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Start Preamble Start Printed Page 66790 Centers buy kamagra oral jelly usa for Medicare &. Medicaid Services (CMS), Department of Health and Human Services (HHS). Final rule buy kamagra oral jelly usa. This final rule sets forth routine updates to the Medicare home health payment rates for calendar year (CY) 2023 in accordance with existing statutory and regulatory requirements. This final rule also finalizes a methodology for determining the impact of 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 finalizes a corresponding permanent prospective adjustment to the CY 2023 home health payment rate.

This rule finalizes the reassignment of certain diagnosis codes under the buy kamagra oral jelly usa PDGM case-mix groups, and establishes 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 finalizes 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 comments buy kamagra oral jelly usa received on the future collection of data regarding the use of telecommunications technology during a 30-day home health period of care on home health claims. This rule also finalizes 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 buy kamagra oral jelly usa services payment rates for CY 2023. These regulations are effective on January 1, 2023. Start Further Info Brian Slater, (410) 786-5229, for home health and home infusion therapy payment inquiries. For general information about home infusion buy kamagra oral jelly usa payment, send your inquiry via email to [email protected]. For general information about the Home Health Prospective Payment System (HH PPS), send your inquiry via email to [email protected].

For information about the Home Health Quality Reporting Program (HH buy kamagra oral jelly usa QRP), send your inquiry via email to [email protected]. 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. End Further Info End Preamble Start Supplemental Information Table of Contents I. Executive Summary A buy kamagra oral jelly usa. Purpose B.

Summary of the Provisions of This Rule C. Summary of Costs, buy kamagra oral jelly usa Transfers, and Benefits II. Home Health Prospective Payment System A. Overview of the Home buy kamagra oral jelly usa Health Prospective Payment System B. Provisions for Payment Under the HH PPS III.

Home Health Quality Reporting Program (HH QRP) and Other Home Health Related Provisions A. End of buy kamagra oral jelly usa the Suspension of OASIS Data Collection on Non-Medicare/Non-Medicaid HHA Patients and Requirement for HHAs To Submit All-Payer OASIS Data for Purposes of the HH QRP, Beginning With the CY 2027 Program Year B. Technical Changes C. Codification of the HH QRP Measure Removal Factors D. Request for buy kamagra oral jelly usa Information.

Health Equity in the HH QRP IV. Expanded Home buy kamagra oral jelly usa Health Value-Based Purchasing (HHVBP) Model A. Background B. Changes to the Baseline Years and New Definitions C. Request for Comment buy kamagra oral jelly usa on a Future Approach to Health Equity in the Expanded HHVBP Model V.

Home Infusion Therapy Services. Annual Payment Updates for CY 2023 A. Home Infusion Therapy Payment Categories buy kamagra oral jelly usa B. Payment Adjustments for CY 2023 Home Infusion Therapy Services C. CY 2023 buy kamagra oral jelly usa Payment Amounts for Home Infusion Therapy Services XI.

Collection of Information Requirements and Waiver of Final Rulemaking A. Statutory Requirement for Solicitation of Comments B. Collection of buy kamagra oral jelly usa Information Requirements C. Submission of PRA-Related Comments D. Waiver of Final Rulemaking XII.

Regulatory Impact buy kamagra oral jelly usa Analysis A. Statement of Need B. Overall Impact C buy kamagra oral jelly usa. Detailed Economic Analysis D. Limitations of Our Analysis E.

Regulatory Review Cost Estimation buy kamagra oral jelly usa F. Alternatives Considered G. Accounting Statement and Tables H. Regulatory Flexibility buy kamagra oral jelly usa Act (RFA) I. Unfunded Mandates Reform Act (UMRA) J.

Federalism K buy kamagra oral jelly usa. Conclusion Regulations Text I. Executive Summary and Advancing Health Information Exchange A. Executive Summary 1 buy kamagra oral jelly usa. 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 final rule updates the payment rates for HHAs for CY 2023. In addition, the rule recalibrates 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 buy kamagra oral jelly usa 2023. Finalizes a methodology to determine the impact of differences between assumed behavior changes and actual behavior changes on estimated aggregate Medicare home health expenditures, in accordance with section 1895(b)(3)(D)(i) of the Act. Finalizes a buy kamagra oral jelly usa permanent payment adjustment to the CY 2023 30-day period payment rate. Updates the case-mix weights, LUPA thresholds, functional impairment levels, and comorbidity subgroups for CY 2023.

And updates 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 final rule also discusses the comments received on the collection of data on the use of telecommunications technology from home health claims buy kamagra oral jelly usa. B. Home Health (HH) Quality Reporting Program (QRP) This final rule finalizes the end of the suspension of the collection of Outcome and Assessment Information Set (OASIS) data from non-Medicare/non-Medicaid patients pursuant to section 704 of the Medicare Prescription Drug, Improvement, and Modernization Act of 2003 and requires HHAs to report all-payer OASIS data for purposes of the Start Printed Page 66791 HH QRP. In response to concerns raised by commenters on the burden associated with the proposed new data collection, buy kamagra oral jelly usa we are finalizing that the new OASIS data reporting for the HH QRP will begin with the CY 2027 program year, with two quarters of data required for that program year.

We are finalizing a phase-in period is in place for January 1, 2025 through June 30, 2025 in which failure to submit the data will not result in a penalty. We are buy kamagra oral jelly usa finalizing as proposed regulatory text change that consolidates the statutory references to data submission. We are also finalizing as proposed the codification of the measure removal factors we adopted in the CY 2019 HH PPS final rule. Finally, this rule summarizes the comments we received in response to our Request for Information regarding health equity in the HH QRP. c buy kamagra oral jelly usa.

Expanded Home Health Value Based Purchasing (HHVBP) Model In accordance with the statutory authority at section 1115A of the Act, we are finalizing proposed policy updates, new definitions and modifications of existing definitions, conforming regulation text changes for the expanded Home Health Value-Based Purchasing (HHVBP) expanded Model. We also summarize the comments received on our request for comment on a potential future approach to health equity in the expanded HHVBP Model included in the proposed rule. D. Medicare Coverage of Home Infusion Therapy This final 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.2. Of this rule, we are finalizing our proposed behavioral adjustment methodology to reflect the impact of differences between assumed behavior changes and actual behavior changes on estimated aggregate payment expenditures under the HH PPS. We are also finalizing a -3.925 percent permanent payment adjustment for CY 2023 (half of the proposed -7.85 percent adjustment), as we recognize the potential hardship of implementing the proposed full permanent adjustment in a single year. In section II.B.3 of this rule, we are finalizing the proposed reassignment of certain ICD-10-CM codes related to the PDGM clinical groups and comorbidity subgroups.

In section II.B.4. Of this rule, we are finalizing the proposed 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 are finalizing our proposals 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 final home health payment update percentage for CY 2023 will be 4.0 percent.

This rule also finalizes a permanent 5-percent cap on wage index reductions in order to smooth the impact of year-to-year changes in home health payments related to changes in the home health wage index. Additionally, this rule finalizes 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 final rule, we respond to the comment solicitation on the collection of data on the use of telecommunications technology from home health claims. B.

HH QRP In section III.D. Of this final rule, we are finalizing our proposal to end the temporary suspension on our collection of non-Medicare/non-Medicaid data, in accordance with 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 submit all-payer OASIS data for purposes of the HH QRP. In response to concerns raised by commenters on the burden associated with the proposed new data collection, we are finalizing that the new OASIS data reporting for the HH QRP will begin January 1, 2025 with a phase-in period for January 1, 2025 through June 30, 2025 in which failure to submit the data will not result in a penalty. In section III.E. Of this rule, we are finalizing technical changes to § 484.245(b)(1).

In section III.F. Of this rule, we are finalizing codification of 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 summarizing the comments we received on our Request for Information regarding health equity in the HH QRP. C.

Expanded Home Health Value Based Purchasing (HHVBP) Model In section IV. Of this final rule, we are finalizing as proposed changes 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 are also making conforming regulation text changes at § 484.350(b) and (c). In addition, we are finalizing proposed amendments to 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 finalizing conforming amendments to definitions in § 484.345.

In section IV.C. Of this final rule, we have included a discussion of comments received in response to the RFI related to a potential future approach to health equity in the expanded HHVBP Model that was included in the proposed rule. D. Medicare Coverage of Home Infusion Therapy In section V. Of this final 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 Table 1—Summary of Costs, Transfers, and Benefits Start Printed Page 66792 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 the goal of data 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.[] 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://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 [] and Common Agreement Start Printed Page 66793 (TEFCA) Version 1.[] The Trusted Exchange Framework is a set of non-binding principles for health information exchange, and the Common Agreement is a contract that advances those principles.

The Common Agreement and the Qualified Health Information Network Technical Framework Version 1 [] (incorporated by reference into the Common Agreement) establish the technical infrastructure model and governing approach for different health information networks and their users to securely share clinical information with each other—all under commonly agreed to terms. The technical and policy architecture of how exchange occurs under the 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.[] 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 Start Printed Page 66794 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 separately by the HHA and paid under Part B, 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 1. 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). Start Printed Page 66795 B.

Provisions for CY 2023 Payment Under the HH PPS 1. Monitoring the Effects of the Implementation of PDGM In the CY 2023 HH PPS proposed rule (87 FR 37605), CMS provided data analysis on Medicare home health benefit utilization, including 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 for all Medicare fee-for-service (FFS) claims. The percentage of periods that receive the LUPA. Estimated costs for 30-day periods of care.

The distribution, by percentage, of 30-day periods of care, using the five clinical variables (clinical group, comorbidity adjustment, admission source, timing, and functional impairment level). The OASIS “GG” functional 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. We will continue to monitor and analyze home health trends and vulnerabilities within the home health payment system. 2.

PDGM Behavioral Assumptions and Adjustments Under the HH PPS a. Background As discussed in section II.A.1. Of this rule, 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, starting with payments for services made on and after January 1, 2020. In determining the CY 2020 standard prospective 30-day payment amount, 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 changes in case-mix adjustment factors, including the elimination of therapy thresholds as a factor in determining case-mix adjustments. 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 Start Printed Page 66796 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 HH PPS final rule with comment period (84 FR 60512), in order to calculate the CY 2020 30-day base payment rates 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 estimated aggregate expenditures in CY 2020 with the application of a 30-day unit of payment under the PDGM. We initially determined a -8.389 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 believed it was reasonable to apply the three behavior change assumptions to only half of the 30-day periods in our analytic file (randomly selected). Therefore, we finalized in the CY 2020 HH PPS final rule with comment period (84 FR 60519), a -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 the CY 2023 HH PPS proposed rule compares the CY 2018 and CY 2019 simulated 30-day periods of care with behavior assumptions applied and actual CY 2020 and CY 2021 30-day periods of care. Specifically, Tables B4, B6, and B7 (87 FR 37607 through 37609) 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, also occurred. Overall, the CYs 2020 and 2021 actual 30-day periods are similar to the simulated CYs 2018 and 2019 30-day periods with the behavior assumptions applied, which is supporting evidence that HHAs did make behavior changes.

We reminded readers that, by law, we are required to ensure that estimated aggregate expenditures under the HH PPS are equal to our determination of estimated aggregate expenditures that otherwise would have been made under the HH PPS in the absence of the change to a 30-day unit of payment and changes in case-mix adjustment factors. 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 also reminded readers that in the CY 2020 HH PPS final rule with comment period (84 FR 60513), we stated that we interpret actual behavior changes to encompass both the assumed behavior changes that were previously identified by CMS, as well as other behavior changes not identified at the time the budget-neutral 30-day payment rate for CY 2020 was established. Subsequently, as noted previously, our analysis resulted in the identification of other behavior changes that occurred after the implementation of the PDGM. Although not originally one of the three finalized behavior assumptions, a decline in therapy utilization is indicative of an additional behavior change.

For example, Table B10 and Figure B3 in section II.B.1. Of the CY 2023 HH PPS proposed rule (87 FR 37612 through 37613) 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 and the PDGM, but prior to implementation. This suggests HHAs were already beginning to decrease their therapy provision in anticipation of the new payment system. Each Health Insurance Prospective Payment System (HIPPS) code is assigned a case-mix weight which determines the base payment of non-LUPA claims prior to any other adjustments (for example, outlier payment adjustments).

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 updated CY 2021 simulated 60-day episodes. Prior to the PDGM, the average case-mix weight for CY 2018 actual 60-day episodes was 1.0176 and the average case-mix weight for CY 2021 simulated 60-day episodes was 0.9682. Using the updated CY 2021 simulated 60-day episodes, we set therapy levels at the pre-PDGM (that is, CY 2018) levels and kept the clinical and functional levels at the PDGM levels (that is, CY 2021).

This resulted in an average case-mix weight of 1.0389, slightly higher than the actual CY 2018 60-day episodes. Next, we kept therapy levels at the PDGM (that is, CY 2021) levels and set the clinical and functional levels at the pre-PDGM levels (that is, CY 2018) and found the average case-mix weight was 0.9383, much lower than the CY 2018 actual 60-day episodes. By controlling for therapy levels, we were able to determine the change in 60-day episode case-mix weights was 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. B.

Method To Annually Determine the Impact of Differences Between Assumed Behavior Changes and Actual Behavior Changes on Estimated Aggregate Expenditures To evaluate if the national, standardized 30-day payment rate and resulting estimated aggregate expenditures maintained budget neutrality after the implementation of the PDGM, we used actual 30-day period claims data to simulate 60-day episodes and estimate what aggregate expenditures would have been under the 153-group case-mix system and 60-day unit of payment. Using the Start Printed Page 66797 estimated aggregate expenditures under the 153-group case-mix system (simulated 60-day episodes from 30-day periods) we are able to calculate permanent and temporary adjustments as discussed in section II.B.2.c of this final rule. We used the following steps. The first step in repricing 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.[] 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)). 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 Beneficiaries and all of their claims if three or more claims from the same provider are linked to the same occurrence code 50 date. 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.

(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 applying the exclusions and assumptions described previously, we have the simulated 60-day episode dataset for each year. Starting with CY 2020 claims, we assign each simulated 60-day episode of care as a normal episode, PEP, LUPA, or outlier based on the payment parameters established in the CY 2020 HH PPS final rule with comment period (84 FR 60478) for 60-day episodes of care.

Next, using the October 2019 3M Home Health Grouper (v8219) [] 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 HH PPS 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, home health payment update). For example, to calculate the CY 2021 simulated 60-day episode base payment rate, we started with the final CY 2020 60-day base payment rate ($3,220.79) multiplied by the final CY 2021 wage index budget neutrality factor (0.9999) and the CY 2021 home health payment update (1.020) to get an adjusted 60-day base payment rate ($3,284.88) for CY 2021. We used the adjusted 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).

Once each simulated 60-day claim is priced under the pre-PDGM HH PPS, we calculate the estimated aggregate expenditures for all simulated 60-day episodes. That is, using actual behavior (using the most current year of PDGM claims) we determine what the aggregate expenditures would have been under the prior 153 group case-mix system. Next, to control for utilization, we calculate the PDGM aggregate expenditures using those specific 30-day periods that were used to create the simulated 60-day episodes. That is, both the actual PDGM aggregate expenditures and the simulated pre-PDGM aggregate expenditures are based on the same number of claims. We received 770 comments on the methodology and implementation of a permanent prospective behavior change adjustment on the CY 2023 home health payment rate.

Comment. A few commenters stated that CMS' proposal would violate three separate statutory requirements. The commenters stated that. (1) the proposal uses therapy thresholds to determine payment despite the statute's mandate to eliminate this practice. (2) ignores the statutory provision by failing to correct its assumptions about how home health agencies would change behaviors in response to the new payment system.

And (3) violates the statute's budget-neutrality requirement by reducing overall aggregate expenditures. Response. The BBA of 2018 tasked CMS with ensuring that Medicare spending under the new 30-day payment system is the same as the estimated spending under the old 60-day home health payment system. Section 1895(b)(3)(A)(iv) of the Act directed the Secretary to calculate a standard prospective payment amount for CY 2020, incorporating assumptions about behavior changes, that could occur as a result of the implementation of a 30-day unit of payment and changes in case-mix adjustment factors. In other Start Printed Page 66798 words, using the data available at the time of rulemaking, we were required to estimate a national, standardized payment rate so that estimated aggregate expenditures with assumed behavior changes (clinical group coding, comorbidity coding, and LUPA thresholds) for CY 2020 would be the same under the PDGM as they would have been under the prior payment system (153 group).

In the CY 2020 HH PPS final rule with comment period (84 FR 60513), we estimated that this would mean a −8.389 percent payment adjustment to the base payment rate in order to avoid overestimating payments under the 30-day system. In response to commenter concerns that the pervasiveness of expected behavioral changes among HHAs was overestimated, we stated that given the scale of the payment system changes, we agree that it might take HHAs more time before they fully changed their behaviors in ways expected by CMS. Therefore, we finalized a policy that applied the three behavioral assumptions only to half (randomly selected) of the simulated 30-day periods of care. This reduction in the application of the assumptions resulted in a −4.36 percent behavior assumption adjustment. Therefore, we met the initial requirement of section 1895(b)(3)(A)(iv) by setting the CY 2020 national, standardized 30-day payment rate ($1,864.03) in a budget-neutral manner, based on available data (simulated 30-day periods) at the time of rulemaking.

Following the implementation of the new payment system, the BBA of 2018 tasks CMS with determining the impact of the difference between our assumed behavior changes and actual behavior changes on estimated aggregate expenditures beginning with CY 2020 through CY 2026, as set out in section 1895(b)(3)(D)(i) of the Act. As the Act requires CMS to look at actual behavior, the methodology 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 the aggregate expenditures would have been in the absence of the PDGM. In other words, CMS used the same claims (actual PDGM 30-day periods and simulated 60-day episodes from the 30-day periods) to compare estimated aggregate expenditures under both systems in order to determine the estimated aggregate impact of behavior change. This allows us to control for actual utilization, not predicted utilization, to determine the impact of differences between what we estimate aggregate expenditures would have been in the absence of the PDGM using actual data and what the expenditures actually were under the PDGM. As stated previously, CMS is not required to correct each of its original assumptions regarding home health agency behavior changes or itemize each behavior change for which its methodology accounts, as commenters asserted.

For example, while paragraph (3)(D)(i) clarifies that the “assumed behavior changes” CMS must use in its calculations are those “described in paragraph (3)(A)(iv),” it contains no such qualification for the “actual behavior changes” to which CMS compares the assumed behavior. CMS accordingly ensured that the payment rate accurately accounts for all “actual behavior changes”, in the aggregate, that occurred in a given year. Neither this provision, nor section 1895(b)(3)(A)(iv) of the Act, requires CMS to ensure that it actually spends the amount of the original estimated aggregate expenditures (that is, $16.2 billion) based on simulated 30-day periods for CY 2020. Rather, section 1895(b)(3)(D)(i) of the Act requires that CMS compare the estimated aggregate expenditures resulting from the 30-day payment rate with estimated assumed behavior changes (resulting in a $1,864.03 standardized rate) to the new estimated aggregate expenditures derived from actual data—incorporating actual behavior changes—that would have occurred under the prior 60-day system. In other words, we are not required to compare our original estimated aggregate expenditures (estimated at $16.2 billion) to actual expenditures (that is, $15.1 billion), and make up the difference.

Rather, under the statute, we re-estimate aggregate expenditures under the pre-PDGM based on actual behavior changes, as derived from actual claims. This is because, the original estimated aggregate expenditures ($16.2 billion) were based on predicted utilization, not actual utilization. With regard to therapy, CMS received comments in the CY 2022 HH PPS final rule (86 FR 62247) and in response to the CY 2023 HH PPS proposed rule that the decrease in therapy utilization, including termination of therapy staff, is related to the removal of the therapy payment incentive. In their comment letter, a leading industry association detailed how HHAs have responded to changes in the benefit structure and have altered their operations, affecting the level of care received by patients. For instance, prior to the PDGM, the industry notes that HHAs were incentivized to provide the highest volume of therapy visits possible, and a low volume of other services.

The industry association goes on to note that under the PDGM, the elimination of the therapy volume adjustment as a case mix measure will likely lead to a reduction in therapy services to patients. In an article published in February 2020,[] the National Association for Home Care and Hospice (NAHC) was quoted as saying “categorically, across the board, we're going to reduce our therapy services” as a result of the PDGM. More recently in an article in April 2022,[] it was estimated that nearly half of HHAs had planned to decrease therapy utilization after the implementation of the PDGM. In that article, NAHC was quoted as saying “There was a precipitous drop in therapy visits in January and February of 2020 before the kamagra hit.” In addition, their consulting firm stated, “Importantly, note that the reduction in therapy visits began before erectile dysfunction treatment PHE started in March 2020—indicating that HHA providers were already experiencing significant declines in therapy visits as a result of PDGM, even before the onset of the kamagra. Thus, the PDGM effect on therapy is not a erectile dysfunction treatment effect, but rather a PDGM effect.” These comments from interested parties confirm that the decrease in therapy is a concerted provider behavior change in response to a financial incentive rather than the erectile dysfunction treatment PHE.

Anecdotal evidence and the data presented in the CY 2023 HH PPS proposed rule (87 FR 37612 through 37613) supports the conclusion there has been a significant change (decline) in therapy visits due to the implementation of the PDGM. If we were to artificially inflate aggregate expenditures in CYs 2020 and 2021 by including payments for therapy visits that may have occurred under the old thresholds, but that were in fact not provided under the new system (as shown by actual data), we would be setting payment based on how providers would have presumably behaved under the old system rather than actual behaviors under the new system, which we believe is not the best reading of the law. It would be inappropriate to manipulate the data so that old behaviors (in this case, inflated therapy visits to reach payment thresholds) Start Printed Page 66799 would change the resulting payment adjustment for assumed versus actual behavior changes under the PDGM. It would be inappropriate for CMS to continue to pay for therapy as if HHAs were still inflating therapy provision based on the former therapy thresholds, when the number of therapy visits after the implementation of the PDGM has actually declined. Despite the commenters' argument that CMS cannot use the reduction in therapy to determine payment because the BBA of 2018 mandated the elimination of therapy thresholds, the law did not mandate a reduction in the provision of therapy or even decrease the payment rates for therapy disciplines.

It simply removed a payment incentive structured around the quantity of therapy visits, which had resulted in provider behavior to maximize payment, exactly the type of actual behavior change that CMS is tasked to consider when setting the base payment rate. We disagree with commenters who read sections 1895(b)(3)(A)(iv) and 1895(b)(3)(D) of the Act to require payments based on earlier, higher therapy utilization rates instead of permitting us to re-run the calculations we used to predict aggregated expenditures with actual 2020 data. Subparagraph (A)(iv) required CMS, in determining budget neutrality for 2020, to estimate a payment amount so that the “estimated aggregate amount of expenditures” under the new 30-day case-mix system—after including “assumptions about behavior changes that could occur” because of the changed methodology—was “equal to the estimated aggregate amount of expenditures that otherwise would have been made” if the new 30-day case-mix system “had not been enacted.” And subparagraph (D) requires CMS, for years 2020-2026, to adjust payments based on how differences between the “assumed” behavior changes that CMS originally predicted and the “actual” behavior changes CMS now observes impact original “estimated aggregate expenditures.” CMS followed subparagraph (A)(iv) by estimating aggregate expenditures for CY 2020 using simulated 30-day case-mix system claims (as this was the only data available at the time of CY 2020 rulemaking) to calculate a 30-day base payment rate as if the 30-day case-mix system “had not been enacted”. CMS followed subparagraph (D) by determining the impact of assumed behavior changes to actual behavior changes by comparing the 30-day base payment rate and aggregate expenditures (based on assumed behaviors) to what the 30-day base payment rate and aggregate expenditures should have been (based on actual behaviors). Some commenters read the requirement in subparagraph (A)(iv) to calculate estimated aggregate expenditures as if one of Congress' payment reforms “had not been enacted” to require payments based on pre-2020 therapy utilization rates—pointing also to subparagraph (A)(iv)'s title of “budget neutrality for 2020.” But that reading ignores the requirement in subparagraph (D) to adjust estimated aggregate expenditures based on “actual behavior changes,” as well as its instruction in subparagraph (A)(iv) to incorporate into CMS's estimated aggregate expenditures “assumptions about behavior changes that could occur as a result of” implementing these payment reforms.

These provisions authorize CMS to account for how behavior changes, like therapy utilization, would have affected payments under the old 60-day system and do not require CMS to pay for therapy that never actually occurred. This ensures that HHAs were still paid the same amount they would have been under the old system for services they actually did provide—thus achieving budget neutrality. We also disagree with the commenter who suggests that subparagraph (D) prohibits CMS from recalculating estimated aggregate expenditures and instead requires CMS to compare the aggregate expenditures CMS estimated in 2019 to actual expenditures CMS observed in 2020. Subparagraph (D) requires CMS to evaluate how using actual behavior changes rather than assumed behavior changes affects predicted expenditures. Comment.

Multiple commenters stated that CMS' proposed rule violates notice and comment rulemaking because “an agency must provide the public with the relevant data and technical studies on which it relies to form decisions”. Commenters indicated that CMS did not disclose to the public both the data model and the post-manipulation data and they were therefore unable to replicate and test the CMS' findings and conclusions. Specifically, commenters requested the baseline payments at the claim level used by CMS to calculate the CY 2023 impacts, any additional adjustments to the CY 2021 data to roll it forward to CY 2022, home health agency level impacts, the dataset CMS used to determine budget neutrality and the adjustment factors for CYs 2020 and 2021, a spreadsheet analogue to the SNF parity-adjustment, and the input data supporting its calculations. In addition, a few commenters stated that the methodology was not clear and did not provide the specific claims to use in analysis. Some commenters stated that agency-level impacts should have been provided and that they could not fully analyze the methodology without such agency-level impacts.

Response. We disagree with commenters that we violated notice and comment rulemaking by not providing the public with relevant data and technical studies. We also remind commenters that this methodology, the corresponding data files and step-by-step instructions also were detailed in the CY 2022 HH PPS proposed rule (86 FR 35889) and CMS solicited comments on this methodology in that proposed rule. Interested parties did not state that the data and instructions provided at that time were insufficient to provide comments on the methodology. Moreover, in the CY 2023 HH PPS proposed rule, we made available sufficient data and methodological descriptions for interested commenters to replicate our calculations to provide comments on this rule.

These are further described below. First, in the CY 2023 HH PPS proposed rule (87 FR 37616 through 37620), CMS provided a detailed methodology and described the results of applying that methodology, citing the year and the source of the home health claims data obtained from the Chronic Conditions Warehouse (CCW) and the Home Health Claims—OASIS limited data set (LDS) file. The CY 2022 HH PPS proposed rule (86 FR 35889 through 35892) also included a comment solicitation on this same detailed methodology, citing the LDS file, a publicly-available claims database. The OASIS LDS includes the same data as the CCW, except de-identified for public release. CMS repeatedly states that at the HH PPS LDS web page [] such raw data are available, and agency records reflect that multiple commenters in fact received the CY 2021 Home Health Claims—OASIS LDS data at issue in this rule.

That file provides the variables and their descriptions for the CY 2023 HH PPS proposed rule as well as diagnostics that provide basic statistics for each variable CMS considered. Second, CMS detailed each methodological step it took in the rules, including the exclusions and assumptions that CMS used to calculate estimated aggregate expenditures. As such, commenters had access to both Start Printed Page 66800 the dataset (including baseline payments at the claim level, and the exact number of claims and the payment rates used in calculating the CY 2020 and CY 2021 proposed permanent and temporary adjustments) they requested, as well as how CMS used that data to calculate the adjustments. Interested parties were thus able to replicate CMS' calculations with the information that CMS made available to them. Commenters' requests for additional information go beyond the critical factual material needed to comment on CMS' proposals.

CMS did not adjust the data to “roll” the CY 2021 data to CY 2022, and so information about CY 2022 data is irrelevant to CMS's calculations. Nor did CMS need to generate an analog to the SNF parity adjustment spreadsheet, which was not part of the critical factual materials the agency considered when making the calculations in the rule. Similarly, commenters did not need home health agency level impacts data, because impacts estimate how the national payment rate may affect HHAs overall, which was not a metric CMS used to calculate the adjustments. Finally, CMS did not need to release the simulated 60-day episodes because CMS provided the detailed instructions on how commenters could simulate those claims themselves based on the data CMS provided. We are aware that some courts have read a procedural requirement into the Administrative Procedure Act (Pub.

L. 89-554) mandating that agencies provide for public comment the critical factual materials on which they rely.[] By releasing sufficient raw data files and methodological descriptions that allowed commenters to replicate CMS's process, CMS has more than satisfied any legal requirements to disclose factual materials. Comment. Multiple commenters expressed concerns that the erectile dysfunction treatment PHE may have impacted CY 2020 and 2021 data. Commenters stated the erectile dysfunction treatment PHE required a shift in priorities, thereby changing utilization patterns.

Response. The proposed methodology controls for changes in utilization as a result of exogenous factors such as the erectile dysfunction treatment PHE by using the same claims dataset, that is the same basket of services, under both payment systems. This ensures any difference in aggregate expenditures is not related to the erectile dysfunction treatment PHE or other exogenous factors. It may be helpful to review the comments received from MedPAC on the proposed rule.[] MedPAC stated in its comments that the methodology presented in the proposed rule was reasonable because applying the case-mix system in effect prior to 2020 reflects how Medicare would have paid in the absence of the BBA 2018 changes. MedPAC explained that any effect of the erectile dysfunction treatment PHE is included in both estimated aggregate expenditures (that is, 60-day episodes and 30-day periods).

Therefore, they noted that methodology presented ensures that any differences between the two calculated spending amounts would not be attributable to the erectile dysfunction treatment PHE. In addition, while the initial onset of the erectile dysfunction treatment PHE in the early months of CY 2020 may have had an impact on home health utilization, the healthcare system has since begun to return to normal and stabilize. For example, studies have shown that elective surgeries and other medical treatments have resumed to pre-kamagra capacity.[] As shown in the CY 2023 HH PPS proposed rule (87 FR 37605 through 37614), many aspects of home health utilization (volume, visits, clinical groups, comorbidity adjustment, admission source, timing, and functional impairment level) are similar throughout CYs 2020 and 2021. Furthermore, in the CY 2023 HH PPS proposed rule, we solicited data from interested parties showing how erectile dysfunction treatment affected these aspects of home health utilization and we did not receive any empirical information on this issue specifically. Therefore, we find the CYs 2020 and 2021 data are sufficient and complete, for the purpose of this methodology, and we believe the data are not significantly impacted as a result of the erectile dysfunction treatment PHE.

Comment. A commenter stated CMS' data shows that after implementation of the PDGM, HHAs continued to provide therapy, but the pattern of therapy provision changed. For example, they noted the most significant decline was for episodes with 13 or more therapy visits. In addition, several commenters stated there has been a decline in therapy visits since the implementation of the PDGM. However, several commenters stated that even if therapy visits were reduced in CYs 2020 and 2021, but outcomes (for example, hospitalizations, meeting goals of the plan of care) did not worsen, then payment reductions should not be made.

Response. We appreciate the commenters' recommendation. However, CMS does not have the authority to tie this payment adjustment to outcomes or other quality measures, or to modify this adjustment on an agency level. Comment. A commenter suggested using Hierarchical Condition Categories (HCC) scores within the behavioral assumptions.

Response. We appreciate the commenter's recommendation. However, we note that the HCC scores are dependent on beneficiaries having a claims history (which may be limited for those newly enrolled in Medicare), and therefore, do not think they would be appropriate to use in this methodology as it may limit our ability to capture beneficiary characteristics needed for case-mix adjustment. Comment. A few commenters questioned why CMS did not include therapy utilization as one of the original three behavior change assumptions when setting the CY 2020 payment rate.

Response. We have noted in past rules that we use the functional impairment level case-mix adjustment, developed as part of the PDGM case-mix, to provide the necessary payment adjustments to ensure that functional care needs necessitating therapy, are met based on actual patient characteristics (84 FR 60497). The functional impairment case-mix factor was not meant to be a direct proxy for the therapy thresholds. However, we expected that functional impairment along with other case-mix factors (for example, admission source), would appropriately compensate HHAs for therapy. Likewise, we expected the functional impairment adjustment, along with other case-mix factors (for example, admission source), to not only alleviate concerns that removal of the therapy thresholds would dissuade providers from delivering needed therapy, but to assure providers that patients can and should still receive the necessary type and amount of therapy based on patient characteristics.

In this respect, while we did note that we were aware of how payment may affect practice patterns and that visits vary in response to financial incentives, we also stated that the therapy thresholds promoted the provision of care based on increased payment associated with each of these Start Printed Page 66801 thresholds as opposed to actual patient needs (83 FR 56485). It was our belief, when setting the original behavior change assumptions, that the functional impairment adjustment would effectively offset reductions in therapy visits that could result from the elimination of the therapy thresholds, especially those patients requiring multiple therapy disciplines or patients with significant functional impairment. As a result, we did not initially contend that removal of the therapy thresholds would significantly alter provider behavior, as we were still compensating therapy through the functional impairment case-mix adjustment. Our expectation was that therapy utilization would reflect actual patient acuity. Comment.

Commenters stated they support the structure of the PDGM, but the budget neutrality adjustment methodology is inconsistent with other methodologies applied to other health care providers and would result in a loss of access to care. Response. We thank interested parties for their comments. However, the commenters did not clarify what they meant by “inconsistent with other methodologies applied to other health care providers”. We believe that the proposed methodology satisfies the budget neutrality requirements at section 1895(b)(3)(A)(iv) of the Act, as well as the requirements at section 1895(b)(3)(D)(i) of the Act, to determine the impact of differences between assumed behavior changes and actual behavior changes on estimated aggregate expenditures for home health periods of care.

Furthermore, MedPAC stated in their March, 2022 report [] that the Commission found positive access, quality, and financial indicators for the sector. As such, we do not believe that this methodology and its resulting payment adjustment would result in a loss of access to care. Comment. Several commenters recommended CMS hold a Technical Expert Panel (TEP) to determine a methodology for calculating the budget neutrality adjustment. Response.

We thank commenters for their suggestion. However, CMS solicited comments on the CY 2022 HH PPS proposed rule (86 FR 35892) for alternative methodologies, and interested parties were able to submit comments on the CY 2023 HH PPS proposed rule. We received 75 comments on the CY 2022 proposed rule and 770 comments on the CY 2023 proposed rule. We also note that a TEP is not required by statute, and there is insufficient time to obtain such input. Comment.

Many commenters stated the proposed methodology was “technically flawed” because the methodology does not compare behaviors assumed by CMS in establishing the CY 2020 rate to actual behaviors observed on aggregate expenditures. A commenter stated the methodology was based on faulty data and that the methodology uses an outdated logic, therefore the behavioral adjustment is based on “poor logic”. Response. As stated previously, CMS is not required to correct or quantify each original assumption regarding home health agency behavior change, but rather, ensure that the payment rate is accurately accounting for all behaviors that actually occurred in a given year. As required by law, CMS determined the base payment rate for CY 2020 incorporating assumptions about behavior changes that could occur as a result of the PDGM.

It is unclear why the commenter believes the data were faulty or how the methodology was outdated. The proposed methodology for adjusting for behavioral changes compares the payment rate and aggregate expenditures based on assumed behaviors to the what the payment rate and estimated aggregate expenditures would have been using actual behaviors. Therefore, CMS' proposed methodology is comparing assumed behaviors to actual behaviors on estimated aggregate expenditures, as required by law. Further, as stated in the CY 2023 HH PPS proposed rule (87 FR 37616), we continue to assert 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. It does not require that our rates be retrospectively adjusted to mirror estimated aggregate spending.

Comment. Several commenters recommended including changes that affect other aspects of Medicare home health spending such as Medicare enrollment. Modification/improvement of enforcement of coverage standards (for example, maintenance therapy, home infusion therapy). Behavior changes in other PAC services that affect home health utilization. Technological advances.

And other factors that may contribute to Medicare spending changes not specifically related to the implementation of the PDGM. Some commenters suggesting adjusting for nominal versus real case-mix change. A commenter recommended replacing the proposed methodology, which they stated focused on a change in average case-mix weight, to a methodology which focuses on behavior changes. Response. We thank the commenters for their suggestions.

While we recognize other factors affect the utilization of home health services, we believe the statute is best read to instruct us to consider only changes related to provider behavior in response to the 30-day unit of payment and case-mix changes. As stated in the CY 2023 HH PPS proposed rule (87 FR 37616), while changes in nominal case-mix may be supplemental to our findings, the law requires CMS to determine the impact of differences 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 believe analyses of nominal case-mix change are provided under a separate authority than the statutory requirement to evaluate what aggregate expenditures would have been in absence of the PDGM and the elimination of therapy thresholds. We disagree the methodology focuses on the change in average case-mix weight.

Instead, the methodology compares assumed behavior to actual behavior and determines the impact of those differences on estimated aggregate expenditures, as required by law. Our discussion of case-mix in section II.B.2. Of this final rule is only used as supporting evidence in the decrease of therapy utilization. Comment. A commenter stated the proposed methodology fails to account for the reduction in average per-episode therapy services under the PDGM, which would have substantially reduced payments under the prior case-mix system.

The commenter stated that this resulted in a behavioral offset in CY 2020 that was too high and would carry over into subsequent years. Response. We recognize commenters are concerned that the methodology does not control for therapy. However, as stated previously, we believe it would be inappropriate to manipulate the data to assume that behaviors (that is, therapy provision) remain the same between both payment systems, when calculating the behavior change adjustment. The commenter is correct that the same methodology will be used Start Printed Page 66802 in subsequent years, meaning we will not control for therapy in subsequent years either.

However, we remind commenters that the law requires we annually determine the impact of the assumed versus actual behavior changes on estimated aggregate expenditures for CY 2020 through CY 2026 and adjust the payment rate to offset for such increases or decreases in a time and manner determined appropriate. Keeping behaviors constant when they changed in between payment systems is inconsistent with this instruction. It is unclear what the commenter suggested by a “carry over” effect. To clarify, the methodology analyzes each year of data independently and captures any behavior changes which occurred in that year, including any changes in therapy provision. As such, if any behaviors continue into subsequent years, these will be captured in the methodology.

We also remind readers the permanent adjustment is based on the percent change between the actual 30-day base payment rate and the repriced 30-day base payment rate for the same year of data (for example, CY 2021). Comment. Multiple commenters recommended modifying the proposed methodology to account for changes in therapy utilization and the onset of the erectile dysfunction treatment PHE. Specifically, many commenters stated that the therapy provision under the prior 153-group payment system would be higher than seen under the PDGM and that CMS should control for the change in therapy utilization. Many commenters recommended that CMS adopt the methodology presented by a consulting firm hired by several interested parties.

The consulting firm recommended applying the Patient Driven Payment Model (PDPM) parity adjustment methodology used in the CY 2023 Skilled Nursing Facility (SNF) PPS proposed [] and final rule (87 FR 47502) [] to CY 2020 PDGM data. The consulting firm stated “based on this approach, we found that CY 2020 PDGM payments were approximately 2.5 percent below budget neutrality (with erectile dysfunction treatment cases included) and 2.4 percent below budget neutrality with erectile dysfunction treatment cases excluded.” Response. We appreciate the commenters' recommendation to modify the proposed methodology to control for therapy utilization in alignment with the SNF parity adjustment methodology. However, the SNF PPS and HH PPS are fundamentally different. SNFs are paid a per-diem payment with different case-mix variables, and HHAs are paid under a bundled payment system.

In addition, unlike the requirements of the SNF PPS parity adjustment, CMS is required, by law, to account for behavior changes related to the implementation of the PDGM, which CMS did by comparing actual PDGM claims to what the same utilization (for example, visits, OASIS responses, etc.) would look like under a 60-day unit of payment. Section 1895(b)(4)(B)(ii) of the Act statutorily required the removal of therapy thresholds in establishing payment, but CMS stated multiple times (83 FR 56481, 84 FR 60497, 86 FR 62247, and 87 FR 37615) that therapy must be provided in accordance with the plan of care and that the PDGM is not limiting or prohibiting the provision of therapy services. As the data, as well as commenters, indicate that HHAs are decreasing therapy utilization in response to the removal of a payment incentive, and not the erectile dysfunction treatment PHE, we disagree with commenters who suggest adjusting attributing decreased therapy to the erectile dysfunction treatment PHE. Given CMS has not directed HHAs to modify the amount of services provided, but rather continue providing services in accordance with the plan of care, then any changes (operational or otherwise) by HHAs are actual behavior changes due to the implementation of the PDGM. As stated earlier, this type of response to a new payment system is what CMS is required by law to evaluate and account for with subsequent payment rate adjustments.

If CMS were to implement the method presented by the consulting firm, we would need to artificially inflate the number of therapy visits in CYs 2020 and 2021. As noted above, doing so is inconsistent with how we read the statute. Instead, the methodology presented by the consulting firm would be comparing the payment rate and aggregate expenditures based on the previous assumed behavior assumptions to a payment rate and aggregate expenditures based on new assumed behavior assumptions. In other words, any method which controls for therapy provision (or other behaviors) would result in CMS comparing assumed versus assumed behavior, which would be inconsistent with what the statute requires. Comment.

Several commenters stated the proposed methodology does not compare the behaviors assumed by CMS in establishing the initial payment rate, but rather creates an artificial target amount to reduce payments as an attempt to rebase the 30-day payment amount. As such, many commenters also recommended the alternative methodology presented by the consulting firm. This methodology recommended comparing the average CY 2020 30-day episode payments to the estimated average CY 2020 payments with behavioral assumptions used by CMS to set CY 2020 payment rates (based on data from CY 2018 60-day episodes converted to 30-day episodes). Response. We appreciate the commenters' recommendation.

However, the law requires us to determine the difference between assumed versus actual behaviors on estimated aggregate expenditures. Therefore, 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 and CY 2021 resulted in the same estimated aggregate expenditures if the change in the unit of payment and the PDGM case-mix adjustment had not been implemented and the visits and OASIS responses did not change. As stated previously, the proposed methodology compares the payment rate and aggregate expenditures based on assumed behaviors to what the payment rate and estimated aggregate expenditures would have been using actual behaviors, which we believe is what the law requires. Comment. Several commenters stated the PDGM claims cannot be reasonably regrouped under an alternative payment system.

Response. We disagree with this comment, as both payment systems (153-group and PDGM) group claims into case-mix groups based on information available on the claim, the OASIS, and other accessible administrative data. While the PDGM removed the payment incentive for excess therapy, it is not only reasonable, but required by law, to compare the same claims under two different case-mix systems. Additionally, the proposed methodology is consistent with the original methodology used in establishing the PDGM. As stated in the CY 2020 HH PPS final rule with comment period (84 FR 60512), we divided actual 60-day episodes from the 153-group payment system into two 30-day periods in order to calculate the 30-day payment amounts.

Specifically, we simulated 9,336,898 30-day periods from 5,471,454 60-day episodes and using estimated aggregate expenditures we calculated what we thought the CY 2020 payment rate would need to be, based on assumed behavior changes. We are replicating this method in reverse to Start Printed Page 66803 evaluate what the CY 2020 base payment rate should have been based on actual behavior changes and actual utilization. Comment. Several commenters indicated that CMS did not provide enough information, specifically the OASIS assessments, to replicate the methodology. In addition, a commenter stated certain OASIS items used to group the 60-day episodes are optional in CYs 2020 and 2021, which may impact the adjustment calculations.

Response. CMS provided a detailed explanation of the methodology in the CY 2023 HH PPS proposed rule (87 FR 37616) and data that can be used to carry out the methodology is made available via the Home Health Claims—OASIS LDS. The LDS file contains all necessary information, including OASIS, and the proposed rule described the necessary steps and the methodology used to allow interested parties the ability to replicate the 60-day simulated episodes. Those replicated 60-day simulated episodes and the actual 30-day periods would have resulted in the ability to calculate estimated aggregate expenditures, a repriced base payment rate, and the permanent and temporary adjustments. If a particular OASIS item did not have a response, then that item would not contribute to the functional or clinical score under the 153-group payment system.

If there were certain OASIS items missing on claims, those items may not have affected the overall functional or clinical score and corresponding level. Additionally, based on the analysis shown in the CY 2023 HH PPS proposed rule (87 FR 37615), the data showed the difference in case-mix weights was largely driven by therapy utilization and not functional or clinical score. Therefore, if a small subset of claims had missing OASIS items, it would not significantly change the overall aggregate expenditures and resulting adjustments. Comment. A commenter noted approximately 40 percent of diagnosis codes, which were previously allowed under the 153 case-mix group system, are no longer accepted as a principal diagnosis under the PDGM.

This commenter stated that this systematic change may have impacted a provider's coding behavior and could have potentially led to the simulated 60-day episodes being inaccurately assigned a “clinical domain.” Response. We thank this commenter for their review of the diagnosis codes. While we acknowledge 41 percent (29,948) of all the diagnosis codes are not assigned a clinical group under the PDGM,[] we disagree that those unassigned codes would have created any significant difference in assigning the clinical level in the 153-group case-mix system. For example, out of all the diagnosis codes available in the final grouper for the 153-group case mix system, only 22 percent (15,936) of the diagnosis codes could potentially contribute to the clinical score. Of those codes which could have contributed to the clinical score, only 6.99 percent (1,114) of the diagnosis codes are not accepted as a principal diagnosis under the PDGM.

In addition, there are only three clinical dimensions (Diabetes, Skin 1, and Neuro 1) under the 153-group system which produced a different score when the diagnosis was counted as a principal diagnosis instead of a secondary diagnosis. The other clinical dimensions awarded the same points with either a primary or other diagnosis listed on the OASIS. Therefore, while approximately 7 percent of the diagnosis codes that contributed to the clinical score under the 153 case-mix group system are no longer accepted as principal under the PDGM, many of these codes could still be used as a secondary diagnosis code and counted towards the clinical score. Additionally, there were thresholds for the clinical level, and even if the diagnosis code was accepted as principal, it would not automatically increase the clinical score to the point where it would have triggered a new clinical level. In the CY 2023 HH PPS proposed rule (87 FR 37615), we described an analysis that shows the decline in the average case-mix weight for simulated 60-day episodes were largely driven by reductions in therapy utilization instead of the clinical score (which may be impacted by diagnoses).

That means, even if all the diagnosis codes were accepted under the PDGM, we find it would be unlikely for the case-mix weight to have increased enough to counteract the reduction in therapy. Comment. A few commenters detailed their interpretation of our proposed methodology for CY 2020 describing a calculation that uses the number of 30-day periods (7,618,061) multiplied by the 30-day base payment rate ($1.936.38) subtracted from actual expenditures ($14.2 million) multiplied by the number of 30-day periods. They stated that this calculation resulted in a different payment adjustment and expressed concern that CMS inaccurately calculated the adjustment or did not provide sufficient detail to allow commenters to accurately replicate the methodology. Response.

The calculations presented by commenters make several incorrect assumptions and do not accurately replicate the detailed methodology described in the CY 2023 HH PPS proposed rule. As stated in the CY 2023 HH PPS proposed rule (87 FR 37617), after all exclusions and assumptions were applied, we designated each 60-day episode of care as a normal episode, PEP, LUPA, or outlier based on the payment parameters established in the CY 2020 HH PPS final rule with comment period (84 FR 60478) for 60-day episodes of care. Next, using the October 2019 3M Home Health Grouper (v8219), we assigned a HIPPS code to each simulated 60-day episode of care using the 153-group methodology. Finally, we priced the CY 2020 simulated 60-day episodes of care using the payment parameters described in the CY 2020 HH PPS final rule with comment period (84 FR 60537) for 60-day episodes of care.[] The CY 2023 HH PPS proposed rule states that each claim is paid based on the type of claim (that is, normal, PEP, LUPA, outlier) and assigned a HIPPS code, which would result in a specific case-mix weight for each claim. Next, each claim (determined by claim type, HIPPS) was priced based on the parameters previously described in the CY 2020 rule for 60-day episodes.

CMS did not simply multiply each claim by the base payment rate, as the commenters suggested, as this would miscalculate aggregate expenditures. As stated earlier, the available Home Health Claims—OASIS LDS dataset included all information for interested parties to determine the claim type and the associated HIPPS code to accurately estimate aggregate expenditures. In addition, the commenters referenced two unrelated numbers. As stated in the CY 2023 HH PPS proposed rule (87 FR 37618), the 7,618,061 claims were the actual 30-day periods after all exclusions and assumptions were applied to create the 4,463,549 simulated 60-day episodes. We then determined what the payment rate should have been to equal the aggregate expenditures that we calculated from the simulated CY 2020 60-day episodes.

We stated to determine the difference in aggregate expenditures, we calculated the “aggregate expenditures for all CY 2020 PDGM 30-day claims” using both payment rates (87 FR 37618). In other Start Printed Page 66804 words, the $14.2 billion referenced by the commenter was determined using the $1,742.52 PDGM payment rate for all 8,423,688 30-day periods, rather than pricing the 7,618,061 claims at their adjusted (for example, wage index, case-mix) rate. Comment. A few commenters stated it was unclear how episode timing and LUPA thresholds were assigned to the simulated 60-day episodes. Response.

As described in the CY 2023 HH PPS proposed rule, we used the October 2019 3M Home Health Grouper (v8219) to group 60-day episodes (87 FR 37617). Episode timing, early and late, were based on the number of 60-day episodes that occur within a sequence of 60-day episodes. Additionally, under the 153-group system, any 60-day episode with 4 or fewer visits was classified as a LUPA (84 FR 60519). Comment. A commenter recommended recalibrating the regression coefficients for the 153-group payment model using the simulated 60-day episodes from the CY 2020 and 2021 data to create an equivalent approach to compare PDGM to the hypothetical pre-PDGM.

The commenter stated that this would be consistent with CMS's policy to annually recalibrate and control for changes in home health resource use and changes in utilization patterns. Response. Any change in the average case-mix weight is counteracted through a corresponding change in the payment rate so that aggregate expenditures are budget neutral regardless of whether recalibration is applied. Recalibration ensures that payment incentives for future utilization are aligned with the design of the payment system (for example, recalibration ensures roughly a third of periods and episodes are in a particular functional level). While we currently do not believe there would be any benefit in recalibrating the case-mix weights for the simulated 60-day episodes, we may consider it in future rulemaking.

Comment. A few commenters were concerned the exclusions of certain categories of claim used in the proposed methodology may have biased the results. Response. As stated in the CY 2023 HH PPS proposed rule, exclusions were made to the CY 2020 and 2021 claims data in order to simulate 60-day episodes of care (87 FR 37617). These exclusions included overlapping claims, three or more claims linked to the same OASIS, and whether it was unclear if there would have been a prior or subsequent 30-day period that would have been a part of a simulated 60-day episode.

All of these exclusions were thoroughly discussed in previous rulemaking cycles. Without these exclusions, we would not be confident we were appropriately grouping 30-day periods into simulated 60-day episodes. It is also important to note, for CY 2020 we excluded 9.5 percent of 30-day periods and for CY 2021 we excluded 16.3 percent of 30-day periods. That is, we kept the majority of 30-day periods in each year (over 90 percent for CY 2020 and over 83 percent for CY 2021). The excluded 30-day periods would need to show large differences compared to the episodes that were not excluded in order to significantly change the estimated aggregate expenditures from the 60-day episodes to produce significant revisions to our calculations.

As we showed in the monitoring section of the CY 2023 HH PPS proposed rule, utilization patterns look largely the same in both CYs 2020 and 2021 (87 FR 37605). Additionally, the permanent adjustment is based on the percent change between the payment rates (which utilizes the same claims) and the temporary adjustment is based on the aggregate expenditures of all claims (that is, no exclusions) using the two payment rates (that is, the actual payment rate and the budget neutral payment rate with the permanent adjustment applied). Therefore, we do not expect the small portion of excluded claims significantly biased our results. Comment. A commenter stated that in their own analysis of CMS data they excluded 30-day claims with a primary diagnosis of erectile dysfunction treatment because they were unable to assign it a HIPPS code.

Response. We appreciate the diligence of the commenter, and are grateful that they were able to make full analytical use of the publicly available data. However, simulated 60-day episodes with a primary diagnosis of erectile dysfunction treatment would still be assigned a HIPPS under the V8219 Home Health Grouper from 3M and would not have been excluded from the repricing analysis unless there was another unrelated issue with the claim that prevented grouping. Final Decision. After consideration of all the comments received and thorough review of section 1895(b) of the Act, we are finalizing the proposed methodology to evaluate the impact of the differences of assumed versus actual behavior changes on estimated aggregate expenditures.

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 Start Printed Page 66805 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 using the pre-PDGM HH PPS data were lower than the estimated aggregate expenditures using the PDGM HH PPS data (see Table 2). This indicates that actual 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. To calculate the temporary adjustment for CY 2020, we calculated the difference in aggregate expenditures for all CY 2020 PDGM 30-day claims using the actual and recalculated payment rates.

This difference between these two aggregate expenditures, based on actual and recalculated payment rates, is the retrospective dollar amount needed to offset any increase or decrease in the estimated aggregate expenditures. Our results are shown in Table 2. Table 2—CY 2020 Proposed Permanent and Temporary Adjustments As shown in Table 2, 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 payments to 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 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 the CY 2023 HH PPS proposed rule was considered “preliminary” and as more data became available from the latter half of CY 2021, we updated our results. 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 9,269,971 30-day periods of care and dropped 570,882 30-day periods of care that had claim occurrence code 50 date after October 31, 2021.

We also excluded 968,434 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 5,868 30-day periods were excluded. Additionally, we excluded 14,302 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 (70.0 percent) and single 30-day periods of care (30.0 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 7,703,261 actual 30-day periods of care and 4,529,498 simulated 60-day episodes of care for CY 2021.

Using the final dataset for CY 2021 (7,703,261 actual 30-day periods which made up the 4,529,498 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 Start Printed Page 66806 payment rate of $1,742.52, multiplied by the CY 2021 wage index budget neutrality factor (0.9999) and the CY 2021 home health 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 (assuming the -6.52 percent adjustment was already taken). Next, we calculated the difference in aggregate expenditures for all CY 2021 PDGM 30-day claims using the actual ($1,901.12) and recalculated ($1,751.90) payment rates. This difference is the retrospective dollar amount needed to offset payment. Our results are shown in Table 3. Table 3—CY 2021 Proposed Permanent and Temporary Adjustments As shown in Table 3, an additional permanent prospective adjustment of −1.42 percent (assuming the −6.52 percent adjustment was already taken) would be required to offset for such increases in estimated aggregate expenditures in future years.

Additionally, we determined that our initial estimate of the base payment rates required to achieve budget neutrality resulted in excess expenditures of approximately $1.2 billion in CY 2021. This would require a temporary adjustment factor to offset for such increases in estimated aggregate expenditures for CY 2021. F. 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 $1,751.90 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 4 and 5. Table 4—Total Permanent Adjustment for CYs 2020 and 2021 Table 5—Total Temporary Adjustment for CYs 2020 and 2021 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 −7.85 percent permanent adjustment to the CY 2023 base payment rate as well as implement a temporary adjustment of approximately $2.1 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 an even larger reduction to adjust for behavioral Start Printed Page 66807 changes in future years. Therefore, we proposed to apply only the permanent adjustment to the CY 2023 base payment rate.

We believed this could mitigate the need for a larger permanent adjustment and could reduce the amount of any additional temporary adjustments in future years. We solicited comments on the application of only the permanent payment adjustment to the CY 2023 30-day payment rate. Additionally, we solicited comments on how best to collect the temporary payment adjustment of approximately $2.0 billion for CYs 2020 and 2021. Comment. MedPAC supported the proposed payment reduction and stated it is consistent with their recommendation of a five percent reduction to the base payment rate in the March 2022 report to Congress.[] MedPAC commented CMS should decrease home health payments to better align payments with actual incurred costs, as they found that Medicare margins for freestanding agencies averaged more than 20 percent from 2001 to 2020.

Response. We appreciate the supportive comment by MedPAC. Comment. Several commenters expressed concern that the proposed permanent behavior assumption adjustment would negatively impact home health providers' business operations. These commenters stated that the negative adjustment does not consider operational and financial challenges providers are currently experiencing related to inflation, staffing shortages, rising costs of gasoline, and medical supplies, including personal protective equipment (PPE).

Commenters also stated that staffing shortages could be the reason for the decline in visits. They stated that a negative 7.69 percent behavior assumption adjustment will cause many agencies to operate with negative margins. Commenters also expressed concerns that the proposed behavior assumption adjustment penalizes HHAs and would put access to home health in jeopardy and impact the quality of care given to home health beneficiaries. Other commenters stated that CMS should utilize the existing program integrity measures to identify and target specific agencies that have excess profit margins rather than impose an across the board reduction for all agencies, and that CMS should use its enforcement authority to target HHAs that are cutting utilization or engaged in other payment-driven behaviors to the detriment of patients. Another commenter stated that CMS should look for ways to reward “good provider behavior.” Response.

We recognize concerns around staffing and appreciate the commenters' recommendation. However, the statutorily required permanent and temporary adjustments due to behavior changes is neither to “reward” nor “penalize” providers. The proposed methodology controls for overall utilization by using a single year of utilization data priced under two payment systems to estimate aggregate expenditures. As such, any effects of staffing issues would be present in the data under both systems. The payment adjustment is solely to offset for any increase or decrease in estimated aggregate expenditures between the two payment systems.

We also recognize the impact inflation and the erectile dysfunction treatment PHE has had on healthcare providers, however, we note that in its March 2022 Report to the Congress,[] MedPAC states that Medicare margins increased under the PDGM, from 15.4 percent in 2019 to 20.2 percent in 2020. Additionally, they projected margins for home health agencies in 2022 will be roughly 17.0 percent. Furthermore, MedPAC stated in their report that the Commission found positive access, quality, and financial indicators for the sector, with average margins of 20.2 percent for freestanding HHAs in 2020, even though the cost per 30-day period increased by 3.1 percent in this year. We believe that these margins, despite economic challenges, demonstrate that the payment rate, along with the market basket update, are more than adequate to support business operations. Finally, while we appreciate the commenters' suggestion regarding targeted claim review for specific home health agencies, we do not believe targeted program integrity efforts would mitigate behavioral changes resulting from a case-mix system.

We previously addressed this suggestion in the CY 2016 HH PPS and CY 2019 HH PPS final rules (80 FR 68421 and 83 FR 56455, respectively). As we previously noted, this strategy is not viable, given the widespread nature of coding changes and improvements, small sample sizes of agencies with significant nominal case-mix across different classes of agencies, and difficulty in precisely distinguishing the agencies that engage in abusive coding from all others. Additionally, we reiterate that we are required to make temporary and permanent payment adjustments to the national, standardized 30-day period payment rate based on the impact of differences between assumed versus actual behavior change, in accordance with sections 1895(b)(3)(D)(ii) and (iii) to offset for such increases or decreases in estimated aggregate expenditures. These adjustments are not intended to account for coding abuses, but rather behavior changes CMS observes across the system. As such, we do not believe that reducing the 30-day payment rate only for agencies with high margins is the best way to implement the by statute.

Comment. A few commenters also stated that reduced payment from the permanent behavior assumption adjustment would exacerbate the already reduced payment that home health agencies receive from Medicare Advantage and Medicaid. A commenter stated that CMS fails to consider that the margins associated with a traditional Medicare beneficiary subsidize the care of managed Medicare Advantage and Medicaid patients. Response. While industry representatives contend that Medicare payments should subsidize payments from other payers (Medicare Advantage and Medicaid), we disagree.

Medicare has never set payments in order to cross-subsidize other payers. Section 1861(v)(1)(A) of the Act states “under the methods of determining costs, the necessary costs of efficiently delivering covered services to individuals covered by the insurance programs established by this title will not be borne by individuals not so covered, and the costs with respect to individuals not so covered will not be borne by such insurance programs.” There is no statutory authority to take the payment rates of other payers into account when setting Medicare fee-for-service payment rates. Comment. Many commenters recommended a phased-in approach over several years for the permanent and temporary adjustments. Specifically, a commenter indicated that a phase-in should reduce payments by no more than 2 percent annually until the adjustment is achieved.

Another commenter recommended the temporary adjustment starting no earlier than 2026. A few commenters recommended postponing any adjustments until more data are made available. Response. We thank the commenters for their recommendations. We recognize the desire to reduce the payment adjustment.

However, note that any delay in the permanent adjustment Start Printed Page 66808 through a phase-in approach may require larger temporary and permanent adjustments in the future. While we didn't propose a temporary adjustment in CY 2023, we will consider the best approach, including a phase-in, when we do propose the temporary adjustment in future rule-making. Final Decision. We stand by the methodology as described previously and maintain our authority to finalize the adjustment as proposed. But we recognize the potential hardship of implementing the full −7.85 percent permanent adjustment in a single year.

As we have the discretion to implement any adjustment in a time and manner determined appropriate, we are finalizing only a −3.925 percent (half of the −7.85 percent) permanent adjustment for CY 2023. However, we note the permanent adjustment to account for actual behavior changes in CYs 2020 and 2021 should be −7.85 percent. Therefore, applying a −3.925 percent permanent adjustment to the CY 2023 30-day payment rate would not adjust the rate fully to account for differences in behavior changes on estimated aggregate expenditures during those years, as well as in CYs 2022 and 2023. We would have to account for that difference, and any other potential adjustments needed to the base payment rate, to account for behavior change based on data analysis in future rulemaking. While we did not propose to adjust the CY 2023 payment rate using our temporary adjustment authority for CYs 2020 and 2021, we did solicit comments on how best to implement the temporary adjustment.

Comment. MedPAC recommended CMS adjust temporary payment rates over several years, such as adjusting the aggregate rate by $502.5 million per year for CYs 2023 through 2026. MedPAC strongly recommended beginning these reductions immediately to avoid potential larger reductions in future years. Response. We thank MedPAC for their recommendation.

However, while CMS proposed the methodology for calculating both the permanent and temporary adjustments, in the CY 2023 HH PPS proposed rule we did not propose collecting the $2.0 billion temporary adjustment for CYs 2020 and 2021 beginning in CY 2023. We did solicit comments on how best to collect the temporary payment adjustment and will take these comments into consideration when we propose any temporary adjustments in future rulemaking. Comment. Many commenters recommended a phase-in over several years for the temporary adjustment and another year delay before recovering any overpayments. Another commenter stated the recoupment should not be applied equally to all HHAs, but rather CMS should target recoupment based on agency level analyses to determine those HHAs who had high margins, egregious behavior changes, and “cherry pick” patients.

Response. We appreciate the commenters recommendation. We note that this is not a recoupment in the legal sense, but, as the statute specifies at section 1895(b)(3)(D)(iii) of the Act, a temporary adjustment to account for retrospective behavior. While there may be different business models between HHAs, those practices are outside the scope of this policy. Specifically, we believe the best way to interpret the statute is to apply any adjustments (permanent and temporary) to the national, standardized 30-day period payment rate on a prospective basis.

Final Decision. We thank commenters for their suggestions about how to implement the temporary payment adjustments and will consider them in future rulemaking. 3. 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” [] (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 reminded 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 erectile dysfunction treatment 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 Start Printed Page 66809 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 HH PPS 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. As we noted in the CY 2019 HH PPS final rule with comment period (83 FR 56486), 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 HH PPS final rule with comment period (83 FR 56450). C.

ICD-10-CM Diagnosis Code Reassignments to a PDGM Clinical Group or Comorbidity Subgroup The following section proposed 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 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.[] Comment. Several commenters supported the general refinement of coding assignments, including all the proposed coding changes. A commenter stated that the changes will help to more accurately reflect patients' needs and why they need home health services, rather than using “pain” as a diagnosis. Response.

We thank these commenters for their support and agree that the changes will provide more specific information related to the needs of the patient under a home health plan of care. Comment. Several commenters expressed concern that reassignment of clinical groups for principal diagnosis codes would result in an access to care issue. For example, commenters were concerned that a reassignment of principal diagnosis codes from a clinical group to no clinical group, would change the case-mix weight and reimbursement, and that the HHA may refuse the patient, thus restricting access to care. There was also concern that if the clinical group changed (for example, MS-Rehab to Wounds), the HHA would restrict the type of services provided, such as physical therapy, also restricting access to care.

Response. It is unclear why commenters believe any reassignments would restrict access to care, and note that the CoPs at § 484.60 state that the individualized plan of care must specify the care and services necessary to meet the patient-specific needs as identified in the comprehensive assessment, including identification of the responsible discipline(s), and the measurable outcomes that the HHA anticipates will occur as a result of implementing and coordinating the plan of care. Services must be furnished in accordance with accepted standards of practice. The purpose of any reassignment is to ensure that diagnoses are assigned to the appropriate clinical group or comorbidity subgroup and to align as closely as possible to ICD-10-CM coding conventions and MCE edits. These edits may have payment effects but should not result in any change in clinical practice or availability of services, unless the agency is failing to act in accordance with the plan of care.

Comment. A few commenters requested that CMS modify the clinical groups to accept and include diagnosis codes which may drive a home health need. Specifically, commenters requested allowing R29.6 (repeated falls), R54 (age-related physical debility), R26.89 (other abnormalities of gait and mobility), R42.82 (altered mental status, unspecified), and M62.81(muscle weakness (generalized)) to be accepted as a principal diagnosis and placed into a clinical group for payment. Response. We thank the commenters for their coding recommendations.

However, we did not propose to assign any of the R-codes to a clinical group and therefore, such suggestions are out of scope for this rule. We remind commenters that R-codes are codes describing symptoms, signs, and abnormal clinical and laboratory findings, not elsewhere classified) and are generally not allowed as a principal diagnosis (except for a few) in accordance with ICD-10-CM coding guidelines. Any changes to the acceptable principal diagnosis list for home health, including the addition of new ICD-10 codes, would have to go through notice and comment rulemaking. (1) Clinical Group Reassignment of Certain Unspecified Diagnosis Codes We reminded readers that in the CY 2019 HH PPS 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 Start Printed Page 66810 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 all the ICD-10-CM diagnosis codes where “unspecified” is used and not just the ones listed on the new MCE edit. We identified 159 ICD-10-CM diagnosis codes that are 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 stated that we believe these 159 ICD-10 CM diagnosis codes are not acceptable as principal diagnoses and we proposed 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 [] 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 proposed to reassign these two ICD-10-CM diagnosis codes' clinical groups as shown in Table 6. Table 6—Reassignment of Clinical Group for “Unspecified” ICD-10-CM Diagnosis Codes Comment. Several commenters were concerned about the proposal to reassign the 159 ICD-10-CM codes to no clinical group (NA) when listed as a principal diagnosis. Commenters stated that only 45 of the 159 ICD-10-CM codes were listed on the MCE 20 list of unacceptable principal diagnoses and that the home health Grouper would be inconsistent with the other MCE edits. While commenters agreed the most specific documentation should be reflected in medical records to assign the most specific code available, they noted that there are certain circumstances in which an unspecified code should be accepted as a principal diagnosis according to the MCE manual and ICD-10-CM Official Guidelines for Coding and Reporting.[] In addition, commenters stated that obtaining additional information may be burdensome to certain HHAs.

Response. We thank interested parties for their comments. As we noted in the CY 2023 HH PPS proposed rule and previously in this final rule, we did not limit our review of unspecified codes only to those on the MCE edit list. Instead, the release of the MCE 20 edit prompted our review of all unspecified codes currently assigned to a clinical group when listed as a principal diagnosis. We also recognize the desire for a consistent unspecified edit for all health care entities.

However, this is not feasible given the vast differences across Medicare benefits and their associated payment systems. As such, CMS has created different groupers to institute edits to a specific program. For example, home health uses the Home Health Resource Group (HHRG), while inpatient rehabilitation facilities use Case Mix Group (CMG), both of which are different from the inpatient and outpatient grouper software. We acknowledge the ICD-10-CM Official Guidelines for Coding and Reporting Section I.B.18 states “If a definitive diagnosis has not been established by the end of the encounter, it is appropriate to report codes for sign(s) and/or symptom(s) in lieu of a definitive diagnosis. When sufficient clinical information is not known or available about a particular health condition to assign a more specific code, it is acceptable to report the appropriate “unspecified” code (for example, a diagnosis of pneumonia has been determined, but not the specific type).

Unspecified codes should be reported when they are the codes that most accurately reflect what is known about the patient's condition at the time of that particular encounter.” However, as previously stated in the CY 2019 HH PPS final rule with comment period (83 Start Printed Page 66811 FR 56473) and the CY 2023 HH PPS proposed rule, “unspecified” codes are used when the record lacks information about location or severity of medical conditions 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. Of the proposed 159 ICD-10-CM diagnosis codes, 85 percent (136 codes) lacked information about location (that is, laterality) while the remaining 15 percent (23 codes) lacked information about severity. We understand commenters concerns that many home health visits may be subsequent to the initial injury or disease and the medical record may lack information. However, we still believe this supports the need for more specific codes in order for the provider to appropriately provide services in alignment with the plan of care. In addition, per the FY 2022 IPPS/LTCH final rule (86 FR 44943), if, upon review, additional information to identify the laterality from the available medical record documentation by any other clinical provider is unable to be obtained, or there is documentation in the record indicating that the physician is clinically unable to determine the laterality because of the nature of the disease/condition, then the provider must enter that information into the remarks section.

If there is no language entered into the remarks section as to the availability of additional information to specify laterality and the provider submits the claim for processing, the claim would then be returned to the provider. While Medicare systems may allow an edit to be bypassable (for example, the NOA timelines extension), it does not currently allow an unacceptable home health principal diagnosis to be bypassable. We may consider adding certain additional edits as bypassable in future rulemaking. In response to the 15 codes where more specific codes identify severity, rather than laterality, we further evaluated if a more specific code would be appropriate in determining the plan of care and home health services required. We determined that 11 of the codes not only had more specific codes, but there are similar unspecified codes in the same subchapter which we do not accept as a principal diagnosis.

For example, for pregnancy-related codes, we expect the trimester to be specified. However, based on comments and further review we determined the four codes listed in Table 7 below should remain with their current assigned clinical group when listed as a principal diagnosis as we believe the information in these codes is sufficient to establish a home health plan of care to address such conditions. Table 7—Unspecified Diagnosis Codes Remaining in Clinical Groups Final Decision. After consideration of the public comments received, we are modifying our proposal of the 159 ICD-10 CM “unspecified” diagnosis codes to be reassigned to N/A by excluding the four codes listed in Table 7. Instead we are finalizing the reassignment of the remaining 155 ICD-10 CM diagnosis codes from their current assigned clinical group to NA when the codes are listed as a principal diagnosis.

We remind readers that if a claim cannot be assigned a clinical group, the claim will be returned to the provider for further information. We are also finalizing the reassignment of B78.9 (strongyloidiasis, unspecified) from clinical group C (Wounds) to clinical group K (MMTA—Infectious Disease, Neoplasms, and Blood-Forming Diseases) and the reassignment of N83.201 (unspecified ovarian cyst, right side) from clinical group A (MMTA-Other) to clinical group J (MMTA—Gastrointestinal Tract and Genitourinary System) when listed as the principal diagnoses. We urge interested parties to review the final HH Clinical Group and Comorbidity Adjustment Diagnosis list released with this final rule, as well as the 3M Grouper January 2023 HH PPS Grouper Software HH PDGM v04.0.23, when determining if an ICD-10 CM diagnosis code is accepted as a principal diagnosis and assigned a clinical group. (2) 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 Start Printed Page 66812 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 did not receive comments on this proposal and therefore are finalizing the reassignment of these 144 gout-related ICD-10-CM diagnosis codes to clinical group E (musculoskeletal rehabilitation) without modification. (3) 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 8. Table 8—ICD-10-CM Diagnosis Codes Related to Crushing Injury of Face, Skull, and Head 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 B that describe injuries requiring neurological rehabilitation.

We did not receive comments on this proposal and therefore are finalizing the reassignment of the ICD-10-CM diagnosis codes listed in Table 8 from clinical group A (MMTA-Other) to clinical group B (Neurological Rehabilitation) without modification. (4) 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 9. Table 9—ICD-10-CM Diagnosis Code Related to Lymphedema 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 proposed to reassign the ICD-10-CM diagnosis codes listed in Table 9 from clinical group E (Musculoskeletal Rehabilitation) and clinical group A (MMTA-Other) to clinical group C (Wounds). Comment. Several commenters questioned whether the reassignment of lymphedema to clinical group C (wounds) would impact the type of practitioner who would be able to treat the wound or limit patient access to resources such as complete decongestive therapy including manual lymph drain Response.

We thank the commenters for their concern. The reassignment of lymphedema, or any other code, would not impact the type of practitioner providing services, as long as the allowed practitioner can perform the care under their scope of practice. In addition, per the CoPs, HHAs should continue to provide services in accordance with the plan of care. Start Printed Page 66813 Comment. A commenter questioned if CMS considers lymphedema a wound type and if we believe lymphedema is correlated to venous disease/wounds.

Response. Although CMS does not consider lymphedema to be a wound type, we believe clinically that the home health services needed to treat and manage lymphedema are equivalent to the time and services needed for managing an open wound regardless of the precipitating condition that resulted in lymphedema. Treatment for lymphedema focuses on reducing swelling and minimizing complications. As such, treatment could involve exercises, manual lymphatic drainage, compression bandages or garments, sequential pneumatic compression, and even wound care for any skin breakdown. Because the home health treatments can be similar in terms of care and intensity of care, we believe lymphedema and wounds are appropriate to be grouped together for clinical groupings.

Final Decision. After consideration of the public comments we received, we are finalizing the reassignment of 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) 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.

We did not receive comments on this proposal, and therefore are finalizing the reassignment of diagnosis code F60.5 to behavioral 5 when listed as a secondary diagnosis. (6) 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.

Therefore, 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 proposed to assign diagnosis code Q82.0 to circulatory 10 (varicose veins and lymphedema) when listed as a secondary diagnosis. Final Decision. We received a comment in support of this assignment.

Therefore, we are finalizing the assignment of Q82.0 (hereditary lymphedema) from “NA” to circulatory 10 (varicose veins and lymphedema) when listed as a secondary diagnosis. (7) 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 10. Table 10—ICD-10-CM Diagnosis Code Related to Malignant Neoplasms of Upper Respiratory Tract Our clinical advisors reviewed the codes listed in Table 10 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 10 should be reassigned Start Printed Page 66814 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. We did not receive comments on this proposal and therefore are finalizing the reassignment of 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. We did not receive comments on this proposal and therefore are finalizing the reassignment of 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) 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 proposed 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 proposed 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”. Comment. A few commenters supported the creation of the neurological subgroup for nondiabetic neuropathy. Response. We thank the commenters for their support.

Final Decision. After consideration of the public comments we received, we are finalizing a new neurological comorbidity subgroup, neurological 12 (nondiabetic neuropathy), and reassigning 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 neurological 12 (nondiabetic neuropathy). We did not receive comments on the proposal to change the description of the comorbidity subgroup, neurological 11, and are therefore finalizing neurological 11, from “Diabetic Retinopathy and Macular Edema” to “Disease of the Macula and Blindness/Low Vision”. (9) 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. We did not receive comments on this proposal and therefore are finalizing the reassignment of 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. We did not receive comments on this proposal and therefore are finalizing the reassignment Start Printed Page 66815 of diagnosis codes J98.2 and J98.3 to respiratory 4 when listed as a secondary diagnosis. (iii) U09.9 Post erectile dysfunction treatment Condition, Unspecified Our clinical advisors reviewed the ICD-10-CM diagnosis code U09.9 (post erectile dysfunction treatment condition, unspecified), which is currently assigned to the comorbidity subgroup, respiratory 2 (whooping cough and pneumonia). However, respiratory 10 (2019 novel erectile dysfunction) contains other erectile dysfunction treatment 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. We did not receive comments on this proposal and therefore are finalizing the reassignment of diagnosis code U09.9 to respiratory 10 when listed as a secondary diagnosis. 4. CY 2023 PDGM LUPA Thresholds and PDGM Case-Mix Weights a. 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 with comment period (83 FR 56492), we finalized setting the LUPA thresholds 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 final 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 HH PPS final rule (85 FR 70305 through 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 erectile dysfunction treatment PHE would have impacted utilization within all case-mix groups similarly. Therefore, the impact of any reduction in resource use caused by the erectile dysfunction treatment 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 erectile dysfunction treatment 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 proposed 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 proposed to update the LUPA thresholds for CY 2023 using data from CY 2021. The final 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 solicited public comments on the proposed updates to the LUPA thresholds for CY 2023. The public comments on our proposal to recalibrate the LUPA thresholds for CY 2023 payment purposes and our responses are summarized in this section of the rule.

Comment. A commenter expressed concern regarding the proposal to recalibrate the LUPA thresholds using CY 2021 utilization data. This commenter stated that while the observed changes in the recalibrated thresholds may not seem large, they could serve as evidence that visits during 2020 and 2021 may well be reduced (when compared to pre-PDGM levels) due to kamagra influence. Response. We acknowledge the commenter's statement and concerns regarding the potential impact of the erectile dysfunction treatment PHE on home health utilization in CYs 2020 and 2021.

However, we continue to believe that it is important to base the LUPA thresholds on actual PDGM utilization data and shift away from the use of data prior to the implementation of the PDGM. Using the most recent data ensures that payment aligns with the most recent cost of providing home health care services. Comment. A commenter recommended that CMS reduce the LUPA threshold in CY 2023 for all case-mix groups to two visits and reassess the impact using CY 2023 data before making any further adjustments. Response.

We thank the commenter for this recommendation. However, this recommendation is out of scope for the CY 2023 HH PPS proposed rule. In the CY 2019 HH PPS final rule with comment period (83 FR 56492), we finalized setting the LUPA thresholds at the 10th percentile of visits or 2 visits, whichever is higher, for each payment group. Any changes to the LUPA threshold policy beyond the proposal to recalibrate the thresholds using the CY 2021 utilization data would need to go through notice and comment rulemaking. Start Printed Page 66816 Final Decision.

We are finalizing the proposal to update the LUPA thresholds for CY 2023. The LUPA thresholds for CY 2023 are located in table 16 and will also be available on the HHA Center web page. 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 proposed 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 web page 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 proposed 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 11 and 12, respectively. We solicited public comments on the updates to functional points and the functional impairment levels by clinical group. Table 11—Final Oasis Points Table for CY 2023 Start Printed Page 66817 Start Printed Page 66818 Table 12—Final Thresholds for Functional Levels by Clinical Group, for CY 2023 Start Printed Page 66819 Start Printed Page 66820 Comment. Some commenters were concerned that changes caused by recalibration were reducing resources to home health agencies.

Commenters argued that since the CY 2022 rates were recalibrated, it should not be done again prior to the availability of the CY 2022 data. Commenters were particularly concerned that changes to the functional impairment points and thresholds did not account for the higher acuity patients they have treated in recent years. Response. It is important to note that recalibration is calculated so that changes to case-mix and related items (for example, functional points) are budget neutral. The adjustments made to functional points, functional threshold levels, comorbidities, LUPA thresholds, and case-mix weights are made so that after the application of the case-mix budget neutrality factor, recalibration does not have any impact on aggregate payments when using data from CY 2021.

Recalibration ensures there is variation in payment between the 432 case-mix groups so that those groups with lower resource use get paid less than those with higher resource use. If we did not adjust the functional points, functional threshold levels, comorbidities, LUPA thresholds, and case-mix weights to reflect resource utilization, then payments would be less accurate. Specifically, if we did not account for changes in functional points, we could potentially pay the same for the low functional impairment patients and the high functional impairments patients (who have more resources associated with their visits). If that occurred, and since payment would be adjusted in a budget neutral way, this could mean we would be overpaying for low functional impairment and underpaying for high functional impairment. Functional points, functional threshold levels, comorbidities, LUPA thresholds and case-mix weights can be impacted even if there are no changes in coding patterns but there are changes in resource use.

In the CY 2019 HH PPS final rule with comment period (83 FR 56486), we stated that after implementation of the PDGM in CY 2020, we would continue to analyze the impact of all of the PDGM case mix variables to determine if any additional refinements need to made. We continue to believe that updating the functional impairment levels using current data ensures that all variables used as part of the overall case-mix adjustment appropriately align home health payment with the actual cost of providing home health care services. Performing a yearly recalibration allows us to be as accurate and up-to-date as possible when measuring relationship between resource use and functional points, functional threshold levels, comorbidities, LUPA thresholds and case-mix weights. The most recent year of data that we have is CY 2021. We feel that relationships seen in the CY 2021 data are going to be more similar to the relationships that we will eventually in see in CY 2023 data versus if we continued to use the relationships we see in the CY 2020 data.

Commenters should note that although functional points did decrease for many items, the functional thresholds also decreased (meaning fewer points are needed to qualify for the higher functional impairment levels). Comment. Some commenters were concerned that CMS grouped patients into one of three functional impairment levels even if it meant potentially reducing resources to patients who previously would have been classified as medium or high functional impairment. Response. We remind commenters that the recalibration is implemented in a budget neutral manner.

We set the functional levels so roughly a third of periods within each clinical group are assigned to low, medium, and high. This is done to ensure that the case-mix system pays appropriately for differences in functional impairment level. If all 30-day periods ended up in one functional impairment level then we'd be paying the same for the low functional impairment patients and the high functional impairment patients (who have more resources associated with their visits). We believe that the functional impairment level adjustment adequately captures the level of functional impairment based on patient characteristics reported on the OASIS. The PDGM not only uses the same five OASIS items used under the previous HH PPS to determine the functional case-mix adjustment (M1810, M1820, M1830, M1830, M1850, and M1860), but also adds two additional OASIS items (M1800 and M1033) to determine the level of functional impairment.

The structure of categorizing functional impairment into low, medium, and high levels has been part of the home health payment structure since the implementation of the HH PPS. The previous HH PPS grouped home health episodes using functional scores based on functional OASIS items with similar average resource use within the same functional level, with approximately a third of episodes classified as low functional score, a third of episodes classified as medium functional score, and a third of episodes classified as high functional score. Likewise, the PDGM groups home health periods of care using functional impairment scores based on functional OASIS items with similar resource use and has three levels of functional impairment severity. Low, medium, and high. However, the PDGM differs from the current HH PPS functional variable in that the three functional impairment level thresholds in the PDGM vary between the clinical groups.

The PDGM functional impairment level structure accounts for the patient characteristics within that clinical group associated with increased resource costs affected by functional impairment. This is to further ensure that payment is more accurately aligned with actual patient characteristics and resource needs. Comment. A commenter indicated that Table B21 in the CY 2023 HH PPS proposed rule (87 FR 37627) showed that a lower functional impairment response was associated with more points than a higher functional impairment response (M1860 responses 2 and 3). Response.

For recalibration, we use the data as they are submitted. Home health agencies should consider the appropriateness of their OASIS responses in relation to the level of resources that should be required for certain functional impairments. CMS would expect to find, on average, that patients who are more functionally impaired would have higher resource use. However, as noted by the commenter, this correlation does not always occur when looking at individual OASIS items and responses. Final Decision.

We are finalizing to update the functional points and functional impairment levels for CY 2023 as proposed, using CY 2021 claims data. Table 11 includes the final functional points based on the most available data. 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. Start Printed Page 66821 • 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 proposed 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 proposed to update the comorbidity subgroups to include 23 low comorbidity adjustment subgroups and 94 high comorbidity adjustment interaction subgroups. The final update to the comorbidity adjustment subgroups includes 22 low comorbidity adjustment subgroups as identified in table 13 and 91 high comorbidity adjustment interaction subgroups as identified in table 14. The final 22 low comorbidity adjustment subgroups and 91 high comorbidity adjustment interactions reflect the final coding changes detailed in section II.B.3.c. Of this final rule. The final 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 web page at https://www.cms.gov/​Center/​Provider-Type/​Home-Health-Agency-HHA-Center.

We invited comments on the proposed updates to the low comorbidity adjustment subgroups and the high comorbidity adjustment interactions for CY 2023. Table 13—Low Comorbidity Adjustment Subgroups for CY 2023 Start Printed Page 66822 Table 14—High Comorbidity Adjustment Interactions for CY 2023 Start Printed Page 66823 Start Printed Page 66824 Start Printed Page 66825 Start Printed Page 66826 Start Printed Page 66827 Start Printed Page 66828 Comment. A commenter expressed support for the proposed updates to the low and high comorbidity subgroups. This commenter stated that the changes achieve the stated goal of ensuring that payment is in alignment with the actual costs of providing care and that the high comorbidity adjustment interaction subgroups acknowledge the impact of multiple diagnoses on care delivery complexity and cost. Response.

We thank the commenter for their support. Final Decision. We are finalizing the proposal 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, the final update to the comorbidity adjustment subgroups includes 22 low comorbidity adjustment subgroups as identified in Table 13 and 91 high comorbidity adjustment interaction subgroups as identified in Table 14. The final 22 low comorbidity adjustment subgroups and 91 high comorbidity adjustment interactions reflect the final coding changes detailed in section II.B.3.c.

Of this final rule. 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 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, as outlined in that rule, 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 were updated based on more complete CY 2021 claims data for this 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 Start Printed Page 66829 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 15 shows the coefficients of the payment regression used to generate the weights, and the coefficients divided by average resource use. Table 15—Coefficient of Payment Regression and Coefficient Divided by Average Resource Use Start Printed Page 66830 Start Printed Page 66831 The case-mix weights proposed for CY 2023 are listed in Table 16 and will also be posted on the HHA Center web page [] upon display of this final rule. Table 16—Final Case-Mix Weights and LUPA Thresholds for Each HHRG Payment Group Start Printed Page 66832 Start Printed Page 66833 Start Printed Page 66834 Start Printed Page 66835 Start Printed Page 66836 Start Printed Page 66837 Start Printed Page 66838 Start Printed Page 66839 Start Printed Page 66840 Start Printed Page 66841 Start Printed Page 66842 Start Printed Page 66843 Start Printed Page 66844 Start Printed Page 66845 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 erectile dysfunction treatment 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 erectile dysfunction treatment 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 Start Printed Page 66846 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 0.9904. We invited comments on the CY 2023 proposed case-mix weights and proposed case-mix weight budget neutrality factor and these are summarized below. Comment. A few commenters expressed support for the proposal to recalibrate the PDGM case-mix weights for CY 2023 using CY 2021 utilization data.

Response. We thank the commenters for their support. Comment. Several commenters were opposed to the proposal to recalibrate the PDGM case-mix weights for CY 2023. A commenter expressed concerns about the influence of the erectile dysfunction treatment surges and its overall effects on the types of patients being served.

This commenter recommended not updating the case-mix weights at this time and resuming this practice once the kamagra is over. Response. CMS appreciates the comments received regarding CY 2021 utilization trends and the impact of the erectile dysfunction treatment PHE on the provision of home health services. We recognize that commenters have concerns regarding how the erectile dysfunction treatment PHE affected the type of home health patients served as well as care practices. However, as stated in the CY 2023 HH PPS proposed rule (87 FR 37626), we believe that visit patterns have stabilized as our data analysis indicates that visits in 2021 were similar to visits in 2020.

As such, we believe that CY 2021 data will be indicative of visit patterns in CY 2023. In the CY 2019 HH PPS final rule, we finalized our proposal to annually recalibrate the PDGM case-mix weights (83 FR 56515) to reflect the most recent utilization data available at the time of rulemaking. We continue to believe that the annual recalibration of the HH PPS case-mix weights ensures that the case-mix weights reflect, as accurately as possible, current home health resource use, changes in utilization patterns, and reflects the types of patients currently receiving home health services. We believe that prolonging recalibration could lead to more significant variation in the case-mix weights than what is observed using CY 2021 utilization data. Therefore, we believe that utilizing CY 2021 data to recalibrate the CY 2023 case-mix weights is appropriate.

Comment. A commenter recommended that any recalibration should be done in a non-budget-neutral manner given the higher-acuity patients, increasing expenses, increased demand for care, and increased shortage of labor. Response. We thank the commenter for this recommendation. However, consistent with our established policy, we apply a case-mix budget neutrality factor to the CY 2023 national, standardized 30-day period payment rate to ensure that there are no changes in aggregate payments due to the recalibration.

Final Decision. We are finalizing the recalibration of the HH PPS case-mix weights as proposed for CY 2023. We are also finalizing the proposal to implement the changes to the PDGM case-mix weights in a budget neutral manner by applying a case-mix budget neutrality factor to the CY 2023 national, standardized 30-day period payment rate. As stated previously, the final case-mix budget neutrality factor for CY 2023 will be 0.9904. 5.

CY 2023 Home Health Payment Rate Updates a. 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 home health 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 was 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 proposed CY 2023 home health market basket update of 3.3 percent was then reduced by a productivity adjustment, as mandated by the section 3401 of the Affordable Care Act, which at the time of the proposed rule was estimated to be 0.4 percentage point for CY 2023. In effect, the proposed home health payment update percentage for CY 2023 was 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 was proposed to be 0.9 percent (2.9 percent minus 2 percentage points). In the CY 2023 HH PPS proposed rule we stated that if more recent data became available after the publication of the Start Printed Page 66847 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. The following is a summary of the public comments received on the CY 2023 annual payment update and our responses. Comment.

A few commenters supported the positive market basket payment update of 2.9 percent. Several commenters opposed the proposed update of 3.3 percent reduced by 0.4 percent productivity adjustment stating it falls short of real-life cost inflation and is insufficient to cover their costs. Commenters noted that home health agencies are struggling with recruitment and retention of staffing and increased costs of staffing due to tight labor markets and paying for sick leave for erectile dysfunction treatment, as well as with increased costs of supplies and equipment (as a result of supply chain shortages), and overall higher inflation. Commenters also noted that home health agencies are struggling to compete for staffing with hospitals that received large amounts of relief funding for erectile dysfunction treatment and offer large sign-on bonuses. A few commenters noted that there are changes impacting the home health PPS that will require additional resources such as OASIS and EVV monitoring and suggested that payment increases are not keeping pace with inflation.

Several commenters stated cost inflation is at a 40-year high and HHAs report continuing labor cost increases in second quarter 2022 and third quarter 2022 that range from 7 to 12 percent. A commenter noted that a recent survey conducted by Dobson &. Davanzo found higher labor cost growth than is reflected in the proposed market basket index, along with a significantly greater nurse labor cost increase as determined by the U.S. Department of Labor, Bureau of Labor Statistics (BLS) average hourly earnings for home health industry, which showed year-over-year growth in the first quarter of 2022 of 5.2 percent. With labor representing 75 percent of home health costs, commenters stated the proposed market basket index is less than half of actual labor cost increases.

In addition, they noted HHAs, unlike many other health care sectors, are hard hit with transportation cost increases—either directly due to vehicle acquisition and gasoline costs or by higher reimbursement rates. With an estimated 7.8 billion miles driven each year, they noted that HHAs face transportation cost increases alone that may exceed the proposed market basket index increase. They stated CMS has the authority to modify its market basket index calculation methodology, stating section 1895(b)(3)(B)(iii) of the Act offers significant discretion to the Secretary to account for cost increases specifically related to “the mix of goods and services included in home health service.” They noted that labor and transportation costs are within the scope of home health services. The commenters stated that the recent market basket index increases for hospitals, SNFs, and hospices is a positive indication that CMS will raise the market basket index in the final rule. However, they stated the increases seen in the other sectors remain short of what HHAs report as actual cost increases in 2022.

Several commenters requested that CMS use the most recent BLS data, and where sector specific data is not recent, use CPI data to determine the market basket increase. Commenters urged CMS to provide a home health market basket update comparable to what was finalized in the fiscal year payment rules, which used IHS Global Inc.'s second quarter forecast. A commenter requested that CMS exercise any additional authorities to ensure market basket updates are based on data that is consistent with what is occurring in the overall economy. A few commenters noted that they believe home health agencies should be getting a 6 percent increase for inflation. A commenter requested that CMS propose an inflation adjustment to enable best practices and allow agencies to continue to provide a high level of care.

Commenters stated that the low reimbursement rates would be detrimental to patient care and may cause HHA closures. Response. We believe the 2016-based home health market basket increase adequately reflects the average change in the price of goods and services hospitals purchase in order to provide HHA medical services, and is appropriate to use as the HHA payment update factor. As described in the CY 2019 HH PPS final rule with comment period (83 FR 56425 through 56436), the home health market basket (similar to the other CMS market baskets) is a fixed-weight, Laspeyres-type index that measures price changes over time and would not reflect increases in costs associated with changes in the volume or intensity of input goods and services. As such, the home health market basket update would reflect the prospective price pressures for the types of inputs described by the commenters (such as labor or wage growth and transportation costs), but would inherently not reflect other factors that might increase the level of costs, such as the quantity of labor used or any changes in occupation (such as the decreased use of home health aides).

We note that cost changes (that is, the product of price and quantities) would only be reflected when a market basket is rebased and the base year weights are updated to a more recent time period. At the time of the CY 2023 HH PPS proposed rule, based on IHS Global Inc.'s first quarter 2022 forecast with historical data through the fourth quarter of 2021, IGI forecasted the 2016-based home health market basket update of 3.3 percent for CY 2023 reflecting forecasted compensation price growth of 3.8 percent (by comparison, compensation price growth in the home health market basket averaged 2.3 percent from 2012-2021). In the CY 2023 HH PPS proposed rule, we proposed that if more recent data became available, we would use such data, if appropriate, to derive the final CY 2023 home health market basket update for the final rule. For this final rule, we now have an updated forecast of the price proxies underlying the market basket that incorporates more recent historical data and reflects a revised outlook regarding the United States economy and expected price inflation for CY 2023 for HHAs (including upward revision to the price growth as compared to the proposed rule for compensation and transportation). Based on IHS Global Inc.'s third quarter 2022 forecast with historical data through the second quarter of 2022 (and reflecting forecasted data for the third quarter of 2022 through fourth quarter of 2023), the final CY 2023 home health market basket update is 4.1 percent (reflecting forecasted compensation price growth of 4.4 percent) and the final CY 2023 productivity adjustment is 0.1 percentage point.

Therefore, for CY 2023, the final home health productivity-adjusted market basket update of 4.0 percent (4.1 percent less 0.1 percentage point) will be applicable, compared to the 2.9 percent productivity-adjusted market basket update that was proposed. We note that the final CY 2023 home health market basket growth rate of 4.1 percent would be the highest market basket increase we have implemented in a final rule since the beginning of the HH PPS. We acknowledge the commenters' concern regarding the tight labor market and competing with hospitals and skilled nursing facilities for labor. For the compensation cost weight in the 2016-based home health market basket (which includes salaried and contract Start Printed Page 66848 labor employees), we use a blend of Employment Cost Indexes (ECI) for wages and salaries and benefits to proxy the price increases of labor for HHAs. The blend of ECIs reflects the occupational composition of HHA staff as measured by the National Industry-Specific Occupational Employment and Wage estimates for North American Industrial Classification System (NAICS) 621600, Home Health Care Services, published by the BLS Office of Occupational Employment Statistics (OES).

A more detailed discussion can be found in the CY 2019 HH PPS final rule with comment period (83 FR 56429). For the Health-Related Professional and Technical workers compensation costs (accounting for 26 percent of the 2016-based home health market basket and including, but not limited to, registered nurses and therapists) we use the ECIs for All Civilian workers in Hospitals as the price proxies. For the Health and Social Assistance Services workers compensation costs (accounting for 27 percent of the 2016-based home health market basket and including, but not limited to, home health aides and licensed practical nurses) we use the ECIs for All Civilian workers in Health Care and Social Assistance. Each of these price proxies reflects the forecasted price factors affecting the labor occupations across the health sector, including those for hospital workers and others that are in high demand. While we appreciate the commenter's recommendation for CMS to exercise any additional authorities to ensure market basket updates are based on data that is consistent with what is occurring in the overall economy, we note that 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.

Additionally, section 1895(b)(3)(B) of the Act requires that in CY 2015 and in subsequent calendar years, 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. Therefore, we do not have additional authority to apply an update to the home health payments beyond what is set out in statute. Comment. Several commenters expressed concerns over the final CY 2022 home health market basket update and the latest CY 2022 market basket forecast. Commenters noted that with more recent data, the market basket for CY 2022 is trending toward 5.0 percent, well above the 3.1 percent HH PPS update implemented in the CY 2022 HH PPS final rule.

Several commenters requested CMS adjust 2022 base rates to conform to actual cost inflation in 2022 that exceeds the 2022 market basket index as was done for SNFs. Response. The commenter seems to be referring to the market basket forecast error adjustment that was implemented in the FY 2023 SNF PPS final rule. However, that forecast error adjustment was to adjust for the difference between actual SNF market basket increase for FY 2021 and the final SNF market basket increase for FY 2021. However, as the commenter is referring to 2022 inflation and not 2021 inflation, it is not clear what the commenter is suggesting.

The HH PPS market basket updates are required by law to be set prospectively, which means that the update relies on a mix of both historical data for part of the period for which the update is calculated and forecasted data for the remainder. There is currently no mechanism to adjust for market basket forecast error in the HH PPS payment update. Comment. A commenter stated the market basket update of 3.3 percent was inadequate due to use of the ECI to update labor costs. They stated the ECI does not include the costs of contracted health care providers which was a key driver of surging input costs.

The commenter stated that by excluding costs related to contracted labor, CMS has dramatically underestimated the true cost of providing care and urged CMS to conduct a one-time forecast error correction to the market basket to adequately capture the true costs of providing care. A commenter stated that they have to rely on more contract labor, which has resulted in increased costs per visit as their contractors charged more per visit. Response. For the compensation cost weight in the 2016-based home health market basket (which includes salaried and contract labor employees), we use a blend of ECIs for wages and salaries and benefits to proxy the price increases of labor for HHAs (for more details see the CY 2019 HH PPS final rule (83 FR 56429). The ECIs (published by the BLS) measure the change in the hourly labor cost to employers, independent of the influence of employment shifts among occupations and industry categories.

We note that the Medicare cost report data shows contract labor costs account for about 7 percent of total compensation for HHAs in 2020, compared to about 10 percent in the 2016-based home health market basket. Data through 2021 are incomplete at this time. Therefore, while we acknowledge that the ECI only reflects price changes for employed staff, we believe that the blended ECIs used in the home health market basket are accurately reflecting the price change associated with the labor used to provide home health services (as employed workers' costs account for 93 percent of HHA compensation costs) and appropriately does not reflect other factors that might affect labor costs. Therefore, we believe it continues to be an appropriate measure to use in the home health market basket. We also note that based on IGI's third quarter 2022 forecast with historical data through second quarter 2022, compensation price growth (using the ECIs) for CY 2023 is now projected to be 4.4 percent, which is 0.6 percentage point higher than projected price growth at the time of the CY 2023 HH PPS proposed rule (3.8 percent) and 2.1 percentage points higher than the historical average from 2012 through 2021.

Comment. Several commenters were concerned about the proposed reduction for productivity. A commenter requested that CMS also elaborate in the final rule on the specific productivity gains that are the basis for the proposed 0.4 percent productivity offset as the latest data actually indicate decreases in productivity, not gains. Another commenter stated that they believe the assumptions underpinning the productivity adjustment are fundamentally flawed as it assumes that HHAs can increase overall productivity—producing more goods with the same or fewer units of labor input—at the same rate as increases in the broader economy. However, the commenters stated that providing home-based care to patients is highly labor intensive and therefore, they strongly disagreed with the continuation of this punitive policy—particularly during the PHE.

They stated that given that CMS is required by statute to implement a productivity adjustment to the market basket update, they ask the agency to work with Congress to permanently eliminate this unjustified reduction in home health payments. Response. Section 1895(b)(3)(B) of the Act requires the market basket percentage under the HH PPS, 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 (as projected by the Secretary for the 10-year period ending Start Printed Page 66849 with the applicable fiscal year, year, cost reporting period, or other annual period). Therefore, we do not have the authority to eliminate the productivity adjustment.

For the CY 2023 HH PPS proposed rule, based on IGI's first quarter 2022 forecast, the productivity adjustment was projected to be 0.4 percentage point for CY 2023. For this final rule, based on IGI's third quarter 2022 forecast, we are incorporating a revised productivity adjustment that reflects more recent historical total factor productivity data as published by BLS through 2021 (previously published by BLS as multifactor productivity) as well as a revised economic outlook for CY 2022 and CY 2023 (including the negative labor productivity quarterly growth rates in the first half of 2022). Using this more recent forecast, the CY 2023 productivity adjustment based on the 10-year moving average growth in economy-wide total factor productivity for the period ending CY 2023 is currently estimated to be 0.1 percent. Comment. A commenter stated that while some of the increased costs due to the kamagra, structural changes in staffing costs and general inflation, may be captured in the proposed market basket update, it does not track with the realized increase of costs of providing quality healthcare.

This commenter also noted that the most recent annual inflation rate for the United States is 9.1 percent. The commenter stated that the proposed home health market basket update for CY 2023 is not keeping pace with the national rate of inflation and is woefully inadequate. They urged CMS to discuss the impact of this disparity in the final rule. Response. As required in section 1895(b)(4)(B)(iii) of the Act, the home health market basket reflects the average change in the price of goods and services HHAs purchase in order to provide medical services.

While the Consumer Price Index (CPI) All Items Urban (BLS' measure of overall inflation for the U.S. Referenced by the commenter) is also a fixed-weight, Laspeyres-type index that measures price changes over time, it reflects a market basket of consumer goods and services purchased by urban consumers. Thus, it is a measure of price change that does not reflect the mix of goods and services included in a home health service but instead reflects a mix of goods and services specific to consumers such as Shelter (33 percent), Food (13 percent), New and used vehicles (9 percent), and energy (7 percent), where the weights are based on relative importance for December 2021. Thus, there is not a direct one-to-one relationship between these two price indices and any disparity would appropriately reflect their different purposes. Comment.

A commenter stated the proposed market basket update does not reflect the increased cost of giving care, but also breaks from longstanding economic policy from the Department of Health and Human Services, citing that the last time that inflation was at this level, from 1979-1982, the then-Health Care Financing Administration, forerunners of CMS, provided a price index update of 11.5 percent in 1980, 11.5 percent in 1981, and 10 percent in 1983. The commenter suggested that CMS provide a home health full market basket adjustment that recognizes the dramatic increases in the cost of care. Response. As stated previously, the home health market basket measures price changes (similar to other CMS market baskets) over time and would not reflect increases in costs associated with changes in the volume or intensity of input goods and services. The price index updates cited by the commenter were implemented when CMS (formerly Health Care Financing Administration) reimbursed HHAs on a cost basis prior to the HH PPS.

Beginning in 2001, CMS implemented the HH PPS with annual updates being equal to the home health market basket percentage increase as stated in section 1895(b)(4)(B)(iii) of the Act, and effective beginning with 2015, reduced by the productivity adjustment described in section 1886(b)(3)(B)(xi)(II) of the Act. As noted previously, the final CY 2023 home health market basket growth rate of 4.1 percent would be the highest market basket increase we have implemented in a final rule since the beginning of the HH PPS. Final Decision. As proposed, we are finalizing our policy to use the most recent data to determine the home health payment update percentage for CY 2023 in this final rule. Based on IHS Global Inc.'s third-quarter 2022 forecast with historical data through second-quarter 2022, the home health market basket update is 4.1 percent.

The CY 2023 home health market basket update of 4.1 percent is then reduced by a productivity adjustment of 0.1 percentage point for CY 2023. For HHAs that submit the required quality data for CY 2022, the home health payment update is a 4.0 percent increase. For HHAs that do not submit the required quality data for CY 2023, the home health payment update is 2.0 percent (4.0 percent minus 2 percentage points). b. CY 2023 Home Health Wage Index (1) 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 proposed 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 proposed 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 proposed 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 proposed to continue to use the same methodology discussed in the CY 2007 Start Printed Page 66850 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 proposed 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 of the majority 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 proposed 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 proposed 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 proposed the CY 2023 wage index value for Hinesville, GA to be 0.8542. 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 0.8799. 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. The following is a summary of the comments received on the CY 2023 wage index and our responses. Comment. Several commenters recommended more far-reaching revisions and reforms to the wage index methodology used under Medicare fee-for-service.

A commenter recommended that CMS create a home health specific wage index as soon as possible. This commenter stated that CMS should discontinue the use of any other segment (for example, IPPS Hospitals) of healthcare as a proxy for home health and create a home health specific wage index that is based solely on the issues impacting the cost of labor and the ability to attract and retain quality staff to the home health industry. Additionally, one commenter suggested that CMS revisit MedPAC's 2007 proposal, which recommended that the Congress repeal the existing hospital wage index statute, including reclassifications and exceptions, and give the Secretary authority to establish new wage index systems. Other commenters recommended that CMS consider establishing a floor for home health wage indices, as it did for hospice in 1983, to establish equity in geographic adjustment among provider types. Response.

While we appreciate these recommendations, these comments are outside the scope of the proposed rule. Any changes to the way we adjust home health payments to account for geographic wage differences beyond the wage index proposals discussed in the CY 2023 HH PPS proposed rule (87 FR 37600), including the creation of a home health specific wage index and the creation of a home health floor would have to go through notice and comment rulemaking. The application of the hospice floor is specific to hospices and does not apply to HHAs. The hospice floor was developed through a negotiated rulemaking advisory committee, under the process established by the Negotiated Rulemaking Act of 1990 (Pub. L.

101- 648). Committee members included representatives of national hospice associations. Rural, urban, large, and small hospices. Multi-site hospices. Consumer groups.

And a government representative. The Committee reached consensus on a methodology that resulted in the hospice wage index. Because there is no home health floor and the hospice floor applies only to hospices, we continue to believe the use of the pre-floor and pre-reclassified hospital wage index results in the most appropriate adjustment to the labor portion of the home health payment rates. This position is longstanding and consistent with other Medicare payment systems (for example, SNF PPS, IRF PPS, and Hospice). Comment.

Several commenters recommended that CMS allow home health providers to utilize geographic reclassification similar to the provision Start Printed Page 66851 used for IPPS hospitals. These commenters expressed concern that home health providers are not afforded the same options to adjust their wage indices as hospitals, yet must compete for the same types of health care professionals. A commenter stated that home health agencies that serve Medicare beneficiaries in Maryland, but who compete for labor with acute care hospitals and other post-acute care providers in the Washington, DC-Virginia metropolitan area that pay average hourly wages that are approximately 11 percent higher than the average hourly wages paid by Maryland acute care hospitals, have had, and will continue to have, difficulty maintaining adequate staffing levels and delivering quality home health care at a time when reliance on these services is at an all-time high. This commenter stated that the negative impact of applying the pre-reclassification, pre-floor IPPS wage index to home health agencies, coupled with the inability of a home health agency to receive any adjustments to their wage index based on close proximity to a major metropolitan area in an adjacent state with which it competes for labor, is greatly exacerbated in Maryland, where acute care hospitals are subject to a capped payment system that limits the ability of such hospitals to increase wages from one year to the next. Response.

We thank the commenters for their recommendations. However, the reclassification provision at section 1886(d)(10)(C)(i) of the Act states that the Board shall consider the application of any subsection (d) hospital requesting the Secretary change the hospital's geographic classification. The reclassification provision found in section 1886(d)(10) of the Act is specific to IPPS hospitals only. Because the reclassification provision applies only to hospitals, we continue to believe the use of the pre-floor and pre-reclassified hospital wage index results in the most appropriate adjustment to the labor portion of the home health payment rates. This position is longstanding and consistent with other Medicare payment systems (for example, SNF PPS, IRF PPS, and Hospice).

Comment. A commenter stated that when fully phased in, the implementation of the $15 per-hour minimum wage increase, and the additional $2 per hour minimum wage increase for home health care aides which takes effect in October 2022 will cost over $4 billion for New York HHAs across all payors (Medicaid, Medicare, managed care, commercial insurance, and private-pay), and will never be adequately addressed due to CMS's ongoing disposition to continue using the pre-floor, pre-reclassified hospital wage index to adjust home health costs. Response. With regard to minimum wage standards, we note that such increases would be reflected in future data used to create the hospital wage index to the extent that these changes to State minimum wage standards are reflected in increased wages to hospital staff. Final Decision.

After considering the comments received in response to the proposed rule, and for the reasons discussed previously, we are finalizing our proposal to use the FY 2023 pre-floor, pre-reclassified hospital wage index data as the basis for the CY 2023 HH PPS wage index. The final CY 2023 wage index is available on the CMS website at. Https://www.cms.gov/​Center/​Provider-Type/​Home-Health-Agency-HHA-Center. (2) Permanent Cap on Wage Index Decreases As discussed in section II.B.5.b.1 of this final 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.

However, because we did not propose any transition policy in the CY 2022 HH PPS proposed rule, we did not extend the transition period for CY 2022. Instead, 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. Consistent with these principles, we considered how best to address potential 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 erectile dysfunction treatment- Start Printed Page 66852 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 proposed a permanent approach 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 by smoothing year-to-year changes in providers' wage indexes. 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 final 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 final 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 proposed 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 proposed 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 proposed 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 proposed 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. We received 47 comments on the proposed permanent cap on wage index decreases. Comment. The majority of commenters expressed support for the proposal to cap wage index decreases at 5 percent.

Response. We thank the commenters for their support of the proposed wage index cap policy. Comment. MedPAC expressed support for the wage index cap proposal, but recommended that the 5-percent cap also extend to wage index increases of more than 5 percent, such that no geographic area would have its wage index value increase or decrease by more than 5 percent in any given year. In addition, MedPAC recommended that the implementation of the revised relative wage index values (where changes are limited to plus or minus 5 percent) should be done in a budget-neutral manner.

Response. We appreciate MedPAC's suggestion that the cap on wage index changes of more than 5 percent should also be applied to increases in the wage index. However, as we discussed in the proposed rule, one purpose of the proposed policy is to help mitigate the significant negative impacts of certain wage index changes. As we noted in the CY 2023 HH PPS proposed rule (87 FR 37600), we believe applying a 5-percent cap on all wage index decreases would support increased predictability about home health payments for providers, enabling them to more effectively budget and plan their operations. That is, we proposed to cap decreases because we believe that a provider would be able to more effectively budget and plan when there is predictability about its expected minimum level of home health payments in the upcoming calendar year.

We did not propose to limit wage index increases because we do not believe such a policy would enable HHAs to more effectively budget and plan their operations. Rather, we believe it would be more appropriate to allow providers that would experience an increase in their wage index value to receive the full benefit of their increased wage index value. Comment. A few commenters recommended lowering the threshold percentage of the cap to percentages to 2 percent. In general, these commenters believe that lowering the cap would better allow HHAs to plan their operations.

Other commenters recommended that CMS finalize the permanent cap in a non-budget neutral way. Response. We believe that the 5-percent cap on wage index decreases is an adequate safeguard against any significant payment reductions and that lowering the cap on wage index decreases to 2 percent is not appropriate. We also believe that 5 percent is a reasonable level for the cap because it would more effectively mitigate any significant decreases in a HHA's wage index for future CYs, while still balancing the importance of ensuring that area wage index values accurately reflect relative differences in area wage levels. Additionally, we believe that a 5-percent cap on wage index decreases in CY 2023 and beyond is sufficient and provides a degree of predictability in payment changes for Start Printed Page 66853 providers.

And it would not be appropriate to implement the cap policy in a non-budget neutral manner. Our longstanding policy is to apply the wage index budget neutrality factor to home health payments to eliminate the aggregate effect of wage index updates and revisions, such as updates in the underlying hospital wage data as well as other proposed wage index policies, resulting in any wage index changes being budget-neutral in the aggregate. In the CY 2023 HH PPS proposed rule (87 FR 37600), we stated that 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. 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 factor for CY 2023 and we expect the impact to the wage index budget neutrality factor in future years will continue to be minimal. Comment.

Several commenters recommended CMS adopt a transition policy that treats affected home health agencies CY 2023 wage index as if a 5-percent cap had also been implemented for CY 2022, while other commenters requested that CMS retroactively apply the permanent wage index cap proposal to CY 2022 payments. Response. We thank commenters for these recommendations. In CY 2021 rulemaking, CMS proposed and finalized the one-year transition policy for CY 2021 only. We have historically implemented 1-year transitions, as discussed in the CY 2006 (70 FR 68132) and in the CY 2015 (79 FR 66032) final rules, to address CBSA changes due to substantial updates to OMB delineations.

Our policy principles with regard to the wage index are to use the most current data and information available. Therefore, we proposed that the CY 2023 HH PPS wage index policy would be prospective to mitigate any significant decreases beginning in CY 2023, not retroactively. As such, we did not calculate or propose the CY 2023 wage index as if the cap was in place for 2022. We note that we received comments on the CY 2022 HH PPS proposed rule requesting an extension to the one-year transition policy for CY 2021. However, because we did not propose this policy, or the wage index budget neutrality factor that we would have anticipated such a potential policy proposal to require in the CY 2023 HH PPS proposed rule, we did not propose a policy that treats affected HHAs CY 2023 wage index as if a 5-percent cap had also been implemented for CY 2022, or include any data and information that warrant the use of a cap for CY 2022 data in order to calculate the CY 2023 wage index.

While such a policy may benefit some providers, it would change the wage index budget neutrality factor, and would impact the CY 2023 payment rates for all providers without allowing them the opportunity to comment. Final Decision. CMS is finalizing, for CY 2023 and subsequent years, the application of 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 finalizing our policy 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 are codifying the permanent cap on wage index decreases in regulation at § 484.220(c).

As previously discussed, we believe this methodology will maintain the HH PPS wage index as a relative measure of the value of labor in prescribed labor market areas, increase predictability of home health payments for providers, and mitigate instability and significant negative impacts to providers resulting from significant changes to the wage index. In section II.B.5.c. Of this final rule, we estimate the impact to payments for providers in CY 2023 based on this policy. We also note that we will 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.

Start Printed Page 66854 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 final rule. As discussed in section II.B.2.f. Of this final rule, we are implementing a permanent behavior adjustment of−3.925 percent to prevent further overpayments. The permanent behavior adjustment factor is 0.96075 (1−0.03925). 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 case-mix weights budget neutrality factor for CY 2023 is 0.9904. 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 erectile dysfunction treatment 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 erectile dysfunction treatment 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 1.0001. We then apply the wage index budget neutrality factor of 1.0001 to the 30-day period payment rate. Next, we update the 30-day period payment rate by the CY 2023 home health payment update percentage of 4.0 percent. The CY 2023 national, standardized 30-day period payment rate is calculated in Table 17.

Table 17—CY 2023 National, Standardized 30-Day Period Payment Amount 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 4.0 percent minus 2 percentage points and is shown in Table 18. Table 18—CY 2023 National, Standardized 30-Day Period Payment Amount for HHAS That Do Not Submit the Quality Data Start Printed Page 66855 (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 home health discipline. The six home health 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 1.0007. 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 behavior adjustment to the per-visit payment rates but only the case-mix adjusted payment rate. 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 30-day periods that occur as the only 30-day period or the initial period in a sequence of adjacent 30-day periods. 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 4.0 percent and are shown in Table 19.

Table 19—CY 2023 National Per-Visit Payment Amounts 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 4.0 percent minus 2 percentage points and are shown in Table 20. Table 20—CY 2023 National Per-Visit Payment Amounts for HHAS That Do Not Submit the Required Quality Data Start Printed Page 66856 (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 $301.29 (1.8451 multiplied by $163.29), 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. We stated in the CY 2022 HH PPS final rule (86 FR 62289) that, as there is 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 will use 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).

D. 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. 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 Start Printed Page 66857 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 limited 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 (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 proposed an FDL ratio of 0.44 for CY 2023.

We noted that we would update the FDL, if needed, in the final rule once we have more complete CY 2021 claims data. Using more complete CY 2021 claims data (as of July 15, 2022), the final FDL ratio for CY 2023 would need to be 0.35 to pay up to, but no more than, 2.5 percent of the total payment as outlier payments in CY 2023. Final Decision. We did not receive any public comments on the proposed FDL ratio. We are finalizing the fixed-dollar loss ratio of 0.35 for CY 2023, in order to ensure that total outlier payments do not exceed 2.5 percent of the total aggregate payments, as required by section 1895(b)(5)(A) of the Act.

As noted previously, this updated ratio is based on more complete CY 2021 claims data than was used to determine the proposed FDL ratio. K. Comment Solicitation on the Collection of Data on the Use of Telecommunications Technology Under the Medicare Home Health Benefit Even prior to the erectile dysfunction treatment 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 period, 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 erectile dysfunction treatment 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 erectile dysfunction treatment. Accordingly, CMS implemented additional policies under the HH PPS to make providing and receiving services via telecommunications technology easier. In the first erectile dysfunction treatment 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 (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 Start Printed Page 66858 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 erectile dysfunction treatment PHE, as described previously. In the first erectile dysfunction treatment 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.[] 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 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.[] As such, to collect more complete data on the use of telecommunications technology in the provision of home health services, we solicited 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 solicited 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. L.

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 requested comments from the public on our reasoning 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 reminded 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 also requested 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 also solicited 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 from the CY 2023 HH PPS Start Printed Page 66859 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. Comment. We received approximately 44 comments on the discussion regarding the collection of telehealth data on home health claims. The majority of commenters agreed that the collection and analysis of data on the use of telecommunications technology on home health claims will greatly assist with accurate cost reporting. A few commenters stated they are already collecting this data, are ready to share with CMS and are willing to confer with CMS on downstream analysis of virtual care delivery integration.

Several commenters strongly suggested that while CMS should continue to support innovation in telehealth (particularly in rural areas of the country where workforce and geographic considerations limit the number of in-home visits that may be possible), we should also remain cognizant that given the rurality of some regions, robust broadband, electronic devices and even cellular networks are not available in some patient service areas. Still, most commenters acknowledged that integration of telecommunications technology under the home health benefit during the erectile dysfunction treatment PHE has proven to decrease ED visits, inpatient hospitalizations, and total cost of care for comorbid high-risk populations. Therefore, access to digital and audio communication is critical for providing patients and families, education, guidance and reassurance needed to avoid use of emergency services and hospitals. We received a few comments on states adopting increased scopes of practice for home health aides that could allow them to utilize telecommunications technology, and suggestions that there may be exceptions to when a home health aide might use telecommunications technology to improve patient outcomes and reduce potential avoidable hospitalizations or ED visits. These exceptions could include responding to a question or urgent need of a care recipient or their family caregiver, monitoring a patient remotely for adverse reactions after a visit or playing a critical role in connecting the patient to a specialist via telemedicine.

However, most commenters agreed that use of telecommunications technology by home health aides should be rare, as they are generally providing hands-on care. We received comments requesting that CMS provide information and training to ensure that providers are prepared to report the requested data accurately when mandatory reporting begins. Specifically, commenters stated that CMS needs to be clear on differentiating between telecommunications technology, telehealth services, communication technology-based services (for example, virtual check-ins, e-visits), and clarify the types of remote patient monitoring that will be allowable under the new G-Codes to ensure that remote patient monitoring is adding to the value of care and not simply tracking steps from a wearable product like a smart watch. Several commenters urged CMS to develop a list of services and care that are appropriate for telehealth and those that should not be provided via virtual care and suggested that telehealth does not translate well to, and may in fact cause patient harm, services related to wound care, physical/occupational/speech therapy, and when patients have sensory impairments with hearing or vision. Conversely, commenters strongly supported that telehealth services may translate well for patients in need of chronic disease management, post-surgical care, mental health and isolation checks, medication management, and those patients with the inability to accurately collect and communicate health-related data, etc.

The majority of commenters supported the development of a mechanism to refine the collection of visit details for the type of clinician and service provided. However, while some commenters supported the implementation of three new G-codes to report telecommunications technology on home health claims, several commenters stated that new G-codes are not needed. Instead, these commenters suggested it would be less cumbersome to use appended modifiers for existing G-codes to identify each type of telecommunications technology by clinician and service provided, as the creation of multiple G-codes may lead to confusion and result in inappropriate assignment of the G-codes on claims. We received comments that support further analysis of the collected data on the use of telecommunications technology as it relates to beneficiary characteristics and utilization patterns, including information related to those beneficiaries who cannot use telecommunications technology because of technological limitations or other factors. Further information such as geographic, racial, ethnic, socioeconomic, sex, and gender identify identifiers, could be collected to identify whether disparities in telehealth usage vary in diverse populations.

Further, several commenters stated that CMS' analysis should include surveys of Medicare beneficiaries using home health services and their family caregivers (as appropriate) and the study of beneficiary appeals as they relate to services furnished via telecommunications technology should also be considered as part of this assessment. Response. CMS appreciates all of the comments and suggestions received regarding the collection of data on the use of telecommunications technology on home health claims. We also acknowledge commenter statements and concerns as they relate to the availability of technology and broadband in some regions of the country. While CMS maintains that the use of telecommunications technology would generally not be appropriate for home health aide services, at this time, we will not limit the use of these G-codes to any particular discipline.

However, we would like to remind commenters that if a service requires in-person, hands-on care from a skilled nurse or other provider, an in-person visit must be made by the HHA to furnish such services (85 FR 39428). We readily recognize and support the on-going integration of telecommunications technology under the home health benefit within the confines of the statute, and anticipate that the collection of data related to the furnishing of these services will increase our knowledge of how HHAs and beneficiaries benefit from its use. As noted previously, the primary goal of collecting the data on use of telecommunication technology under the home health benefit is to allow CMS to analyze the characteristics of the beneficiaries utilizing services furnished remotely, so that we have a broader understanding of the social determinants that affect who benefits most from these services, and what barriers may potentially exist for certain subsets of beneficiaries. Moreover, we appreciate the additional suggestions for analyzing the collected data on the use of telecommunication technology under the home health benefit in a more granular manner. We will consider these suggestions to help us connect how such technology is impacting the provision of care to certain beneficiaries, costs, quality, and outcomes, and determine if further Start Printed Page 66860 requirements surrounding the use of telecommunications technology are needed.

As stated previously, program instruction will be issued 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. Additionally, although we plan to begin collecting this data on home health claims by January 1, 2023, it will initially be collected on a voluntary basis by HHAs. Further program instruction on the voluntary reporting (beginning in January 2023) and required reporting (requirement will be effectuated in July 2023) will be issued in January 2023. 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.

Table C1—Measures Currently Adopted for the CY 2023 HH QRP Start Printed Page 66861 Start Printed Page 66862 D. End of the Suspension of OASIS Data Collection on Non-Medicare/Non-Medicaid HHA Patients and Requirement for HHAs To Submit All-Payer OASIS Data for Purposes of the HH QRP, Beginning With the CY 2027 Program Year In the CY 2023 HH PPS proposed rule, we noted for background that 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 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 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 typically raise concerns and OASIS 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.[] The Secretary conducted the study required under section 704 of the MMA from 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-M/non-Medicaid 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 titled, “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 the HH QRP.

These systems can now support an extensive range of provider reports, including case-mix reports for private pay patients. The HH QRP expanded quality domains to include HH CAHPS 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.[] In the July 28, 2017 and November 7, 2017 proposed and final rules titled “Home Health Prospective Payment System Rate Update and CY 2018 Case-Mix Adjustment Methodology Refinements. Home Health Value-Based Purchasing Model.

And Start Printed Page 66863 Home Health Quality Reporting Requirements” (82 FR 35372 through 35373 and 82 FR 51736 through 51737, respectively) and in the July 18, 2019 and November 8, 2019 proposed and final rules titled, “Medicare and Medicaid Programs. CY 2020 Home Health Prospective Payment System Rate Update” (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.

A few commenters also raised the issue of whether it would be appropriate to collect and report private pay data, given that private payers 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. In the CY 2023 HH PPS proposed rule, we stated our belief 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 receiving skilled care, regardless of payer. New risk adjustment models with all-payer data would better represent the full spectrum of patients receiving 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, the Changes in Skin Integrity Post-Acute Care quality measure 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 skilled-care patients will enable us to make these comparisons, which we believe will realize our goal of establishing consistent measures of quality across PAC settings. We stated in the CY 2023 HH PPS proposed rule that the concerns raised surrounding privacy outlined previously have been mitigated. We also stated that 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 proposed in the CY 2023 HH PPS proposed rule to end the suspension of non-Medicare/non-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 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 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 stated in the CY 2023 HH PPS proposed rule 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'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 proposed that for the CY 2025 HH QRP, the expanded reporting would be required for patients discharged between January 1, 2024 and June 30, 2024. After consideration of the comments on this proposal, we are finalizing that the new OASIS data reporting will be required beginning with the CY 2027 program year, with data for that program year required for patients discharged between July 1, 2025 and June 30, 2026. Consistent with the two-quarter phase-in that we typically use, HHAs will have an opportunity to begin submitting this data for patients discharged between January 1, 2025 through June 30, 2025, but we will not use that data to make a compliance determination. Beginning with the CY 2027 program year, HHAs will be required to report OASIS data on all patients, regardless of payer, for the applicable 12-month performance period (which for the CY 2027 program year, would be patients discharged between July 1, 2025 and June 30, 2026).

We stated in the CY 2023 HH PPS proposed rule that while we appreciate Start Printed Page 66864 that submitting OASIS data on all HHA patients regardless of payer source may create additional burden for HHAs, we 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. We solicited comments on this proposal. The following is a summary of the public comments received and our responses.

Comment. Several commenters supported the proposal to require quality data collection for all patients receiving skilled care from HHAs, regardless of payer source. Commenters agreed with the CMS' conclusion that this proposal would help standardize data across PAC settings. Supporters of the policy also noted that the implementation of all-payer data collection would be critical in establishing health equity standards, regardless of payment type for patients. Commenters further agreed that CMS is in a strong position to address privacy concerns regarding non-Medicare/non-Medicaid OASIS data collection and that the infrastructure to support reporting non-Medicare/Medicaid data has steadily improved.

Response. We appreciate the feedback and support for this proposal to end the suspension of non-Medicare/non-Medicaid data collection and to require HHAs to submit all-payer OASIS data for the HH QRP. Comment. Some commenters supported the proposal to require quality data reporting and collection for HHA patients with all payer sources, but also suggested modifications for improvement. A few commenters recommended delaying implementation of the policy until CY 2025 or at least until a year after the close of the current public health emergency.

Others shared the need to specify any populations that should be excluded from OASIS data collection, including pediatric and maternal patients. A commenter supported the all-payer collection proposal but stated that it should also be implemented for Home Health Care Consumer Assessment of Healthcare Providers and Systems (HHCAHPS) data. Some commenters supported the proposal but requested that CMS increase payments to offset the burden of implementation of this policy. Response. We thank the commenters for their feedback.

We believe that requiring the collection of all-payer quality measure data for which the data source is OASIS will further inform our quality work at CMS by allowing us to gain a more complete picture of the quality of care furnished at HHAs. We will take the commenter's suggestion to expand our all-payer policy to the collection of HHCAHPS data into consideration for future rulemaking. We have considered the concerns raised by commenters on the burden of this new reporting requirement and, in response to those comments, will delay this requirement until the CY 2027 program year. Under the new implementation schedule, we are finalizing, the new reporting requirement will be effective beginning with the CY 2027 program year. For that program year, HHAs will be required to submit all payer OASIS data for discharges from July 1, 2025 through and including June 30, 2026.

We continue to believe that a two-quarter phase-in period for this new reporting, along with the current systems in place to collect OASIS data, will give HHAs enough time to prepare to implement it. The two-quarter phase-in period is consistent with the phase-in schedule that we typically adopt for all new HH QRP reporting requirements. We appreciate feedback from commenters about the need to specify any populations that should be excluded from the new OASIS data collection. The policy would not change the current patient exemptions for OASIS, which are as follows. Patients under the age of 18.

Patients receiving maternity services. And patients receiving only personal care, housekeeping, or chore services. With respect to the commenter's request that we increase payment to HHAs to assist them financially in implementing this new requirement, we do not have authority under section 1895(b)(3)(B)(v) of the Act to provide bonuses or otherwise increase payment to HHAs that comply with the requirements of the HH QRP. Comment. Many commenters opposed this proposal.

Additionally, some commenters noted that CMS should not implement proposals that may add burden while HHAs are still impacted by the ongoing public health emergency (PHE). Other commenters questioned whether the benefits of implementation would outweigh the cost of implementation, including costs attributable to the burden associated with completing the new reporting and the costs of HHA staffing. A few commenters opposed the proposal and believe that CMS underestimated the burden both in terms of time for completion and costs of HHA staffing. Response. We acknowledge that HHAs may continue to be impacted by the PHE and that collecting quality data on all patients regardless of payer may create additional burden for some HHAs.

However, there are factors that limit the scope of the associated burden. For example, Medicare certified HHAs already have processes in place to collect OASIS data for Medicare/Medicaid patients which will limit the overall financial impact of this new reporting requirement. Additionally, our understanding is that many HHAs already collect all-payer OASIS data for other purposes. We continue to believe that the benefits of collecting data on patients regardless of payer source outweigh the costs related to the resumption of collection and submission requirements. Regarding concerns that we underestimated the national impact of this proposal, we have utilized a consistent process used for the estimate of burden in each HH Final rule for time spent and labor costs associated with the implementation of OASIS E, the version of the OASIS that would be used with the implementation of this proposal.

This process includes establishing an estimate for time required to submit each assessment item on the OASIS for each time point in which the item is collected, estimating the costs related to item submission based on bureau of labor statistics HHA staff labor costs, and calculating an overall estimate of burden based on the number of active HHAs. For further details on burden calculations, please reference Section VI of this final rule. We have properly estimated the burden being established for this proposal in compliance with ongoing processes established for regulatory impact. Comment. Many commenters who opposed the proposal cited concerns related to the burden of implementation implementing at a time when HHAs are concerned about an overall reduction in payments by Medicare.

Response. We note that while there is a permanent adjustment to the national, standardized 30-day payment rate in CY 2023 to account for actual behavior change upon implementation of the PDGM, the overall impact in CY 2023 is a net increase of 0.7% in home health payments. Furthermore, we believe given that delaying the implementation of this new reporting requirement until the CY 2027 program year will provide HHAs with ample time to incorporate this policy into their business operations. Start Printed Page 66865 Comment. Some commenters opposed the proposal and questioned CMS' authority to require collection of patient data from all-payer sources.

Response. 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. We have complied with the statutory requirements to end the suspension in this published final regulation in submitting the aforementioned report. We continue to believe that the collection of all payer OASIS data will provide a more complete and accurate picture of the quality of care furnished by HHAs. We also believe that the collection of all-payer OASIS data will enable us to calculate measure rates in the HH setting that can be more meaningfully compared with rates on those same measures in the LTCH, IRF, and SNF settings.

Comment. Some commenters raised privacy concerns regarding non-Medicare/non-Medicaid data collection and submission. Response. We safeguard all OASIS data in a secure data system (iQIES) that limits data access to authorized users and monitors such users to ensure against unauthorized data access or disclosures. This data system conforms to all applicable Federal laws and regulations, as well as Federal government, HHS, and CMS policies and standards as they relate to information security and data privacy.

Comment. Some commenters raised a concern that including non-Medicare/non-Medicaid patients in the OASIS data collection would significantly affect HHA outcome results because these patients could have a different case-mix profile. Some commenters raised concerns related to this issue especially for HHAs that have a high percentage of non-Medicare/non-Medicaid patients whose requirements for care are not mandated by CMS but by other payers. Some suggested that this proposal could result in HHAs limiting their care to non-Medicare/non-Medicaid patients to limit the potential impact on their HHA. Response.

We acknowledge that the collection of non-Medicare/non-Medicaid OASIS data could change the measure results for HHAs. However, we believe it is in the public's best interest, and more representative of the quality of care provided by HHAs, to collect data on all HHA patients. We believe that the collecting and reporting of the quality data will in time improve quality for all patients regardless of payer source. We intend to monitor and evaluate the impacts of this policy as necessary and consider modifications, if warranted, through future notice and comment rulemaking. After consideration of the public comments we received, we are finalizing the End of the Suspension of OASIS Data Collection on non-Medicare/non-Medicaid HHA Patients and the Requirement for HHAs to Submit All-Payer OASIS Data for Purposes of the HH QRP, Beginning with the CY 2027 Program Year.

E. Technical Changes We proposed 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 also proposed 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 proposed to move quality data required under section 1895(b)(3)(B)(v)(II) from § 484.245(b)(1)(iii) to § 484.245(b)(1)(i).[] 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 purposes of HHCAHPS survey data submission, the following additional requirements apply:”. We invited but did not receive public comments on this proposal.

We have modified § 484.245(b)(1)(i) to clarify that HHAs must report to CMS data—(1) that is required under section 1895(b)(3)(B)(v)(II) of the Act, including HHCAHPS survey data. And (2) on measures specified under sections 1899B(c)(1) and 1899B(d)(1) of the Act. F. 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 proposed to amend 42 CFR 484.245 to add eight HH QRP measure removal factors in a new paragraph (b)(3). We invited public comments on this proposal. Comment. Most commenters expressed support for this proposal, citing the importance of alignment across quality reporting programs and the value of transparency in the process of measure removal and additions from the HH QRP. Response.

We thank commenters for their support. Comment. A few commenters supported this proposal and raised a few additional considerations. A commenter noted that the expert panels that provide input into measure additions or removals often lack sufficient therapy staff participation. They encouraged CMS to increase feedback from multiple disciplines in the process of considering measure removals.

Response. These comments are outside the scope of this proposal to amend 42 CFR 484.245. Comment. A commenter generally supported this proposal but opposed the inclusion of measure removal factor #8 because they believe this removal factor will be misused by providers. They were concerned providers would advocate removal of measures of value to the public simply because they do not Start Printed Page 66866 want to collect the underlying assessment data required for the calculation of the measure.

Response. This comment is outside the scope of this proposal to amend 42 CFR 484.245. After consideration of the public comments we received, we are finalizing the proposal to codify the HH QRP measure removal factors. G. Request for Information.

Health Equity in the HH QRP In the CY 2023 HH PPS proposed rule, we stated that 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.[] We noted in the CY 2023 proposed rule that 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.[] 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. 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/​. We outlined in the CY 2023 proposed rule that belonging to an underserved community is often associated with worse health outcomes.[] 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.[] 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).[] 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.[] 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.[] 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.[] 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.[] The issue of disparity in access is especially critical to address currently with the erectile dysfunction treatment 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.[] 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 [] or a provider's biased perception of a patient's risk behavior and adherence to care plans.[] 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.[] CMS is committed to closing the equity gap in CMS quality programs. We thank commenters for their 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 Start Printed Page 66867 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.[] 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 solicited public comment in the CY 2023 HH PPS proposed rule 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 stated in the CY 2023 HH PPS proposed rule that we were 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),[] health equity, and implicit bias is an important step the HHA can take to provide quality care to underserved 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 also stated in the CY 2023 HH PPS proposed rule that 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 solicited public comment on the conceptual domains and quality measures described in this section. Furthermore, we solicited public comment 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 Start Printed Page 66868 measures. And the impact of the domains and quality measure concepts on organizational culture change. The following is a summary of the comments we received in response to this RFI. Commenters broadly applauded CMS for seeking to address health equity in home health. Many noted that health equity is critical to address in home health and requires attention from CMS and providers.

Many commenters representing organizations outlined some work they were engaged in to address health equity. Many commenters provided specific feedback on components of the quality measure concept along with broad-based feedback. Commenters suggested using a scale relative to responses in the measure concept rather than a yes/no approach. Some commenters noted that it would be critical to solicit direct input from HH patients on health equity issues in addition to soliciting that input from HHAs. Others shared that it is critical that CMS provide HHAs with a range of ways to address health equity needs that would be unique to the populations they serve.

Others suggested different issues that could be addressed with health equity measures, such as premature discharge, counteracting the impacts of HHAs coverage relative to the area deprivation index, and considerations of how disability is addressed when assessing health equity. A number of commenters shared their support for CMS pursuing other ways to aid HHAs in understanding health equity issues that may exist by providing stratified data to providers. Some commenters did not support the health equity quality measure because it would be compelling HHAs to improperly adopt CMS' approach to organizational culture changes. Other commenters shared concerns that a major issue related to health equity in home health is access to home health benefits and that CMS does not have a sufficiently robust approach to address scenarios in which access to home health is denied. Some commenters raised concerns that the health equity quality measure would add burden to the workload of HHAs and suggested that CMS utilize data currently available to address disparities and other health equity concerns.

Other commenters addressed more broad-based issues related to health equity. Others suggested CMS provide funding to address health equity issues and additionally consider supporting trainings for providers. Multiple commenters recommended using the terms “health related social needs” for individual health equity factors and “social determinants of health” for community health equity factors. Commenters raised the need to address issues such as expanding gender categorizations and updating race categories for some groupings. We appreciate the comments we received on this RFI.

Public input is very valuable for the continuing development of CMS' health equity quality measurement efforts and our broader commitment to health equity. A key pillar of our strategic vision as further described here, https://www.cms.gov/​files/​document/​health-equity-fact-sheet.pdf. We will take these comments into consideration in our future policy development. G. Advancing Health Information Exchange We are removing this section and note that it was erroneously included in this section of the CY 2023 HH PPS proposed rule.

We also note that this section of the proposed rule was duplicative of section I.B. Of the proposed rule. 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.[] 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.[] 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.[] 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. Start Printed Page 66869 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 HH PPS final rule (86 FR 62312), we summarized and responded to these comments received. In the CY 2023 HH PPS proposed rule (87 FR 37667 through 37671), we proposed 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 solicited comment on future approaches to health equity in the expanded HHVBP Model. B. 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 CY 2021, and the first performance year is the first full calendar year (beginning with CY 2023) following the baseline year.

b. Amended 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 differentiating 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 proposed 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 proposed 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 proposed to make conforming revisions to 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 proposed 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 using the Model baseline year) and improvement thresholds (determined using the HHA baseline year) is described at § 484.360. We invited public comments on these proposals. Comment.

A few commenters supported the proposed addition of the definitions of HHA baseline year and Model baseline year, and the associated proposal to modify the definitions of achievement threshold and benchmark. Response. We appreciate the commenters' support for these provisions. We did not receive comments on the proposed amendments to § 484.360 or to paragraph (a) of § 484.370. After consideration of the public comments received, we are finalizing the provisions at § 484.345, § 484.360, and § 484.370 without modification.

2. 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 proposed 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 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. Table D1—New and Existing HHAS Baseline Years as Finalized and Illustrated in Table 23 of the CY 2022 HH PPS Final Rule (86 FR 62301) Start Printed Page 66870 b. Change to 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 erectile dysfunction treatment 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. Start Printed Page 66871 In contrast, Figures D1 and D2 that were derived from the archived HH quality data from CMS.data.gov  [] 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 kamagra. In the 5 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.

Table D2—Average National Performance on Applicable Measures CY 2019-CY 2021 Start Printed Page 66872 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 treatment and 88.3 percent were fully vaccinated.[] In addition, there were viable treatments available and healthcare providers had nearly 2 years of experience managing erectile dysfunction treatment 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 proposed 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 proposed 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 to HHAs in the first IPR in the summer of the first performance year (CY 2016).

The proposed provision was made in conjunction with the proposed addition of the definition of the term HHA baseline year discussed previously. We believe that this proposed provision 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 kamagra. Accordingly, we proposed 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 proposed provisions. Table D3—Example.

Proposed HHA Baseline Years, Performance Year and Payment Year for HHAs Certified Through December 31, 2023 Start Printed Page 66873 In developing the 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 proposed 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 proposed 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 invited public comments on these proposals. Comment. A few commenters supported the proposal to establish the HHA baseline year for HHAs certified by Medicare prior to CY 2022 to have the same baseline period, CY 2022, for all measures, using the most recent available data, for the performance year beginning CY 2023. A commenter stated that they also observed variation in outcome performance, and believes that utilization of CY 2019 as the HHA baseline year would not be comparable to current agency performance or outcome trends, as it preceded both the transition to PDGM as well as the erectile dysfunction treatment kamagra. Another commenter, encouraged CMS to expedite the typical reporting cycle to provide preliminary HHA baseline measures to each agency by the end of Q1 2023.

Response. We thank those who expressed support for this provision. We believe most commenters that did not distinguish between HHA baseline year and the Model baseline year were referring to the Model baseline year because they often referenced the availability of benchmarks and achievement thresholds, and those comments are included in section IV.B.3 of this final rule. To help provide feedback to HHAs, we plan to make the most current HHA-specific performance data for the applicable measures available to each HHA in iQIES. We intend for this to include current performance relative to other HHAs nationally as soon as administratively possible and before the start of the CY 2023 performance year and again before the first IPR scheduled for July 2023.

After consideration of the public comments received, we are finalizing our proposals without modification. 3. Change to 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 proposed change to more clearly define the Model baseline year in section IV.B.1.b.

Of the proposed rule, we also proposed 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 erectile dysfunction treatment 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 2 years of experience managing erectile dysfunction treatment 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 our 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 invited public comments on this proposal. Comment. Several commenters support our rationale to use the most recent data available to establish the “baseline” years.

A few of these stakeholders suggested that CMS move the Model baseline year forward annually as is done in other value-based purchasing programs. Response. We thank commenters for their support. We believe that updating the Model baseline year to CY 2022 enables us to measure competing HHAs' performance using benchmarks and achievement thresholds that are based on the most recent data available. And, that it allows the benchmarks and achievement thresholds to be set using data from after the most acute phase of the erectile dysfunction treatment PHE, which we believe would provide a more appropriate basis for assessing performance under the expanded Model than the CY 2019 pre-PHE period.

CMS will consider the possibility of moving the Model baseline year forward annually. However, this consideration would need to be proposed in future rulemaking. Comment. Multiple commenters submitted concerns about changing the “baseline year” from CY 2019 to CY 2022 for the CY 2023 performance year. Commenters were concerned that the quality improvement efforts they have made in preparation for the Model would be negated or “expunged” if the Model baseline year was updated to CY Start Printed Page 66874 2022.

A few of these commenters were from States in the original Model. Response. We interpret commenters to be referring to the Model baseline year as opposed to the HHA baseline year, because they often referenced the availability of benchmarks and achievement thresholds and not the improvement thresholds. We recognize that changing the Model baseline year from CY 2019 to CY 2022 will affect individual HHAs differently based on their quality performance efforts over the last year. The expanded HHVBP Model performance scoring methodology rewards progress in raising quality scores not only through improvement points, but also through achievement points.

Under the expanded Model, achievement is prioritized relative to improvement. Quality improvement efforts undertaken by HHAs that show impact on performance year quality scores may be recognized through achievement points, regardless of when those efforts were initiated. For example, an HHA that has improved their overall quality will potentially get more achievement points attributed to their TPS than from improvement points and would potentially result in the same payment adjustment if we had not changed the baseline. Comment. Multiple commenters asked that we keep the baseline as CY 2019.

One commenter suggested that we change the baseline year to CY 2021. Another commenter stated that it will take years for HHAs to pivot appropriately and have that reflected in their scores and suggested that usage of the CY 2019 data until the fully updated CY 2022 data is available would be more appropriate. Response. We continue to believe that updating the Model baseline year to CY 2022 enables us to measure competing HHAs' performance using benchmarks and achievement thresholds that are based on the most recent data available. And, that it allows the benchmarks and achievement thresholds to be set using data from after the most acute phase of the erectile dysfunction treatment PHE, which we believe would provide a more appropriate basis for assessing performance under the expanded Model than the CY 2019 pre-PHE period.

Comment. A few commenters suggested that if we move the Model baseline year, that we postpone the first performance year to CY 2024 or until the CY 2022 data is available. Response. The applicable measures (including the components of the TNC measures) are familiar to HHAs as they are used in the HH QRP. To help provide feedback, we plan to make the most current HHA-specific performance data for the applicable measures to each HHA available in iQIES.

We intend for this to include current performance relative to other HHAs nationally as soon as administratively possible and before the start of the CY 2023 performance year and again periodically before the first IPR scheduled for July 2023. Thus, CMS does not believe that it is necessary to postpone the first performance year. Comment. Commenters expressed concern that they would not have baseline data until July 2023 (half-way through the first performance year). Some cautioned that 2022 data cannot be analyzed quickly enough to be accurately applied in 2023, with some stating it would prevent them from establishing improvement goals or understanding the metrics against which Model participants are being judged, as well as an inability to plan financially or benchmark against any data until the CY 2022 data is released.

These commenters asked that we provide baseline data prior to the start of each performance year. A few asked that we provide baseline data prior to April 2023. And, a commenter requested that CMS provide baseline data by January 31, 2023. Response. We encourage HHAs to use current performance data in iQIES and the performance data on the Care Compare website which includes the OASIS-based measures (including those included in the TNC measures), claims-based measures, and HHCAHPS-based measures applicable to the expanded HHVBP Model.

The data specific to each individual HHA as well as the state and national averages (similar to the HHVBP achievement thresholds) can help HHAs determine where they are currently performing to continue to establish quality improvement goals. To help provide feedback, we plan to make the most current HHA-specific performance data for the applicable measures to each HHA available in iQIES. We intend for this to include current performance relative to other HHAs in their assigned cohort as soon as administratively possible and before the start of the CY 2023 performance year and again periodically before the first IPR scheduled for July 2023. Comment. Commenters expressed concern about a compounding effect of changing the Model baseline year and the proposed Medicare payment adjustments described in the proposed rule (87 FR 37616 through 37620), claiming that it will be difficult for HHAs to demonstrate improvement going forward.

These commenters believe that the proposed payment adjustments threaten the quality improvement gains demonstrated in the HHVBP Model, and if finalized, may severely limit the capacity for the Expanded HHVBP Model to produce the results and savings currently projected. Response. Quality improvement efforts undertaken by HHAs that show impact on performance year quality scores may be recognized through achievement points, regardless of when those efforts were initiated. For example, an HHA that has improved their overall quality will potentially get more achievement points attributed to their TPS than from improvement points and would potentially result in the same payment adjustment if we had not changed the baseline. The payment adjustment being finalized in section II.B.4.

Of this final rule is estimated to result in an estimated net increase in home health payments of 0.7 percent for CY 2023 ($125 million). For details, see Table F5. Estimated HHA Impacts by Facility Type and Area of The Country, CY 2023. After consideration of the public comments received, we are finalizing our proposal as proposed. 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.[] In line with Start Printed Page 66875 Executive Order 13985 of January 20, 2021 “Advancing Racial Equity and Support for Underserved Communities Through the Federal Government,[]  ” 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.[] 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,[] the CMS Innovation Center's Accountable Health Communities Model,[] the CMS Disparity Methods stratified reporting program,[] 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,[] and the CMS Framework for Health Equity 2022-2023.[] 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 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.[] 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 requested public comments on policy changes that we should consider on the topic of health equity.

We specifically requested 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 requested commenters' views on which of these adjustments, if any, would be most effective for the expanded HHVBP Model. Comment.

Commenters encouraged our efforts to advance health equity within the expanded HHVBP Model. Additionally, commenters provided specific comments, concerns, and requests related to the expanded HHVBP Model falling into the following themes. Commenters believe that applying health equity to payments may create disincentives to admit some patients and create unintended consequences and requests to examine strategies to reduce the risks for unintended consequence prior to implementing health equity adjustments to the expanded HHVBP Model. Particularly, commenters requested CMS ensure that incorporating health equity into the Model does not unintentionally disadvantage any HHAs serving communities with notably low levels of diversity and does not undermine access to care for beneficiaries. Commenters suggested that prior to adding new measures to value-based purchasing initiatives, measures should first be included in its related quality reporting program.

Commenters believed that payment should not be tied to measure performance until a measure is thoroughly tested, evaluated, and has NQF-endorsement. They believe that measure methodology and implementation of individual measures should be sufficiently vetted prior to inclusion, and specifically part of the HH QRP prior to advancing to the expanded HHVBP Model. Commenters requested that CMS select measures that are reliable, reflect true differences in performance and are not attributable to random variation. And, consider outcome measures for the expanded Model related to beneficiary access and outcomes, as well as costs. Commenters requested that CMS use existing data sources for data collection and not require HHAs to collect additional data to support incorporating health equity into the expanded HHVBP Model.

Commenters requested that CMS expand the use of and leveraging existing tools that are used to document existing equity data, including data on social determinants of health, specifically Z codes. Commenters requested that CMS reconsider incorporating health equity in the expanded HHVBP Model and instead work to incorporate an evidence-based tool into the Patient-Driven Groupings Model in order to properly incentivize HHAs serving communities where health inequities exist. Commenters requested that CMS apply health equity principals to homecare differently from inpatient settings. Commenters pointed out that the Evaluation of the Home Health Value-Based Purchasing (HHVBP) Model Fifth Start Printed Page 66876 Annual Report indicated that there were disparities among the Medicaid population for acute care hospitalizations and functional measures and suggest that these are particularly important to rural providers in underserved areas who have a disproportionate share of patients with social and economic challenges. Commenters suggested that CMS incorporate patient-level data like race and ethnicity or the proportion of dually eligible patients served by an agency into the development of the HHVBP cohorts to create more level playing fields for agencies in historically marginalized areas to improve as the current cohort designations do not consider the diversity of patient population and have the potential to negatively impact providers in underserved areas.

Commenters suggested that CMS apply a stronger risk adjustment model as some HHAs care for much sicker and more complex populations than others. And, any advancements within the expanded HHVBP Model that account for pre-existing health disparities and population differences upon the start of care will help ensure agencies are compared fairly and that incentives are aligned to accommodate those requiring more complex care and those for individuals with maintenance goals whom some believe are not sufficiently weighted in the Model to incentivize HHAs to serve beneficiaries whose conditions may not improve, especially in the context of payment, quality reporting, and auditing policies and practices that favor beneficiaries with strong rehabilitation potential. Commenters suggested that CMS adjust payments based on a provider's performance compared with its peers. Provider performance compared to providers with similar mixes of patients to determine rewards or penalties based on performance. And, performance relative to national performance scales and the shares of beneficiaries at high social risk.

Commenters suggested that CMS convene a Technical Expert Panel for stakeholder input to ensure that metrics for health equity and the application to the expanded HHVBP Model are determined through evidence-based research. Commenters had varying opinions about stratifying by dual eligible status, ranging from its importance to concerns that dual status does not reflect many other SDOHs that impact health outcomes or discrimination which affect access to care. Response. We appreciate the comments that we received on this request for information. We are not responding to individual specific comments submitted in response to this RFI in this final rule, but we will take this feedback into consideration as we develop our policies for the future.

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. The CPI-U for the 12-month period ending in June of 2022 is 9.1 percent and the corresponding productivity adjustment is 0.4 percent based on IHS Global Inc.'s third-quarter 2022 forecast of the CY 2023 productivity adjustment (which reflects the 10-year moving average of changes in annual economy-wide private nonfarm business TFP for the period ending June 30, 2022).

Therefore, the final home infusion therapy payment rate update for CY 2023 is 8.7 percent. 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. For discussion regarding the next full update to the GPCIs and the GAFs see the CY 2023 PFS proposed rule (87 FR 46004). The CY 2023 final GAFs will be posted as an addendum on the PFS website at https://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​PhysicianFeeSched. We also apply a GAF budget neutrality factor to home infusion therapy payments whenever there are changes to the GAFs in order to eliminate the aggregate effect of variations in the GAFS.

The CY 2023 GAF standardization factor that will be used in updating the final HIT payment amounts for CY 2023 is not available for this final rule, but will be posted once the CY 2023 GAFs are finalized. The final GAFs, GAF standardization factor, 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 [] 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. Start Printed Page 66877 Recommendations to minimize the information collection burden on the affected public, including automated collection techniques. B. Information Collection Requirements (ICRs) In the CY2023 HH PPS rule, we solicited public comment on each of these issues for the following sections of this document that contain information collection requirements (ICRs).

1. ICRs for HH QRP In section III. Of this final rule, we are finalizing our proposal to end the temporary suspension 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 2026 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 payer source will ensure that CMS can appropriately assess the quality of care provided to all patients receiving 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. Table F1—U.S.

Bureau of Labor Statistics' May 2020 National Occupational Employment and Wage Estimates We estimate that this new requirement will 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.[] For purposes of estimating burden, we utilize item-level burden estimates for OASIS-E that will be released on 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 F2—CY 2020 OASIS Submissions by Time Point 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. Table F3—Summary of Estimated Clinician Hourly Burden Start Printed Page 66878 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 = 256,941 Hours 6.6 clinician minutes × 2,335,875 TOC assessments = 15,416,775 minutes/60 minutes = 256,941 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 = 2,953 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.

Table F4. Summary of Estimated Clinician Costs Start Printed Page 66879 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, 2025 HHA discharges C.

Submission of PRA-Related Comments We have submitted a copy of this final 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 invited public comments on these information collection requirements. Comment. A few commenters outlined opposition to the proposal based on CMS's underestimate of the burden both in terms of time for completion and current costs of HHA staffing.

Response. Regarding concerns that we underestimated the burden of this proposal, we have utilized a consistent process for time spent and labor costs associated with the implementation of updates to OASIS, including OASIS E, the version of the OASIS that would be used with the implementation of this proposal. There are also factors that limit the scope of the associated burden. As we noted in our response to the policy proposal, providers already have processes in place to collect OASIS data for Medicare/Medicaid patients which limit the broader impact of the resumption of collection to include patients of all payer sources. Another factor is that when CMS surveyed providers, they shared that there are already cases in which OASIS data is collected on non-Medicare/Medicaid patients but not submitted to CMS.

As this policy is focused on HHAs with systems in place to collect and submit OASIS data, the economy of scale is anticipated to limit the impacts on staffing or other burden issues. After consideration of the public comments received, and as addressed in section III.D. Of this final rule, we are finalizing the proposal to end the suspension of non-Medicare/non-Medicaid OASIS data collection and to require HHAs to submit all-payer OASIS data for purposes of the HH QRP beginning with the CY 2027 HH QRP program year. 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 Start Printed Page 66880 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) required the Secretary to implement a new methodology used to determine rural add-on payments for CYs 2019 through 2022. This methodology used to determine rural add-on payments has expired and will not affect payments for CY 2023. 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. Section 1895(b)(3)(D)(i) of the Act, as added by section 51001(a)(2)(B) of the BBA of 2018, 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. 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 was 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 finalizing the establishment of 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 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 erectile dysfunction treatment 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 final 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 erectile dysfunction treatment 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 kamagra. 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 Start Printed Page 66881 (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. 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 finalizes 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 125 million (0.7 percent). The $125 million increase in estimated payments for CY 2023 reflects the effects of the proposed CY 2023 home health payment update percentage of 4.0 percent ($725 million increase), an estimated 3.5 percent decrease that reflects the effects of the permanent behavioral adjustment ($635 million decrease) and an estimated 0.2 percent increase that reflects the effects of an updated FDL ($35 million increase). 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 increase by 0.7 percent which reflects the 3.5 percent decrease from the permanent behavioral adjustment, the 4.0 payment update percentage increase, and the 0.2 percent increase from lowering 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. Table F5—Estimated HHA Impacts by Facility Type and Area of the Country, CY 2023 Start Printed Page 66882 Start Printed Page 66883 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 10.5 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 final rule, we are ending the temporary suspension on our collection 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, requiring HHAs to report all-payer OASIS data for purposes of the HH QRP, beginning with the CY 2026 program year. Section III. Of this final rule provides a detailed description of the net increase in burdens associated with the proposed changes.

We proposed that HHAs would be required to begin reporting all-payer OASIS data beginning with January 1, 2025 discharges. The cost impact of this proposed changes was 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 2026. We described the estimated burden and cost reductions for these measures in section V1.B.1. Of this final 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 HH PPS final rule (86 FR 62402 through 62410), we estimated that the expanded HHVBP Model would generate a total projected 5-year gross FFS savings for CYs 2023 through 2027 of $3,376,000,000. We are finalizing our proposed changes to the baseline years and note that it 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 We did not propose any changes 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 overall economic impact of the statutorily-required HIT payment rate updates is an estimated increase in payments to HIT suppliers of 8.7 percent ($600,000) for CY 2023 based on the CPI-U for the 12-month period ending in June of 2022 of 9.1 percent and the corresponding productivity adjustment is 0.4 percent D. Regulatory Review Cost Estimation If regulations impose administrative costs on private entities, such as the time needed to read and interpret this final rule, we should estimate the cost associated with the regulatory review. Due to the uncertainty involved with accurately quantifying the number of entities that will review the rule, we assume that the total number of unique commenters on this year's proposed rule will be the number of reviewers of this final rule. We acknowledge that this assumption may understate or overstate the costs of reviewing this rule.

It is possible that not all commenters reviewed this year's proposed rule in detail, and it is also possible that some reviewers chose not to comment on the proposed rule. For these reasons we thought that the number of commenters would be a fair estimate of the number of reviewers of this rule. We also recognize that different types of entities are in many cases affected by mutually exclusive sections of this final rule, and therefore for the purposes of our estimate we assume that each reviewer reads approximately 50 percent of the rule. 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 2.54 hours for the staff to review half of this final rule.

For each entity that reviews the rule, the estimated cost is $292.33 (2.54 hours × $115.22). Therefore, we estimate that the total cost of reviewing this regulation is $ 263,389.33 ($292.33 × 901) [901 is the number of estimated Start Printed Page 66884 reviewers, which is based on the total number of unique commenters from this year's proposed rule]. E. Alternatives Considered 1. HH PPS For the CY 2023 HH PPS final rule, we considered alternatives to the provisions articulated in section II.B.2.

Of this final rule. Specifically, we considered other potential methodologies recommended by commenters 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 recommended alternate methodologies controlled for certain actual behavior changes (for example, the reduction in therapy visits or LUPA visits) and this is not in alignment with our interpretation of the statute at section 1895(b)(3)(D)(i) of the Act, which requires CMS to examine actual behavior change and make temporary and permanent adjustments to the standardized payment amounts. Therefore, any method that would control for an actual behavior change affecting payment would be contrary to what is required by the Social Security Act. 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 of −7.85 percent 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 and are finalizing half of the determined adjustment which is −3.925 percent for CY 2023. One alternative to the −3.925 percent permanent payment adjustment included taking the full −7.85 percent adjustment for CY 2023. However, due to the potential hardship to some providers of implementing the full −7.85 percent at once, we decided it would be more appropriate to take half the adjustment resulting in a −3.925 percent permanent payment adjustment for CY 2023. However, we note the permanent adjustment to account for actual behavior changes in CYs 2020 and 2021 should be −7.85 percent.

Therefore, applying a −3.925 percent permanent adjustment to the CY 2023 30-day payment rate would not adjust the rate fully to account for differences in behavior changes on estimated aggregate expenditures during those years. We would have to account for that difference, and any other potential adjustments needed to the base payment rate, to account for behavior change based on data analysis in future rulemaking. Another alternative would be to delay the full permanent adjustment to a future year. However, we conclude that delaying the full permanent adjustment would not be appropriate, as this would further impact budget neutrality and likely lead to a compounding effect creating the need for a much larger reduction to the payment rate in future years. 2.

HHQRP We did not consider any alternatives in this final rule. 3. Expanded HHVBP Model We discuss the alternative we considered to the finalized change to the HHA baseline year for each applicable measure in the expanded HHVBP Model in section IV.B.2.b. Of this final rule. 4.

Home Infusion Therapy We did not consider any alternatives in this final 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. Table F7—Accounting Statement.

HH PPS Classification of Estimated Transfers and Benefits, From CY 2022 to 2023 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 final rule as they relate to HHAs. Table F8 provides our best estimate of the increase in burden for OASIS submission. Table F8—Accounting Statement. Classification of Estimated Costs of Oasis Item Collection, From CY 2026 to CY 2027 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. Table F9—Accounting Statement. Expanded HHVBP Model Classification of Estimated Transfers for CYs 2023-2027 Start Printed Page 66885 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 [] 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. Table F10—Number of Firms, Revenue, and Estimated Impact of Home Health Care Services by NAICS Code 621610 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 finalized 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 final rule will 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 $125 million in increased payments to HHAs in CY 2023. The $125 million in increased payments is reflected in the last column of the first row in Table F5 as a 0.7 percent increase in expenditures when comparing CY 2023 payments to estimated CY 2022 payments. The 0.7 percent increase 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 with comment period (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. While we find that the −7.85 percent permanent payment adjustment, described in section II.B.2.c. Of this final 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, we will also continue to reprice claims, per the finalized methodology, and make any additional adjustments at a time and manner deemed appropriate in future rulemaking.

As mentioned previously, Start Printed Page 66886 we recognize that implementing the full permanent and temporary adjustments to the CY 2023 payment rate may adversely affect HHAs, including small entities. Therefore, due to the potential hardship of implementing the full −7.85 percent at once, we find it would be more appropriate to take half of the adjustment for CY 2023. Therefore, we are finalizing a permanent prospective adjustment of −3.925 percent for CY 2023. We solicited comments on the overall HH PPS RFA analysis and received no comments. 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 final 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 an RIA if a rule may have a significant impact on the operations of a substantial number of small rural hospitals. This analysis must conform to the provisions of section 604 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 final 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 final 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 final rule under these criteria of Executive Order 13132, and have determined that it would not impose substantial direct costs on State or local governments. K. Conclusion In conclusion, we estimate that the provisions in this final rule will result in an estimated net increase in home health payments of 0.7 percent for CY 2023 ($125 million).

The $125 million increase in estimated payments for CY 2023 reflects the effects of the CY 2023 home health payment update percentage of 4.0 percent ($725 million increase), a 0.2 percent increase in payments due to the new lower FDL ratio, which will increase outlier payments in order to target to pay no more than 2.5 percent of total payments as outlier payments ($35 million increase) and an estimated 3.5 percent decrease in payments that reflects the effects of the permanent behavior adjustment ($635 million decrease). Chiquita Brooks-LaSure, Administrator of the Centers for Medicare &. Medicaid Services, approved this document on October 26, 2022. Start List of Subjects Health facilitiesHealth professionsMedicare, and Reporting and recordkeeping requirements End List of Subjects For the reasons set forth in the preamble, the Centers for Medicare &. Medicaid Services amends 42 CFR chapter IV as follows.

Start Part End Part Start Amendment Part1. The authority citation for part 484 continues to read as follows. End Amendment Part Start Authority 42 U.S.C. 1302 and 1395hh. End Authority Start Amendment Part2.

Section 484.220 is amended by adding paragraph (c) to read as follows. End Amendment Part 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. Start Amendment Part3.

Section 484.245 is amended— End Amendment Part Start Amendment Parta. By revising paragraph (b)(1)(i). End Amendment Part Start Amendment Partb. In paragraph (b)(1)(iii) by removing the sentence “Quality data required under section 1895(b)(3)(B)(v)(ii) of the Act, including HHCAHPS survey data.”. And End Amendment Part Start Amendment Partc.

By adding paragraph (b)(3). End Amendment Part The revision and addition read as follows. Requirements under the Home Health Quality Reporting Program (HH QRP). * * * * * (b) * * * (1) * * * (i) Data— (A) Required under section 1895(b)(3)(B)(v)(II) of the Act, including HHCAHPS survey data. And (B) On measures specified under sections 1899B(c)(1) and 1899B(d)(1) of the Act.

* * * * * (3) Measure removal factors. 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. Start Printed Page 66887 (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.

* * * * * Start Amendment Part4. Section 484.345 is amended— End Amendment Part Start Amendment Parta. In the definition of “Achievement threshold” removing the phrase “during a baseline year” and adding in its place the phrase “during a Model baseline year”. End Amendment Part Start Amendment Partb. By removing the definition of “Baseline year”.

End Amendment Part Start Amendment Partc. In the definition of “Benchmark” removing the phrase “during the baseline year” and adding in its place the phrase “during the Model baseline year”. End Amendment Part Start Amendment Partd. By adding the definition of “HHA baseline year” in alphabetical order. End Amendment Part Start Amendment Parte.

In the definition of “Improvement threshold” removing the phrase “during the baseline year.” and adding in its place the phrase “during the HHA baseline year.”. And End Amendment Part Start Amendment Partf. By adding the definition of “Model baseline year” in alphabetical order. End Amendment Part The additions read as follows. 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. * * * * * Start Amendment Part5. Section 484.350 is amended by revising paragraph (b) and adding paragraph (c) to read as follows. End Amendment Part Applicability of the Expanded Home Health Value-Based Purchasing (HHVBP) Model.

* * * * * (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 CY 2022. Start Amendment Part6. Section 484.370(a) is amended by removing the phrase “Model for the baseline year, and CMS” and adding in its place the phrase “Model, and CMS”. End Amendment Part Start Signature Dated.

October 26, 2022. Xavier Becerra, Secretary, Department of Health and Human Services. End Signature End Supplemental Information BILLING CODE 4120-01-PBILLING CODE 4120-01-CBILLING CODE 4120-01-PBILLING CODE 4120-01-CBILLING CODE 4120-01-PBILLING CODE 4120-01-CBILLING CODE 4120-01-PBILLING CODE 4120-01-CBILLING CODE 4120-01-PBILLING CODE 4120-01-CBILLING CODE 4120-01-PBILLING CODE 4120-01-CBILLING CODE 4120-01-PBILLING CODE 4120-01-CBILLING CODE 4120-01-PBILLING CODE 4120-01-C[FR Doc. 2022-23722 Filed 10-31-22. 4:15 pm]BILLING CODE 4120-01-P.

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To the Editor kamagra not working can you buy over the counter kamagra. For persons who received a single dose of the Ad26.COV2.S treatment (Johnson & kamagra not working. Johnson–Janssen) against erectile dysfunction disease 2019 (erectile dysfunction treatment), a booster dose of a kamagra not working messenger RNA (mRNA) treatment at least 2 months after the primary dose is recommended. Recipients of Ad26.COV2.S for both the primary and booster doses may receive a second booster dose of an mRNA erectile dysfunction treatment at least 4 months after the first Ad26.COV2.S booster dose.1 Immunogenicity data from a phase 1–2 clinical trial conducted before kamagra not working B.1.1.529 and the BA sublineages of omicron emerged showed that increases in the titers of binding and neutralizing antibodies with heterologous boosting were similar to or greater than the increases with homologous boosting.2 In a study involving U.S. Veterans, data that were obtained during a period in which omicron was the predominant circulating variant also showed that among Ad26.COV2.S recipients, treatment effectiveness against omicron was higher with heterologous boosting than with homologous boosting3.

However, data from the general adult population and on treatment effectiveness over time kamagra not working are lacking. More than 18 million doses of the Ad26.COV2.S treatment have been kamagra not working administered in the United States alone4. Therefore, data are needed on boosting strategies that are effective over time kamagra not working. We performed a test-negative, case–control analysis to assess the effectiveness of four vaccination regimens against symptomatic with severe acute respiratory syndrome erectile dysfunction 2 (erectile dysfunction) during a period when omicron was the predominant circulating variant. A single priming dose of Ad26.COV2.S, a single priming dose of Ad26.COV2.S plus a booster dose of Ad26.COV2.S (Ad26.COV2.S/Ad26.COV2.S), a single priming dose of Ad26.COV2.S plus a booster dose of mRNA treatment (Ad26.COV2.S/mRNA), and two priming doses kamagra not working of an mRNA treatment plus a booster dose of mRNA treatment (mRNA/mRNA/mRNA).

In the regimens that included an mRNA treatment, either the BNT162b2 treatment (Pfizer–BioNTech) or the mRNA-1273 treatment (Moderna) was used kamagra not working. The methods have been published previously5 and are kamagra not working described in the Supplementary Appendix, available with the full text of this letter at NEJM.org. A total of 512,928 rapid and laboratory-based nucleic acid amplification tests (NAATs) were used in the current study. The tests were obtained between January 2 and March 23, 2022, from kamagra not working the Increasing Community Access to Testing (ICATT) platform, which facilitates no-cost, drive-through erectile dysfunction testing at pharmacies.5 In our analysis, we included tests from adults 18 years of age or older who reported vaccination status (product and month and year of receipt of each dose) and at least one erectile dysfunction treatment–like symptom, which most likely reflected mild disease. The included tests were kamagra not working from 7036 testing sites across 49 states, Washington, D.C., and Puerto Rico.

All sites belonged to kamagra not working a single pharmacy chain that obtained booster-dose information during this period. This chain had widespread national coverage. During the period when this study was conducted, 93.5% of kamagra not working all tests in adults provided through the ICATT platform, including those that did not meet our inclusion criteria, were conducted at this one chain. Swab samples were collected by the participants on-site, kamagra not working and the results were processed either on-site by the pharmacy (rapid polymerase-chain-reaction tests) or were sent out for processing at contracted laboratories (laboratory-based NAATs). All positive tests were assumed to involve the omicron variant, because more than 90% of the kamagra not working s detected nationally during this period were caused by this variant.4 Tests from persons who reported previous erectile dysfunction were excluded.

A sensitivity analysis that included tests regardless of previous erectile dysfunction was performed (see the Supplementary Appendix). treatment effectiveness (calculated as [1−the odds ratio]×100) of each of the four vaccination regimens, as compared with kamagra not working no vaccination, against symptomatic during the periods of 14 days to 1 month and of 2 to 4 months since receipt of the last treatment dose was estimated by means of logistic regression. The number of months since receipt of the last dose was calculated as the difference between the month and year of kamagra not working testing and the month and year of the last treatment dose. For doses received in the month of or month preceding test registration, persons were asked whether the most recent dose was received at least 2 weeks before the test date, and tests from persons with less than 2 weeks between the date of the last dose and the date of kamagra not working testing were excluded. Models were adjusted for calendar day of testing, age group, sex, race, ethnic group, testing site location (the Department of Health and Human Services region where the test was performed), Social Vulnerability Index of the U.S.

Census tract containing the testing site, and number of underlying chronic conditions (Tables kamagra not working S1 and S2 in the Supplementary Appendix). Figure 1 kamagra not working. Figure 1 kamagra not working. Effectiveness of Four Vaccination Regimens against Symptomatic with the Omicron Variant among Adults. treatment effectiveness was assessed among adults 18 years of kamagra not working age or older who were tested in the Increasing Community Access to Testing platform during the period from January 2 to March 23, 2022.

The treatment effectiveness (calculated as [1−the odds ratio]×100) of each of the four regimens, as compared with no vaccination, against symptomatic with the kamagra not working omicron variant of severe acute respiratory syndrome erectile dysfunction 2 was estimated by means of logistic regression. Regression models were adjusted for the number of days between the start of the analysis period and the test date (as a continuous variable with linear and quadratic terms), age group (18 to kamagra not working 24, 25 to 34, 35 to 44, 45 to 54, 55 to 64, and ≥65 years), sex, race, ethnic group, testing site location (the Department of Health and Human Services region where the test was performed), Social Vulnerability Index of the U.S. Census tract containing the testing site (dichotomized as 0 to <0.5 and ≥0.5 to 1.0. The Social Vulnerability Index ranges from 0 to kamagra not working 1.0, with higher scores indicating greater social vulnerability), and number of underlying chronic conditions (0, 1, or ≥2) to control for possible confounding (Table S1). No adjustment kamagra not working was made for multiplicity.

The number of months since receipt of the last dose was kamagra not working calculated as the difference between the month and year of testing and the month and year of the last treatment dose. Tests from participants with less than 2 weeks between the date of the last dose and the date of testing were excluded. For the three regimens that included a booster dose (Ad26.COV2.S/Ad26.COV2.S, Ad26.COV2.S/messenger kamagra not working RNA (mRNA) treatment, and mRNA/mRNA/mRNA), tests were excluded if a booster dose was administered less than 2 months after an Ad26.COV2.S primary series or less than 5 months after an mRNA treatment primary series. In estimating the treatment effectiveness of the single-dose kamagra not working Ad26.COV2.S regimen over time, tests were not excluded from evaluation on the basis of months since primary vaccination. Additional details of the methods are provided in the Supplementary Methods section in the Supplementary Appendix.The treatment effectiveness of the Ad26.COV2.S regimen, as compared with no vaccination, against symptomatic was 17.8% (95% confidence interval [CI], 4.3 to 29.5) during the period of 14 days to 1 month since receipt of the last dose and 8.4% (95% CI, 1.5 to 14.8) during the period of 2 to 4 months kamagra not working since receipt of the last dose.

The corresponding values for the kamagra not working Ad26.COV2.S/Ad26.COV2.S regimen were 27.9% (95% CI, 18.3 to 36.5) and 29.2% (95% CI, 23.1 to 34.8). For the Ad26.COV2.S/mRNA regimen, 61.3% (95% CI, 58.4 to 64.0) and 54.3% (95% CI, 52.2 to 56.3). And for the mRNA/mRNA/mRNA regimen, 68.9% (95% CI, 68.3 to 69.5) and 62.8% kamagra not working (95% CI, 62.2 to 63.4) (Figure 1). Our results show that all the regimens that included a booster dose, as compared with no vaccination, offered protection against symptomatic omicron (the 95% confidence intervals did not include 0), although treatment effectiveness was highest for the kamagra not working regimens that included a booster dose of an mRNA treatment and was lowest for the homologous Ad26.COV2.S/Ad26.COV2.S regimen. The treatment effectiveness of the three-dose mRNA regimen and the Ad26.COV2.S/mRNA regimen was lower during the period of 2 to 4 months since receipt of the booster dose than kamagra not working during the period of 14 days to 1 month since receipt of the booster dose.

For the Ad26.COV2.S/Ad26.COV2.S regimen, the 95% confidence intervals of the estimates for the two time periods overlapped, but sample sizes were smaller and confidence intervals wider than for other boosted regimens. The limitations of our study have been described previously5 and include residual or unmeasured confounding related to unmeasured differences according to kamagra not working vaccination status and test-seeking behavior. Nonetheless, the results of this study suggest that a single booster dose of an mRNA erectile dysfunction treatment in persons who received primary vaccination with single-dose Ad26.COV2.S provided protection close to that of the three-dose mRNA treatment regimen and support the current recommendation of a booster dose of mRNA treatment at least 2 months after primary vaccination kamagra not working with single-dose Ad26.COV2.S or at least 4 months after an Ad26.COV2.S booster dose. Emma K kamagra not working. Accorsi, Ph.D.Amadea Britton, M.D.Nong Shang, Ph.D.Katherine E.

Fleming-Dutra, M.D.Ruth kamagra not working Link-Gelles, Ph.D.Zachary R. Smith, M.A.Gordana kamagra not working Derado, Ph.D.Joseph Miller, Ph.D.Stephanie J. Schrag, D.Phil.Jennifer R kamagra not working. Verani, M.D.Centers for Disease Control and Prevention, Atlanta, GA [email protected] Supported by the CDC. Funding for the Increasing Community Access to Testing platform was provided by the Department of Health and Human kamagra not working Services.

Disclosure forms provided by the kamagra not working authors are available with the full text of this letter at NEJM.org. The views expressed in this letter are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention (CDC).This article was published on May kamagra not working 25, 2022, at NEJM.org. Drs. Schrag and Verani kamagra not working contributed equally to this letter. 5 References1 kamagra not working.

Centers for kamagra not working Disease Control and Prevention. Use of erectile dysfunction treatments in the United States. Interim clinical kamagra not working considerations. 2022 (https://www.cdc.gov/treatments/erectile dysfunction treatment/clinical-considerations/erectile dysfunction treatment-treatments-us.html).Google kamagra not working Scholar2. Atmar RL, kamagra not working Lyke KE, Deming ME, et al.

Homologous and heterologous erectile dysfunction treatment booster vaccinations. N Engl kamagra not working J Med 2022;386:1046-1057.3. Mayr FB, Talisa VB, Shaikh kamagra not working O, Yende S, Butt AA. Effectiveness of homologous or heterologous erectile dysfunction treatment boosters in veterans kamagra not working. N Engl J Med 2022;386:1375-1377.4.

Centers for Disease Control kamagra not working and Prevention. erectile dysfunction treatment data tracker kamagra not working. (https://erectile dysfunction treatment.cdc.gov/erectile dysfunction treatment-data-tracker/#datatracker-home).Google Scholar5 kamagra not working. Accorsi EK, Britton A, Fleming-Dutra KE, et al. Association between 3 doses of mRNA erectile dysfunction treatment and symptomatic caused by the erectile dysfunction kamagra not working omicron and delta variants.

JAMA 2022;327:639-651.Mortality from Motor Vehicle Crashes kamagra not working and Firearms among Children, Adolescents, and Young Adults, United States, 2000–2020. The rates are age-adjusted and are from the Web-based Injury Statistics Query and Reporting System, Centers for Disease Control and Prevention.1Injuries are the most common cause of death among children, adolescents, and young adults kamagra not working between 1 and 24 years of age in the United States. Indeed, injuries are responsible for more deaths among children and adolescents than all other causes combined.1 For more than 60 years, motor vehicle crashes were the leading cause of injury-related death among young people. Beginning in 2017, however, firearm-related injuries took their place to become the most common cause of death from injury (see graph).1 This change occurred because of both the rising number of firearm-related deaths in this age group and the nearly continuous reduction in deaths from motor vehicle kamagra not working crashes. The crossing of these trend lines demonstrates how a concerted approach to injury prevention can reduce injuries and deaths — and, conversely, how kamagra not working a public health problem can be exacerbated in the absence of such attention.

Between 2000 and 2020, the number of firearm-related deaths among children, adolescents, and young adults increased from 6998 (7.30 per 100,000 persons) to 10,186 (10.28 per 100,000 persons), according to the Centers for Disease Control and Prevention (CDC).1Research has shown that most injuries can be prevented by means of the manufacture kamagra not working and appropriate use of safe products and the implementation of policies reducing product-related danger and the occurrence of hazardous situations — the principles of harm reduction. Since the 1960s, kamagra not working continuous efforts have been directed toward preventing deaths from motor vehicle crashes. As a result, there has been a substantial reduction not just in fatality rates, but in rates of serious nonfatal injuries associated with motor vehicle crashes, among people of all ages. In 2000, motor vehicle–related kamagra not working injuries resulted in 13,049 deaths among young people (13.62 per 100,000 persons). Twenty years later, there has been a nearly 40% decrease, with 8234 motor vehicle traffic deaths (8.31 per 100,000 persons) recorded in 2020.1Two kamagra not working decades ago, the CDC proclaimed the reduction in deaths attributable to motor vehicle crashes to be one of the most substantial public health achievements of the 20th century.2 Most important, the United States established an infrastructure permitting continuous improvements in motor vehicle safety.

At the forefront of this effort has been the National Highway Traffic Safety Administration (NHTSA), a federal agency whose mission is to save lives and prevent kamagra not working injuries caused by road-traffic crashes. Firearms, however, are one of the few products whose safety isn’t regulated by a designated federal agency.Dr. William Haddon, kamagra not working the first NHTSA director, is credited with articulating the comprehensive scientific (i.e., public health) approach now used to reduce unintentional and intentional injuries. The first kamagra not working step is to create comprehensive data systems. The NHTSA maintains a public database that includes entries for all motor vehicle–related deaths occurring on U.S kamagra not working.

Public roads (https://www.nhtsa.gov/research-data/fatality-analysis-reporting-system-fars) and collects data on a large, nationally representative sample of police-reported crashes. By contrast, it kamagra not working has taken 20 years to build a database of firearm-related deaths that includes data from all 50 states, known as the National Violent Death Reporting System. This database is kamagra not working already quite useful, and it should improve over time because of enhanced data quality and variable coding. Work on creating a reliable database for nonfatal firearm-related injuries is ongoing.Injury and fatality data are of little use without research kamagra not working to uncover important trends, disparities, and associations. Such research is critical to developing, implementing, and evaluating injury-prevention initiatives.

Although substantial federal funding has been devoted to research on motor vehicle crashes, the firearm industry and gun-rights organizations, led by the National Rifle Association (NRA), have been effective at keeping federal dollars from financing firearm-related kamagra not working research. Between 1996 and 2019, little federal research funding was appropriated for firearm-injury prevention, owing in large part to the Dickey Amendment.3 Unsurprisingly, researchers and kamagra not working policymakers know much more about the circumstances surrounding deaths from motor vehicle crashes and effective interventions for preventing traffic-related injuries and deaths than they do about firearm-related harm. Only in the past couple of years has there been a substantial increase in federal funding for firearm-related research — kamagra not working though not to levels commensurate with the size of the problem. The work of federally funded groups, such as the Firearm Safety Among Children and Teens consortium, will be important in advancing the science of firearm-injury prevention.To support automotive safety, the NHTSA and the nonprofit Insurance Institute for Highway Safety provide vehicle safety ratings using crash-test results and fatality data. Motor vehicle companies, which for decades resisted kamagra not working competing on the basis of safety, reversed course and now often advertise their vehicles’ safety features.

An important contributor to the nearly continuous reduction in traffic fatalities among both children and adults during the 21st century has been the implementation of vehicular safety improvements, such as automatic emergency braking, electronic stability controls, lane-departure warnings, blind-spot detection, side airbags, and rear-facing kamagra not working cameras. In recent years, on the other hand, the firearms available to civilians have become more lethal, in part because manufacturers are increasingly selling weapons designed for kamagra not working military use. There also appears to have been little effort by the gun industry to develop or market personalized “smart” guns. Such weapons can be fired by the authorized user only and should therefore reduce the risk of children unintentionally shooting themselves or others and of adolescents using guns for homicide or suicide.Another important component of traffic-safety infrastructure has been universal state-level requirements for the licensing of kamagra not working drivers and the registration of vehicles. Licensing and registration kamagra not working policies also make it easier for states to establish and enforce safety mandates.

Some safety kamagra not working measures have focused specifically on young people. In the 2000s, states began implementing booster-seat laws, child car seats became sturdier and more protective, and anticipatory guidance for parents on child-passenger safety was emphasized, which reduced deaths from motor vehicle crashes among children. Following the example of states that created graduated-licensing programs for kamagra not working new drivers in the late 1990s — which reduced fatal crashes among teenagers — the remaining states have adopted graduated licensing, which includes standardized driver education, mandatory supervised-driving hours, and other policies.4By contrast, many states have made it easier for children and young adults, as well as adults with criminal records, to gain access to firearms. Some states don’t require background checks when firearms are purchased kamagra not working from private sellers, such as at gun shows. In recent kamagra not working years, many of the same states have passed legislation allowing people to carry a concealed weapon without a permit.

At the federal level, the government has given the firearm industry partial protection against certain tort-liability suits (i.e., against negligence claims contending that they could have foreseen their product being diverted for criminal use), which has reduced the industry’s incentive to help prevent firearm-related deaths.One takeaway from ongoing success in improving motor vehicle safety may be the importance of a system that tracks firearm-related injuries and promotes the type of continuous reduction in injury rates that has been seen for motor vehicle crashes, including among children. At the federal level, such an approach could involve establishing an agency whose mission kamagra not working is to prevent harm caused by firearms. Eliminating tort protections that have been carved out for the kamagra not working firearm industry could encourage manufacturers to reduce harm. Successful negligence claims against insured manufacturers might give the insurance industry more incentive to help reduce gun violence — and perhaps kamagra not working to create a gun-focused organization analogous to the Insurance Institute for Highway Safety to advocate for beneficial regulations and policies. Federal and state laws, such as strong child-access prevention laws, which hold firearm owners liable if a child gains or could gain access to a firearm, could reduce related injuries and deaths among children.5 All cost-effective programs and policies that reduce injuries among children deserve support from researchers and policymakers, but we may want to prioritize those that could generate increasing benefits over time.As the progress made in reducing deaths from motor vehicle crashes shows, we don’t have to accept the high rate of firearm-related deaths among U.S.

Children and kamagra not working adolescents. Preventable deaths among young people not only are associated with tremendous medical costs, but take a great personal toll on kamagra not working families and communities. To reverse the kamagra not working trend of increasing firearm-related deaths among U.S. Children, experts and policymakers should be intentional in their efforts to develop and implement a multipronged scientific strategy centered on continuous improvement..

To the buy kamagra oral jelly usa Editor. For persons who received a single dose buy kamagra oral jelly usa of the Ad26.COV2.S treatment (Johnson &. Johnson–Janssen) against erectile dysfunction disease 2019 (erectile dysfunction treatment), a booster dose of a messenger RNA (mRNA) buy kamagra oral jelly usa treatment at least 2 months after the primary dose is recommended. Recipients of Ad26.COV2.S for both the primary buy kamagra oral jelly usa and booster doses may receive a second booster dose of an mRNA erectile dysfunction treatment at least 4 months after the first Ad26.COV2.S booster dose.1 Immunogenicity data from a phase 1–2 clinical trial conducted before B.1.1.529 and the BA sublineages of omicron emerged showed that increases in the titers of binding and neutralizing antibodies with heterologous boosting were similar to or greater than the increases with homologous boosting.2 In a study involving U.S.

Veterans, data that were obtained during a period in which omicron was the predominant circulating variant also showed that among Ad26.COV2.S recipients, treatment effectiveness against omicron was higher with heterologous boosting than with homologous boosting3. However, data from buy kamagra oral jelly usa the general adult population and on treatment effectiveness over time are lacking. More than 18 million doses of the Ad26.COV2.S treatment have been administered in the United States alone4 buy kamagra oral jelly usa. Therefore, data are needed on boosting strategies that are effective buy kamagra oral jelly usa over time.

We performed a test-negative, case–control analysis to assess the effectiveness of four vaccination regimens against symptomatic with severe acute respiratory syndrome erectile dysfunction 2 (erectile dysfunction) during a period when omicron was the predominant circulating variant. A single priming dose of Ad26.COV2.S, a single priming dose of Ad26.COV2.S plus a booster dose of Ad26.COV2.S (Ad26.COV2.S/Ad26.COV2.S), a single priming dose of Ad26.COV2.S plus a booster dose buy kamagra oral jelly usa of mRNA treatment (Ad26.COV2.S/mRNA), and two priming doses of an mRNA treatment plus a booster dose of mRNA treatment (mRNA/mRNA/mRNA). In the regimens that included an mRNA treatment, either the BNT162b2 treatment buy kamagra oral jelly usa (Pfizer–BioNTech) or the mRNA-1273 treatment (Moderna) was used. The methods have been published previously5 and are described in the Supplementary buy kamagra oral jelly usa Appendix, available with the full text of this letter at NEJM.org.

A total of 512,928 rapid and laboratory-based nucleic acid amplification tests (NAATs) were used in the current study. The tests were obtained buy kamagra oral jelly usa between January 2 and March 23, 2022, from the Increasing Community Access to Testing (ICATT) platform, which facilitates no-cost, drive-through erectile dysfunction testing at pharmacies.5 In our analysis, we included tests from adults 18 years of age or older who reported vaccination status (product and month and year of receipt of each dose) and at least one erectile dysfunction treatment–like symptom, which most likely reflected mild disease. The included tests were from 7036 testing sites across 49 states, Washington, D.C., buy kamagra oral jelly usa and Puerto Rico. All sites belonged to a single pharmacy chain that buy kamagra oral jelly usa obtained booster-dose information during this period.

This chain had widespread national coverage. During the period when this study was conducted, 93.5% of all tests in adults provided through the ICATT platform, including those that did not meet our inclusion criteria, were buy kamagra oral jelly usa conducted at this one chain. Swab samples were collected by the participants on-site, and the results were processed either on-site by buy kamagra oral jelly usa the pharmacy (rapid polymerase-chain-reaction tests) or were sent out for processing at contracted laboratories (laboratory-based NAATs). All positive tests were assumed to involve the omicron variant, because more than 90% of the buy kamagra oral jelly usa s detected nationally during this period were caused by this variant.4 Tests from persons who reported previous erectile dysfunction were excluded.

A sensitivity analysis that included tests regardless of previous erectile dysfunction was performed (see the Supplementary Appendix). treatment effectiveness (calculated as [1−the odds ratio]×100) of each of the four vaccination regimens, as compared with no vaccination, against buy kamagra oral jelly usa symptomatic during the periods of 14 days to 1 month and of 2 to 4 months since receipt of the last treatment dose was estimated by means of logistic regression. The number buy kamagra oral jelly usa of months since receipt of the last dose was calculated as the difference between the month and year of testing and the month and year of the last treatment dose. For doses received in the month of or month preceding test registration, persons were asked whether the most recent dose was received at least 2 weeks before the test date, and tests from persons with less than 2 weeks between the date of the last dose and the date buy kamagra oral jelly usa of testing were excluded.

Models were adjusted for calendar day of testing, age group, sex, race, ethnic group, testing site location (the Department of Health and Human Services region where the test was performed), Social Vulnerability Index of the U.S. Census tract containing the testing site, and number of underlying chronic conditions (Tables S1 and S2 in buy kamagra oral jelly usa the Supplementary Appendix). Figure 1 buy kamagra oral jelly usa. Figure 1 buy kamagra oral jelly usa.

Effectiveness of Four Vaccination Regimens against Symptomatic with the Omicron Variant among Adults. treatment effectiveness was assessed among adults 18 years of age or older who were tested in the buy kamagra oral jelly usa Increasing Community Access to Testing platform during the period from January 2 to March 23, 2022. The treatment effectiveness (calculated as [1−the odds ratio]×100) of each of the four regimens, as compared with no vaccination, against symptomatic buy kamagra oral jelly usa with the omicron variant of severe acute respiratory syndrome erectile dysfunction 2 was estimated by means of logistic regression. Regression models were adjusted for buy kamagra oral jelly usa the number of days between the start of the analysis period and the test date (as a continuous variable with linear and quadratic terms), age group (18 to 24, 25 to 34, 35 to 44, 45 to 54, 55 to 64, and ≥65 years), sex, race, ethnic group, testing site location (the Department of Health and Human Services region where the test was performed), Social Vulnerability Index of the U.S.

Census tract containing the testing site (dichotomized as 0 to <0.5 and ≥0.5 to 1.0. The Social Vulnerability Index ranges from 0 to 1.0, with higher scores indicating greater social vulnerability), and number of buy kamagra oral jelly usa underlying chronic conditions (0, 1, or ≥2) to control for possible confounding (Table S1). No adjustment buy kamagra oral jelly usa was made for multiplicity. The number of months since receipt of the last dose was calculated as the difference between the month and year of testing and the month and year buy kamagra oral jelly usa of the last treatment dose.

Tests from participants with less than 2 weeks between the date of the last dose and the date of testing were excluded. For the three regimens that included a buy kamagra oral jelly usa booster dose (Ad26.COV2.S/Ad26.COV2.S, Ad26.COV2.S/messenger RNA (mRNA) treatment, and mRNA/mRNA/mRNA), tests were excluded if a booster dose was administered less than 2 months after an Ad26.COV2.S primary series or less than 5 months after an mRNA treatment primary series. In estimating the buy kamagra oral jelly usa treatment effectiveness of the single-dose Ad26.COV2.S regimen over time, tests were not excluded from evaluation on the basis of months since primary vaccination. Additional details of the methods are provided in the Supplementary Methods section in the Supplementary Appendix.The treatment effectiveness of the Ad26.COV2.S regimen, as compared with no vaccination, buy kamagra oral jelly usa against symptomatic was 17.8% (95% confidence interval [CI], 4.3 to 29.5) during the period of 14 days to 1 month since receipt of the last dose and 8.4% (95% CI, 1.5 to 14.8) during the period of 2 to 4 months since receipt of the last dose.

The corresponding values for the Ad26.COV2.S/Ad26.COV2.S regimen were 27.9% (95% CI, 18.3 to 36.5) and buy kamagra oral jelly usa 29.2% (95% CI, 23.1 to 34.8). For the Ad26.COV2.S/mRNA regimen, 61.3% (95% CI, 58.4 to 64.0) and 54.3% (95% CI, 52.2 to 56.3). And for the mRNA/mRNA/mRNA regimen, 68.9% (95% CI, 68.3 to 69.5) and buy kamagra oral jelly usa 62.8% (95% CI, 62.2 to 63.4) (Figure 1). Our results show that all the regimens that included a booster dose, as compared with no vaccination, offered protection against symptomatic omicron (the 95% confidence intervals did not include 0), although treatment effectiveness was highest for the regimens that included a booster dose of an mRNA treatment and was lowest for the buy kamagra oral jelly usa homologous Ad26.COV2.S/Ad26.COV2.S regimen.

The treatment effectiveness of the three-dose mRNA regimen and the buy kamagra oral jelly usa Ad26.COV2.S/mRNA regimen was lower during the period of 2 to 4 months since receipt of the booster dose than during the period of 14 days to 1 month since receipt of the booster dose. For the Ad26.COV2.S/Ad26.COV2.S regimen, the 95% confidence intervals of the estimates for the two time periods overlapped, but sample sizes were smaller and confidence intervals wider than for other boosted regimens. The limitations of our study have been described previously5 and include residual or unmeasured confounding related to buy kamagra oral jelly usa unmeasured differences according to vaccination status and test-seeking behavior. Nonetheless, the results of this study suggest that a single booster dose of an mRNA erectile dysfunction treatment in persons who received primary vaccination with single-dose Ad26.COV2.S provided protection close to that of buy kamagra oral jelly usa the three-dose mRNA treatment regimen and support the current recommendation of a booster dose of mRNA treatment at least 2 months after primary vaccination with single-dose Ad26.COV2.S or at least 4 months after an Ad26.COV2.S booster dose.

Emma K buy kamagra oral jelly usa. Accorsi, Ph.D.Amadea Britton, M.D.Nong Shang, Ph.D.Katherine E. Fleming-Dutra, M.D.Ruth buy kamagra oral jelly usa Link-Gelles, Ph.D.Zachary R. Smith, M.A.Gordana buy kamagra oral jelly usa Derado, Ph.D.Joseph Miller, Ph.D.Stephanie J.

Schrag, D.Phil.Jennifer buy kamagra oral jelly usa R. Verani, M.D.Centers for Disease Control and Prevention, Atlanta, GA [email protected] Supported by the CDC. Funding for the Increasing Community Access to Testing platform was provided by the Department of Health and Human buy kamagra oral jelly usa Services. Disclosure forms provided by the authors buy kamagra oral jelly usa are available with the full text of this letter at NEJM.org.

The views expressed in this letter are those of the authors and do not necessarily represent the official buy kamagra oral jelly usa position of the Centers for Disease Control and Prevention (CDC).This article was published on May 25, 2022, at NEJM.org. Drs. Schrag and Verani contributed equally to this buy kamagra oral jelly usa letter. 5 References1 buy kamagra oral jelly usa.

Centers for Disease Control and Prevention buy kamagra oral jelly usa. Use of erectile dysfunction treatments in the United States. Interim clinical buy kamagra oral jelly usa considerations. 2022 (https://www.cdc.gov/treatments/erectile dysfunction treatment/clinical-considerations/erectile dysfunction treatment-treatments-us.html).Google Scholar2 buy kamagra oral jelly usa.

Atmar RL, Lyke KE, Deming ME, et buy kamagra oral jelly usa al. Homologous and heterologous erectile dysfunction treatment booster vaccinations. N Engl J Med 2022;386:1046-1057.3 buy kamagra oral jelly usa. Mayr FB, Talisa VB, Shaikh O, Yende S, Butt AA buy kamagra oral jelly usa.

Effectiveness of homologous or heterologous erectile dysfunction treatment boosters in veterans buy kamagra oral jelly usa. N Engl J Med 2022;386:1375-1377.4. Centers for Disease buy kamagra oral jelly usa Control and Prevention. erectile dysfunction treatment data buy kamagra oral jelly usa tracker.

(https://erectile dysfunction treatment.cdc.gov/erectile dysfunction treatment-data-tracker/#datatracker-home).Google Scholar5 buy kamagra oral jelly usa. Accorsi EK, Britton A, Fleming-Dutra KE, et al. Association between buy kamagra oral jelly usa 3 doses of mRNA erectile dysfunction treatment and symptomatic caused by the erectile dysfunction omicron and delta variants. JAMA 2022;327:639-651.Mortality from Motor Vehicle Crashes and Firearms among Children, Adolescents, and Young Adults, buy kamagra oral jelly usa United States, 2000–2020.

The rates are age-adjusted and are from the Web-based Injury Statistics Query and Reporting System, Centers for Disease Control and Prevention.1Injuries are the most common cause of death among children, adolescents, and young adults between 1 buy kamagra oral jelly usa and 24 years of age in the United States. Indeed, injuries are responsible for more deaths among children and adolescents than all other causes combined.1 For more than 60 years, motor vehicle crashes were the leading cause of injury-related death among young people. Beginning in 2017, however, firearm-related injuries took their place buy kamagra oral jelly usa to become the most common cause of death from injury (see graph).1 This change occurred because of both the rising number of firearm-related deaths in this age group and the nearly continuous reduction in deaths from motor vehicle crashes. The crossing of these trend lines demonstrates how a concerted approach to injury prevention can reduce injuries and deaths — and, conversely, how a public health problem can be exacerbated in the absence buy kamagra oral jelly usa of such attention.

Between 2000 and 2020, the number of firearm-related deaths among children, adolescents, buy kamagra oral jelly usa and young adults increased from 6998 (7.30 per 100,000 persons) to 10,186 (10.28 per 100,000 persons), according to the Centers for Disease Control and Prevention (CDC).1Research has shown that most injuries can be prevented by means of the manufacture and appropriate use of safe products and the implementation of policies reducing product-related danger and the occurrence of hazardous situations — the principles of harm reduction. Since the 1960s, continuous efforts have been directed toward preventing deaths from motor vehicle buy kamagra oral jelly usa crashes. As a result, there has been a substantial reduction not just in fatality rates, but in rates of serious nonfatal injuries associated with motor vehicle crashes, among people of all ages. In 2000, motor vehicle–related injuries resulted in 13,049 buy kamagra oral jelly usa deaths among young people (13.62 per 100,000 persons).

Twenty years later, there has been a buy kamagra oral jelly usa nearly 40% decrease, with 8234 motor vehicle traffic deaths (8.31 per 100,000 persons) recorded in 2020.1Two decades ago, the CDC proclaimed the reduction in deaths attributable to motor vehicle crashes to be one of the most substantial public health achievements of the 20th century.2 Most important, the United States established an infrastructure permitting continuous improvements in motor vehicle safety. At the forefront of buy kamagra oral jelly usa this effort has been the National Highway Traffic Safety Administration (NHTSA), a federal agency whose mission is to save lives and prevent injuries caused by road-traffic crashes. Firearms, however, are one of the few products whose safety isn’t regulated by a designated federal agency.Dr. William Haddon, the buy kamagra oral jelly usa first NHTSA director, is credited with articulating the comprehensive scientific (i.e., public health) approach now used to reduce unintentional and intentional injuries.

The first step is to buy kamagra oral jelly usa create comprehensive data systems. The NHTSA maintains a public database that includes entries for all motor vehicle–related deaths occurring on buy kamagra oral jelly usa U.S. Public roads (https://www.nhtsa.gov/research-data/fatality-analysis-reporting-system-fars) and collects data on a large, nationally representative sample of police-reported crashes. By contrast, it has taken 20 years to build a database of firearm-related deaths buy kamagra oral jelly usa that includes data from all 50 states, known as the National Violent Death Reporting System.

This database is already quite useful, and it should improve over time buy kamagra oral jelly usa because of enhanced data quality and variable coding. Work on creating a reliable database for nonfatal firearm-related injuries is ongoing.Injury and fatality data are of little use without research to uncover important trends, disparities, and associations buy kamagra oral jelly usa. Such research is critical to developing, implementing, and evaluating injury-prevention initiatives. Although substantial federal funding has been devoted to research on motor vehicle crashes, the firearm industry buy kamagra oral jelly usa and gun-rights organizations, led by the National Rifle Association (NRA), have been effective at keeping federal dollars from financing firearm-related research.

Between 1996 and 2019, little federal research funding was appropriated for firearm-injury prevention, owing in large part to the Dickey Amendment.3 Unsurprisingly, researchers and policymakers know much more about the circumstances surrounding deaths from motor vehicle crashes and effective interventions for preventing traffic-related injuries and deaths than they do about firearm-related buy kamagra oral jelly usa harm. Only in the past couple of years has there been a substantial increase in buy kamagra oral jelly usa federal funding for firearm-related research — though not to levels commensurate with the size of the problem. The work of federally funded groups, such as the Firearm Safety Among Children and Teens consortium, will be important in advancing the science of firearm-injury prevention.To support automotive safety, the NHTSA and the nonprofit Insurance Institute for Highway Safety provide vehicle safety ratings using crash-test results and fatality data. Motor vehicle companies, which buy kamagra oral jelly usa for decades resisted competing on the basis of safety, reversed course and now often advertise their vehicles’ safety features.

An important contributor to the nearly continuous reduction in traffic fatalities among both children and adults during the 21st century has been the implementation of vehicular safety improvements, such as automatic emergency braking, electronic stability controls, lane-departure warnings, blind-spot buy kamagra oral jelly usa detection, side airbags, and rear-facing cameras. In recent years, on the other hand, the firearms available buy kamagra oral jelly usa to civilians have become more lethal, in part because manufacturers are increasingly selling weapons designed for military use. There also appears to have been little effort by the gun industry to develop or market personalized “smart” guns. Such weapons can be fired by the authorized user only and should therefore reduce the risk of buy kamagra oral jelly usa children unintentionally shooting themselves or others and of adolescents using guns for homicide or suicide.Another important component of traffic-safety infrastructure has been universal state-level requirements for the licensing of drivers and the registration of vehicles.

Licensing and registration policies also make it easier for states to establish and buy kamagra oral jelly usa enforce safety mandates. Some safety buy kamagra oral jelly usa measures have focused specifically on young people. In the 2000s, states began implementing booster-seat laws, child car seats became sturdier and more protective, and anticipatory guidance for parents on child-passenger safety was emphasized, which reduced deaths from motor vehicle crashes among children. Following the example of states that created graduated-licensing programs for new drivers in the late 1990s — which reduced buy kamagra oral jelly usa fatal crashes among teenagers — the remaining states have adopted graduated licensing, which includes standardized driver education, mandatory supervised-driving hours, and other policies.4By contrast, many states have made it easier for children and young adults, as well as adults with criminal records, to gain access to firearms.

Some states don’t require background checks when firearms are purchased from private sellers, such buy kamagra oral jelly usa as at gun shows. In recent buy kamagra oral jelly usa years, many of the same states have passed legislation allowing people to carry a concealed weapon without a permit. At the federal level, the government has given the firearm industry partial protection against certain tort-liability suits (i.e., against negligence claims contending that they could have foreseen their product being diverted for criminal use), which has reduced the industry’s incentive to help prevent firearm-related deaths.One takeaway from ongoing success in improving motor vehicle safety may be the importance of a system that tracks firearm-related injuries and promotes the type of continuous reduction in injury rates that has been seen for motor vehicle crashes, including among children. At the federal level, such an approach could involve establishing an agency whose mission is to buy kamagra oral jelly usa prevent harm caused by firearms.

Eliminating tort protections that have been buy kamagra oral jelly usa carved out for the firearm industry could encourage manufacturers to reduce harm. Successful negligence buy kamagra oral jelly usa claims against insured manufacturers might give the insurance industry more incentive to help reduce gun violence — and perhaps to create a gun-focused organization analogous to the Insurance Institute for Highway Safety to advocate for beneficial regulations and policies. Federal and state laws, such as strong child-access prevention laws, which hold firearm owners liable if a child gains or could gain access to a firearm, could reduce related injuries and deaths among children.5 All cost-effective programs and policies that reduce injuries among children deserve support from researchers and policymakers, but we may want to prioritize those that could generate increasing benefits over time.As the progress made in reducing deaths from motor vehicle crashes shows, we don’t have to accept the high rate of firearm-related deaths among U.S. Children and adolescents buy kamagra oral jelly usa.

Preventable deaths among buy kamagra oral jelly usa young people not only are associated with tremendous medical costs, but take a great personal toll on families and communities. To reverse the trend of increasing firearm-related deaths among buy kamagra oral jelly usa U.S. Children, experts and policymakers should be intentional in their efforts to develop and implement a multipronged scientific strategy centered on continuous improvement..