4)(C) of the Act for hospital wage adjustments.

2. HH QRP

Section 1895(b)(3)(B)(v) of the Act authorizes the HH QRP, which requires HHAs to submit data in accordance with the requirements specified by CMS. Failure to submit data required under section 1895(b)(3)(B)(v) of the Act with respect to a program year will result in the reduction of the annual home health market basket percentage increase otherwise applicable to an HHA for the corresponding calendar year by 2 percentage points.

3. Expanded HHVBP Model

In the CY 2022 HH PPS final rule (86 FR 62292 through 62336) and codified at 42 CFR part 484, subpart F, we finalized our policy to expand the HHVBP Model to all Medicare certified HHAs in the 50 States, territories, and District of Columbia beginning January 1, 2022. CY 2022 was designated as a pre-implementation year during which CMS will provide HHAs with resources and training. This pre-implementation year as intended to allow HHAs time to prepare and learn about the expectations and requirements of the expanded HHVBP Model without risk to payments.

We also finalized that the expanded Model will use a baseline year to establish the benchmarks and achievement thresholds for each cohort on each measure for HHAs. The baseline year is currently 2019. In this rule, we are proposing to establish a separate HHA baseline year to determine HHA improvement thresholds by measure for each individual agency to assess achievement or improvement of HHA performance on applicable quality measures. As codified at § 484.350(b), for an HHA that is certified by Medicare on or after January 1, 2019, the baseline year is the first full calendar year of services beginning after the date of Medicare certification, with the exception of HHAs certified on January 1, 2019, through December 31, 2019, for which the baseline year is calendar year (CY) 2021, and the first performance year is the first full calendar year (beginning with CY 2023) following the baseline year. As discussed in that final rule, we stated that we may conduct analyses of the impact of using various baseline periods and consider any changes for future rulemaking.

Due to the continuation of the COVID-19 PHE through CY 2021 and its effects on the quality measures in the expanded HHVBP Model used to determine payment adjustments for eligible HHAs (as described in section IV.B.2.b. of this proposed rule), we believe an HHA's baseline year that would be CY 2021 should be adjusted to CY 2022. This policy aligns with similar proposals in the Hospital VBP and SNF VBP Programs to account for the continued effects of the PHE on measures in 2021. Additionally, amending the HHA baseline year (and defining this term) for HHAs certified prior to 2022 starting in the CY 2023 performance year as well as changing the Model baseline year (and defining this term) to CY 2022 starting in the CY 2023 performance year allows eligible HHAs to be scored on measure data that is more current and is intended to compare HHAs to a base year that is 2 years after the peak of the pandemic.

4. Medicare Coverage of Home Infusion Therapy

Section 1834(u)(1) of the Act, as added by section 5012 of the 21st Century Cures Act, requires the Secretary to establish a home infusion therapy services payment system under Medicare. This payment system requires a single payment to be made to a qualified home infusion therapy supplier for items and services furnished by a qualified home infusion therapy supplier in coordination with the furnishing of home infusion drugs. Section 1834(u)(1)(A)(ii) of the Act states that a unit of single payment is for each infusion drug administration calendar day in the individual's home. The Secretary shall, as appropriate, establish single payment amounts for types of infusion therapy, including to consider variation in utilization of nursing services by therapy type. Section 1834(u)(1)(A)(iii) of the Act provides a limitation to the single payment amount, requiring that it shall not exceed the amount determined under the Physician Fee Schedule (under section 1848 of the Act) for infusion therapy services furnished in a calendar day if furnished in a physician office setting, except such single payment shall not reflect more than 5 hours of infusion for a particular therapy in a calendar day. Section 1834(u)(1)(B)(i) of the Act requires that the single payment amount be adjusted by a geographic wage index. Finally, section 1834(u)(1)(C) of the Act allows for discretionary adjustments which may include outlier payments and other factors as deemed appropriate by the Secretary, and are required to be made in a budget neutral manner. Section 1834(u)(3) of the Act specifies that annual updates to the single payment are required to be made beginning January 1, 2022, by increasing the single payment amount by the percentage increase in the CPI-U for all urban consumers for the 12 month period ending with June of the preceding year, reduced by the productivity adjustment. The unit of single payment for each infusion drug administration calendar day, including the required adjustments and the annual update, cannot exceed the amount determined under the fee schedule under section 1848 of the Act for infusion therapy services if furnished in a physician's office, and the single payment amount cannot reflect more than 5 hours of infusion for a particular therapy per calendar day. Finally, Division N, section 101 of CAA 2021 amended section 1848(t)(1) of the Act and modified the CY 2021 PFS rates by providing a 3.75 percent increase in PFS payments only for CY 2021.

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 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), and the Congressional Review Act (5 U.S.C. 804(2))

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 (also referred to as “economically significant”); (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 the Executive order. Therefore, we estimate that this rule is “economically significant” as measured by the $100 million threshold, and hence also a major rule under the Congressional Review Act. Accordingly, we have prepared a Regulatory Impact Analysis that presents our best estimate of the costs and benefits of this rule.

C. Detailed Economic Analysis

This rule proposes updates to Medicare payments under the HH PPS for CY 2023. The net transfer impact related to the changes in payments under the HH PPS for CY 2023 is estimated to be −$810 million (−4.2 percent). The $810 million decrease in estimated payments for CY 2023 reflects the effects of the proposed CY 2023 home health payment update percentage of 2.9 percent ($560 million increase), an estimated 6.9 percent decrease that reflects the effects of the permanent behavioral adjustment ($1.33 billion decrease) and an estimated 0.2 percent decrease that reflects the effects of an updated FDL ($40 million decrease).

We use the latest data and analysis available, however, we do not adjust for future changes in such variables as number of visits or case-mix. This analysis incorporates the latest estimates of growth in service use and payments under the Medicare home health benefit, based primarily on Medicare claims data for periods that ended on or before December 31, 2021. 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 errors resulting from other changes in the impact time period assessed. Some examples of such possible events are newly-legislated general Medicare program funding changes made by the Congress or changes specifically related to HHAs. In addition, changes to the Medicare program may continue to be made as a result of new statutory provisions. Although these changes may not be specific to the HH 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 HHAs.

Table F5 represents how HHA revenues are likely to be affected by the finalized policy changes for CY 2023. For this analysis, we used an analytic file with linked CY 2021 OASIS assessments and home health claims data for dates of service that ended on or before December 31, 2021. The first column of Table F5 classifies HHAs according to a number of characteristics including provider type, geographic region, and urban and rural locations. The second column shows the number of facilities in the impact analysis. The third column shows the payment effects of the permanent behavioral adjustment on all payments. The fourth column shows the payment effects of the recalibration of the case-mix weights offset by the case-mix weights budget neutrality factor. The fifth column shows the payment effects of updating to the CY 2023 wage index with a 5-percent cap on wage index decreases. The sixth column shows the payment effects of the final CY 2023 home health payment update percentage. The seventh column shows the payment effects of the new FDL, and the last column shows the combined effects of all the finalized provisions.

Overall, it is projected that aggregate payments in CY 2023 would decrease by 4.2 percent which reflects the 6.9 percent decrease from the permanent behavioral adjustment, the 2.9 payment update percentage increase, and the 0.2 percent decrease from increasing the FDL. As illustrated in Table F5, the combined effects of all of the changes vary by specific types of providers and by location. We note that some individual HHAs within the same group may experience different impacts on payments than others due to the distributional impact of the CY 2023 wage index, the percentage of total HH PPS payments that were subject to the LUPA or paid as outlier payments, and the degree of Medicare utilization.

2. Impacts for the HH QRP for CY 2023

Failure to submit HH QRP data required under section 1895(b)(3)(B)(v) of the Act with respect to a program year will result in the reduction of the annual home health market basket percentage increase otherwise applicable to an HHA for the corresponding calendar year by 2 percentage points. For the CY 2022 program year, 1,169 of the 11,128 active Medicare-certified HHAs, or approximately 10.4 percent, did not receive the full annual percentage increase because they did not meet assessment submission requirements. The 1,169 HHAs that did not satisfy the reporting requirements of the HH QRP for the CY 2022 program year represent $437 million in home health claims payment dollars during the reporting period out of a total $17.3 billion for all HHAs.

As discussed in section III. of this proposed rule, we are proposing to end the temporary suspension of non-Medicare/Medicaid data under section 704 of the Medicare Prescription Drug, Improvement, and Modernization Act of 2003 and, in accordance with section 1895(b)(3)(B)(v) of the Act, to require HHAs to report all-payer OASIS data for purposes of the HH QRP, beginning with the CY 2025 program year.

Section III. of this proposed rule provides a detailed description of the net increase in burdens associated with these proposed changes. We are proposing that HHAs would be required to begin reporting all-payer OASIS data beginning with January 1, 2024, discharges. The cost impact of this proposal is estimated to be a net increase of $267,157,680.3 in annualized cost to HHAs, discounted at 7 percent relative to year 2020, over a perpetual time horizon beginning in CY 2025. We described the estimated burden and cost reductions for these measures in section V1V1.B.1. of this proposed rule. In summary, the submission of data on non-Medicare/Medicaid patients for the HH QRP is estimated to increase the burden on HHAs to $23,529.82 per HHA annually, or $267,157,680.3 for all HHAs annually.

3. Impacts for the Expanded HHVBP Model

In the CY 2022 HHPPS final rule (86 FR 62402 through 62410), we estimated that the expanded HHVBP Model would generate a total projected 5-year gross FFS savings, CYs 2023 through 2027, of $3,376,000,000. The proposed changes to the baseline years in this proposed rule will not change those estimates because they do not change the number of HHAs in the Model or the payment methodology.

4. Impact of the CY 2023 Payment for Home Infusion Therapy Services

There are no new proposals in this rule related to payments for home infusion therapy services in CY 2023. The CY 2023 home infusion therapy service payments will be updated by the CPI-U reduced by the productivity adjustment and geographically adjusted in a budget neutral manner using the GAF standardization factor. The CY 2023 final GAF values (and the CPI-U as of June 2022) were not available at the time of rulemaking, therefore, we are unable to estimate the impact of these adjustments on the CY 2023 HIT service payment amounts compared to the CY 2022 HIT service payment amounts.

D. Regulatory Review Cost Estimation

If regulations impose administrative costs on private entities, such as the time needed to read and interpret this proposed or final 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 last year's proposed rule will be the number of reviewers of this proposed rule. We acknowledge that this assumption may understate or overstate the costs of reviewing this rule. It is possible that not all commenters reviewed last year's rule in detail, and it is also possible that some reviewers chose not to comment on the proposed rule. For these reasons we thought that the number of past commenters would be a fair estimate of the number of reviewers of this rule. We seek comments on the approach used in estimating the number of entities reviewing 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. We seek comments on this assumption. Using the wage information from the BLS for medical and health service managers (Code 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 2.32 hours for the staff to review half of this proposed rule. For each entity that reviews the rule, the estimated cost is $267 (2.32 hours × $115.22). Therefore, we estimate that the total cost of reviewing this regulation is $ 55,269 ($267 × 207) [207 is the number of estimated reviewers, which is based on the total number of unique commenters from last year's proposed rule].

E. Alternatives Considered

1. HH PPS

For the CY 2023 HH PPS proposed rule, we considered alternatives to the provisions articulated in section II.B.2. of this proposed rule. Specifically, we considered other potential methodologies to determine the difference between assumed versus actual behavior change on estimated aggregate expenditures in response to the comment solicitation in the CY 2022 HH PPS proposed rule (86 FR 35892). However, most of the alternate methodologies controlled for certain actual behavior changes (for example, the reduction in therapy visits) and this is not in alignment with what the statute requires at section 1895(b)(3)(D)(i) of the Act where we must examine actual behavior change. Therefore, any method that would control for an actual behavior change would be counter to what is required by law. Additionally, we considered alternative approaches to the implementation of the permanent and temporary behavior assumption adjustments. As described in section II.B.2. of this rule, to help prevent future over or underpayments, we calculated a permanent prospective adjustment by determining what the 30-day base payment amount should have been in CYs 2020 and 2021 in order to achieve the same estimated aggregate expenditures as obtained from the simulated 60-day episodes. One alternative to the proposed −7.69 percent permanent payment adjustment included a phase-in approach, where we could reduce the permanent adjustment, by spreading out the adjustment over a period of a few years. Another alternative would be to delay the permanent adjustment to a future year. However, we believe that a phase-in approach or delay for the permanent adjustment would not be appropriate, as phasing in or delaying the permanent adjustment would further impact budget neutrality and likely lead to a compounding effect creating the need for a larger reduction to the payment rate in future years.

Finally, we considered proposing to implement the one-time temporary adjustment to reconcile retrospective overpayments in CYs 2020 and 2021. We note that MedPAC's March 2022 Report to Congress ^[78] has found that in 2020, the aggregate Medicare margin for freestanding HHAs was 20.2 percent, a nearly 5 percentage point increase from the previous year. However, as stated previously in this rule, we believe that implementing both the permanent and temporary adjustments to the CY 2023 payment rate may adversely affect HHAs. Likewise, section 1895(b)(3)(D)(iii) of the Act gives CMS the authority to make any temporary adjustment in a time and manner appropriate though notice and comment rulemaking. Therefore, we believe it is best to propose only the implementation of the permanent decrease of 7.69 percent to the CY 2023 base payment rate, while soliciting comments on the best approach to implement the temporary adjustment for overpayments to HHAs for CYs 2020 and 2021.

2. HHQRP

We did not consider any alternatives in this proposed rule.

3. Expanded HHVBP Model

We discuss the alternative we considered to the proposed change to the HHA baseline year for each applicable measure in the expanded HHVBP Model in section IV.B.2.b. of this proposed rule.

4. Home Infusion Therapy

We did not consider any alternatives in this proposed rule.

F. Accounting Statements and Tables

1. HH PPS

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 F7, we have prepared an accounting statement showing the classification of the transfers and benefits associated with the CY 2023 HH PPS provisions of this rule.

2. HHQRP

As required by OMB Circular A-4 (available at https://www.whitehouse.gov/​sites/​whitehouse.gov/​files/​omb/​circulars/​A4/​a-4.pdf ), in Table F8, we have prepared an accounting statement showing the classification of the expenditures associated with this proposed rule as they relate to HHAs. Table F8 provides our best estimate of the increase in burden for OASIS submission.

3. Expanded HHVBP Model

As required by OMB Circular A-4 (available at https://www.whitehouse.gov/​sites/​whitehouse.gov/​files/​omb/​circulars/​A4/​a-4.pdf ), in Table F9, we have prepared an accounting statement Table F9 provides our best estimate of the decrease in Medicare payments under the expanded HHVBP Model.

G. Regulatory Flexibility Act (RFA)

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. In addition, HHAs and home infusion therapy suppliers are small entities, as that is the term used in the RFA. Individuals and States are not included in the definition of a small entity.

The North American Industry Classification System (NAICS) was adopted in 1997 and is the current standard used by the Federal statistical agencies related to the U.S. business economy. We utilized the NAICS U.S. industry title “Home Health Care Services” and corresponding NAICS code 621610 in determining impacts for small entities. The NAICS code 621610 has a size standard of $16.5 million ⁷⁹ and approximately 96 percent of HHAs and home infusion therapy suppliers are considered small entities. Table F10 shows the number of firms, revenue, and estimated impact per home health care service category.

The economic impact assessment is based on estimated Medicare payments (revenues) and HHS's practice in interpreting the RFA is to consider effects economically “significant” only if greater than 5 percent of providers reach a threshold of 3 to 5 percent or more of total revenue or total costs. The majority of HHAs' visits are Medicare paid visits and therefore the majority of HHAs' revenue consists of Medicare payments. Based on our analysis, we conclude that the policies proposed in this rule would result in an estimated total impact of 3 to 5 percent or more on Medicare revenue for greater than 5 percent of HHAs. Therefore, the Secretary has determined that this HH PPS proposed rule would have significant economic impact on a substantial number of small entities. We estimate that the net impact of the policies in this rule is approximately $810 million in decreased payments to HHAs in CY 2023. The $810 million in decreased payments is reflected in the last column of the first row in Table F5 as a 4.2 percent decrease in expenditures when comparing CY 2023 payments to estimated CY 2022 payments. The 4.2 percent decrease is mostly driven by the impact of the permanent behavior assumption adjustment reflected in the third column of Table F5. Further detail is presented in Table F5, by HHA type and location.

With regards to options for regulatory relief, we note that section 1895(b)(3)(D)(i) of the Act requires CMS to annually determine the impact of differences between the assumed behavior changes finalized in the CY 2019 HH PPS final rule (83 FR 56455) and actual behavior changes on estimated aggregate expenditures under the HH PPS with respect to years beginning with 2020 and ending with 2026. Additionally, section 1895(b)(3)(D)(ii) and (iii) of the Act requires that CMS make permanent and temporary adjustments to the payment rate to offset for such increases or decreases in estimated aggregate expenditures through notice and comment rulemaking. Since the permanent and temporary adjustments are mandated by statute, we cannot offer HHAs relief from these adjustments. While we are not proposing to implement the temporary payment adjustments in CY 2023, we believe that the −7.69 percent permanent payment adjustment, described in section II.B.2.c. of this proposed rule, is necessary to offset the increase in estimated aggregate expenditures for CYs 2020 and 2021 based on the impact of the differences between assumed behavior changes and actual behavior changes. In the alternatives considered previously, we noted that we considered a phase-in approach to the permanent adjustment. However, we believe that a phase-in of the permanent adjustment is not appropriate for CY 2023 because it would further impact budget neutrality and likely lead to a compounding effect creating the need for a larger reduction to the payment rate in future years. As mentioned previously, we recognize that implementing both the permanent and temporary adjustments to the CY 2023 payment rate may adversely affect HHAs, including small entities. Therefore, we are soliciting comments on the best approach to collect the temporary payment adjustment of $2.0 billion for CYs 2020 and 2021. We solicit comments on the overall HH PPS RFA analysis.

Guidance issued by HHS interpreting the Regulatory Flexibility Act considers the effects economically ‘significant’ only if greater than 5 percent of providers reach a threshold of 3- to 5-percent or more of total revenue or total costs. Among the over 7,500 HHAs that are estimated to qualify to compete in the expanded HHVBP Model, we estimate that the percent payment adjustment resulting from this rule would be larger than 3 percent, in magnitude, for about 28 percent of competing HHAs (estimated by applying the proposed 5-percent maximum payment adjustment under the expanded Model to CY 2019 data). As a result, more than the RFA threshold of 5-percent of HHA providers nationally would be significantly impacted. We refer readers to Tables 43 and 44 in the CY 2022 HH PPS final rule (86 FR 62407 through 62410) for our analysis of payment adjustment distributions by State, HHA characteristics, HHA size and percentiles.

Thus, the Secretary has certified that this proposed rule would have a significant economic impact on a substantial number of small entities. Though the RFA requires consideration of alternatives to avoid economic impacts on small entities, the intent of the rule, itself, is to encourage quality improvement by HHAs through the use of economic incentives. As a result, alternatives to mitigate the payment reductions would be contrary to the intent of the rule, which is to test the effect on quality and costs of care of applying payment adjustments based on HHAs' performance on quality measures.

In addition, section 1102(b) of the Act requires us to prepare a Regulatory Impact Analysis (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 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. This rule is not applicable to hospitals. Therefore, the Secretary has certified that this proposed rule would not have a significant economic impact on the operations of small rural hospitals.

I. Unfunded Mandates Reform Act (UMRA)

Section 202 of UMRA of 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 2022, that threshold is approximately $165 million. This proposed rule would not impose a mandate that will result in the expenditure by State, local, and Tribal Governments, in the aggregate, or by the private sector, of more than $165 million in any one year.

J. Federalism

Executive Order 13132 establishes certain requirements that an agency must meet when it promulgates 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. We have reviewed this proposed rule under these criteria of Executive Order 13132, and have determined that it would not impose substantial direct costs on State or local governments.

Chiquita Brooks-LaSure, Administrator of the Centers for Medicare & Medicaid Services, approved this document on June 10, 2022.

List of Subjects in 42 CFR Part 484

• Health facilities
• Health professions
• Medicare, and 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 follows:

PART 484—HOME HEALTH SERVICES

1. The authority citation for part 484 continues to read as follows:

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

2. Section 484.220 is amended by adding paragraph (c) to read as follows:

§ 484.220

Calculation of the case-mix and wage area adjusted prospective payment rates.

* * * * *

(c) Beginning on January 1, 2023, CMS applies a cap on decreases to the home health wage index such that the wage index applied to a geographic area is not less than 95 percent of the wage index applied to that geographic area in the prior calendar year. The 5-percent cap on negative wage index changes is implemented in a budget neutral manner through the use of wage index budget neutrality factors.

3. Section 484.245 is amended—

a. In paragraph (b)(1)(i) by removing the reference “sections 1899B(c)(1) and 1899B(d)(1) of the Act” and adding in its place the reference “sections 1895(b)(3)(B)(v)(II), 1899B(c)(1), and 1899B(d)(1) of the Act”;

b. In paragraph (b)(1)(iii) by removing the first sentence; and

c. By adding paragraph (b)(3).

The addition reads as follows:

§ 484.245

Requirements under the Home Health Quality Reporting Program (HH QRP).

* * * * *

(b) * * *

(3) CMS may remove a quality measure from the HH QRP based on one or more of the following factors:

(i) Measure performance among HHAs is so high and unvarying that meaningful distinctions in improvements in performance can no longer be made.

(ii) Performance or improvement on a measure does not result in better patient outcomes.

(iii) A measure does not align with current clinical guidelines or practice.

(iv) The availability of a more broadly applicable (across settings, populations, or conditions) measure for the particular topic.

(v) The availability of a measure that is more proximal in time to desired patient outcomes for the particular topic.

(vi) The availability of a measure that is more strongly associated with desired patient outcomes for the particular topic.

(vii) Collection or public reporting of a measure leads to negative unintended consequences other than patient harm.

(viii) The costs associated with a measure outweigh the benefit of its continued use in the program.

* * * * *

4. Section 484.345 is amended—

a. In the definition of “Achievement threshold” by removing the phrase “during a baseline year” and adding in its place the phrase “during a Model baseline year”;

b. By removing the definition of “Baseline year”;

c. In the definition of “Benchmark” by removing the phrase “during the baseline year” and adding in its place the phrase “during the Model baseline year”;

d. By adding the definition of “HHA baseline year” in alphabetical order;

e. In the definition of “Improvement threshold” by removing the phrase “during the baseline year” and adding in its place the phrase “during the HHA baseline year”; and

f. By adding the definition of “Model baseline year” in alphabetical order.

The additions read as follows:

§ 484.345

Definitions.

* * * * *

HHA baseline year means the calendar year used to determine the improvement threshold for each measure for each individual competing HHA.

* * * * *

Model baseline year means the calendar year used to determine the benchmark and achievement threshold for each measure for all competing HHAs.

* * * * *

5. Section 484.350 is amended by revising paragraph (b) and adding paragraph (c) to read as follows:

* * * * *

(b) New HHAs. A new HHA is certified by Medicare on or after January 1, 2022. For new HHAs, the following apply:

(1) The HHA baseline year is the first full calendar year of services beginning after the date of Medicare certification.

(2) The first performance year is the first full calendar year following the HHA baseline year.

(c) Existing HHAs. An existing HHA is certified by Medicare before January 1, 2022 and the HHA baseline year is calendar year (CY) 2022.

§ 484.370

[Amended]

6. Section 484.370 is amended in paragraph (a) by removing the phrase “Model for the baseline year, and CMS” and adding in its place the phrase “Model, and CMS”.

Dated: June 16, 2022.

Xavier Becerra,

Secretary, Department of Health and Human Services.

Footnotes

1.   http://pacioproject.org/​.

2.  The Trusted Exchange Framework (TEF): Principles for Trusted Exchange (Jan. 2022), https://www.healthit.gov/​sites/​default/​files/​page/​2022-01/​Trusted_​Exchange_​Framework_​0122.pdf.

3.  Common Agreement for Nationwide Health Information Interoperability Version 1 (Jan. 2022), https://www.healthit.gov/​sites/​default/​files/​page/​2022-01/​Common_​Agreement_​for_​Nationwide_​Health_​Information_​Interoperability_​Version_​1.pdf.

4.  Qualified Health Information Network (QHIN) Technical Framework (QTF) Version 1.0 (Jan. 2022), https://rce.sequoiaproject.org/​wp-content/​uploads/​2022/​01/​QTF_​0122.pdf.

5.  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.

6.   http://www.medpac.gov/​docs/​default-source/​reports/​mar20_​medpac_​ch9_​sec.pdf?​sfvrsn=​0.

7.   https://www.medpac.gov/​wp-content/​uploads/​2022/​03/​Mar22_​MedPAC_​ReportToCongress_​Ch8_​SEC.pdf.

8.   https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​HomeHealthPPS/​HH-PDGM.

9.  Medicare Benefit Policy Manual, Chapter 7 Home Health Services, Section 40.2 Skilled Therapy Services https://www.cms.gov/​Regulations-and-Guidance/​Guidance/​Manuals/​Downloads/​bp102c07.pdf.

10.  There are no 30-day PDGM claims which started in CY 2019 and ended in CY 2020, and therefore this exclusion would not apply to the CY 2020 dataset.

11.  All of a beneficiary's claims are dropped so as not to create problems with assigning episode timing if only a subset of claims is dropped.

12.  This is done because if three or more claims link to the same OASIS it would not be clear which claims should be joined to simulate a 60-day episode.

13.   https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​HomeHealthPPS/​CaseMixGrouperSoftware.

14.   https://www.federalregister.gov/​documents/​2009/​01/​16/​E9-743/​hipaa-administrative-simplification-modifications-to-medical-data-code-set-standards-to-adopt.

15.  Home Health Prospective Payment System Regulations and Notices web page. https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​HomeHealthPPS/​Home-Health-Prospective-Payment-System-Regulations-and-Notices .

16.  Home Health Prospective Payment System Regulations and Notices web page. https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​HomeHealthPPS/​Home-Health-Prospective-Payment-System-Regulations-and-Notices .

17.  HHA Center web page: https://www.cms.gov/​Center/​Provider-Type/​Home-Health-Agency-HHA-Center.

18.  Found in Ch47 of the Provider Reimbursement Manual at https://www.cms.gov/​Regulations-and-Guidance/​Guidance/​Manuals/​Paper-Based-Manuals-Items/​CMS021935.

19.  Medicare Payment Advisory Commission (MedPAC), Report to the Congress: Medicare Payment Policy. March 2022, P. 271. found at https://www.medpac.gov/​wp-content/​uploads/​ 2022/03/Mar22_MedPAC_ReportToCongress_SEC.pdf.

20.   https://www.govinfo.gov/​content/​pkg/​PLAW-108publ173/​pdf/​PLAW-108publ173.pdf.

21.  National Quality Forum. MAP Coordination Strategy for Post-Acute Care and Long-Term Care Performance Measurement. February 2012. Available at https://www.qualityforum.org/​Publications/​2012/​02/​MAP_​Coordination_​Strategy_​for_​Post-Acute_​Care_​and_​Long-Term_​Care_​Performance_​Measurement.aspx. Accessed March 21, 2022.

22.  Section 1895(b)(3)(B)(v)(II) requires data submission for HHCAHPS.

23.   https://www.cms.gov/​pillar/​health-equity .

24.  CMS Framework for Health Equity 2022-2032.

25.  Joynt KE, Orav E, Jha AK. Thirty-Day Readmission Rates for Medicare Beneficiaries by Race and Site of Care. JAMA. 2011; 305(7):675-681.

26.  Lindenauer PK, Lagu T, Rothberg MB, et al. Income Inequality and 30 Day Outcomes After Acute Myocardial Infarction, Heart Failure, and Pneumonia: Retrospective Cohort Study. British Medical Journal. 2013; 346.

27.  Trivedi AN, Nsa W, Hausmann LRM, et al. Quality and Equity of Care in U.S. Hospitals. New England Journal of Medicine. 2014; 371(24):2298- 2308.

28.  Polyakova, M., et al. Racial Disparities In Excess All-Cause Mortality During The Early COVID-19 Pandemic Varied Substantially Across States. Health Affairs. 2021; 40(2): 307-316.

29.  Rural Health Research Gateway. Rural Communities: Age, Income, and Health Status. Rural Health Research Recap. November 2018.

30.   https://www.minorityhealth.hhs.gov/​assets/​PDF/​Update_​HHS_​Disparities_​Dept-FY2020.pdf.

31.   www.cdc.gov/​mmwr/​volumes/​70/​wr/​mm7005a1.htm.

32.  Poteat TC, Reisner SL, Miller M, Wirtz AL. COVID-19 Vulnerability of Transgender Women With and Without HIV Infection in the Eastern and Southern U.S. Preprint. medRxiv. 2020;2020.07.21.20159327. Published 2020 Jul 24. doi:10.1101/2020.07.21.20159327.

33.  Milkie Vu et al. Predictors of Delayed Healthcare Seeking Among American Muslim Women, Journal of Women's Health 26(6) (2016) at 58; S.B. Nadimpalli, et al., The Association between Discrimination and the Health of Sikh Asian Indians Health Psychol. 2016 Apr; 35(4): 351-355.

34.  Joynt Maddox KE, Chen LM, Zuckerman R, Epstein AM. Association between race, neighborhood, and Medicaid enrollment and outcomes in Medicare home health care. J Am Geriatr Soc. 2018;66(2):239-46.

35.  IBID.

36.  Smith DB, Feng Z, Fennell ML, Zinn J, Mor V. Racial disparities in access to long-term care: the illusive pursuit of equity. J Health Polit Policy Law. 2008;33(5):861-81.

37.  Gaskin DJ, Dinwiddie GY, Chan KS, McCleary R. Residential segregation and disparities in health care services utilization. Med Care Res Rev. 2012;69(2):158-75.

38.  Rahman M, Foster AD. Racial segregation and quality of care disparity in U.S. nursing homes. J Health Econ. 2015;39:1-16.

39.  Fashaw-Walters, SA. Rahman, M., Gee, G. et al. Out Of Reach: Inequities In The Use Of High-Quality Home Health Agencies. Health Affairs 2022 41(2):247-255.

40.  IBID.

41.  Fashaw-Walters, SA. Rahman, M., Gee, G. et al. Out Of Reach: Inequities In The Use Of High-Quality Home Health Agencies. Health Affairs 2022 41(2):247-255.

42.  Werner RM, Bressman E. Trends in post-acute care utilization during the COVID-19 pandemic. J Am Med Dir Assoc. 2021;22(12):2496-9.

43.  Werner RM, Asch DA. The unintended consequences of publicly reporting quality information. JAMA. 2005;293(10):1239-44.

44.  Davitt JK, Bourjolly J, Frasso R. Understanding inequities in home health care outcomes: staff views on agency and system factors. Res Gerontol Nurs. 2015;8(3):119-29.

45.   https://www.cms.gov/​Medicare/​Quality-Initiatives-Patient-Assessment-Instruments/​QualityInitiativesGenInfo/​Downloads/​CMS-Quality-Strategy.pdf.

46.  Report to Congress: Improving Medicare PostAcute Care Transformation (IMPACT) Act of 2014 Strategic Plan for Accessing Race and Ethnicity Data. January 5, 2017. Available at https://www.cms.gov/​About-CMS/​Agency-Information/​OMH/​Downloads/​Research-Reports-2017-Report-to-Congress-IMPACT-ACT-of-2014.pdf.

47.  Healthy People 2030, U.S. Department of Health and Human Services, Office of Disease Prevention and Health Promotion. Retrieved 06/09/22.

48.   https://www.cms.gov/​About-CMS/​Agency-Information/​OMH/​Downloads/​CLAS-Toolkit-12-7-16.pdf.

49.   http://www.pacioproject.org/​.

50.  The Trusted Exchange Framework (TEF): Principles for Trusted Exchange (Jan. 2022), https://www.healthit.gov/​sites/​default/​files/​page/​2022-01/​Trusted_​Exchange_​Framework_​0122.pdf .

51.  Common Agreement for Nationwide Health Information Interoperability Version 1 (Jan. 2022), https://www.healthit.gov/​sites/​default/​files/​page/​2022-01/​Common_​Agreement_​for_​Nationwide_​Health_​Information_​Interoperability_​Version_​1.pdf.

52.  Qualified Health Information Network (QHIN) Technical Framework (QTF) Version 1.0 (Jan. 2022), https://www.rce.sequoiaproject.org/​wp-content/​uploads/​2022/​01/​QTF_​0122.pdf.

53.  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.

54.   https://innovation.cms.gov/​data-and-reports/​2020/​hhvbp-thirdann-rpt.

55.   https://www.cms.gov/​files/​document/​certificationhome-health-value-based-purchasing-hhvbpmodel.pdf.

56.   https://www.cms.gov/​newsroom/​press-releases/​cms-takes-action-improve-home-health-care-seniors-announces-intent-expand-home-health-value-based.

57.  Derived from data at https://data.cms.gov/​provider-data/​archived-data/​home-health-services.

58.   https://www.cdc.gov/​coronavirus/​2019-ncov/​covid-data/​covidview/​past-reports/​01282022.html.

59.  Joynt KE, Orav E, Jha AK. (2011). Thirty-day readmission rates for Medicare beneficiaries by race and site of care. JAMA, 305(7):675-681.

60.  Lindenauer PK, Lagu T, Rothberg MB, et al. (2013). Income inequality and 30 day outcomes after acute myocardial infarction, heart failure, and pneumonia: Retrospective cohort study. British Medical Journal, 346.

61.  Trivedi AN, Nsa W, Hausmann LRM, et al. (2014). Quality and equity of care in U.S. hospitals. New England Journal of Medicine, 371(24):2298-2308.

62.  Polyakova, M., et al. (2021). Racial disparities in excess all-cause mortality during the early COVID-19 pandemic varied substantially across states. Health Affairs, 40(2): 307-316.

63.  Rural Health Research Gateway. (2018). Rural communities: age, income, and health status. Rural Health Research Recap. https://www.ruralhealthresearch.org/​assets/​2200-8536/​rural-communities-age-incomehealth-status-recap.pdf.

64.   https://www.minorityhealth.hhs.gov/​assets/​PDF/​Update_​HHS_​Disparities_​Dept-FY2020.pdf.

65.   www.cdc.gov/​mmwr/​volumes/​70/​wr/​mm7005a1.htm.

66.  Milkie Vu et al. Predictors of Delayed Healthcare Seeking Among American Muslim Women, Journal of Women's Health 26(6) (2016) at 58; S.B. Nadimpalli, et al., The Association between Discrimination and the Health of Sikh Asian Indians Health Psychol. 2016 Apr; 35(4): 351-355.

67.  Poteat TC, Reisner SL, Miller M, Wirtz AL. (2020). COVID-19 vulnerability of transgender women with and without HIV infection in the Eastern and Southern U.S. preprint. medRxiv. 2020;2020.07.21. 20159327. doi:10.1101/2020.07.21.20159327.

68.  86 FR 7009 (January 25, 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/​.

69.   https://www.cms.gov/​pillar/​health-equity.

70.   https://www.cms.gov/​About-CMS/​Agency-Information/​OMH/​OMH-Mapping-Medicare-Disparities.

71.   https://innovation.cms.gov/​innovation-models/​ahcm.

72.   https://qualitynet.cms.gov/​inpatient/​measures/​disparity-methods.

73.   https://www.cms.gov/​Medicare/​Quality-Initiatives-Patient-Assessment-Instruments/​Post-Acute-Care-Quality-Initiatives/​IMPACT-Act-of-2014/​-IMPACT-Act-Standardized-Patient-Assessment-Data-Elements.

74.   https://www.cms.gov/​sites/​default/​files/​2022-04/​CMS%20Framework%20for%20Health%20Equity_​2022%2004%2006.pdf.

75.  Office of the Assistant Secretary for Planning and Evaluation, U.S. Department of Health & Human Services. Second Report to Congress on Social Risk Factors and Performance in Medicare's Value-Based Purchasing Program. 2020. https://aspe.hhs.gov/​social-risk-factors-and-medicares-value-basedpurchasing-programs.

76.  Home Infusion Therapy Services Billing and Rates. https://www.cms.gov/​medicare/​home-infusion-therapy-services/​billing-and-rates.

77.  As estimated by CMS analysis of payor source indicators in CY20 HH Cost report data compared to the CY20 HH OASIS data file.

78.  Home Health Services. MedPAC Report to Congress- 2022. https://www.medpac.gov/​wp-content/​uploads/​2022/​03/​Mar22_​MedPAC_​ReportToCongress_​Ch8_​SEC.pdf.

79.   https://www.sba.gov/​sites/​default/​files/​2019-08/​SBA%20Table%20of%20Size%20Standards_​Effective%20Aug%2019%2C%202019_​Rev.pdf.