[Federal Register Volume 87, Number 120 (Thursday, June 23, 2022)]
[Proposed Rules]
[Pages 37600-37683]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2022-13376]



[[Page 37599]]

Vol. 87

Thursday,

No. 120

June 23, 2022

Part III





 Department of Health and Human Services





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 Centers for Medicare & Medicaid Services





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42 CFR Part 484





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

  Federal Register / Vol. 87, No. 120 / Thursday, June 23, 2022 / 
Proposed Rules  

[[Page 37600]]


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DEPARTMENT OF HEALTH AND HUMAN SERVICES

Centers for Medicare & Medicaid Services

42 CFR Part 484

[CMS-1766-P]
RIN 0938-AU77


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

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

ACTION: Proposed rule.

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

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

ADDRESSES: In commenting, please refer to file code CMS-1766-P. Because 
of staff and resource limitations, we cannot accept comments by 
facsimile (FAX) transmission.
    Comments, including mass comment submissions, must be submitted in 
one of the following three ways (please choose only one of the ways 
listed):
    1. Electronically. You may submit electronic comments on this 
regulation to https://www.regulations.gov. Follow the ``Submit a 
comment'' instructions.
    2. By regular mail. You may mail written comments to the following 
address ONLY: Centers for Medicare & Medicaid Services, Department of 
Health and Human Services, Attention: CMS-1766-P, P.O. Box 8013, 
Baltimore, MD 21244-8013.
    Please allow sufficient time for mailed comments to be received 
before the close of the comment period.
    3. By express or overnight mail. You may send written comments to 
the following address ONLY: Centers for Medicare & Medicaid Services, 
Department of Health and Human Services, Attention: CMS-1766-P, Mail 
Stop C4-26-05, 7500 Security Boulevard, Baltimore, MD 21244-1850.
    For information on viewing public comments, see the beginning of 
the SUPPLEMENTARY INFORMATION section.

FOR FURTHER INFORMATION CONTACT: Brian Slater, (410) 786-5229, for home 
health and home infusion therapy payment inquiries.
    For general information about home infusion 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 
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.

SUPPLEMENTARY INFORMATION:

I. Executive Summary and Advancing Health Information Exchange

A. Executive Summary

1. Purpose and Legal Authority
a. Home Health Prospective Payment System (HH PPS)
    As required under section 1895(b) of the Social Security Act (the 
Act), this proposed rule would update the payment rates for HHAs for CY 
2023. In addition, the rule would: recalibrate the case-mix weights 
under section 1895(b)(4)(A)(i) and (b)(4)(B) of the Act for 30-day 
periods of care in CY 2023; determine the impact of differences between 
assumed behavior changes and actual behavior changes on estimated 
aggregate expenditures for CYs 2020-2021 in accordance with section 
1895(b)(3)(D)(i) of the Act; propose a permanent payment adjustment to 
the CY 2023 30-day payment rate and solicit comments on a temporary 
payment adjustment to the 30-day payment rate in accordance with 
section 1895(b)(3)(D)(ii) and (iii) of the Act; update the LUPA 
thresholds, functional impairment levels, and comorbidity subgroups for 
CY 2023; and update the CY 2023 fixed-dollar loss ratio (FDL) for 
outlier payments (so that outlier payments as a percentage of estimated 
total payments are not to exceed 2.5 percent, as required by section 
1895(b)(5)(A) of the Act). This proposed rule also includes a 
solicitation of comments on the collection of data on the use of 
telecommunications technology on home health claims.
b. Home Health (HH) Quality Reporting Program (QRP)
    This proposed rule proposes to end the suspension of the collection 
of Outcome and Assessment Information Set (OASIS) data on non-Medicare 
and non-Medicaid patients under section 704 of the Medicare 
Prescription Drug, Improvement, and Modernization Act of 2003, and to 
require HHAs to report all-payer OASIS data for purposes of the HH QRP, 
beginning with the CY 2025 program year. We are proposing to amend the 
regulatory text to make a technical change that consolidates the 
statutory references to data submission. We also propose to codify in 
our regulations the factors we adopted in the CY 2019 HH PPS final rule 
as the factors we will consider when determining whether to remove 
measures from the HH QRP measure set. Finally, we are requesting 
feedback on a Request for Information on Health Equity in the HH QRP.

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c. Expanded Home Health Value Based Purchasing (HHVBP) Model
    In accordance with the statutory authority at section 1115A of the 
Act, we are proposing updated policies, new definitions and modifying 
existing definitions, and conforming regulation text changes for the 
expanded Home Health Value-Based Purchasing (HHVBP) expanded Model and 
requesting comment on a potential future approach to health equity in 
the expanded HHVBP Model.
d. Medicare Coverage of Home Infusion Therapy
    This proposed rule discusses updates to the home infusion therapy 
services payment rates for CY 2023 under section 1834(u) of the Act.
2. Summary of the Provisions of This Rule
a. Home Health Prospective Payment System (HH PPS)
    In section II.B.1. of this proposed rule, we provide monitoring and 
data analysis on PDGM utilization for CYs 2020 and 2021. In section 
II.B.2. of this rule, we propose payment adjustments to reflect the 
impact of differences between assumed behavior changes and actual 
behavior changes on estimated aggregate payment expenditures under the 
HH PPS. In section II.B.3 of this rule, we discuss the proposal to 
reassign certain ICD-10-CM codes related to the PDGM clinical groups 
and comorbidity subgroups.
    In section II.B.4. of this rule, we are proposing the recalibration 
of the PDGM case-mix weights, LUPA thresholds, functional levels, and 
comorbidity adjustment subgroups for CY 2023.
    In section II.B.5. of this rule, we propose to update the home 
health wage index, the CY 2023 national, standardized 30-day period 
payment rates and the CY 2023 national per-visit payment amounts by the 
home health payment update percentage. The proposed home health payment 
update percentage for CY 2023 would be 2.9 percent. This rule also 
proposes a permanent 5-percent cap on HHA's applicable wage index 
reductions from their wage index from the prior year, regardless of the 
circumstances causing the decline. Additionally, this rule proposes the 
FDL ratio to ensure that aggregate outlier payments do not exceed 2.5 
percent of the total aggregate payments, as required by section 
1895(b)(5)(A) of the Act.
    In section II.B.6. of this proposed rule, we include a comment 
solicitation on the collection of data on the use of telecommunications 
technology on home health claims.
b. HH QRP
    In section III.D. of this proposed rule, we are proposing to end 
the temporary suspension of non-Medicare/non-Medicaid data under 
section 704 of the Medicare Prescription Drug, Improvement, and 
Modernization Act of 2003 and, in accordance with section 
1895(b)(3)(B)(v) of the Act, to require HHAs to report all-payer OASIS 
data for purposes of the HH QRP, beginning with the CY 2025 program 
year. In section III.E. of this rule, we are proposing technical 
changes in Sec.  484.245(b)(1). In section III.F. of this rule, we are 
proposing to codify in our regulations the factors we adopted in the CY 
2019 HH PPS final rule as the factors we will consider when determining 
whether to remove measures from the HH QRP measure set. Lastly, in 
section III.G. of this rule, we are requesting feedback on a Request 
for Information on Health Equity in the HH QRP.
c. Expanded Home Health Value Based Purchasing (HHVBP) Model
    In section IV. of this proposed rule, we are proposing to change 
the HHA baseline year to CY 2022 for all HHAs that were certified prior 
to January 1, 2022 starting in the CY 2023 performance year. We would 
make conforming regulation text changes at Sec.  484.350(b) and (c). We 
are also proposing to amend the Model baseline year from CY 2019 to CY 
2022 starting in the CY 2023 performance year to enable CMS to measure 
competing HHAs performance on benchmarks and achievement thresholds 
that are more current. We are making conforming amendments to 
definitions in Sec.  484.345. In section IV.C. of this proposed rule, 
we have included an RFI related to a potential future approach to 
health equity in the expanded HHVBP Model.
d. Medicare Coverage of Home Infusion Therapy
    In section V. of this proposed rule, we discuss updates to the home 
infusion therapy services payment rates for CY 2023, under section 
1834(u) of the Act.
3. Summary of Costs, Transfers, and Benefits

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[GRAPHIC] [TIFF OMITTED] TP23JN22.001

B. Advancing Health Information Exchange

    The Department of Health and Human Services (HHS) has a number of 
initiatives designed to encourage and support the adoption of 
interoperable health information technology and to promote nationwide 
health information exchange to improve health care and patient access 
to their digital health information.
    To further interoperability in post-acute care settings, CMS and 
the Office of the National Coordinator for Health Information 
Technology (ONC) participate in the Post-Acute Care Interoperability 
Workgroup (PACIO) to facilitate collaboration with industry 
stakeholders to develop Health Level Seven International[supreg] (HL7) 
Fast Healthcare Interoperability Resources[supreg] (FHIR) standards.\1\ 
These standards could support the exchange and reuse of patient 
assessment data derived from the Minimum Data Set (MDS), Inpatient 
Rehabilitation Facility-Patient Assessment Instrument (IRF-PAI), Long-
term Care Hospital (LTCH) Continuity Assessment Record and Evaluation 
(CARE) Data Set (LCDS), Outcome and Assessment Information Set (OASIS), 
and other sources. The PACIO Project has focused on HL7 FHIR 
implementation guides for functional status, cognitive status and new 
use cases on advance directives, re-assessment timepoints, and Speech, 
Language, Swallowing, Cognitive communication and Hearing (SPLASCH) 
pathology. We encourage PAC provider and health information technology 
(IT) vendor participation as the efforts advance.
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    \1\ http://pacioproject.org/.
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    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

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interoperability for providers in settings across the care continuum. 
Section 4003(b) of the Cures Act required ONC to take steps to advance 
interoperability through the development of a trusted exchange 
framework and common agreement aimed at establishing a universal floor 
of interoperability across the country. On January 18, 2022, ONC 
announced a significant milestone by releasing the Trusted Exchange 
Framework \2\ and Common Agreement Version 1.\3\ The Trusted Exchange 
Framework is a set of non-binding principles for health information 
exchange, and the Common Agreement is a contract that advances those 
principles. The Common Agreement and the Qualified Health Information 
Network Technical Framework Version 1 \4\ (incorporated by reference 
into the Common Agreement) establish the technical infrastructure model 
and governing approach for different health information networks and 
their users to securely share clinical information with each other--all 
under commonly agreed to terms. The technical and policy architecture 
of how exchange occurs under the Trusted Exchange Framework and the 
Common Agreement follows a network-of-networks structure, which allows 
for connections at different levels and is inclusive of many different 
types of entities at those different levels, such as health information 
networks, healthcare practices, hospitals, public health agencies, and 
Individual Access Services (IAS) Providers.\5\ For more information, we 
refer readers to https://www.healthit.gov/topic/interoperability/trusted-exchange-framework-and-common-agreement.
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    \2\ The Trusted Exchange Framework (TEF): Principles for Trusted 
Exchange (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Trusted_Exchange_Framework_0122.pdf.
    \3\ Common Agreement for Nationwide Health Information 
Interoperability Version 1 (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
    \4\ Qualified Health Information Network (QHIN) Technical 
Framework (QTF) Version 1.0 (Jan. 2022), https://rce.sequoiaproject.org/wp-content/uploads/2022/01/QTF_0122.pdf.
    \5\ The Common Agreement defines Individual Access Services 
(IAS) as ``with respect to the Exchange Purposes definition, the 
services provided utilizing the Connectivity Services, to the extent 
consistent with Applicable Law, to an Individual with whom the QHIN, 
Participant, or Subparticipant has a Direct Relationship to satisfy 
that Individual's ability to access, inspect, or obtain a copy of 
that Individual's Required Information that is then maintained by or 
for any QHIN, Participant, or Subparticipant.'' The Common Agreement 
defines ``IAS Provider'' as: ``Each QHIN, Participant, and 
Subparticipant that offers Individual Access Services.'' See Common 
Agreement for Nationwide Health Information Interoperability Version 
1, at 7 (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
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    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 Sec.  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

[[Page 37604]]

health services for applicable years, on a prospective basis, to offset 
for such increases or decreases in estimated aggregate expenditures, as 
determined under section 1895(b)(3)(D)(i) of the Act. Such a temporary 
increase or decrease shall apply only with respect to the year for 
which such temporary increase or decrease is made, and the Secretary 
shall not take into account such a temporary increase or decrease in 
computing the payment amount for a unit of home health services for a 
subsequent year. Finally, section 51001(a)(3) of the BBA of 2018 amends 
section 1895(b)(4)(B) of the Act by adding a new clause (ii) to require 
the Secretary to eliminate the use of therapy thresholds in the case-
mix system for CY 2020 and subsequent years.
2. Current System for Payment of Home Health Services
    For home health periods of care beginning on or after January 1, 
2020, Medicare makes payment under the HH PPS on the basis of a 
national, standardized 30-day period payment rate that is adjusted for 
case-mix and area wage differences in accordance with section 
51001(a)(1)(B) of the BBA of 2018. The national, standardized 30-day 
period payment rate includes payment for the six home health 
disciplines (skilled nursing, home health aide, physical therapy, 
speech-language pathology, occupational therapy, and medical social 
services). Payment for non-routine supplies (NRS) is also part of the 
national, standardized 30-day period rate. Durable medical equipment 
(DME) provided as a home health service, as defined in section 1861(m) 
of the Act, is paid the fee schedule amount or is paid through the 
competitive bidding program and such payment is not included in the 
national, standardized 30-day period payment amount. Additionally, the 
30-day period payment rate does not include payment for certain 
injectable osteoporosis drugs and negative pressure wound therapy 
(NPWT) using a disposable device, but such drug and services must be 
billed by the HHA while a patient is under a home health plan of care, 
as the law requires consolidated billing of osteoporosis drugs and NPWT 
using a disposable device.
    To better align payment with patient care needs and to better 
ensure that clinically complex and ill beneficiaries have adequate 
access to home health care, in the CY 2019 HH PPS final rule with 
comment period (83 FR 56406), we finalized case-mix methodology 
refinements through the Patient-Driven Groupings Model (PDGM) for home 
health periods of care beginning on or after January 1, 2020. The PDGM 
did not change eligibility or coverage criteria for Medicare home 
health services, and as long as the individual meets the criteria for 
home health services as described at 42 CFR 409.42, the individual can 
receive Medicare home health services, including therapy services. For 
more information about the role of therapy services under the PDGM, we 
refer readers to the Medicare Learning Network (MLN) Matters article 
SE2000 available at https://www.cms.gov/regulations-and-guidanceguidancetransmittals2020-transmittals/se20005. To adjust for 
case-mix for 30-day periods of care beginning on and after January 1, 
2020, the HH PPS uses a 432-category case-mix classification system to 
assign patients to a home health resource group (HHRG) using patient 
characteristics and other clinical information from Medicare claims and 
the Outcome and Assessment Information Set (OASIS) assessment 
instrument. These 432 HHRGs represent the different payment groups 
based on five main case-mix categories under the PDGM, as shown in 
Figure B1. Each HHRG has an associated case-mix weight that is used in 
calculating the payment for a 30-day period of care. For periods of 
care with visits less than the low-utilization payment adjustment 
(LUPA) threshold for the HHRG, Medicare pays national per-visit rates 
based on the discipline(s) providing the services. Medicare also 
adjusts the national standardized 30-day period payment rate for 
certain intervening events that are subject to a partial payment 
adjustment (PEP). For certain cases that exceed a specific cost 
threshold, an outlier adjustment may also be available.
    Under this case-mix methodology, case-mix weights are generated for 
each of the different PDGM payment groups by regressing resource use 
for each of the five categories (admission source, timing, clinical 
grouping, functional impairment level, and comorbidity adjustment) 
using a fixed effects model. A detailed description of each of the 
case-mix variables under the PDGM have been described previously, and 
we refer readers to the CY 2021 HH PPS final rule (85 FR 70303 through 
70305).

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[GRAPHIC] [TIFF OMITTED] TP23JN22.002

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

1. Monitoring the Effects of the Implementation of PDGM
a. Routine PDGM Monitoring
    CMS routinely analyzes Medicare home health benefit utilization, 
including but not limited to, overall total 30-day periods of care and 
average periods of care per HHA user; distribution of the type of 
visits in a 30-day period of care; the percentage of periods that 
receive the LUPA; estimated costs; the percentage of 30-day periods of 
care by clinical group, comorbidity adjustment, admission source, 
timing, and functional impairment level; GG items by response type; and 
the proportion of 30-day periods of care with and without any therapy 
visits, nursing visits, and/or aide/social worker visits. For the 
monitoring included in this rule, we examine simulated CY 2018 and CY 
2019 data and actual CY 2020 and CY 2021 data for 30-day periods of 
care. We provide interpretation of results for CY 2020 and CY 2021. We 
refer readers to the CY 2022 HH PPS final rule (86 FR 35881) for 
discussion about simulated data for CYs 2018 and 2019.
(1) Utilization
    Table B2 shows the overall utilization of home health and Table B3 
shows the average utilization of visits per 30-day period of care by 
home health discipline. This data indicates the average number of 30-
day periods of care per unique HHA user is similar per 30-day period of 
care between CY 2020 and CY 2021. Table B3 shows utilization of visits 
per 30-day period of care by home health discipline over time. The data 
indicates that the number of 30-day periods of care decreased between 
CY 2018 and CY 2021. Table B4 shows the proportion of 30-day periods of 
care that are LUPAs and the average number of visits per discipline of 
those LUPA 30-day periods of care over time.
BILLING CODE 4120-01-P

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[GRAPHIC] [TIFF OMITTED] TP23JN22.004


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[GRAPHIC] [TIFF OMITTED] TP23JN22.005

BILLING CODE 4120-01-C
(2) Analysis of 2020 Cost Report Data for 30-Day Periods of Care
    In the CY 2020 HH PPS final rule with comment period (84 FR 60483), 
we provided a summary of analysis on FY 2017 HHA cost report data and 
how such data, if used, would impact our estimate of the percentage 
difference between the CY 2020 30-day payment amount and estimated, 
average HHA costs for a 30-day period of care. In that rule, we 
utilized FY 2017 cost reports and CY 2017 home health claims to 
estimate the costs of both 60-day episodes of care and 30-day periods 
of care. We then updated the estimated CY 2017 60-day episode costs and 
30-day period of care costs by the home health market basket update, 
reduced by the productivity adjustment for CYs 2018, 2019, and 2020 to 
calculate the 2020 estimated 60-day episode costs and 30-day period of 
care costs. As stated in the CY 2020 HH PPS final rule with comment 
period (84 FR 60485), we estimated that the CY 2020 30-day payment 
amount was approximately 16 percent higher than the average costs for a 
30-day period of care. In MedPAC's March 2020 Report to Congress,\6\ 
their review of home health payment adequacy found that ``access is 
more than adequate in most areas and that Medicare payments are 
substantially in excess of costs''.
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    \6\ http://www.medpac.gov/docs/default-source/reports/mar20_medpac_ch9_sec.pdf?sfvrsn=0.
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    In this proposed rule, we examined 2020 HHA Medicare cost reports, 
as this is the most recent and complete cost report data at the time of 
rulemaking, and CY 2021 home health claims, to estimate 30-day period 
of care costs. We excluded LUPAs and PEPs in the average number of 
visits. The 2020 average NRS costs per visit is $4.53. To update the 
estimated 30-day period of care costs, we begin with the 2020 average 
costs per visit with NRS for each discipline and multiply that amount 
by the CY 2021 home health payment update percentage of 2.0 percent. 
That amount for each discipline is then multiplied by the 2021 average 
number of visits by discipline to determine the 2021 Estimated 30-day 
Period Costs. Table B5 shows the estimated average costs for 30-day 
periods of care by discipline with NRS and the total 30-day period of 
care costs with NRS for CY 2021.

[[Page 37608]]

[GRAPHIC] [TIFF OMITTED] TP23JN22.006

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

    \7\ https://www.medpac.gov/wp-content/uploads/2022/03/Mar22_MedPAC_ReportToCongress_Ch8_SEC.pdf.
---------------------------------------------------------------------------

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

[[Page 37609]]

[GRAPHIC] [TIFF OMITTED] TP23JN22.007

    Thirty-day periods of care will receive a comorbidity adjustment 
category based on the presence of certain secondary diagnoses reported 
on home health claims. These diagnoses are based on a home health 
specific list of clinically and statistically significant secondary 
diagnosis subgroups with similar resource use. We refer readers to 
section II.B.4.c. of this proposed rule and the CY 2020 final rule with 
comment period (84 FR 60493) for further information on the comorbidity 
adjustment categories. Home health 30-day periods of care can receive a 
low or a high comorbidity adjustment, or no comorbidity adjustment. 
Table B7 shows the distribution of 30-day periods of care by 
comorbidity adjustment category for all 30-day periods.
[GRAPHIC] [TIFF OMITTED] TP23JN22.008

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

[[Page 37610]]

on when they occur within a sequence of 30-day periods of care. The 
first 30-day period of care is classified as early and all subsequent 
30-day periods of care in the sequence (second or later) are classified 
as late. A subsequent 30-day period of care would not be considered 
early unless there is a gap of more than 60 days between the end of one 
previous period of care and the start of another. Information regarding 
the timing of a 30-day period of care comes from Medicare home health 
claims data and not the OASIS assessment to determine if a 30-day 
period of care is ``early'' or ``late''. Table B8 shows the 
distribution of 30-day periods of care by admission source and timing.
[GRAPHIC] [TIFF OMITTED] TP23JN22.009

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

    \8\ https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/HomeHealthPPS/HH-PDGM.
[GRAPHIC] [TIFF OMITTED] TP23JN22.010


[[Page 37611]]


(6) CY 2023 Discussion and Analysis of GG Items
    The Improving Medicare Post-Acute Care Transformation Act of 2014 
(IMPACT Act) (Pub. L. 113-185, enacted on October 6, 2014) amended 
Title XVIII of the Act to include new data reporting requirements for 
certain post-acute care (PAC) providers, such as HHAs. Section 
1899B(b)(1)(A) of the Act requires that HHAs report standardized 
patient assessment data beginning no later than January 1, 2019. Since 
the standardized patient assessment data categories included functional 
status, such as mobility and self-care at admission and discharge, in 
accordance with section 1899B(b)(1)(B)(i) of the Act, CMS finalized 
adding the functional items, Section GG, ``Functional Abilities and 
Goals'', to the OASIS data set, effective January 1, 2019, in order to 
measure functional status across PAC providers. However, for payment 
purposes under the PDGM, CMS did not have the data to determine the 
effect, if any, of these newly added items on resource costs during a 
home health period of care. Therefore, the GG functional items are not 
currently used to determine the functional impairment level under the 
PDGM. CMS continues to use the M1800-1860 items to determine functional 
impairment level for case-mix purposes. As such, the purpose of the 
following analysis is to explore the relationship between the M1800-
1860 items used in the PDGM and the analogous GG items. The analysis of 
the M1800 functional items and the analogous GG items shows there was a 
small decline in the percentage of individuals who were associated with 
the ``most independent'' responses with a large percentage of the 
responses using the ``Activity not Attempted'' (ANA) response option. 
If the activity was not attempted, there are various codes that explain 
the reason for this response, such as ``Not attempted due to medical or 
safety concerns,'' and ``Not applicable.''
    To conduct this analysis, we reviewed OASIS data from January 1, 
2019, to December 31, 2021, that was linked to 30-day home health 
periods. Responses for each of the M1800 functional items used in the 
PDGM functional scores were compared to the responses of the analogous 
GG items. There is a correlation between the current responses to the 
M1800-1860 items and the GG items; however, certain information in the 
M1800 items is collected at follow--up, but is not collected at follow-
up for the GG items (for example, the M1800 items associated with upper 
and lower body dressing are collected at follow up, but the analogous 
GG item is not collected at follow-up). Additionally, ongoing analysis 
of the GG items shows a significant amount of ANA responses, making it 
difficult to map to the corresponding M1800-1860 item responses. Figure 
B2 demonstrates the frequencies by response type in CY 2021 of the 
OASIS GG items.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TP23JN22.011


[[Page 37612]]


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

    \9\ Medicare Benefit Policy Manual, Chapter 7 Home Health 
Services, Section 40.2 Skilled Therapy Services https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Downloads/bp102c07.pdf.
[GRAPHIC] [TIFF OMITTED] TP23JN22.012


[[Page 37613]]


[GRAPHIC] [TIFF OMITTED] TP23JN22.013

    Both Table B10 and Figure B3, as previously discussed, indicate 
there have been changes in the distribution of both therapy and non-
therapy visits in CY 2021 compared to CY 2020. For example, the percent 
of 30-day periods with seven or less therapy visits during a 30-day 
period increased in CY 2021 compared to CY 2020.
    In addition, we also examined the proportion of 30-day periods of 
care with and without skilled nursing, social work, or home health aide 
visits. Table B11 shows the number of 30-day periods of care with only 
skilled nursing visits, at least one skilled nursing visit and one 
other visit type (therapy or non-therapy), and no skilled nursing 
visits. Table B12 shows the number of 30-day periods of care with and 
without home health aide and/or social worker visits.
[GRAPHIC] [TIFF OMITTED] TP23JN22.014


[[Page 37614]]


[GRAPHIC] [TIFF OMITTED] TP23JN22.015

BILLING CODE 4120-01-C
    We will continue to monitor the provision of home health services, 
including any changes in the number and duration of home health visits, 
composition of the disciplines providing such services, and overall 
home health payments to determine if refinements to the case-mix 
adjustment methodology may be needed in the future.
2. Proposed Methodology for Behavioral Assumptions and Adjustments 
Under the HH PPS,
a. Background and Comment Solicitation From the CY 2022 HH PPS Proposed 
Rule
(1) Background
    As discussed in section II.A.1. of this rule, starting in CY 2020, 
the Secretary was statutorily required to change the unit of payment 
under the HH PPS from a 60-day episode of care to a 30-day period of 
care. CMS was also required to make assumptions about behavior changes 
that could occur as a result of the implementation of the 30-day unit 
of payment and the case-mix adjustment factors that eliminated the use 
of therapy thresholds, when calculating the standard prospective 
payment amount for CY 2020. In the CY 2019 HH PPS final rule with 
comment period (83 FR 56455), we finalized the following three behavior 
assumptions:
     Clinical Group Coding: The clinical group is 
determined by the principal diagnosis code for the patient as reported 
by the HHA on the home health claim. This behavior assumption assumes 
that HHAs will change their documentation and coding practices and put 
the highest paying diagnosis code as the principal diagnosis code in 
order to have a 30-day period be placed into a higher-paying clinical 
group.
     Comorbidity Coding: The PDGM further adjusts 
payments based on patients' secondary diagnoses as reported by the HHA 
on the home health claim. The OASIS only allows HHAs to designate 1 
principal diagnosis and 5 secondary diagnoses while the home health 
claim allows HHAs to designate 1 principal diagnosis and up to 24 
secondary diagnoses. This behavior assumption assumes that by 
considering additional ICD-10- CM diagnosis codes listed on the home 
health claim (beyond the 6 allowed on the OASIS), more 30-day periods 
of care will receive a comorbidity adjustment.
     LUPA Threshold: This behavior assumption assumes 
that for one-third of LUPAs that are 1 to 2 visits away from the LUPA 
threshold HHAs will provide 1 to 2 extra visits to receive a full 30-
day payment.
    As described in the CY 2020 final rule with comment period (84 FR 
60512), in order to calculate the CY 2020 budget neutral 30-day payment 
amounts both with and without behavior assumptions, we first calculated 
the total, aggregate amount of expenditures that would occur under the 
pre-PDGM case-mix adjustment methodology (60-day episodes under 153 
case-mix groups). We then calculated what the 30-day payment amount 
would need to be set at in order for CMS to pay the same total 
expenditures in CY 2020 with the application of a 30-day unit of 
payment under the PDGM.
    We initially determined a negative 8.39 percent behavior change 
adjustment to the base payment rate would be needed in order to ensure 
that the payment rate in CY 2020 would be budget neutral, as required 
by law. However, based on the comments received and reconsideration as 
to the frequency of the assumed behaviors during the first year of the 
transition to a new unit of payment and case-mix adjustment 
methodology, we finalized in the CY 2020 HH PPS final rule with comment 
period (84 FR 60519) a negative 4.36 percent behavior change assumption 
adjustment (``assumed behaviors'') in order to calculate the 30-day 
payment rate in a budget-neutral manner for CY 2020. After applying the 
wage index budget neutrality factor and the home health payment update, 
the CY 2020 30-day payment rate was set at $1,864.03.
    Our data analysis in section II.B.1. of this proposed rule compares 
the 2018 simulated 30-day periods with behavior assumptions applied and 
actual 30-day periods. Specifically, Tables B4, B6, and B7 indicate 
that the three assumed behavior changes did occur as a result of the 
implementation of the PDGM. Additionally, this monitoring shows that 
other behaviors, such as changes in the provision of therapy and 
changes in functional impairment levels also occurred. Overall, the 
actual 30-day periods are similar to the simulated 30-day periods, 
which is supporting evidence that HHAs did make behavioral changes. 
However, we remind readers that by law we are required to ensure that 
estimated aggregate expenditures under the HH PPS during CY 2020 are 
equal to the estimated aggregate expenditures that otherwise would have 
been made under the HH PPS during CY 2020 in the absence of the change 
to a 30-day unit of payment. Regardless of the magnitude and frequency 
of individual behavior change (for example, LUPAs, therapy, etc.), the 
occurrence of any behavior change is captured by the methodology to 
determine the impact on aggregate expenditures.
    We remind readers that in the CY 2020 HH PPS final rule (84 FR 
60513), we stated that we interpret actual behavior changes to 
encompass both behavior changes that were previously outlined as 
assumed by CMS, and other behavior changes not identified at the

[[Page 37615]]

time the budget-neutral 30-day payment rate for CY 2020 was 
established. Subsequently, our analysis resulted in the identification 
of other behavior changes that occurred after the implementation of the 
PDGM. For example, Table B10 and Figure B3 in section II.B.1. of this 
proposed rule indicates the number of therapy visits declined in CYs 
2020 and 2021. However, the data, as depicted in Figure B3, also 
indicates a slight decline in therapy visits began in CY 2019 after the 
finalization of the removal of therapy thresholds, but prior to 
implementation of the PDGM. This suggests HHAs were already beginning 
to decrease their therapy provision. Although not originally one of the 
three finalized behavior assumptions, the decline in therapy 
utilization is indicative of an additional behavior change.
    Each Health Insurance Prospective Payment System (HIPPS) code is 
assigned a case-mix weight and the case-mix weight determines the base 
payment of non-LUPA claims prior to any other adjustments (for example 
outlier). Prior to the PDGM, the first position of the HIPPS code was a 
numeric value that represented the interaction of episode timing and 
number of therapy visits (grouping step). The second, third, and fourth 
positions of the pre-PDGM HIPPS code reflected clinical severity, 
functional severity, and service utilization respectively. Therefore, 
to evaluate how the decrease in therapy visits related to payments, we 
compared the average case mix weights of CY 2018 actual 60-day episodes 
and CY 2021 simulated 60-day episodes. Prior to the PDGM, the average 
case-mix weight for CY 2018 60-day episodes was 1.0176. When we set 
therapy levels at the pre-PDGM (that is, CY 2018) level and kept the 
clinical and functional levels at the PDGM levels (that is, CY 2021) 
the average case-mix weight was 1.0389. After the PDGM, the average 
case-mix weight for CY 2021 simulated 60-day episodes was 0.9664. When 
we kept therapy levels at the PDGM (that is, CY 2021) level and set the 
clinical and functional levels at the pre-PDGM levels (that is, CY 
2018) the average case-mix weight was 0.9361. By controlling for 
therapy levels, we were able to determine the change in 60-day episode 
case-mix weights were largely driven by therapy utilization. The 
decrease in therapy visits led to a decrease in case-mix weight, and 
therefore a decrease in aggregate expenditures under the pre-PDGM HH 
PPS.
(2) Summary of Comment Solicitation From the CY 2022 Proposed Rule
    As required by section 1895(b)(3)(D)(i) of the Act, CMS must 
annually determine the impact of differences between assumed and actual 
behavior changes on estimated aggregate expenditures under the HH PPS 
with respect to years beginning with 2020 and ending with 2026. Section 
1895(b)(3)(D)(ii) and (iii) of the Act requires that CMS make permanent 
and temporary adjustments to the payment rate to offset for such 
increases or decreases in estimated aggregate expenditures through 
notice and comment rulemaking. Therefore, to evaluate the impact of 
assumed versus actual behavior changes for CYs 2020 through 2026, we 
developed a methodology that uses actual claims data for 30-day periods 
under the 432-group case-mix model (PDGM claims) to simulate 60-day 
episodes under the 153-group case-mix model (representing pre-PDGM HH 
PPS claims) in order to estimate what aggregate expenditures would have 
been in the absence of the PDGM. This methodology mirrors the initial 
approach used to calculate the CY 2020 30-day period payment amount for 
the PDGM, where we used a single year of claims data (that is, CY 2018 
claims data for 60-day episodes of care under the 153-group case-mix 
model) and simulated payments for 30-day periods of care with the 
application of the PDGM case-mix adjustment methodology. We then 
compared actual aggregate expenditures under the existing system (that 
is, 60-day episodes of care under the 153-group case-mix model) to 
simulated payments under the PDGM for 30-day periods of care with 
assumed behavior changes, and used the difference between the two 
amounts to construct the budget neutrality factor. We described this 
methodology in the CY 2022 HH PPS proposed rule (86 FR 35889 through 
35892). For determining the impact of the difference between assumed 
and actual behavior changes on overall expenditures for CY 2020 and CY 
2021, we analyzed a single year of claims data (for example, CY 2020 
claims data for 30-day periods of care under the 432-group PDGM case-
mix model) and simulated payments for 60-day episodes of care under the 
153-group case-mix model. We then compared the actual aggregate 
expenditures under the PDGM to what aggregate expenditures would have 
been pre-PDGM.
    In the CY 2022 HH PPS proposed rule (86 FR 35892), we solicited 
comments on this approach (86 FR 35892). Commenters raised concerns 
about this methodology, most notably about the elimination of therapy 
thresholds, the onset of the COVID-19 PHE, interpretation of section 
1895(b)(3)(D)(i) of the Act, the differing case-mix weight systems (153 
vs 432 case-mix groups), and inappropriate data exclusions and 
assumptions when creating the simulated 60-day episodes.
    Commenters stated that there has been a large decrease in therapy 
utilization since the implementation of the PDGM. Commenters stated 
several possible reasons for the decrease in therapy utilization, 
including that the PDGM resulted in significant differences in payment 
incentives. Specifically, commenters noted that HHAs could have 
received higher payments if certain therapy volume thresholds were met 
pre-PDGM; whereas that incentive no longer exists under the PDGM. 
Therefore, many commenters indicated the estimated aggregate 
expenditures calculated with simulated 60-day episodes (pre PDGM) is 
inaccurate because it does not control for the payment incentives which 
would have been present under the old system. However, we stated in the 
CY 2019 HH PPS final rule with comment period (83 FR 56481), that the 
PDGM is not limiting or prohibiting the provision of therapy services 
or the number of home health periods of care. In addition, we believe 
that regardless of the case-mix system in place, HHAs should continue 
to provide the most appropriate care to Medicare home health 
beneficiaries, in accordance with the home health CoP requirements at 
Sec.  484.60.
    While overall utilization may have decreased in the early months of 
CY 2020 due to the onset of the COVID-19 PHE, the methodology described 
in the CY 2022 HH PPS proposed rule used the same claims dataset (for 
example, CY 2020) to compare aggregate expenditures under the two 
payment systems. Any effect of the COVID-19 PHE is included in the 
estimated aggregate expenditures for both simulated 60-day episodes and 
actual 30-day periods, and therefore this methodology ensures that any 
differences between the two calculated amounts is not attributable to 
the COVID-19 PHE. In other words, any potential changes due to the 
COVID-19 PHE (for example, decreased utilization) in the 30-day periods 
would also be present in the simulated 60-day episodes, making the two 
datasets comparable.
    However, we recognize that the COVID-19 PHE presented unique 
challenges for all healthcare settings, including HHAs. For example, we 
understand elective procedures were

[[Page 37616]]

cancelled or postponed and some beneficiaries decreased the care in 
their home, including potentially both the number of care providers 
furnishing services inside their homes and the frequency of services to 
avoid exposure to COVID-19. While we believe the proposed methodology 
presented best controls for the effects of the COVID-19 PHE, we are 
soliciting comments on how the COVID-19 PHE may have impacted service 
provision in a manner not reflected in the proposed methodology 
described above. We expect that such comments will include empirical 
evidence to support the commenter's position on how the COVID-19 PHE 
affected provider behavior.
    Commenters stated that the statute requires CMS to analyze solely 
the differences between the three assumed behavior changes (clinical 
group coding, comorbidity coding, LUPA threshold) that were 
incorporated into the original CY 2020 rate setting and what the actual 
behavior change was for just those three assumptions. Commenters stated 
that any adjustments to the 30-day payment amount must be related to 
the impact of those three assumed behavior changes and the actual 
behavior changes for those same three assumptions on estimated 
aggregate expenditures; rather than other behavior changes that 
occurred that impacted aggregate expenditures. As such, commenters 
presented an alternative method that compares aggregate expenditures 
between the CY 2018 simulated 30-day periods with the three behavior 
assumptions applied to the CY 2020 actual 30-day periods. As we have 
stated previously in the CY 2020 HH PPS final rule with comment period 
and in the CY 2022 HH PPS final rule (84 FR 60513, 86 FR 62248), we 
interpret actual behavior changes to encompass both behavior changes 
that were previously outlined, as assumed by CMS, and other behavior 
changes not identified at the time that the budget neutral 30-day 
payment amount for CY 2020 was determined. We use claims data to 
calculate estimated aggregate expenditures under the HH PPS, regardless 
of methodology. All claims data are products of behavior changes, 
(whether or not acknowledged in previous rules), as well as 
interactions between behaviors. Therefore, any behavior changes 
observed under the PDGM are considered when determining an adjustment.
    A few commenters also proposed determining the extent to which 
nominal case-mix changes affected aggregate expenditures under the PDGM 
versus the old payment system as an alternative methodology to evaluate 
the behavior change assumptions. In order to evaluate case-mix changes, 
CMS previously utilized a regression model that estimated whether 
changes in case-mix were due to changes in agency coding practices or 
other nominal factors, versus real changes in patient characteristics 
or acuity. While changes in nominal case-mix may be supplemental to our 
findings, the law requires CMS to determine the effect of the 
difference between assumed versus actual behavioral changes on 
estimated aggregate expenditures, which are not factored into our 
calculations of case-mix adjustment authority. Section 
1895(b)(3)(B)(iv) of the Act states that CMS has the authority to 
adjust for case-mix changes that are a result of changes in the coding 
or classification of different units of services that do not reflect 
real changes in case mix. Therefore, at this time we do not believe 
analyses of nominal case-mix change is the most accurate method to 
evaluate what aggregate expenditures would have been in absence of the 
PDGM. Upon continued review of what the law requires us to do in 
regards to determining the difference between assumed versus actual 
behaviors on estimated aggregate expenditures, we continue to believe 
that the best reading of the law requires us to retrospectively 
determine if the 30-day payment amount in CY 2020 resulted in the same 
estimated aggregate expenditures that would have been made if the 
change in the unit of payment and the PDGM case-mix adjustment 
methodology had not been implemented.
    Furthermore, if the estimated aggregate expenditures are determined 
not to be equal, we are required, by law, to make permanent and 
temporary adjustments to the PDGM payment rate so that the expenditures 
across the two payments systems would be equal. We believe using the 
methodology described previously in the CY 2022 HH PPS proposed rule 
(85 FR 35890 through 35892 and in this proposed rule, best satisfies 
our interpretation of section 1895(b)(3)(D)(i) of the Act.
    Lastly, commenters raised concerns about the differing case-mix 
weight systems and that the data exclusions and assumptions made when 
creating the simulated 60-day episodes introduced some level of bias. 
Commenters stated that each case-mix system are unique to each payment 
system as they are dependent on the underlying variables used to 
describe clinical characteristics or resource use. For this reason, 
commenters had concerns that the two case-mix weight systems (153 vs 
432 case-mix groups) are not comparable. We recognize that the 
underlying variables in the payment regression are different, but a 
case-mix of 1.0 is interpreted the same way under both systems. For 
example, a case-mix of 1.000 means the predicted resource use for a 
particular home health 60-day episode or 30-day period is equal to 
overall average resource use. Therefore, we disagree with commenters 
that comparing the two case-mix systems is flawed. We note there may be 
some selection bias present due to the data exclusions and assumptions 
described in section II.B.2.b. of this proposed rule, but we believe 
this is minimal and does not significantly affect the overall 
calculation of estimated aggregate expenditures. For example, when we 
dropped fewer claims we got approximately the same results. Therefore, 
if we did not exclude claims (for example, there was no linked OASIS 
data available in the CCW VRDC) or make assumptions about which two 30-
day periods to combine, we would further introduce informational and 
analytical bias.
    We reiterate that this methodology uses simulated 60-day episodes 
priced using the pre-PDGM payment system parameters to determine what 
the estimated aggregate expenditures would have been in the absence of 
the PDGM and a 30-day unit of payment. The resulting estimated 
aggregate expenditures from the pre-PDGM payment system are compared to 
actual aggregate expenditures from the PDGM 30-day periods to 
determine, if a permanent prospective adjustment and/or a temporary 
retrospective adjustment are needed to offset the difference in 
estimated aggregate expenditures. We propose to use this methodology, 
as described in this section of this rule, for CYs 2020 through 2026. 
We refer readers to sections II.B.2.d and II.B.2.e of this proposed 
rule for our preliminary results of our analysis for CYs 2020 and 2021, 
respectively.
b. Proposed Method To Annually Determine the Impact of Differences 
Between Assumed Behavior Changes and Actual Behavior Changes on 
Estimated Aggregate Expenditures
    We analyzed data to determine if the CY 2020 30-day payment amount 
resulted in the same estimated aggregate expenditures that would have 
been paid if the PDGM and change in the unit of payment had not been 
implemented. To evaluate if the 30-day budget neutral payment amount 
for CY 2020 maintained budget neutrality given the change to a 30-day 
unit of payment and the implementation of a new case-mix adjustment 
methodology without

[[Page 37617]]

therapy thresholds was accurate, we used actual CY 2020 30-day period 
claims data to simulate 60-day episodes, and we determined what CY 2020 
payments would have been under the 153-group case-mix system and 60-day 
unit of payment. To do this, we used the following steps:
    The first step in repricing CY 2020 PDGM claims was to calculate 
estimated aggregate expenditures under the pre-PDGM, 153-group case-mix 
system and 60-day unit of payment, by determining which PDGM 30-day 
periods of care could be grouped together to form simulated 60-day 
episodes of care. To facilitate grouping, we made some exclusions and 
assumptions as described later in this section prior to pricing out the 
simulated 60-day episodes of care. We note in the early months of CY 
2020, there were 60-day episodes which started in 2019 and ended in 
2020 and therefore, some of these exclusions and assumptions may be 
specific to the first year of the PDGM. We identify, through footnotes, 
if an exclusion or assumption is specific to CY 2020 only. The 
following describes the steps in determining the annual estimated 
aggregate expenditures including the exclusions and assumptions made 
when simulating 60-day episodes from actual 30-day periods.
(1) Exclusions
     Claims where the claim occurrence code 50 date (OASIS 
assessment date) occurred on or after October 31 of that year. This 
exclusion was applied to ensure the simulated 60-day episodes contained 
both 30-day periods from the same year and would not overlap into the 
following year (for example, 2021, 2022, 2023). This is done because 
any 30-day periods with an OASIS assessment date in November or 
December might be part of a simulated 60-day episode that would 
continue into the following year and where payment would have been made 
based on the ``through'' date. For CYs 2021 through 2026, we also 
excluded claims with an OASIS assessment date before January 1 of that 
year. \10\ Again, this is to ensure a simulated 60-day episode 
(simulated from two 30-day periods) does not overlap years.
---------------------------------------------------------------------------

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

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

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

     Beneficiaries and all of their claims if three or more 
claims from the same provider are linked to the same occurrence code 50 
date.\12\
---------------------------------------------------------------------------

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

(2) Assumptions
     If two 30-day periods of care from the same provider 
reference the same OASIS assessment date (using occurrence code 50), 
then we assume those two 30-day periods of care would have been billed 
as a 60-day episode of care under the 153-group system.
     If two 30 day-periods of care reference different OASIS 
assessment dates and each of those assessment dates is referenced by a 
single 30-day period of care, and those two 30-day periods of care 
occur together close in time (that is, the ``from'' date of the later 
30-day period of care is between 0 to 14 days after the ``through'' 
date of the earlier 30-day period of care), then we assume those two 
30-day periods of care also would have been billed as a 60-day episode 
of care under the 153-group system.
     For all other 30-day periods of care, we assume that they 
would not be combined with another 30-day period of care and would have 
been billed as a single 30-day period.
(3) Calculating Estimated Aggregate Expenditures--Pricing Simulated 60-
Day Episode Claims
    After application of the exclusions and assumptions described 
previously we have the simulated the 60-day episode datasets for each 
year. Starting with CY 2020, we assign each 60-day episode of care as a 
normal episode, PEP, LUPA, or outlier based on the payment parameters 
established in the CY 2020 final rule with comment period (84 FR 60478) 
for 60-day episodes of care. Next, using the October 2019 3M Home 
Health Grouper (v8219) \13\ we assign a HIPPS code to each simulated 
60-day episode of care using the 153-group methodology. Finally, we 
price the CY 2020 simulated 60-day episodes of care using the payment 
parameters described in the CY 2020 final rule with comment period (84 
FR 60537) for 60-day episodes of care. For CYs 2021 through 2026, we 
would adjust the simulated 60-day base payment rate to align with 
current payments for the analysis year (that is, wage index budget 
neutrality factor, HH payment update). For example, to calculate the CY 
2021 simulated 60-day episode base payment rate, we would start with 
the final CY 2020 60-day base payment rate ($3,220.79) and multiply by 
the final CY 2021 wage index budget neutrality factor (0.9999) and the 
CY 2021 HH payment update (1.020) to get an adjusted 60-day base 
payment rate ($3,284.88) for CY 2021. We would use the 60-day base 
payment rate ($3,284.88) to price the CY 2021 simulated 60-day claims 
under the pre-PDGM HH PPS (60-day episodes under 153 case-mix groups) 
based on actual behaviors. Once each claim is priced under the pre-PDGM 
HH PPS, we calculate the estimated aggregate expenditures for all 
simulated 60-day episodes in CY 2021. This method would be used to 
reprice claims to simulated 60-day episodes for each subsequent year 
(that is, through CY 2026).
---------------------------------------------------------------------------

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

    Next, we calculated the PDGM aggregate expenditures for CY 2020 
using those specific 30-day periods that were used to create the 
simulated 60-day episodes. Therefore, both the actual CY 2020 PDGM 
expenditures and the simulated pre-PDGM CY 2020 aggregate expenditures 
are based on the same claims for the permanent adjustment calculation.
c. Calculating Permanent and Temporary Payment Adjustments
    To offset for such increases or decreases in estimated aggregate 
expenditures as a result of the impact of differences between assumed 
behavior changes and actual behavior changes, in any given year, we 
calculate a permanent prospective adjustment by determining what the 30 
day base payment amount should have been in order to achieve the same 
estimated aggregate expenditures as obtained from the simulated 60-day 
episodes. This would be our recalculated base payment rate. The percent 
change between the actual 30-day base payment rate and the recalculated 
30-day base payment rate would be the permanent prospective adjustment.
    To calculate a temporary retrospective adjustment for each year we 
would determine the dollar amount difference between the estimated 
aggregate expenditures from all 30-day periods using the recalculated 
30-day base payment rate, and the aggregate expenditures for all 30-day 
periods using the actual 30-day base payment rate for the same year. In 
determining the temporary retrospective dollar

[[Page 37618]]

amount, we use the full dataset of actual 30-day periods using both the 
actual and recalculated base payment rates to ensure utilization and 
distribution of claims are the same. In accordance with section 
1895(b)(3)(D)(iii) of the Act, the temporary adjustment is to be 
applied on a prospective basis and shall apply only with respect to the 
year for which such temporary increase or decrease is made. Therefore, 
after we determine the dollar amount to be reconciled in any given 
year, we calculate a temporary adjustment factor to be applied to the 
base payment rate. The temporary adjustment factor is based on an 
estimated number of 30-day periods in the next year using historical 
data trends, and as applicable, we control for a permanent adjustment 
factor, case-mix weight recalibration neutrality factor, wage index 
budget neutrality factor, and the home health payment update. The 
temporary adjustment factor is applied last.
d. CY 2020 Results
    Using the methodology described previously, we simulated 60-day 
episodes using actual CY 2020 30-day periods to determine what the CY 
2020 permanent and temporary payment adjustments should be to offset 
for such increases or decreases in estimated aggregate expenditures. 
For CY 2020, we began with 8,423,688 30-day periods and dropped 603,157 
30-day periods that had a claim occurrence code 50 date after October 
31, 2020. We also eliminated 79,328 30-day periods that didn't appear 
to group with another 30-day period to form a 60-day episode if the 30-
day period had a ``from date'' before January 15, 2020 or a ``through 
date'' after November 30, 2020. This was done to ensure a 30-day period 
would not have been part of a 60-day episode that would have overlapped 
into CY 2021. Applying the additional exclusions and assumptions as 
described previously, an additional 14,062 30-day periods were excluded 
from this analysis. Additionally, we excluded 66,469 simulated 60-day 
episodes of care where no OASIS information was available in the CCW 
VRDC or could not be grouped to a HIPPS due to a missing primary 
diagnosis or other reason. Our simulated 60-day episodes of care 
produced a distribution of two 30-day periods of care (70.6 percent) 
and single 30-day periods of care (29.4 percent). This distribution is 
similar to what we found when we simulated 30-day periods of care for 
implementation of the PDGM. After all exclusions and assumptions were 
applied, the final dataset included 7,618,061 actual 30-day periods of 
care and 4,463,549 simulated 60-day episodes of care for CY 2020.
    Using the final dataset for CY 2020 (7,618,061 actual 30-day 
periods which made up the 4,463,549 simulated 60-day episodes) we 
determined the estimated aggregate expenditures under the pre-PDGM HH 
PPS was lower than the actual estimated aggregate expenditures under 
the PDGM HH PPS (see Table B13). This indicates that aggregate 
expenditures under the PDGM were higher than if the 153-group payment 
system was still in place in CY 2020. As described previously, we 
recalculated what the CY 2020 30-day base payment rate should have been 
to equal aggregate expenditures that we calculated using the simulated 
CY 2020 60-day episodes. The percent change between the two payment 
rates would be the permanent adjustment. Next, we calculated the 
difference in aggregate expenditures for all CY 2020 PDGM 30-day claims 
using the actual and recalculated payment rates. This difference is the 
retrospective dollar amount needed to offset payment. Our results are 
shown in Table B13.
[GRAPHIC] [TIFF OMITTED] TP23JN22.016

    As shown in Table B13, a permanent prospective adjustment of -6.52 
percent to the CY 2023 30-day payment rate would be required to offset 
for such increases in estimated aggregate expenditures in future years. 
Additionally, we determined that our initial estimate of base payment 
rates required to achieve budget neutrality resulted in excess 
expenditures of HHAs of approximately $873 million in CY 2020. This 
would require a temporary adjustment to offset for such increase in 
estimated aggregate expenditures for CY 2020.
e. CY 2021 Preliminary Results
    We will continue the practice of using the most recent complete 
home health claims data at the time of rulemaking. The CY 2021 analysis 
presented in this proposed rule is considered preliminary and as more 
data become available from the latter half of CY 2021, we will update 
our results in the final rule. Using the methodology described 
previously, we simulated 60-day episodes using actual CY 2021 30-day 
periods to determine what the permanent and temporary payment 
adjustments should be to offset for such increases or decreases in 
estimated aggregate expenditures as a result of the impact of 
differences between assumed behavior changes and actual behavior 
changes. For CY 2021, we began with 8,962,690 30-day periods of care 
and dropped 478,105 30-day periods of care that had claim occurrence 
code 50 date after October 31, 2021. We also excluded 968,361 30-day 
periods of care that had claim occurrence code 50 date before January 
1, 2021 to ensure the 30-day period would not be part of a simulated 
60-day episode that began in

[[Page 37619]]

CY 2020. Applying the additional exclusions and assumptions as 
described previously, an additional 4,853 30-day periods were excluded.
    Additionally, we excluded 11,143 simulated 60-day episodes of care 
where no OASIS information was available in the CCW VRDC or could not 
be grouped to a HIPPS due to a missing primary diagnosis or other 
reason. Our simulated 60-day episodes of care produced a distribution 
of two 30-day periods of care (69.1 percent) and single 30-day periods 
of care (30.9 percent) that was similar to what we found when we 
simulated two 30-day periods of care for implementation of the PDGM. 
After all exclusions and assumptions were applied, the final dataset 
included 7,494,836 actual 30-day periods of care and 4,431,238 
simulated 60-day episodes of care for CY 2021.
    Using the final dataset for CY 2021 (7,494,836 actual 30-day 
periods which made up the 4,431,238 simulated 60-day episodes) we 
determined the estimated aggregate expenditures under the pre-PDGM HH 
PPS was lower than the actual estimated aggregate expenditures under 
the PDGM HH PPS. This indicates that aggregate expenditures under the 
PDGM were higher than if the 153-group payment system was still in 
place in CY 2021. As described previously, we recalculated what the CY 
2021 30-day base payment rate should have been to equal aggregate 
expenditures that we calculated using the simulated CY 2021 60-day 
episodes. We note, the actual CY 2021 base payment rate of $1,901.12 
does not account for any adjustments previously made for CY 2020 and 
therefore to evaluate changes for only CY 2021 we need to control for 
the -6.52 percent prospective adjustment that we determined for CY 
2020. Therefore, using the recalculated CY 2020 base payment rate of 
$1,742.52, multiplied by the CY 2021 wage index budget neutrality 
factor (0.9999) and the CY 2021 HH payment update (1.020), the CY 2021 
base payment rate for assumed behavior would have been $1,777.19. The 
percent change between the two payment rates would be the permanent 
adjustment. Next, we calculated the difference in aggregate 
expenditures for all CY 2021 PDGM 30-day claims using the actual and 
recalculated payment rates. This difference is the retrospective dollar 
amount needed to offset payment. Our results are shown in Table B14.
[GRAPHIC] [TIFF OMITTED] TP23JN22.017

    As shown in Table B14, a permanent prospective adjustment of -1.26 
percent and would be required to offset for such increases in estimated 
aggregate expenditures in future years. Additionally, we determined 
that our initial estimate of base payment rates required to achieve 
budget neutrality resulted in excess expenditures of approximately $1.1 
billion in CY 2021. This would require a one-time temporary adjustment 
factor to offset for such increases in estimated aggregate expenditures 
for CY 2021.
f. Proposed CY 2023 Permanent and Temporary Adjustments
    The percent change between the actual CY 2021 base payment rate of 
$1,901.12 and the CY 2021 recalculated base payment rate of $1,754.88 
is the total permanent adjustment for CYs 2020 and 2021, because no 
previous adjustments were applied to the CY 2020 rate to reset the CY 
2021 rate. The summation of the dollar amount for CYs 2020 and 2021 is 
the amount that represents the temporary payment adjustment to offset 
for increased aggregate expenditures in both CYs 2020 and 2021. Our 
results are shown in Table B15 and B16.

[[Page 37620]]

[GRAPHIC] [TIFF OMITTED] TP23JN22.018

[GRAPHIC] [TIFF OMITTED] TP23JN22.019

    To offset the increase in estimated aggregate expenditures for CYs 
2020 and 2021 based on the impact of the differences between assumed 
and actual behavior changes, CMS would need to apply a -7.69 percent 
permanent adjustment to the CY 2023 base payment rate as well as 
implement a temporary adjustment of approximately $2.0 billion to 
reconcile retrospective overpayments in CYs 2020 and 2021. We recognize 
that applying the full permanent and temporary adjustment immediately 
would result in a significant negative adjustment in a single year. 
However, if the PDGM base 30-day payment rate remains higher than it 
should be, then there would likely be a compounding effect potentially 
creating the need for a larger reduction in future years. Therefore, we 
propose initially to apply only the permanent adjustment of -7.69 
percent to the CY 2023 base payment rate. We believe this could 
mitigate the need for a larger permanent adjustment and could reduce 
the amount of any additional temporary adjustments in future years. We 
are soliciting comments on the application of only the permanent 
payment adjustment to the CY 2023 30-day payment rate. Additionally, we 
solicit comments on how best to collect the temporary payment 
adjustment of approximately $2.0 billion for CYs 2020 and 2021. As 
noted previously, we will update these permanent and temporary 
adjustments in the final rule to reflect more complete claims data for 
CY 2021.
    3. Proposed Reassignment of Specific ICD-10-CM Codes Under the PDGM
a. Background
    The 2009 final rule, ``HIPAA Administrative Simplification: 
Modifications to Medical Data Code Set Standards To Adopt ICD-10-CM and 
ICD-10-PCS'' \14\ (74 FR 3328, January 16, 2009), set October 1, 2013, 
as the compliance date for all covered entities under the Health 
Insurance Portability and Accountability Act of 1996 (HIPAA) to use the 
International Classification of Diseases, 10th Revision, Clinical 
Modification (ICD-10-CM) and the International Classification of 
Diseases, 10th Revision, Procedure Coding System (ICD-10-PCS) medical 
data code sets. The ICD-10-CM diagnosis codes are granular and 
specific, and provide HHAs a better opportunity to report codes that 
best reflect the patient's conditions that support the need for home 
health services. However, as stated in the CY 2019 HH PPS final rule 
with comment period (83 FR 56473), because the ICD-10-CM is 
comprehensive, it also contains many codes that may not support the 
need for home health services. For example, diagnosis codes that 
indicate death as the outcome are Medicare covered codes, but are not 
relevant to home health. In addition, diagnosis and procedure coding 
guidelines may specify the sequence of ICD-10-CM coding conventions. 
For example, the underlying condition must be listed first (for 
example, Parkinson's disease must be listed prior to Dementia if both 
codes were listed on a claim). Therefore, not all the ICD-10-CM 
diagnosis codes are appropriate as principal diagnosis codes for 
grouping home health periods into clinical groups or to be placed into 
a comorbidity subgroup when listed as a secondary diagnosis. As such, 
each ICD-10-CM diagnosis code is assigned, including those diagnosis 
codes designated as ``not assigned'' (NA), to a clinical group and 
comorbidity subgroup within the HH PPS grouper software (HHGS). We 
remind commenters the ICD-10-CM diagnosis code list is updated each 
fiscal year with an effective date of October 1st and therefore, the HH 
PPS is generally subject to a minimum of two HHGS releases, one in 
October and one in January of each year, to ensure that claims are 
submitted with the most current code set available. Likewise, there may 
be new ICD-10-CM diagnosis codes created (for example, codes for 
emergency use) or a new or revised edit in the Medicare Code Editor 
(MCE) so an update to the HHGS may occur on the first of each quarter 
(January, April, July, October).
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    \14\ https://www.federalregister.gov/documents/2009/01/16/E9-743/hipaa-administrative-simplification-modifications-to-medical-data-code-set-standards-to-adopt.
---------------------------------------------------------------------------

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

[[Page 37621]]

reporting COVID-19 vaccination status were effective April 1, 2022) or 
minor tweaks to a descriptor of an existing ICD-10-CM diagnosis code 
generally would not require rulemaking, and may occur at any time. 
However, if an ICD-10-CM diagnosis code is to be reassigned from one 
clinical group and/or a comorbidity subgroup to another, which may 
affect payment, then we believe it is appropriate to propose these 
changes through notice and comment rulemaking.
    We rely on the expert opinion of our clinical reviewers (for 
example, nurse consultants and medical officers) and current ICD-10-CM 
coding guidelines to determine if the ICD-10-CM diagnosis codes under 
review for reassignment are significantly similar or different to the 
existing clinical group and/or comorbidity subgroup assignment. As we 
stated in the CY 2018 proposed rule (82 FR 35313), the intent of the 
clinical groups is to reflect the reported principal diagnosis, 
clinical relevance, and coding guidelines and conventions. Therefore, 
for the purposes of assignment of ICD-10-CM diagnosis codes into the 
PDGM clinical groups we would not conduct additional statistical 
analysis as such decisions are clinically based and the clinical groups 
are part of the overall case-mix weights.
    In the CY 2019 final rule with comment period (83 FR 56486), we 
stated the home health-specific comorbidity list is based on the 
principles of patient assessment by body systems and their associated 
diseases, conditions, and injuries to develop larger categories of 
conditions that identified clinically relevant relationships associated 
with increased resource use meaning the diagnoses have at least as high 
as the median resource use and are reported in more than 0.1 percent of 
30-day periods of care. If specific ICD-10-CM diagnosis codes are to be 
reassigned to a different comorbidity subgroup (including NA), we will 
first evaluate the clinical characteristics (as discussed previously 
for clinical groups) and if the ICD-10-CM diagnosis code does not meet 
the clinical criteria, then no reassignment will occur. However, if an 
ICD-10-CM diagnosis code does meet the clinical criteria for a 
comorbidity subgroup reassignment, then we will evaluate the resource 
consumption associated with the ICD-10-CM diagnosis codes, the current 
assigned comorbidity subgroup, and the proposed (reassigned) 
comorbidity subgroup. This analysis is to ensure that any reassignment 
of an ICD-10-CM diagnosis code (if reported as secondary) in any given 
year would not significantly alter the overall resource use of a 
specific comorbidity subgroup. For resource consumption, we use non-
LUPA 30-day periods to evaluate the total number of 30-day periods for 
the comorbidity subgroup(s) and the ICD-10-CM diagnosis code, the 
average number of visits per 30-day periods for the comorbidity 
subgroup(s) and the ICD-10-CM diagnosis code, and the average resource 
use for the comorbidity subgroup(s) and the ICD-10-CM diagnosis code. 
The average resource use measures the costs associated with visits 
performed during a home health period, and was previously described in 
the CY 2019 final rule with comment period (83 FR 56450).
c. Proposed ICD-10-CM Diagnosis Code Reassignments to a PDGM Clinical 
Group or Comorbidity Subgroup
    The following section proposes reassignment of 320 diagnosis codes 
to a different clinical group when listed as a principal diagnosis, 
reassignment of 37 diagnosis codes to a different comorbidity subgroup 
when listed as a secondary diagnosis, and the establishment of a new 
comorbidity subgroup for certain neurological conditions and disorders. 
Due to the amount of diagnosis codes proposed for reassignment this 
year, we have posted the ``CY 2023 Proposed Reassignment of ICD-10-CM 
Diagnosis Codes for HH PDGM Clinical Groups and Comorbidity Subgroups'' 
supplemental file on the Home Health Prospective Payment System 
Regulations and Notices web page.\15\ The supplemental file can be 
accessed through the CY 2023 Home Health Prospective Payment System 
Rate Update; Home Health Quality Reporting Requirements; and Home 
Infusion Therapy Requirements link. The following tables are included 
in the supplemental file:
---------------------------------------------------------------------------

    \15\ Home Health Prospective Payment System Regulations and 
Notices web page. https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/HomeHealthPPS/Home-Health-Prospective-Payment-System-Regulations-and-Notices.
[GRAPHIC] [TIFF OMITTED] TP23JN22.020

(1) Proposed Clinical Group Reassignment of Certain Unspecified 
Diagnosis Codes
    We remind readers that in the CY 2019 final rule with comment 
period (83 FR 56473) we stated that whenever possible, the most 
specific code that describes a medical disease, condition, or injury 
should be used. Generally, ``unspecified'' codes are used when there is 
lack of information about location or severity of medical conditions in 
the medical record. However, we would expect a provider to use a 
precise code whenever more specific codes are available. Furthermore, 
if additional information regarding the diagnosis is needed, we would 
expect the HHA to follow-up with the referring provider in order to 
ensure the care plan is sufficient in

[[Page 37622]]

meeting the needs of the patient. For example, T14.90 ``Injury, 
unspecified'' does not provide sufficient information (for example, the 
type and extent of the injury) that would be necessary in care planning 
for home health services. The ICD-10-CM code set also includes 
laterality. We believe a home health clinician should not report an 
``unspecified'' code if that clinician can identify the side or site of 
a condition. For example, a home health clinician should be able to 
state whether a fracture of the arm is on the right or left arm. In the 
FY 2022 Inpatient Prospective Payment System/Long-Term Care Hospital 
Prospective Payment System (IPPS/LTCH PPS) final rule (86 FR 44940 
through 44943), CMS finalized the implementation of a new MCE to expand 
the list of unacceptable principal diagnoses for ``unspecified'' ICD-
10-CM diagnosis codes when there are other diagnosis codes available in 
that diagnosis code subcategory that further specify the anatomic site. 
As such, we reviewed the ICD-10-CM diagnosis codes where 
``unspecified'' is used. We identified 159 ICD-10-CM diagnosis codes 
currently accepted as a principal diagnosis that have more specific 
codes available for such medical conditions that would more accurately 
identify the primary reason for home health services. For example, 
S59.109A (Unspecified physeal fracture of upper end of radius, 
unspecified arm, initial encounter for closed fracture) does not 
specify which arm has the fracture; whereas, S59.101A (Unspecified 
physeal fracture of upper end of radius, right arm, initial encounter 
for closed fracture) does indicate the fracture is on the right arm and 
therefore more accurately identifies the primary reason for home health 
services. Therefore, in accordance with our expectation that the most 
precise code be used, we believe these 159 ICD-10 CM diagnosis codes 
are not acceptable as principal diagnoses and we propose to reassign 
them to ``no clinical group'' (NA). We refer readers to Table 1.A of 
the CY 2023 Proposed Reassignment of ICD-10-CM Diagnosis Codes 
supplemental file \16\ for the list of the 159 unspecified diagnosis 
codes.
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    \16\ Home Health Prospective Payment System Regulations and 
Notices web page. https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/HomeHealthPPS/Home-Health-Prospective-Payment-System-Regulations-and-Notices.
---------------------------------------------------------------------------

    We also determined that B78.9 strongyloidiasis, unspecified was 
assigned to clinical group C (Wounds), and should be reassigned to 
clinical group K (MMTA--Infectious Disease, Neoplasms, and Blood-
Forming Diseases) because it would be consistent with the assignment of 
the other strongyloidiasis codes. We also identified that N83.201 
unspecified ovarian cyst, right side was assigned to clinical group A 
(MMTA-Other) and should be reassigned to clinical group J (MMTA--
Gastrointestinal Tract and Genitourinary System) because it would be 
consistent with the assignment of other ovarian cyst codes. We propose 
to reassign these two ICD-10-CM diagnosis codes' clinical groups as 
shown in Table B17.
[GRAPHIC] [TIFF OMITTED] TP23JN22.021

(2) Proposed Clinical Group Reassignment of Gout-Related Codes
    We identified that certain groups of gout-related ICD-10-CM 
diagnosis codes, such as idiopathic gout and drug-induced gout, were 
assigned to clinical group E (musculoskeletal rehabilitation) when 
listed as a principal diagnosis. However, other groups of gout related 
ICD-10-CM diagnosis codes, such as gout due to renal impairment, were 
assigned to ``no clinical group'' (NA). Therefore, we reviewed all 
gout-related codes and determined there are 144 gout related codes with 
an anatomical site specified, not currently assigned to a clinical 
group that should be moved to clinical group E (musculoskeletal 
rehabilitation) for consistency with the aforementioned gout codes. In 
the ICD-10-CM code set, gout codes and osteoarthritis codes are found 
in chapter 13 Diseases of the Musculoskeletal System and Connective 
Tissue (M00-M99). Gout and osteoarthritis affect similar joints such as 
the fingers, toes, and knees and they can initially be treated with 
medications. However, generally, as a part of a treatment program, once 
the initial inflammation is reduced, physical therapy can be started to 
stretch and strengthen the affected joint to restore flexibility and 
joint function. Because those cases may require therapy, we believe 
gout codes are more appropriately placed into MS rehab along with other 
codes affecting the musculoskeletal system. We refer readers to Table 
1.B of the CY 2023 Proposed Reassignment of ICD-10-CM Diagnosis Codes 
supplemental file for the list of the 144 gout related codes. We 
propose to reassign these 144 gout-related ICD-10-CM diagnosis codes to 
clinical group E (musculoskeletal rehabilitation).
(3) Proposed Clinical Group Reassignment of Crushing Injury-Related 
Codes
    We identified 12 ICD-10-CM diagnosis codes related to crushing 
injury of the face, skull, and head that warrant reassignment. These 
codes are listed in Table B18.

[[Page 37623]]

[GRAPHIC] [TIFF OMITTED] TP23JN22.022

    Our clinical advisors reviewed the 12 ICD-10-CM diagnosis codes 
related to crushing injury of the face, skull, and head and determined 
that reassignment of these codes to clinical group B (Neurological 
Rehabilitation) is clinically appropriate because they are consistent 
with other diagnosis codes in clinical group E that describe injuries 
requiring neurological rehabilitation. Therefore, we propose to 
reassign the ICD-10-CM diagnosis codes listed in Table B18 from 
clinical group A (MMTA-Other) to clinical group B (Neurological 
Rehabilitation).
(4) Proposed Clinical Group Reassignment of Lymphedema-Related Codes
    We received questions from interested parties regarding three 
lymphedema codes with conflicting clinical group assignments when 
listed as a principal diagnosis. These codes are listed in Table B19.
[GRAPHIC] [TIFF OMITTED] TP23JN22.023

    Our clinical advisors reviewed the three ICD-10-CM diagnosis codes 
related to lymphedema and determined that assessing and treating 
lymphedema is similar to the assessment and staging of wounds. It 
requires the assessment of pulses, evaluation of the color and amount 
of drainage, and measurement. In addition, some lymphedema can require 
compression bandaging, similar to wound care. Because of these 
similarities, we determined the reassignment of the three ICD-10-CM 
diagnosis codes related to lymphedema to clinical group C (Wounds) is 
clinically appropriate. Therefore, we propose to reassign the ICD-10-CM 
diagnosis codes listed in Table B19 from clinical group E 
(Musculoskeletal Rehabilitation) and clinical group A (MMTA-Other) to 
clinical group C (Wounds).
(5) Proposed Behavioral Health Comorbidity Subgroups
    Our clinical advisors reviewed the ICD-10-CM diagnosis code F60.5

[[Page 37624]]

(obsessive-compulsive personality disorder) which is currently assigned 
to the comorbidity subgroup behavioral 6 (Schizotypal, Persistent Mood, 
and Adult Personality Disorders). However, they noted that behavioral 5 
(Phobias, Other Anxiety and Obsessive-Compulsive Disorders) contains 
other obsessive-compulsive disorders (for example, F42.8 and F42.9) and 
clinically F60.5 should be reassigned to the comorbidity subgroup 
behavioral 5. In addition, we evaluated resource consumption related to 
the comorbidity subgroup behavioral 5, the comorbidity subgroup 
behavioral 6, and F60.5 and found no significant variations negating a 
reassignment, meaning the reassignment is still in alignment with the 
actual costs of providing care. Therefore, we propose to reassign 
diagnosis code F60.5 to behavioral 5 when listed as a secondary 
diagnosis.
(6) Proposed Circulatory Comorbidity Subgroups
    We reviewed Q82.0 (hereditary lymphedema) for clinical group 
reassignment, as described in section II.B.3.4. of this rule. During 
this review, we discovered Q82.0 is not currently assigned to a 
comorbidity subgroup when listed as a secondary diagnosis. The 
comorbidity subgroup circulatory 10 includes ICD-10-CM diagnosis codes 
related to varicose veins and lymphedema and our clinical advisors 
determined that Q82.0 should be assigned to the comorbidity subgroup 
circulatory 10 similar to other lymphedema diagnosis codes. In 
addition, we evaluated resource consumption related to the comorbidity 
subgroup circulatory 10 and Q82.0 and found no significant variations 
negating a reassignment. Therefore, we propose to assign diagnosis code 
Q82.0 to circulatory 10 (varicose veins and lymphedema) when listed as 
a secondary diagnosis.
(7) Proposed Neoplasm Comorbidity Subgroups
(i) Malignant Neoplasm of Upper Respiratory
    In response to interested parties' questions regarding upper 
respiratory malignant neoplasms, we reviewed 14 ICD-10-CM diagnosis 
codes related to malignant neoplasms of the upper respiratory tract 
currently assigned to the comorbidity subgroup neoplasm 6 (malignant 
neoplasms of trachea, bronchus, lung, and mediastinum). These 14 codes 
are listed in Table B20.
[GRAPHIC] [TIFF OMITTED] TP23JN22.024

    Our clinical advisors reviewed the codes listed in Table B20 and 
determined that C32.3, C32.8, and C32.9 are currently assigned to the 
most clinically appropriate neoplasm comorbidity subgroup (neoplasm 6), 
and therefore no further analysis was conducted for these three ICD-10 
CM diagnosis codes. However, upon review of all the neoplasm 
comorbidity subgroups, they determined that the remaining 11 codes 
listed in Table B20 should be reassigned to neoplasm 1 (malignant 
neoplasms of lip, oral cavity, and pharynx, including head and neck

[[Page 37625]]

cancers) in alignment with clinically similar diagnosis codes already 
assigned (for example, C11.0 malignant neoplasm of superior wall of 
nasopharynx). In addition, we evaluated resource consumption related to 
the comorbidity subgroup, neoplasm 1, as well as diagnosis codes, 
C30.0, C30.1, C31.0, C31.1, C31.2, C31.3, C31.8, C31.9, C32.0, C32.1, 
or C32.2 and found no significant variations negating a reassignment.
    Therefore, we propose to reassign diagnosis codes C30.0, C30.1, 
C31.0, C31.1, C31.2, C31.3, C31.8, C31.9, C32.0, C32.1, or C32.2 from 
neoplasm 6 to neoplasm 1 when listed as a secondary diagnosis.
(ii) Malignant Neoplasm of Unspecified Adrenal Gland
    While reviewing unspecified codes for a change in clinical group, 
we noticed that ICD-10-CM diagnosis codes C74.00 (malignant neoplasm of 
cortex of unspecified adrenal gland) and C74.90 (malignant neoplasm of 
unspecified part of unspecified adrenal gland) were coded as ``N/A'' 
instead of placed in a comorbidity subgroup. The comorbidity subgroup 
neoplasm 15 currently includes ICD-10-CM diagnosis codes related to 
malignant neoplasm of adrenal gland, endocrine glands and related 
structures; specifically, C74.10 (malignant neoplasm of medulla of 
unspecified adrenal gland). At this time, we believe that C74.00 and 
C74.90 should be reassigned to neoplasm 15 based on clinical 
similarities of other codes currently assigned. In addition, we 
evaluated resource consumption related to the comorbidity subgroup 
neoplasm 15, as well as diagnosis codes C74.00, and C74.90 and found no 
significant variations negating a reassignment. Therefore, we propose 
to reassign diagnosis codes C74.00 and C74.90 from ``NA'' to neoplasm 
15 (malignant neoplasm of adrenal gland, endocrine glands and related 
structures) when listed as secondary diagnoses.
(8) Proposed New Neurological Comorbidity Subgroup
    In response to a comment received, we discussed in the CY 2022 
final rule (86 FR 62263, 62264) our review of ICD-10-CM diagnosis codes 
related to specified neuropathy or unspecified polyneuropathy. These 
include specific ICD-10-CM G-codes. We stated that the codes were 
assigned to the most clinically appropriate subgroup at the time. 
However, upon further clinical review we believe a new neurological 
comorbidity subgroup to include ICD-10-CM diagnosis codes related to 
nondiabetic neuropathy is warranted. We identified 18 ICD-10-CM 
diagnosis codes for potential reassignment to a proposed new 
comorbidity subgroup, neurological 12. We refer readers to Table 1.C of 
the CY 2023 Proposed Reassignment of ICD-10-CM Diagnosis Codes 
supplemental file for a list of the G-codes related to specified 
neuropathy or unspecified polyneuropathy. Of the 18 codes, 11 diagnosis 
codes were not currently assigned a comorbidity group and seven 
diagnosis codes were assigned to neurological 11 comorbidity subgroup.
    Using claims data from the CY 2021 HH PPS analytical file, we 
identified that the 18 diagnosis G-codes related to specified 
neuropathy or unspecified polyneuropathy would have sufficient claims 
(>400,000) for a new comorbidity subgroup. The removal of the seven 
codes from the neurological 11 comorbidity subgroup, would still allow 
for sufficient claims (>250,000) and include the remaining 146 
diagnosis codes currently listed in the neurological 11 comorbidity 
subgroup. We evaluated resource consumption related to the comorbidity 
subgroup neurological 11, the 18 diagnosis G-codes, and the proposed 
comorbidity subgroup neurological 12 and found no significant 
variations negating a reassignment. A new neurological comorbidity 
subgroup allows more clinically similar codes, nondiabetic neuropathy, 
to be grouped together. Therefore, we propose to reassign the 18 
diagnosis codes listed in Table 1.C of the CY 2023 Proposed 
Reassignment of ICD-10 CM Diagnosis Codes supplemental file, to the new 
comorbidity subgroup neurological 12 (nondiabetic neuropathy) when 
listed as secondary diagnoses. In conjunction with the proposed new 
comorbidity subgroup, we propose to change the description of the 
current comorbidity subgroup, neurological 11, from ``Diabetic 
Retinopathy and Macular Edema'' to ``Disease of the Macula and 
Blindness/Low Vision''.
(9) Proposed Respiratory Comorbidity Subgroups
(i) J18.2 Hypostatic Pneumonia, Unspecified Organism
    Our clinical advisors reviewed the ICD-10-CM diagnosis code J18.2 
(hypostatic pneumonia, unspecified organism) which is currently 
assigned to the comorbidity subgroup respiratory 4 (bronchitis, 
emphysema, and interstitial lung disease). However, respiratory 2 
(whooping cough and pneumonia) contains other pneumonia with 
unspecified organism (for example, J18.1 and J18.8). Clinically, J18.2 
is similar to the other pneumonias in respiratory 2 and therefore, 
should be reassigned from comorbidity subgroup respiratory 4 to 
comorbidity subgroup respiratory 2. In addition, we evaluated resource 
consumption related to the comorbidity subgroups respiratory 2 and 
respiratory 4, and J18.2 and found no significant variations negating a 
reassignment.
    Therefore, we propose to reassign diagnosis code J18.2 (hypostatic 
pneumonia, unspecified organism) to respiratory 2 when listed as a 
secondary diagnosis.
(ii) J98.2 Interstitial Emphysema and J98.3 Compensatory Emphysema
    Our clinical advisors reviewed the ICD-10-CM diagnosis codes J98.2, 
interstitial emphysema and J98.3, compensatory emphysema, which are 
currently assigned to the comorbidity subgroup respiratory 9 
(respiratory failure and atelectasis). However, respiratory 4 
(bronchitis, emphysema, and interstitial lung disease) contains other 
emphysema codes (for example, J43.0 through J43.9) and therefore 
clinically we believe it is appropriate to reassign J98.2 and J98.3 to 
the comorbidity subgroup respiratory 9. In addition, we evaluated 
resource consumption related to the comorbidity subgroups respiratory 4 
and respiratory 9, as well as diagnosis codes J98.2, and J98.3 and 
found no significant variations negating a reassignment. Therefore, we 
propose to reassign diagnosis codes J98.2 and J98.3 to respiratory 4 
when listed as a secondary diagnosis.
(iii) U09.9 Post COVID-19 Condition, Unspecified
    Our clinical advisors reviewed the ICD-10-CM diagnosis code U09.9 
(post COVID-19 condition, unspecified), which is currently assigned to 
the comorbidity subgroup, respiratory 2 (whooping cough and pneumonia). 
However, respiratory 10 (2019 novel Coronavirus) contains other COVID-
19 codes (for example, U07.1). Therefore, we believe clinically that 
U09.9 should be reassigned to the comorbidity subgroup, respiratory 10. 
In addition, we evaluated resource consumption related to the 
comorbidity subgroups respiratory 2 and respiratory 10, and diagnosis 
codes U09.9 and found no significant variations negating a 
reassignment.
    Therefore, we propose to reassign diagnosis code U09.9 to 
respiratory 10 when listed as a secondary diagnosis.
    We solicit comments on all of the proposed clinical group and

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comorbidity subgroup reassignments described in this section.
4. Proposed CY 2023 PDGM LUPA Thresholds and PDGM Case-Mix Weights
a. Proposed CY 2023 PDGM LUPA Thresholds
    Under the HH PPS, LUPAs are paid when a certain visit threshold for 
a payment group during a 30-day period of care is not met. In the CY 
2019 HH PPS final rule (83 FR 56492), we finalized that the LUPA 
thresholds would be set at the 10th percentile of visits or 2 visits, 
whichever is higher, for each payment group. This means the LUPA 
threshold for each 30 day period of care varies depending on the PDGM 
payment group to which it is assigned. If the LUPA threshold for the 
payment group is met under the PDGM, the 30-day period of care will be 
paid the full 30-day period case-mix adjusted payment amount (subject 
to any PEP or outlier adjustments). If a 30-day period of care does not 
meet the PDGM LUPA visit threshold, then payment will be made using the 
CY 2023 per-visit payment amounts as described in Section II.B.5.c. of 
this proposed rule. For example, if the LUPA visit threshold is four, 
and a 30-day period of care has four or more visits, it is paid the 
full 30-day period payment amount; if the period of care has three or 
less visits, payment is made using the per-visit payment amounts.
    In the CY 2019 HH PPS final rule with comment period (83 FR 56492), 
we finalized our policy that the LUPA thresholds for each PDGM payment 
group would be reevaluated every year based on the most current 
utilization data available at the time of rulemaking. However, as CY 
2020 was the first year of the new case-mix adjustment methodology, we 
stated in the CY 2021 final rule (85 FR 70305, 70306) that we would 
maintain the LUPA thresholds that were finalized and shown in Table 17 
of the CY 2020 HH PPS final rule with comment period (84 FR 60522) for 
CY 2021 payment purposes. We stated that at that time, we did not have 
sufficient CY 2020 data to reevaluate the LUPA thresholds for CY 2021.
    In the CY 2022 HH PPS final rule (86 FR 62249), we finalized the 
proposal to recalibrate the PDGM case-mix weights, functional 
impairment levels, and comorbidity subgroups while maintaining the LUPA 
thresholds for CY 2022. We stated that because there are several 
factors that contribute to how the case-mix weight is set for a 
particular case-mix group (such as the number of visits, length of 
visits, types of disciplines providing visits, and non-routine 
supplies) and the case-mix weight is derived by comparing the average 
resource use for the case-mix group relative to the average resource 
use across all groups, we believe the PHE would have impacted 
utilization within all case-mix groups similarly. Therefore, the impact 
of any reduction in resource use caused by the PHE on the calculation 
of the case-mix weight would be minimized since the impact would be 
accounted for both in the numerator and denominator of the formula used 
to calculate the case-mix weight. However, in contrast, the LUPA 
thresholds are based on the number of overall visits in a particular 
case-mix group (the threshold is the 10th percentile of visits or 2 
visits, whichever is greater) instead of a relative value (like what is 
used to generate the case-mix weight) that would control for the 
impacts of the PHE. We noted that visit patterns and some of the 
decrease in overall visits in CY 2020 may not be representative of 
visit patterns in CY 2022. Therefore, to mitigate any potential future 
and significant short-term variability in the LUPA thresholds due to 
the COVID-19 PHE, we finalized the proposal to maintain the LUPA 
thresholds finalized and displayed in Table 17 in the CY 2020 HH PPS 
final rule with comment period (84 FR 60522) for CY 2022 payment 
purposes.
    For CY 2023, we are proposing to update the LUPA thresholds using 
CY 2021 Medicare home health claims (as of March 21, 2022) linked to 
OASIS assessment data. After reviewing the CY 2021 home health claims 
utilization data we determined that visit patterns have stabilized. Our 
data analysis indicates that visits in 2021 were similar to visits in 
2020. We believe that CY 2021 data will be more indicative of visit 
patterns in CY 2023 rather than continuing to use the LUPA thresholds 
derived from the CY 2018 data pre-PDGM. Therefore, we are proposing to 
update the LUPA thresholds for CY 2023 using data from CY 2021. In 
general, there is not much variation in the updated LUPA thresholds; 
280 case-mix groups had no change in their LUPA threshold. There are 
120 case-mix groups that had their LUPA threshold go down by one visit 
and 18 case-mix groups that have their LUPA threshold go up by a visit. 
There are 12 case-mix groups that had their LUPA threshold go down by 
two visits and 2 case-mix groups that had their LUPA threshold go down 
by three visits.
    The proposed LUPA thresholds for the CY 2023 PDGM payment groups 
with the corresponding Health Insurance Prospective Payment System 
(HIPPS) codes and the case-mix weights are listed in Table B26. We 
solicit public comments on the proposed updates to the LUPA thresholds 
for CY 2023.
b. CY 2023 Functional Impairment Levels
    Under the PDGM, the functional impairment level is determined by 
responses to certain OASIS items associated with activities of daily 
living and risk of hospitalization; that is, responses to OASIS items 
M1800-M1860 and M1033. A home health period of care receives points 
based on each of the responses associated with these functional OASIS 
items, which are then converted into a table of points corresponding to 
increased resource use. The sum of all of these points results in a 
functional score which is used to group home health periods into a 
functional level with similar resource use. That is, the higher the 
points, the higher the response is associated with increased resource 
use. The sum of all of these points results in a functional impairment 
score which is used to group home health periods into one of three 
functional impairment levels with similar resource use. The three 
functional impairment levels of low, medium, and high were designed so 
that approximately one-third of home health periods from each of the 
clinical groups fall within each level. This means home health periods 
in the low impairment level have responses for the functional OASIS 
items that are associated with the lowest resource use, on average. 
Home health periods in the high impairment level have responses for the 
functional OASIS items that are associated with the highest resource 
use on average.
    For CY 2023, we propose to use CY 2021 claims data to update the 
functional points and functional impairment levels by clinical group. 
The CY 2018 HH PPS proposed rule (82 FR 35320) and the technical report 
from December 2016, posted on the Home Health PPS Archive webpage 
located at: https://www.cms.gov/medicare/home-health-pps/home-health-pps-archive, provide a more detailed explanation as to the construction 
of these functional impairment levels using the OASIS items. We are 
proposing to use this same methodology previously finalized to update 
the functional impairment levels for CY 2023. The updated OASIS 
functional points table and the table of functional impairment levels 
by clinical group for CY 2023 are listed in Tables B21 and B22, 
respectively. We solicit public comments on the updates to

[[Page 37627]]

functional points and the functional impairment levels by clinical 
group.
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c. CY 2023 Comorbidity Subgroups
    Thirty-day periods of care receive a comorbidity adjustment 
category based on the presence of certain secondary diagnoses reported 
on home health claims. These diagnoses are based on a home-health 
specific list of clinically and statistically significant secondary 
diagnosis subgroups with similar resource use, meaning the diagnoses 
have at least as high as the median resource use and are reported in 
more than 0.1 percent of 30-day periods of care. Home health 30-day 
periods of care can receive a comorbidity adjustment under the 
following circumstances:
     Low comorbidity adjustment: There is a reported secondary 
diagnosis on the home health-specific comorbidity subgroup list that is 
associated with higher resource use.
     High comorbidity adjustment: There are two or more 
secondary diagnoses on the home health-specific comorbidity subgroup 
interaction list that are associated with higher resource use when both 
are reported together compared to when they are reported separately. 
That is, the two diagnoses may interact with one another, resulting in 
higher resource use.
     No comorbidity adjustment: A 30-day period of care 
receives no comorbidity adjustment if no secondary diagnoses exist or 
do not meet the criteria for a low or high comorbidity adjustment.
    In the CY 2019 HH PPS final rule with comment period (83 FR 56406), 
we stated that we would continue to examine the relationship of 
reported comorbidities on resource utilization and make the appropriate 
payment refinements to help ensure that payment is in alignment with 
the actual costs of providing care. For CY 2023, we propose to use the 
same methodology used to establish the comorbidity subgroups to update 
the comorbidity subgroups using CY 2021 home health data.
    For CY 2023, we propose to update the comorbidity subgroups to 
include 23 low comorbidity adjustment subgroups as identified in Table 
B23 and 94 high comorbidity adjustment interaction subgroups as 
identified in Table B24. The proposed 23 low comorbidity adjustment 
subgroups and 94 high comorbidity adjustment interactions reflect the 
proposed coding changes detailed in section II.B.3.c. of this proposed 
rule. The proposed CY 2023 low comorbidity adjustment subgroups and the 
high comorbidity adjustment interaction subgroups including those 
diagnoses within each of these comorbidity adjustments will also be 
posted on the HHA Center webpage at https://www.cms.gov/Center/Provider-Type/Home-Health-Agency-HHA-Center.
    We invite comments on the proposed updates to the low comorbidity 
adjustment subgroups and the high comorbidity adjustment interactions 
for CY 2023.
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BILLING CODE 4120-01-C
d. CY 2023 PDGM Case-Mix Weights
    As finalized in the CY 2019 HH PPS final rule with comment period 
(83 FR 56502), the PDGM places patients into meaningful payment 
categories based on patient and other characteristics, such as timing, 
admission source, clinical grouping using the reported principal 
diagnosis, functional impairment level, and comorbid conditions. The 
PDGM case-mix methodology results in 432 unique case-mix groups called 
home health resource groups (HHRGs). We also finalized a policy in the 
CY 2019 HH PPS final rule with comment period (83 FR 56515) to 
recalibrate annually the PDGM case-mix weights using a fixed effects 
model with the most recent and complete utilization data available at 
the time of annual rulemaking. Annual recalibration of the PDGM case-
mix weights ensures that the case-mix weights reflect, as accurately as 
possible, current home health resource use and changes in utilization 
patterns. To generate the proposed recalibrated CY 2023 case-mix 
weights, we used CY 2021 home health claims data with linked OASIS data 
(as of March 21, 2021). These data are the most current and complete 
data available at this time. We believe that recalibrating the case-mix 
weights using data from CY 2021 would be reflective of PDGM utilization 
and patient resource use for CY 2023. The proposed recalibrated case-
mix weights will be updated based on more complete CY 2021 claims data 
for the final rule.
    The claims data provide visit-level data and data on whether non-
routine supplies (NRS) were provided during the period and the total 
charges of NRS. We determine the case-mix weight for each of the 432 
different PDGM payment groups by regressing resource use on a series of 
indicator variables for each of the categories using a fixed effects 
model as described in the following steps:
    Step 1: Estimate a regression model to assign a functional 
impairment level to each 30-day period. The regression model estimates 
the relationship between a 30-day period's resource use and the 
functional status and risk of hospitalization items included in the 
PDGM, which are obtained from certain OASIS items. We refer readers to 
Table B21 for further information on the OASIS items used for the 
functional impairment level under the PDGM. We measure resource use 
with the cost-per-minute + NRS approach that uses information from 2020 
home health cost reports. We use 2020 home health cost report data 
because it is the most complete cost report data available at the time 
of rulemaking. Other variables in the regression model include the 30-
day period's admission source, clinical group, and 30-day period 
timing. We also include home health agency level fixed effects in the 
regression model. After estimating the regression model using 30-day 
periods, we divide the coefficients that correspond to the functional 
status and risk of hospitalization items by 10 and round to the nearest 
whole number. Those rounded numbers are used to compute a functional 
score for each 30-day period by summing together the rounded numbers 
for the functional status and risk of hospitalization items that are 
applicable to each 30-day period. Next, each 30-day period is assigned 
to a functional impairment level (low, medium, or high) depending on 
the 30-day period's total functional score. Each clinical group has a 
separate set of functional thresholds used to assign 30-day periods 
into a low, medium or high functional impairment level. We set those 
thresholds so that we assign roughly a third of 30-day periods within 
each clinical group to each functional impairment level (low, medium, 
or high).
    Step 2: A second regression model estimates the relationship 
between a 30-day period's resource use and indicator variables for the 
presence of any of the comorbidities and comorbidity interactions that 
were originally examined for inclusion in the PDGM. Like the first 
regression model, this model also includes home health agency level 
fixed effects and includes control variables for each 30-day period's 
admission source, clinical group, timing, and functional impairment 
level. After we estimate the model, we assign comorbidities to the low 
comorbidity adjustment if any comorbidities have a coefficient that is 
statistically significant (p-value of 0.05 or less) and which have a 
coefficient that is larger than the 50th percentile of positive and 
statistically significant comorbidity coefficients. If two 
comorbidities in the model and their interaction term have coefficients 
that sum together to exceed $150 and the interaction term is 
statistically significant (p-value of 0.05 or less), we assign the two 
comorbidities together to the high comorbidity adjustment.
    Step 3: After Step 2, each 30-day period is assigned to a clinical 
group, admission source category, episode timing category, functional 
impairment level, and comorbidity adjustment category. For each 
combination of those variables (which represent the 432 different 
payment groups that comprise the PDGM), we then calculate the 10th 
percentile of visits across all 30-day periods within a particular 
payment group. If a 30-day period's number of visits is less than the 
10th percentile for their payment group, the 30-day period is 
classified as a Low Utilization Payment Adjustment (LUPA). If a payment 
group has a 10th percentile of visits that is less than two, we set the

[[Page 37638]]

LUPA threshold for that payment group to be equal to two. That means if 
a 30-day period has one visit, it is classified as a LUPA and if it has 
two or more visits, it is not classified as a LUPA.
    Step 4: Take all non-LUPA 30-day periods and regress resource use 
on the 30-day period's clinical group, admission source category, 
episode timing category, functional impairment level, and comorbidity 
adjustment category. The regression includes fixed effects at the level 
of the home health agency. After we estimate the model, the model 
coefficients are used to predict each 30-day period's resource use. To 
create the case-mix weight for each 30-day period, the predicted 
resource use is divided by the overall resource use of the 30-day 
periods used to estimate the regression.
    The case-mix weight is then used to adjust the base payment rate to 
determine each 30-day period's payment. Table B25 shows the 
coefficients of the payment regression used to generate the weights, 
and the coefficients divided by average resource use.
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    The case-mix weights proposed for CY 2023 are listed in Table B26 
and will also be posted on the HHA Center web-page \17\ upon display of 
this proposed rule.
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BILLING CODE 4120-01-C
    For CY 2023, there are 238 groups that experience a -5% to 0% 
change in case-mix weights and 183 groups that experience a 0% to +5% 
change in weights compared to their CY 2022 case-mix weights. There are 
10 groups that experience a change between +5% and +10% and one group 
that experiences a 10% to 12% increase in weights compared to the CY 
2022 case-mix weights. Changes to the PDGM case-mix weights are 
implemented in a budget neutral manner by multiplying the CY 2023 
national standardized 30-day period payment rate by a case-mix budget 
neutrality factor. Typically, the case-mix weight budget neutrality 
factor

[[Page 37651]]

is also calculated using the most recent, complete home health claims 
data available. However, in the CY 2022 HH PPS proposed rule (86 FR 
35908), due to the COVID-19 PHE, we discussed using the previous 
calendar year's home health claims data (CY 2019) to determine if there 
were significant differences between utilizing CY 2019 and CY 2020 
claims data. We noted that CY 2020 was the first year of actual PDGM 
utilization data, therefore, if we were to use CY 2019 data due to the 
PHE we would need to simulate 30-day periods from 60-day episodes under 
the old system. We determined that using CY 2020 utilization data was 
more appropriate than using CY 2019 utilization data, as it is actual 
PDGM utilization data. For CY 2023, we will continue the practice of 
using the most recent complete home health claims data at the time of 
rulemaking, which is CY 2021 data. The case-mix budget neutrality 
factor is calculated as the ratio of 30-day base payment rates such 
that total payments when the CY 2023 PDGM case mix weights (developed 
using CY 2021 home health claims data) are applied to CY 2021 
utilization (claims) data are equal to total payments when CY 2022 PDGM 
case-mix weights (developed using CY 2020 home health claims data) are 
applied to CY 2021 utilization data. This produces a case-mix budget 
neutrality factor for CY 2023 of 0.9895.
    We invite comments on the CY 2023 proposed case-mix weights and 
proposed case-mix weight budget neutrality factor.
5. Proposed CY 2023 Home Health Payment Rate Updates
a. Proposed CY 2023 Home Health Market Basket Update for HHAs
    Section 1895(b)(3)(B) of the Act requires that the standard 
prospective payment amounts for home health be increased by a factor 
equal to the applicable home health market basket update for those HHAs 
that submit quality data as required by the Secretary. In the CY 2019 
HH PPS final rule with comment period (83 FR 56425), we finalized a 
rebasing of the home health market basket to reflect 2016 cost report 
data. A detailed description of how we rebased the HHA market basket is 
available in the CY 2019 HH PPS final rule with comment period (83 FR 
56425 through 56436).
    Section 1895(b)(3)(B) of the Act requires that in CY 2015 and in 
subsequent calendar years, except CY 2018 (under section 411(c) of the 
Medicare Access and CHIP Reauthorization Act of 2015 (MACRA) (Pub. L. 
114-10, enacted April 16, 2015)), and CY 2020 (under section 53110 of 
the Bipartisan Budget Act of 2018 (BBA) (Pub. L. 115-123, enacted 
February 9, 2018)), the market basket percentage under the HHA 
prospective payment system, as described in section 1895(b)(3)(B) of 
the Act, be annually adjusted by changes in economy-wide productivity. 
Section 1886(b)(3)(B)(xi)(II) of the Act defines the productivity 
adjustment to be equal to the 10-year moving average of changes in 
annual economy-wide private nonfarm business multifactor productivity 
(MFP) (as projected by the Secretary for the 10-year period ending with 
the applicable fiscal year, calendar year, cost reporting period, or 
other annual period). The United States Department of Labor's Bureau of 
Labor Statistics (BLS) publishes the official measures of productivity 
for the United States economy. We note that previously the productivity 
measure referenced in section 1886(b)(3)(B)(xi)(II) was published by 
BLS as private nonfarm business multifactor productivity. Beginning 
with the November 18, 2021 release of productivity data, BLS replaced 
the term ``multifactor productivity'' with ``total factor 
productivity'' (TFP). BLS noted that this is a change in terminology 
only and will not affect the data or methodology. As a result of the 
BLS name change, the productivity measure referenced in section 
1886(b)(3)(B)(xi)(II) of the Act is now published by BLS as ``private 
nonfarm business total factor productivity''. We refer readers to 
https://www.bls.gov for the BLS historical published TFP data. A 
complete description of IGI's TFP projection methodology is available 
on the CMS website at https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/MedicareProgramRatesStats/MarketBasketResearch.
    The proposed home health update percentage for CY 2023 is based on 
the estimated home health market basket update, specified at section 
1895(b)(3)(B)(iii) of the Act, of 3.3 percent (based on IHS Global 
Inc.'s first-quarter 2022 forecast with historical data through fourth-
quarter 2021). The estimated CY 2023 home health market basket update 
of 3.3 percent is then reduced by a productivity adjustment, as 
mandated by the section 3401 of the Patient Protection and Affordable 
Care Act (the Affordable Care Act) (Pub. L. 111-148), currently 
estimated to be 0.4 percentage point for CY 2023. In effect, the 
proposed home health payment update percentage for CY 2023 is a 2.9 
percent increase. Section 1895(b)(3)(B)(v) of the Act requires that the 
home health update be decreased by 2 percentage points for those HHAs 
that do not submit quality data as required by the Secretary. For HHAs 
that do not submit the required quality data for CY 2023, the home 
health payment update would be 0.9 percent (2.9 percent minus 2 
percentage points). If more recent data become available after the 
publication of this proposed rule and before the publication of the 
final rule (for example, more recent estimates of the home health 
market basket update and productivity adjustment), we would use such 
data, if appropriate, to determine the home health payment update 
percentage for CY 2023 in the final rule.
b. CY 2023 Home Health Wage Index
(1) Proposed CY 2023 Home Health Wage Index
    Sections 1895(b)(4)(A)(ii) and (b)(4)(C) of the Act require the 
Secretary to provide appropriate adjustments to the proportion of the 
payment amount under the HH PPS that account for area wage differences, 
using adjustment factors that reflect the relative level of wages and 
wage-related costs applicable to the furnishing of home health 
services. Since the inception of the HH PPS, we have used inpatient 
hospital wage data in developing a wage index to be applied to home 
payments. We propose to continue this practice for CY 2023, as we 
continue to believe that, in the absence of home health-specific wage 
data that accounts for area differences, using inpatient hospital wage 
data is appropriate and reasonable for the HH PPS.
    In the CY 2021 HH PPS final rule (85 FR 70298), we finalized our 
proposal to adopt the revised Office of Management and Budget (OMB) 
delineations with a 5-percent cap on wage index decreases, where the 
estimated reduction in a geographic area's wage index would be capped 
at 5-percent in CY 2021 only, meaning no cap would be applied to wage 
index decreases for the second year (CY 2022). Therefore, we proposed 
and finalized the use of the FY 2022 pre-floor, pre reclassified 
hospital wage index with no 5-percent cap on decreases as the CY 2022 
wage adjustment to the labor portion of the HH PPS rates (86 FR 62285). 
For CY 2023, we propose to base the HH PPS wage index on the FY 2023 
hospital pre-floor, pre-reclassified wage index for hospital cost 
reporting periods beginning on or after October 1, 2018, and before 
October 1, 2019 (FY 2019 cost report data). The proposed CY 2023 HH PPS 
wage index would not take into

[[Page 37652]]

account any geographic reclassification of hospitals, including those 
in accordance with section 1886(d)(8)(B) or 1886(d)(10) of the Act. We 
also propose that the CY 2023 HH PPS wage index would include a 5-
percent cap on wage index decreases as discussed later in this section. 
If finalized, we will apply the appropriate wage index value to the 
labor portion of the HH PPS rates based on the site of service for the 
beneficiary (defined by section 1861(m) of the Act as the beneficiary's 
place of residence).
    To address those geographic areas in which there are no inpatient 
hospitals, and thus, no hospital wage data on which to base the 
calculation of the CY 2023 HH PPS wage index, we propose to continue to 
use the same methodology discussed in the CY 2007 HH PPS final rule (71 
FR 65884) to address those geographic areas in which there are no 
inpatient hospitals. For rural areas that do not have inpatient 
hospitals, we propose to use the average wage index from all contiguous 
Core Based Statistical Areas (CBSAs) as a reasonable proxy. Currently, 
the only rural area without a hospital from which hospital wage data 
could be derived is Puerto Rico. However, for rural Puerto Rico, we do 
not apply this methodology due to the distinct economic circumstances 
that exist there (for example, due to the close proximity to one 
another of almost all of Puerto Rico's various urban and non-urban 
areas, this methodology would produce a wage index for rural Puerto 
Rico that is higher than that in half of its urban areas). Instead, we 
propose to continue to use the most recent wage index previously 
available for that area. The most recent wage index previously 
available for rural Puerto Rico is 0.4047, which is what we propose to 
use. For urban areas without inpatient hospitals, we use the average 
wage index of all urban areas within the State as a reasonable proxy 
for the wage index for that CBSA. For CY 2023, the only urban area 
without inpatient hospital wage data is Hinesville, GA (CBSA 25980). 
Using the average wage index of all urban areas in Georgia as proxy, we 
propose the CY 2023 wage index value for Hinesville, GA to be 0.8535.
    On February 28, 2013, OMB issued Bulletin No. 13-01, announcing 
revisions to the delineations of MSAs, Micropolitan Statistical Areas, 
and CBSAs, and guidance on uses of the delineation of these areas. In 
the CY 2015 HH PPS final rule (79 FR 66085 through 66087), we adopted 
OMB's area delineations using a 1-year transition.
    On August 15, 2017, OMB issued Bulletin No. 17-01 in which it 
announced that one Micropolitan Statistical Area, Twin Falls, Idaho, 
now qualifies as a Metropolitan Statistical Area. The new CBSA (46300) 
comprises the principal city of Twin Falls, Idaho in Jerome County, 
Idaho and Twin Falls County, Idaho. The CY 2022 HH PPS wage index value 
for CBSA 46300, Twin Falls, Idaho, will be 0.8803. Bulletin No. 17-01 
is available at https://www.whitehouse.gov/wp-content/uploads/legacy_drupal_files/omb/bulletins/2017/b-17-01.pdf.
    On April 10, 2018, OMB issued OMB Bulletin No. 18-03, which 
superseded the August 15, 2017 OMB Bulletin No. 17-01. On September 14, 
2018, OMB issued OMB Bulletin No. 18-04 which superseded the April 10, 
2018, OMB Bulletin No. 18-03. These bulletins established revised 
delineations for Metropolitan Statistical Areas, Micropolitan 
Statistical Areas, and Combined Statistical Areas, and provided 
guidance on the use of the delineations of these statistical areas. A 
copy of OMB Bulletin No. 18-04 may be obtained at: https://www.bls.gov/bls/omb-bulletin-18-04-revised-delineations-of-metropolitan-statistical-areas.pdf.
    On March 6, 2020, OMB issued Bulletin No. 20-01, which provided 
updates to and superseded OMB Bulletin No. 18-04 that was issued on 
September 14, 2018. The attachments to OMB Bulletin No. 20-01 provided 
detailed information on the update to statistical areas since September 
14, 2018, and were based on the application of the 2010 Standards for 
Delineating Metropolitan and Micropolitan Statistical Areas to Census 
Bureau population estimates for July 1, 2017, and July 1, 2018. (For a 
copy of this bulletin, we refer readers to https://www.whitehouse.gov/wp-content/uploads/2020/03/Bulletin-20-01.pdf.) In OMB Bulletin No. 20-
01, OMB announced one new Micropolitan Statistical Area, one new 
component of an existing Combined Statistical Are and changes to New 
England City and Town Area (NECTA) delineations. In the CY 2021 HH PPS 
final rule (85 FR 70298) we stated that if appropriate, we would 
propose any updates from OMB Bulletin No. 20-01 in future rulemaking. 
After reviewing OMB Bulletin No. 20-01, we have determined that the 
changes in Bulletin 20-01 encompassed delineation changes that would 
not affect the Medicare home health wage index for CY 2022. 
Specifically, the updates consisted of changes to NECTA delineations 
and the re-designation of a single rural county into a newly created 
Micropolitan Statistical Area. The Medicare home health wage index does 
not utilize NECTA definitions, and, as most recently discussed in the 
CY 2021 HH PPS final rule (85 FR 70298) we include hospitals located in 
Micropolitan Statistical areas in each State's rural wage index. In 
other words, these OMB updates did not affect any geographic areas for 
purposes of the wage index calculation for CY 2022.
    The proposed CY 2023 wage index is available on the CMS website at: 
https://www.cms.gov/Center/Provider-Type/Home-Health-Agency-HHA-Center.
(2) Proposed Permanent Cap on Wage Index Decreases
    As discussed in section II.B.5.b.1 of this proposed rule, we have 
proposed and finalized temporary transition policies in the past to 
mitigate significant changes to payments due to changes to the home 
health wage index. Specifically, in the CY 2015 HH PPS final rule (79 
FR 66086), we implemented a 50/50 blend for all geographic areas 
consisting of the wage index values using the then-current OMB area 
delineations and the wage index values using OMB's new area 
delineations based on OMB Bulletin No. 13-01. In the CY 2021 HH PPS 
final rule (85 FR 73100), we adopted the revised OMB delineations with 
a 5-percent cap on wage index decreases, where the estimated reduction 
in a geographic area's wage index would be capped at 5-percent in CY 
2021. We explained that we believed the 5-percent cap would provide 
greater transparency and would be administratively less complex than 
the prior methodology of applying a 50/50 blended wage index. We noted 
that this transition approach struck an appropriate balance by 
providing a transition period to mitigate the resulting short-term 
instability and negative impacts on providers and time for them to 
adjust to their new labor market area delineations and wage index 
values.
    In the CY 2022 HH PPS final rule (86 FR 62285), a few commenters 
stated that providers should be protected against substantial payment 
reductions due to dramatic reductions in wage index values from one 
year to the next. Because we did not propose any transition policy in 
the CY 2022 proposed rule, we did not extend the transition period for 
CY 2022. In the CY 2022 HH PPS final rule, we stated that we continued 
to believe that applying the 5-percent cap transition policy in year 
one provided an adequate safeguard against any significant payment 
reductions associated with the adoption of the revised CBSA 
delineations in CY 2021, allowed for sufficient time to make 
operational

[[Page 37653]]

changes for future calendar years, and provided a reasonable balance 
between mitigating some short-term instability in home health payments 
and improving the accuracy of the payment adjustment for differences in 
area wage levels. However, we acknowledged that certain changes to wage 
index policy may significantly affect Medicare payments. In addition, 
we reiterated that our policy principles with regard to the wage index 
include generally using the most current data and information available 
and providing that data and information, as well as any approaches to 
addressing any significant effects on Medicare payments resulting from 
these potential scenarios, in notice and comment rulemaking. With these 
policy principles in mind, we considered for this CY 2023 HH PPS 
proposed rule how best to address the potential scenarios, which 
commenters raised concerns; that is, scenarios in which changes to wage 
index policy may significantly affect Medicare home health payments.
    In the past, we have established transition policies of limited 
duration to phase in significant changes to labor market areas. In 
taking this approach in the past, we sought to mitigate short-term 
instability and fluctuations that can negatively impact providers due 
to wage index changes. Sections 1895(b)(4)(A)(ii) and (b)(4)(C) of the 
Act requires the Secretary to provide appropriate adjustments to the 
proportion of the payment amount under the HH PPS that account for area 
wage differences, using adjustment factors that reflect the relative 
level of wages and wage-related costs applicable to the furnishing of 
home health services. We have previously stated that, because the wage 
index is a relative measure of the value of labor in prescribed labor 
market areas, we believe it is important to implement new labor market 
area delineations with as minimal a transition as is reasonably 
possible. However, we recognize that changes to the wage index have the 
potential to create instability and significant negative impacts on 
certain providers even when labor market areas do not change. In 
addition, year-to-year fluctuations in an area's wage index can occur 
due to external factors beyond a provider's control, such as the COVID-
19 PHE, and for an individual provider, these fluctuations can be 
difficult to predict. We also recognize that predictability in Medicare 
payments is important to enable providers to budget and plan their 
operations.
    In light of these considerations, we are proposing a permanent 
approach to smooth year-to-year changes in providers' wage indexes. We 
are proposing a policy that increases the predictability of home health 
payments for providers and mitigates instability and significant 
negative impacts to providers resulting from changes to the wage index.
    As previously discussed, we believe that applying a 5-percent cap 
on wage index decreases for CY 2021 provided greater transparency and 
was administratively less complex than prior transition methodologies. 
In addition, we believe this methodology mitigates short-term 
instability and fluctuations that can negatively impact providers due 
to wage index changes. Lastly, we note that we believe the 5-percent 
cap we applied to all wage index decreases for CY 2021 provided an 
adequate safeguard against significant payment reductions related to 
the adoption of the revised CBSAs. However, as discussed earlier in 
this section of this proposed rule, we recognize there are 
circumstances that a one-year mitigation policy would not effectively 
address future years in which providers continue to be negatively 
affected by significant wage index decreases.
    Typical year-to-year variation in the home health wage index has 
historically been within 5-percent, and we expect this will continue to 
be the case in future years. Therefore, we believe that applying a 5-
percent cap on all wage index decreases in future years, regardless of 
the reason for the decrease, would effectively mitigate instability in 
home health payments due to any significant wage index decreases that 
may affect providers in any year that commenters raised in the CY 2022 
HH PPS final rule. Additionally, we believe that applying a 5-percent 
cap on all wage index decreases would increase the predictability of 
home health payments for providers, enabling them to more effectively 
budget and plan their operations. Lastly, we believe that applying a 5-
percent cap on all wage index decreases, from the prior year, would 
have a small overall impact on the labor market area wage index system. 
As discussed in further detail in section VII.C. of this proposed rule, 
we estimate that applying a 5-percent cap on all wage index decreases, 
from the prior year, will have a very small effect on the wage index 
budget neutrality factors for CY 2023. Because the wage index is a 
measure of the value of labor (wage and wage-related costs) in a 
prescribed labor market area relative to the national average, we 
anticipate that most providers will not experience year-to-year wage 
index declines greater than 5-percent in any given year. We believe 
that applying a 5-percent cap on all wage index decreases, from the 
prior year, would continue to maintain the accuracy of the overall 
labor market area wage index system.
    Therefore, for CY 2023 and subsequent years, we are proposing to 
apply a permanent 5 percent cap on any decrease to a geographic area's 
wage index from its wage index in the prior year, regardless of the 
circumstances causing the decline. That is, we are proposing that a 
geographic area's wage index for CY 2023 would not be less than 95 
percent of its final wage index for CY 2022, regardless of whether the 
geographic area is part of an updated CBSA, and that for subsequent 
years, a geographic area's wage index would not be less than 95 percent 
of its wage index calculated in the prior CY. We further propose that 
if a geographic area's prior CY wage index is calculated based on the 
5-percent cap, then the following year's wage index would not be less 
than 95 percent of the geographic area's capped wage index. For 
example, if a geographic area's wage index for CY 2023 is calculated 
with the application of the 5-percent cap, then its wage index for CY 
2024 would not be less than 95 percent of its capped wage index in CY 
2023. Likewise, we are proposing to make the corresponding regulations 
text changes at Sec.  484.220(c) as follows: Beginning on January 1, 
2023, CMS will apply a cap on decreases to the home health wage index 
such that the wage index applied to a geographic area is not less than 
95 percent of the wage index applied to that geographic area in the 
prior CY. This 5-percent cap on negative wage index changes would be 
implemented in a budget neutral manner through the use of wage index 
budget neutrality factors.
    In section VII.C. of this proposed rule, we estimate the impact to 
payments for providers in CY 2023 based on this proposed policy. We 
also note that we would examine the effects of this policy on an 
ongoing basis in the future in order to assess its appropriateness.
c. CY 2023 Annual Payment Update
(1) Background
    The HH PPS has been in effect since October 1, 2000. As set forth 
in the July 3, 2000 final rule (65 FR 41128), the base unit of payment 
under the HH PPS was a national, standardized 60-day episode payment 
rate. As finalized in the CY 2019 HH PPS final rule with comment period 
(83 FR 56406), and as described in the CY 2020 HH PPS final rule with 
comment period (84 FR 60478), the unit of home health payment changed 
from a 60-day episode to a 30-day period effective for those 30-

[[Page 37654]]

day periods beginning on or after January 1, 2020.
    As set forth in Sec.  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 Sec.  484.225(i), for an HHA 
that does not submit home health quality data, as specified by the 
Secretary, the unadjusted national prospective 30-day period rate is 
equal to the rate for the previous calendar year increased by the 
applicable home health payment update, minus 2 percentage points. Any 
reduction of the percentage change would apply only to the calendar 
year involved and would not be considered in computing the prospective 
payment amount for a subsequent calendar year.
    The final claim that the HHA submits for payment determines the 
total payment amount for the period and whether we make an applicable 
adjustment to the 30-day case-mix and wage-adjusted payment amount. The 
end date of the 30-day period, as reported on the claim, determines 
which calendar year rates Medicare will use to pay the claim.
    We may adjust a 30-day case-mix and wage-adjusted payment based on 
the information submitted on the claim to reflect the following:
     A LUPA is provided on a per-visit basis as set forth in 
Sec. Sec.  484.205(d)(1) and 484.230.
     A PEP adjustment as set forth in Sec. Sec.  484.205(d)(2) 
and 484.235.
     An outlier payment as set forth in Sec. Sec.  
484.205(d)(3) and 484.240.
(2) CY 2023 National, Standardized 30-Day Period Payment Amount
    Section 1895(b)(3)(A)(i) of the Act requires that the standard 
prospective payment rate and other applicable amounts be standardized 
in a manner that eliminates the effects of variations in relative case-
mix and area wage adjustments among different home health agencies in a 
budget-neutral manner. To determine the CY 2023 national, standardized 
30-day period payment rate, we apply a permanent behavioral adjustment 
factor, a case-mix weights recalibration budget neutrality factor, a 
wage index budget neutrality factor and the home health payment update 
percentage discussed in section II.C.2. of this proposed rule. As 
discussed in section II.B.2.f. of this proposed rule, we are 
implementing a permanent behavior adjustment of -7.69 percent to 
prevent further overpayments. The permanent behavior adjustment factor 
is 0.9231 (1-0.0769). As discussed previously, to ensure the changes to 
the PDGM case-mix weights are implemented in a budget neutral manner, 
we apply a case-mix weights budget neutrality factor to the CY 2022 
national, standardized 30-day period payment rate. The proposed case-
mix weights budget neutrality factor for CY 2023 is 0.9895. 
Additionally, we also apply a wage index budget neutrality to ensure 
that wage index updates and revisions are implemented in a budget 
neutral manner. Typically, the wage index budget neutrality factor is 
calculated using the most recent, complete home health claims data 
available. However, in the CY 2022 HH PPS final rule due to the COVID-
19 PHE, we looked at using the previous calendar year's home health 
claims data (CY 2019) to determine if there were significant 
differences between utilizing 2019 and 2020 claims data. Our analysis 
showed that there was only a small difference between the wage index 
budget neutrality factors calculated using CY 2019 and CY 2020 home 
health claims data. Therefore, for CY 2022 we decided to continue our 
practice of using the most recent, complete home health claims data 
available; that is, we used CY 2020 claims data for the CY 2022 payment 
rate updates. For CY 2023 rate setting, we do not anticipate 
significant differences between using pre COVID-19 PHE data (CY 2019 
claims) and the most recent claims data at the time of rulemaking (CY 
2021 claims). Therefore, we will continue our practice of using the 
most recent, complete utilization data at the time of rulemaking; that 
is, we are using CY 2021 claims data for CY 2023 payment rate updates.
    To calculate the wage index budget neutrality factor, we first 
determine the payment rate needed for non-LUPA 30-day periods using the 
CY 2023 wage index so those total payments are equivalent to the total 
payments for non-LUPA 30-day periods using the CY 2022 wage index and 
the CY 2022 national standardized 30-day period payment rate adjusted 
by the case-mix weights recalibration neutrality factor. Then, by 
dividing the payment rate for non-LUPA 30-day periods using the CY 2023 
wage index with a 5-percent cap on wage index decreases by the payment 
rate for non-LUPA 30-day periods using the CY 2022 wage index, we 
obtain a wage index budget neutrality factor of 0.9975. We then apply 
the wage index budget neutrality factor of 0.9975 to the 30-day period 
payment rate.
    Next, we would update the 30-day period payment rate by the CY 2023 
home health payment update percentage of 2.9 percent. The CY 2023 
national, standardized 30-day period payment rate is calculated in 
Table B27.

[[Page 37655]]

[GRAPHIC] [TIFF OMITTED] TP23JN22.049

    The CY 2023 national, standardized 30-day period payment rate for a 
HHA that does not submit the required quality data is updated by the CY 
2023 home health payment update of 2.9 percent minus 2 percentage 
points and is shown in Table B28.
[GRAPHIC] [TIFF OMITTED] TP23JN22.050

(3) CY 2023 National Per-Visit Rates for 30-Day Periods of Care
    The national per-visit rates are used to pay LUPAs and are also 
used to compute imputed costs in outlier calculations. The per-visit 
rates are paid by type of visit or HH discipline. The six HH 
disciplines are as follows:
     Home health aide (HH aide).
     Medical Social Services (MSS).
     Occupational therapy (OT).
     Physical therapy (PT).
     Skilled nursing (SN).
     Speech-language pathology (SLP).

    To calculate the CY 2023 national per-visit rates, we started with 
the CY 2022 national per-visit rates. Then we applied a wage index 
budget neutrality factor to ensure budget neutrality for LUPA per-visit 
payments. We calculated the wage index budget neutrality factor by 
simulating total payments for LUPA 30-day periods of care using the CY 
2023 wage index with a 5-percent cap on wage index decreases and 
comparing it to simulated total payments for LUPA 30-day periods of 
care using the CY 2022 wage index (with no 5-percent cap). By dividing 
the total payments for LUPA 30-day periods of care using the CY 2023 
wage index by the total payments for LUPA 30-day periods of care using 
the CY 2022 wage index, we obtained a wage index budget neutrality 
factor of 0.9992. We apply the wage index budget neutrality factor in 
order to calculate the CY 2022 national per visit rates.
    The LUPA per-visit rates are not calculated using case-mix weights. 
Therefore, no case mix weights budget neutrality factor is needed to 
ensure budget neutrality for LUPA payments. Additionally, we are not 
applying the permanent adjustment to the per visit payment rates but 
only the case-mix adjusted payment rate. Lastly, the per-visit rates 
for each discipline are updated by the CY 2023 home health payment 
update percentage of 2.9 percent. The national per-visit rates are 
adjusted by the wage index based on the site of service of the 
beneficiary. The per-visit payments for LUPAs are separate from the 
LUPA add-on payment amount, which is paid for episodes that occur as 
the only episode or initial episode in a sequence of adjacent episodes. 
The CY 2023 national per visit rates for HHAs that submit the required 
quality data are updated by the CY 2023 home health payment update 
percentage of 2.9 percent and are shown in Table B29.

[[Page 37656]]

[GRAPHIC] [TIFF OMITTED] TP23JN22.051

    The CY 2023 per-visit payment rates for HHAs that do not submit the 
required quality data are updated by the CY 2023 home health payment 
update percentage of 2.9 percent minus 2 percentage points and are 
shown in Table B30.
[GRAPHIC] [TIFF OMITTED] TP23JN22.052

(4) LUPA Add-On Factors
    Prior to the implementation of the 30-day unit of payment, LUPA 
episodes were eligible for a LUPA add-on payment if the episode of care 
was the first or only episode in a sequence of adjacent episodes. As 
stated in the CY 2008 HH PPS final rule, the average visit lengths in 
these initial LUPAs are 16 to 18 percent higher than the average visit 
lengths in initial non-LUPA episodes (72 FR 49848). LUPA episodes that 
occur as the only episode or as an initial episode in a sequence of 
adjacent episodes are adjusted by applying an additional amount to the 
LUPA payment before adjusting for area wage differences. In the CY 2014 
HH PPS final rule (78 FR 72305), we changed the methodology for 
calculating the LUPA add-on amount by finalizing the use of three LUPA 
add-on factors: 1.8451 for SN; 1.6700 for PT; and 1.6266 for SLP. We 
multiply the per-visit payment amount for the first SN, PT, or SLP 
visit in LUPA episodes that occur as the only episode or an initial 
episode in a sequence of adjacent episodes by the appropriate factor to 
determine the LUPA add-on payment amount.
    In the CY 2019 HH PPS final rule with comment period (83 FR 56440), 
in addition to finalizing a 30-day unit of payment, we finalized our 
policy of continuing to multiply the per-visit payment amount for the 
first skilled nursing, physical therapy, or speech-language pathology 
visit in LUPA periods that occur as the only period of care or the 
initial 30-day period of care in a sequence of adjacent 30-day periods 
of care by the appropriate add-on factor (1.8451 for SN, 1.6700 for PT, 
and 1.6266 for SLP) to determine the LUPA add-on payment amount for 30-
day periods of care under the PDGM. For example, using the proposed CY 
2023 per-visit payment rates for HHAs that submit the required quality 
data, for LUPA periods that occur as the only period or an initial 
period in a sequence of adjacent periods, if the first skilled visit is 
SN, the payment for that visit would be $297.65 (1.8451 multiplied by 
$161.32), subject to area wage adjustment.
(5) Occupational Therapy LUPA Add-On Factor
    In order to implement Division CC, section 115, of CAA 2021, CMS 
finalized changes to regulations at Sec.  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

[[Page 37657]]

establishing a LUPA add-on factor for calculating the LUPA add-on 
payment amount for the first skilled occupational therapy (OT) visit in 
LUPA periods that occurs as the only period of care or the initial 30-
day period of care in a sequence of adjacent 30-day periods of care.
    As stated in the CY 2022 HH PPS final rule with comment period (86 
FR 62289) since there was not sufficient data regarding the average 
excess of minutes for the first visit in LUPA periods when the initial 
and comprehensive assessments are conducted by occupational therapists 
we finalized the use of the PT LUPA add-on factor of 1.6700 as a proxy. 
We also stated that we would use the PT LUPA add-on factor as a proxy 
until we have CY 2022 data to establish a more accurate OT add-on 
factor for the LUPA add-on payment amounts (86 FR 62289). Therefore, we 
continue to believe the similarity in the per-visit payment rates for 
both PT and OT make the PT LUPA add-on factor the most appropriate 
proxy until we have CY 2022 data to propose a LUPA add-on factor 
specific to OT in future rulemaking.
d. Proposed Payments for High-Cost Outliers Under the HH PPS
(1) Background
    Section 1895(b)(5) of the Act allows for the provision of an 
addition or adjustment to the home health payment amount otherwise made 
in the case of outliers because of unusual variations in the type or 
amount of medically necessary care. Under the HH PPS and the previous 
unit of payment (that is, 60-day episodes), outlier payments were made 
for 60-day episodes whose estimated costs exceed a threshold amount for 
each HHRG. The episode's estimated cost was established as the sum of 
the national wage-adjusted per visit payment amounts delivered during 
the episode. The outlier threshold for each case-mix group or PEP 
adjustment defined as the 60-day episode payment or PEP adjustment for 
that group plus a fixed-dollar loss (FDL) amount. For the purposes of 
the HH PPS, the FDL amount is calculated by multiplying the home health 
FDL ratio by a case's wage-adjusted national, standardized 60-day 
episode payment rate, which yields an FDL dollar amount for the case. 
The outlier threshold amount is the sum of the wage and case-mix 
adjusted PPS episode amount and wage-adjusted FDL amount. The outlier 
payment is defined to be a proportion of the wage-adjusted estimated 
cost that surpasses the wage-adjusted threshold. The proportion of 
additional costs over the outlier threshold amount paid as outlier 
payments is referred to as the loss-sharing ratio.
    As we noted in the CY 2011 HH PPS final rule (75 FR 70397 through 
70399), section 3131(b)(1) of the Affordable Care Act amended section 
1895(b)(3)(C) of the Act to require that the Secretary reduce the HH 
PPS payment rates such that aggregate HH PPS payments were reduced by 5 
percent. In addition, section 3131(b)(2) of the Affordable Care Act 
amended section 1895(b)(5) of the Act by redesignating the existing 
language as section 1895(b)(5)(A) of the Act and revised the language 
to state that the total amount of the additional payments or payment 
adjustments for outlier episodes could not exceed 2.5 percent of the 
estimated total HH PPS payments for that year. Section 3131(b)(2)(C) of 
the Affordable Care Act also added section 1895(b)(5)(B) of the Act, 
which capped outlier payments as a percent of total payments for each 
HHA for each year at 10 percent.
    As such, beginning in CY 2011, we reduced payment rates by 5 
percent and targeted up to 2.5 percent of total estimated HH PPS 
payments to be paid as outliers. To do so, we first returned the 2.5 
percent held for the target CY 2010 outlier pool to the national, 
standardized 60-day episode rates, the national per visit rates, the 
LUPA add-on payment amount, and the NRS conversion factor for CY 2010. 
We then reduced the rates by 5 percent as required by section 
1895(b)(3)(C) of the Act, as amended by section 3131(b)(1) of the 
Affordable Care Act. For CY 2011 and subsequent calendar years we 
targeted up to 2.5 percent of estimated total payments to be paid as 
outlier payments, and apply a 10 percent agency-level outlier cap.
    In the CY 2017 HH PPS proposed and final rules (81 FR 43737 through 
43742 and 81 FR 76702), we described our concerns regarding patterns 
observed in home health outlier episodes. Specifically, we noted the 
methodology for calculating home health outlier payments may have 
created a financial incentive for providers to increase the number of 
visits during an episode of care in order to surpass the outlier 
threshold; and simultaneously created a disincentive for providers to 
treat medically complex beneficiaries who require fewer but longer 
visits. Given these concerns, in the CY 2017 HH PPS final rule (81 FR 
76702), we finalized changes to the methodology used to calculate 
outlier payments, using a cost-per-unit approach rather than a cost-
per-visit approach. This change in methodology allows for more accurate 
payment for outlier episodes, accounting for both the number of visits 
during an episode of care and the length of the visits provided. Using 
this approach, we now convert the national per-visit rates into per 15-
minute unit rates. These per 15-minute unit rates are used to calculate 
the estimated cost of an episode to determine whether the claim will 
receive an outlier payment and the amount of payment for an episode of 
care. In conjunction with our finalized policy to change to a cost-per-
unit approach to estimate episode costs and determine whether an 
outlier episode should receive outlier payments, in the CY 2017 HH PPS 
final rule we also finalized the implementation of a cap on the amount 
of time per day that would be counted toward the estimation of an 
episode's costs for outlier calculation purposes (81 FR 76725). 
Specifically, we limit the amount of time per day (summed across the 
six disciplines of care) to 8 hours (32 units) per day when estimating 
the cost of an episode for outlier calculation purposes.
    In the CY 2017 HH PPS final rule (81 FR 76724), we stated that we 
did not plan to re-estimate the average minutes per visit by discipline 
every year. Additionally, the per unit rates used to estimate an 
episode's cost were updated by the home health update percentage each 
year, meaning we would start with the national per visit amounts for 
the same calendar year when calculating the cost-per-unit used to 
determine the cost of an episode of care (81 FR 76727). We will 
continue to monitor the visit length by discipline as more recent data 
becomes available, and may propose to update the rates as needed in the 
future.
    In the CY 2019 HH PPS final rule with comment period (83 FR 56521), 
we finalized a policy to maintain the current methodology for payment 
of high-cost outliers upon implementation of PDGM beginning in CY 2020 
and calculated payment for high-cost outliers based upon 30-day period 
of care. Upon implementation of the PDGM and 30-day unit of payment, we 
finalized the FDL ratio of 0.56 for 30-day periods of care in CY 2020. 
Given that CY 2020 was the first year of the PDGM and the change to a 
30-day unit of payment, we finalized to maintain the same FDL ratio of 
0.56 in CY 2021 as we did not have sufficient CY 2020 data at the time 
of CY 2021 rulemaking to proposed a change to the FDL ratio for CY 
2021. In the CY 2022 HH PPS final rule with comment period (86 FR 
62292), we estimated that outlier payments would be approximately 1.8 
percent of total HH PPS final rule payments if we maintained an FDL of 
0.56 in CY 2022. Therefore, in order to

[[Page 37658]]

pay up to, but no more than, 2.5 percent of total payments as outlier 
payments we finalized an FDL of 0.40 for CY 2022.
(2) FDL Ratio for CY 2023
    For a given level of outlier payments, there is a trade-off between 
the values selected for the FDL ratio and the loss-sharing ratio. A 
high FDL ratio reduces the number of periods that can receive outlier 
payments, but makes it possible to select a higher loss-sharing ratio, 
and therefore, increase outlier payments for qualifying outlier 
periods. Alternatively, a lower FDL ratio means that more periods can 
qualify for outlier payments, but outlier payments per period must be 
lower.
    The FDL ratio and the loss-sharing ratio are selected so that the 
estimated total outlier payments do not exceed the 2.5 percent 
aggregate level (as required by section 1895(b)(5)(A) of the Act). 
Historically, we have used a value of 0.80 for the loss-sharing ratio, 
which, we believe, preserves incentives for agencies to attempt to 
provide care efficiently for outlier cases. With a loss-sharing ratio 
of 0.80, Medicare pays 80 percent of the additional estimated costs 
that exceed the outlier threshold amount. Using CY 2021 claims data (as 
of March 21, 2022) and given the statutory requirement that total 
outlier payments do not exceed 2.5 percent of the total payments 
estimated to be made under the HH PPS, we are proposing an FDL ratio of 
0.44 for CY 2023. CMS will update the FDL, if needed, once we have more 
complete CY 2021 claims data.

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

    Even prior to the COVID-19 PHE, CMS acknowledged the importance of 
technology in allowing HHAs the flexibility of furnishing services 
remotely. In the CY 2019 HH PPS final rule with comment (83 FR 56406), 
for purposes of the Medicare home health benefit, we finalized the 
definition of ``remote patient monitoring'' in regulation at 42 CFR 
409.46(e) as the collection of physiologic data (for example, 
electrocardiogram (ECG), blood pressure, glucose monitoring) digitally 
stored and/or transmitted by the patient and/or caregiver to the HHA. 
In the CY 2019 HH PPS final rule with comment, we also finalized in 
regulation at Sec.  409.46(e) that the costs of remote patient 
monitoring are considered allowable administrative costs (operating 
expenses) if remote patient monitoring is used by the HHA to augment 
the care planning process (83 FR 56527).
    With the declaration of the COVID-19 PHE in early 2020, the use of 
telecommunications technology has become more prominent in the delivery 
of healthcare in the United States. Anecdotally, many beneficiaries 
preferred to stay home than go to physician's offices and outpatient 
centers to seek care, while also limiting the number and frequency of 
care providers furnishing services inside their homes to avoid exposure 
to COVID-19. Accordingly, CMS implemented additional policies under the 
HH PPS to make providing and receiving services via telecommunications 
technology easier. In the first COVID-19 PHE interim final rule with 
comment period (IFC) (85 FR 19230), we changed the plan of care 
requirements at Sec.  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 Sec.  409.43(a) also state that these services cannot 
substitute for a home visit ordered as part of the plan of care and 
cannot be considered a home visit for the purposes of patient 
eligibility or payment, in accordance with section 1895(e)(1)(A) and 
(B) of the Act. The CY 2021 HH PPS final rule with comment period (85 
FR 70298) finalized these changes on a permanent basis, as well as 
amended Sec.  409.46(e) to include not only remote patient monitoring, 
but other communication or monitoring services consistent with the plan 
of care for the individual, on the home health cost report as allowable 
administrative costs.
    Sections 1895(e)(1)(A) and (B) of the Act specify that 
telecommunications services cannot substitute for in-person home health 
services ordered as part of the plan of care certified by a physician 
and are not considered a home health visit for purposes of eligibility 
or payment under Medicare. Though the use of telecommunications 
technology is not to be used as a substitute for in-person home health 
services, as ordered on the plan of care, and services provided through 
the use of telecommunications technology (rather than in-person) are 
not considered a home health visit, anecdotally we have heard that HHAs 
are using telecommunication services during the course of a 30-day 
period of care and as a result of the COVID-19 PHE, as described 
previously. In the first COVID-19 PHE IFC, we provided an example 
describing a situation where the use of technology is not a substitute 
for the provision of in-person visits as ordered on the plan of care, 
rather the plan of care is updated to reflect a change in the frequency 
of the in-person visits and to include ``virtual visits'' as part of 
the management of the home health patient (85 FR 19248).
    Currently, the collection of data on the use of telecommunications 
technology is limited to overall cost data on a broad category of 
telecommunications services as a part of an HHA's administrative costs 
on line 5 of the HHA Medicare cost reports.\18\ As we noted in the CY 
2019 HH PPS proposed rule, these costs would then be factored into the 
costs per visit. Factoring the costs associated with telecommunications 
systems into the costs per visit has important implications for 
assessing home health costs relevant to payment, including HHA Medicare 
margin calculations (83 FR 32426). Data on the use of 
telecommunications technology during a 30-day period of care at the 
beneficiary level is not currently collected on the home health claim. 
While the provision of services furnished via a telecommunications 
system must be included on the patient's plan of care, CMS does not 
routinely review plans of care to determine the extent to which these 
services are actually being furnished.
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    \18\ Found in Ch47 of the Provider Reimbursement Manual at 
https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Paper-Based-Manuals-Items/CMS021935.
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    Collecting data on the use of telecommunications technology on home 
health claims would allow CMS to analyze the characteristics of the 
beneficiaries utilizing services furnished remotely, and will give us a 
broader understanding of the social determinants that affect who 
benefits most from these services, including what barriers may 
potentially exist for certain subsets of beneficiaries. Furthermore, in 
their March 2022 Report to the Congress: Medicare's Payment Policy, 
MedPAC recommended tracking the use of telehealth in the home health 
care benefit on home health claims in order to improve payment 
accuracy.\19\ As such, to collect

[[Page 37659]]

more complete data on the use of telecommunications technology in the 
provision of home health services, we are soliciting comments on the 
collection of such data on home health claims, which we aim to begin 
collecting by January 1, 2023 on a voluntary basis by HHAs, and will 
begin to require this information be reported on claims by July of 
2023. Specifically, we are soliciting comments on the use of three new 
G-codes identifying when home health services are furnished using 
synchronous telemedicine rendered via a real-time two-way audio and 
video telecommunications system; synchronous telemedicine rendered via 
telephone or other real-time interactive audio-only telecommunications 
system; and the collection of physiologic data digitally stored and/or 
transmitted by the patient to the home health agency, that is, remote 
patient monitoring. We would capture the utilization of remote patient 
monitoring through the inclusion of the start date of the remote 
patient monitoring and the number of units indicated on the claim. This 
may help us understand in general how long remote monitoring is used 
for individual patients and for which conditions. Although we plan to 
begin collecting this information beginning with these three G-codes on 
January 1, 2023, we are interested in comments on whether there are 
other common uses of telecommunications technology under the home 
health benefit that would warrant additional G-codes that would be 
helpful in tracking the use of such technology in the provision of 
care.
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    \19\ Medicare Payment Advisory Commission (MedPAC), Report to 
the Congress: Medicare Payment Policy. March 2022, P. 271. found at 
https://www.medpac.gov/wp-content/uploads/2022/03/Mar22_MedPAC_ReportToCongress_SEC.pdf.
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    In accordance with section 40.2 in Chapter 10 of the Medicare 
Claims Processing Manual (Pub. 100-04), we plan to issue instructions 
that these forthcoming G-codes are to be used to report services in 
line item detail and each service must be reported as a separate line 
under the appropriate revenue code (04x--Physical Therapy, 043x--
Occupational Therapy, 044x--Speech-Language Pathology, 055x--Skilled 
Nursing, 056x--Medical Social Services, or 057x--Home Health Aide). 
While we do not plan on limiting the use of these G-codes to any 
particular discipline, we would not anticipate use of such technology 
would be reported under certain revenue codes such as 027x or 0623--
Medical Supplies, or revenue code 057x--Home Health Aide. We are 
interested in comments from the public on our belief that, due to the 
hands-on nature of home health aide services, the use of 
telecommunications technology would generally not be appropriate for 
such services. We remind interested parties that if there is a service 
that cannot be provided through telecommunications technology (for 
example, wound care that requires in-person, hands-on care from a 
skilled nurse), the HHA must make an in-person visit to furnish such 
services (85 FR 39428). We are also requesting comments regarding the 
appropriateness of such technology for particular services in order to 
more clearly delineate when the use of such technology is appropriate. 
This may help inform how we use this analysis, for instance, connecting 
how such technology is impacting the provision of care to certain 
beneficiaries, costs, quality, and outcomes, and determine if further 
requirements surrounding the use of telecommunications technology are 
needed.
    We are also soliciting comments on future refinement of these G-
codes beginning July 1, 2023. Specifically whether the codes should 
differentiate the type of clinician performing the service via 
telecommunications technology, such as a therapist versus therapist 
assistant; and whether new G-codes should differentiate the type of 
service being performed through the use of telecommunications 
technology, such as: skilled nursing services performed for care plan 
oversight (for example, management and evaluation or observation and 
assessment) versus teaching; or physical therapy services performed for 
the establishment or performance of a maintenance program versus other 
restorative physical therapy services.
    We will issue program instruction outlining the use of new codes 
for the purposes of tracking the use of telecommunications technology 
under the home health benefit with sufficient notice to enable HHAs to 
make the necessary changes in their electronic health records and 
billing systems. As stated previously, we will begin collecting this 
information on home health claims by January 1, 2023, on a voluntary 
basis by HHAs, and will require this information be reported on home 
health claims beginning in July, 2023. We would issue further program 
instruction prior to July 1, 2023, if the G-code description changes 
between January 1, 2023, and July 1, 2023, based on comments in this 
proposed rule. However, we reiterate that the collection of information 
on the use of telecommunications technology does not mean that such 
services are considered ``visits'' for purposes of eligibility or 
payment. In accordance with section 1895(e)(1)(A) and (B) of the Act, 
such data will not be used or factored into case-mix weights, or count 
towards outlier payments or the LUPA threshold per payment period.

III. Home Health Quality Reporting Program (HH QRP)

A. Background and Statutory Authority

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

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

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

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

    The HH QRP currently includes 20 measures for the CY 2023 program 
year, as described in Table C1.
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[[Page 37661]]


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[[Page 37662]]

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

    In 1987, Congress added a new section 1891(d) to the Act (section 
4021(b) of Pub. L. 100-203 (December 22, 1987)). The statute required 
the Secretary to develop a comprehensive assessment for Medicare-
participating HHAs. In 1993, CMS (then known as HCFA) developed an 
assessment instrument that identified each patient's need for home care 
and that meets the patient's medical, nursing, rehabilitative, social 
and discharge planning needs. As part of this assessment, Medicare-
certified HHAs were required to use a standard core assessment data 
set, the ``Outcome and Assessment Information Set'' (``OASIS''). 
Section 1891(d) of the Act requires, as part of the home health 
assessment, a survey of the quality of care and services furnished by 
the agency as measured by indicators of medical, nursing, and 
rehabilitative care provided by the HHA. OASIS is the designated 
assessment instrument (or instruments) for use by an HHA in complying 
with the requirement. In the January 25, 1999, final rule titled, 
``Medicare and Medicaid Programs: Comprehensive Assessment and Use of 
the OASIS as Part of the Conditions of Participation for Home Health 
Agencies,'' we also required HHAs to submit the data collected by the 
OASIS assessment to HCFA as an HHA condition of participation (64 FR 
3772).
    Early on, privacy concerns were raised by HHAs around the 
collection of all-payer data and the release of personal health 
information. As we indicated in the study, any new collection 
requirements such as this raise concerns and this was no exception. In 
response to the privacy concerns, CMS took steps to mask the personal 
health information before the data was transmitted to the Quality 
Improvement and Evaluation System (QIES). In the study, we collected 
information from HHAs and the industry including the surveying of 
Agencies by one of the trade organizations and note that the privacy 
concerns initially raised were not raised as an ongoing concern. Based 
upon this feedback, we conclude that the privacy issues raised 
initially are no longer a concern.
    Subsequently, Congress enacted section 704 of the Medicare 
Prescription Drug, Improvement, and Modernization Act of 2003 (MMA), 
which suspended the legal authority of the Secretary to require HHAs to 
report OASIS information on non-Medicare/non-Medicaid patients until at 
least 2 months after the Secretary published final regulations on CMS's 
collection and use of those data following the submission of a report 
to Congress on the study required under section 704(c) of the MMA. This 
study required the Secretary to examine the use of non-Medicare/non-
Medicaid OASIS data by large HHAs, including whether there were unique 
benefits from the analysis of that information that CMS could not 
obtain from other sources, and the value of collecting such data by 
small HHAs versus the administrative burden of collection. In 
conducting the study, the Secretary was also required to obtain 
recommendations from quality assessment experts on the use of such 
information and the necessity of HHAs collecting such information.\20\
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    \20\ https://www.govinfo.gov/content/pkg/PLAW-108publ173/pdf/PLAW-108publ173.pdf.
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    The Secretary conducted the study required under section 704 of the 
MMA in 2004 to 2005 and submitted it to Congress in December 2006 
(https://www.cms.gov/files/document/cms-oasis-study-all-payer-data-submission-2006.pdf). The study made the following key findings:
     There are significant differences between private pay and 
Medicare/Medicaid patients in terms of diagnosis, patient 
characteristics, and patient outcomes. Within-agency correlation 
between Medicare/Medicaid and private pay patient outcomes was low, 
indicating that outcomes based on Medicare/Medicaid patient data cannot 
be generalized to serve as a proxy for private pay patients.
     Risk adjustment models at the time did not account for all 
of the sources of variation in outcomes across different payer groups 
and as a result, measures could produce misleading information.
     Requiring OASIS data collection on private pay patients at 
Medicare-certified HHAs could increase staff and patient burden and 
would require CMS to develop a mechanism for these agencies to receive 
reports from CMS on their private pay patients.
     A change to all-payer assessment data collection would 
strengthen CMS's ability to assess and report indicators of the quality 
of care furnished by HHAs to their entire patient population.
    After considering the study's findings, the Secretary noted that 
the suspension of OASIS collection from non-Medicare patients would 
continue because ``it would be unfair to burden the providers with the 
collection of OASIS at this time since the case mix and outcomes 
reports are not designed to include private pay patients.'' The 
Secretary also noted that it would be inappropriate for CMS to collect 
the private pay OASIS data and not use it. The Secretary further stated 
that ``if funding for the development of HHA patient outcome and case 
mix reports for private pay patients is identified as a priority 
function, CMS would not hesitate to call for the removal of the 
suspension of OASIS for private pay patients.''
    In the November 9, 2006, final rule, ``Medicare Program; Home 
Health Prospective Payment System Rate Update for Calendar Year 2007 
and Deficit Reduction Act of 2005 Changes to Medicare Payment for 
Oxygen Equipment and Capped Rental Durable Medical Equipment'', we 
finalized our policy that the agency would continue to suspend 
collection of OASIS all payer data (71 FR 65883 and 65889).
    Since 2006, CMS has laid the groundwork for the resumption of all-
payer data submission because we want to represent overall care being 
provided to all patients in an HHA. CMS implemented the QIES and iQIES 
provider data reporting systems to securely transfer and manage 
assessment data across QRPs, including HH. These systems can now 
support an extensive range of provider reports, including case-mix 
reports for private pay patients. The HH QRP program expanded quality 
domains to include patient reported outcome measures and new assessment 
and claims-based quality measures. We sought and received public 
comment on several occasions regarding data reporting on all HHA 
patients, regardless of payer type. In February 2012, the NQF-convened 
MAP also issued a report that encouraged establishing a data collection 
and transmission infrastructure for all payers that would work across 
PAC settings.\21\ In the July 28, 2017, and November 7, 2017, ``Home 
Health Prospective Payment System Rate Update and CY 2018 Case-Mix 
Adjustment Methodology Refinements; Home Health Value-Based Purchasing 
Model; and Home Health Quality Reporting Requirements'' proposed and 
final rules (at 82 FR 35372 through 35373 and 82 FR 51736 through 
51737, respectively) and in the July 18, 2019,

[[Page 37663]]

and November 8, 2019, ``Medicare and Medicaid Programs; CY 2020 Home 
Health Prospective Payment System Rate Update'' proposed and final 
rules (at 84 FR 34686 and 84 FR 60478, respectively), we sought and 
responded to input on whether we should require quality data reporting 
on all HHA patients, regardless of payer source, to ensure 
representation of the quality of the services provided to the entire 
HHA population. In the ``CY 2018 Home Health Prospective Payment System 
Rate Update and CY 2019 Case-Mix Adjustment Methodology Refinements; 
Home Health Value-Based Purchasing Model; and Home Health Quality 
Reporting Requirements'' final rule, some commenters shared that there 
would be increased burden from requiring all-payer data submissions (82 
FR 51676). A few commenters also raised the issue of whether it would 
be appropriate to collect and report private pay data, given that 
private payors may have different care pathways, approval, and 
authorization processes. In the CY 2020 HH PPS proposed rule, we also 
sought input on whether collection of quality data used in the HH QRP 
should include all HHA patients, regardless of their payer source (84 
FR 60478). Several commenters supported expanding the HH QRP to include 
collection of data on all patients regardless of payer. Several 
commenters noted that this expanded data collection would not be overly 
burdensome because the majority of HHAs already complete the OASIS on 
all patients, regardless of payer status. Commenters were concerned 
that the usefulness of all-payer data collection to CMS's health policy 
development would not outweigh the additional reporting burden. Several 
commenters supporting all-payer data collection stated that expansion 
of the data collection would align the HH QRP's data collection policy 
with that of Hospices and Long-Term Care Hospitals (LTCHs), as well as 
the data collection policy under the Merit-based Incentive Payment 
System. Other reasons cited by commenters who supported the expanded 
data collection included more accurate representation of the quality of 
care furnished by HHAs to the entire HH population, the ability of such 
data to better guide quality improvement activities, and the reduction 
of current administrative efforts made by HHAs to ensure that only 
OASIS data for Medicare and Medicaid patients are reported to CMS.
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    \21\ National Quality Forum. MAP Coordination Strategy for Post-
Acute Care and Long-Term Care Performance Measurement. February 
2012. Available at https://www.qualityforum.org/Publications/2012/02/MAP_Coordination_Strategy_for_Post-Acute_Care_and_Long-Term_Care_Performance_Measurement.aspx. Accessed March 21, 2022.
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    We believe that collecting OASIS data on all HHA patients, 
regardless of payer, would align our data collection requirements under 
the HH QRP with the data collection requirements for the LTCH QRP and 
Hospice QRP. We also believe that the most accurate representation of 
the quality of care furnished by HHAs is best captured by calculating 
the assessment-based measures rates using OASIS data submitted on all 
HHA patients, regardless of payer. New risk adjustment models with all-
payer data would better represent the full spectrum of patients 
receiving skilled care in HHAs. The submission of all-payer OASIS data 
would also enable us to meaningfully compare performance on quality 
measures across PAC settings. For example, Changes in Skin Integrity 
Post-Acute Care is currently reported by different PAC payers on 
different denominators of payer populations, which greatly inhibits our 
ability to compare performance on this measure across PAC settings. 
Standardizing the denominator for cross setting PAC measures to include 
all patients will enable us to make these comparisons, which we believe 
will realize our goal of establishing consistent measures of quality 
across PAC settings.
    The concerns raised surrounding privacy outlined above have been 
mitigated. We take the privacy and security of individually 
identifiable health information of all patients very seriously. CMS 
data systems conform to all applicable Federal laws, regulations and 
standards on information security and data privacy. The systems limit 
data access to authorized users and monitor such users to help protect 
against unauthorized data access or disclosures. CMS anticipates 
updating the current provider data reporting system in iQIES to address 
the addition of private payer patients.
    For these reasons, we are proposing to end the suspension of non-
Medicare/Medicaid OASIS data collection and to require HHAs to submit 
all-payer OASIS data for purposes of the HH QRP beginning with the CY 
2025 HH QRP program year. We would use the OASIS data to calculate all 
measures for which OASIS is a data source. Although the 2006 report 
recommended that the suspension continue, the subsequent passage of the 
IMPACT Act (Pub. L. 113-185) in 2014, requiring us to create a uniform 
quality measurement system which would allow us to compare outcomes 
across post-acute care providers, requires us to revisit the policy. We 
have indeed established such a uniform quality measurement system, 
based on standardized patient assessment data leading us to propose 
OASIS data collection on Non-Medicare/Non-Medicaid patients. There are 
now cross-setting quality measures in place that should have consistent 
reporting parameters but currently do not have consistent reporting 
parameters because they currently have only Medicare and Medicaid 
populations. The goal of CMS is to have these measures reported for all 
patients for all payer sources. The iQIES system utilized by providers 
is robust enough to make feasible the generation of outcome and case 
mix reports for private pay patients whereas the 2006 QIES system 
lacked this functionality. The HH QRP program also has a more robust 
measure set, including patient reported outcomes, a criteria of 
importance for CMS to move forward with all-payer collection. We 
believe that the maturation of the HH QRP as described previously 
argues for the collection of OASIS all-payer data. It will improve the 
HH QRP program's ability to assess HHA quality and allow the HH QRP to 
foster better quality care for patients regardless of payer source. It 
will also support CMS's ability to compare standardized outcome 
measures across PAC settings.
    Consistent with the two-quarter phase-in that we typically use when 
adopting new reporting requirements for the HHAs, we are proposing that 
for the CY 2025 HH QRP, the expanded reporting would be required for 
patients discharged between January 1, 2024, and June 30, 2024. 
Beginning with the CY 2026 HH QRP, HHAs would be required to report 
assessment based quality measure data and standardized patient 
assessment data on all patients, regardless of payer, for the 
applicable 12 month performance period (which for the CY 2026 program, 
would be patients discharged between July 1, 2024, and June 30, 2025).
    While we appreciate that submitting OASIS data on all HHA patients 
regardless of payer source may create additional burden for HHAs, we 
also note that the current practice of separating and submitting OASIS 
data on only Medicare beneficiaries has clinical and workflow 
implications with an associated burden. As noted previously, we also 
understand that it is common practice for HHAs to collect OASIS data on 
all patients, regardless of payer source. Requiring HHAs to report 
OASIS data on all patients will provide CMS with the most robust, 
accurate reflection of the quality of care delivered to Medicare 
beneficiaries as compared with non-Medicare patients.

E. Proposed Technical Changes

    We are proposing to amend the regulation text in Sec.  
484.245(b)(1) as a technical change to consolidate the statutory 
references to data submission

[[Page 37664]]

to Sec.  484.245(b)(1)(i) and Sec.  484.245(b)(1)(ii). We are also 
proposing to modify Sec.  484.245(b)(1)(iii) to describe additional 
requirements specific to HHCAHPS to make it clear that A through E only 
apply to HHCAHPS.
    In this technical change we specifically propose moving quality 
data required under section 1895(b)(3)(B)(v)(II) from Sec.  
484.245(b)(1)(iii) to Sec.  484.245(b)(1)(i).\22\ Specifically, the 
proposed Sec.  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 Sec.  484.245(b)(1)(iii) would 
state, ``For the purposes of this HHCAHPS survey data submission, the 
following additional requirements apply:''.
---------------------------------------------------------------------------

    \22\ Section 1895(b)(3)(B)(v)(II) requires data submission for 
HHCAHPS.
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    We invite public comments on this proposal.

F. Proposed Codification of the HH QRP Measure Removal Factors

    In the CY 2019 HH PPS final rule with comment period (83 FR 56548 
through 56550), we adopted eight measure removal factors that we 
consider when determining whether to remove measures from the HH QRP 
measure set:
     Factor 1. Measure performance among HHAs is so high and 
unvarying that meaningful distinctions in improvements in performance 
can no longer be made.
     Factor 2. Performance or improvement on a measure does not 
result in better patient outcomes.
     Factor 3. A measure does not align with current clinical 
guidelines or practice.
     Factor 4. A more broadly applicable measure (across 
settings, populations, or conditions) for the particular topic is 
available.
     Factor 5. A measure that is more proximal in time to 
desired patient outcomes for the particular topic is available.
     Factor 6. A measure that is more strongly associated with 
desired patient outcomes for the particular topic is available.
     Factor 7. Collection or public reporting of a measure 
leads to negative unintended consequences other than patient harm.
     Factor 8. The costs associated with a measure outweigh the 
benefit of its continued use in the program. To align the HH QRP with 
similar quality reporting programs (that is SNF QRP, IRF QRP, and LTCH 
QRP) we are proposing to amend 42 CFR 484.245 to add eight HH QRP 
measure removal factors in a new paragraph (b)(3). We welcome comments 
on this proposal.

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

    CMS defines health equity as the attainment of the highest level of 
health for all people, where everyone has a fair and just opportunity 
to attain their optimal health regardless of race, ethnicity, 
disability, sexual orientation, gender identity, socioeconomic status, 
geography, preferred language, or other factors that affect access to 
care and health outcomes.\23\ CMS is working to advance health equity 
by designing, implementing, and operationalizing policies and programs 
that support health for all the people served by our programs, 
eliminating avoidable differences in health outcomes experienced by 
people who are underserved, and providing the care and support that our 
enrollees need to thrive.\24\ CMS' goals are in line with Executive 
Order 13985, on the advancement of racial equity and support for the 
underserved communities, which can be found at 86 FR 7009 (January 25, 
2021) (https://www.whitehouse.gov/briefing-room/presidential-actions/2021/06/25/executive-order-on-diversity-equity-inclusion-and-accessibility-in-the-federal-workforce/).
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    \23\ https://www.cms.gov/pillar/health-equity.
    \24\ CMS Framework for Health Equity 2022-2032.
    \25\ Joynt KE, Orav E, Jha AK. Thirty-Day Readmission Rates for 
Medicare Beneficiaries by Race and Site of Care. JAMA. 2011; 
305(7):675-681.
    \26\ Lindenauer PK, Lagu T, Rothberg MB, et al. Income 
Inequality and 30 Day Outcomes After Acute Myocardial Infarction, 
Heart Failure, and Pneumonia: Retrospective Cohort Study. British 
Medical Journal. 2013; 346.
    \27\ Trivedi AN, Nsa W, Hausmann LRM, et al. Quality and Equity 
of Care in U.S. Hospitals. New England Journal of Medicine. 2014; 
371(24):2298- 2308.
    \28\ Polyakova, M., et al. Racial Disparities In Excess All-
Cause Mortality During The Early COVID-19 Pandemic Varied 
Substantially Across States. Health Affairs. 2021; 40(2): 307-316.
    \29\ Rural Health Research Gateway. Rural Communities: Age, 
Income, and Health Status. Rural Health Research Recap. November 
2018.
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    Belonging to an underserved community is often associated with 
worse health outcomes.25 26 27 28 29 30 31 32 33 
Such disparities in health outcomes are the result of multiple factors. 
Although not the sole determinants, poor access to care and provision 
of lower quality health care are important contributors to health 
disparities notable for CMS programs. Prior research has shown that 
home health agencies serving higher proportions of Black and low-income 
older adults furnish lower quality care than those with lower 
proportions of such patients.\34\ It is unclear why this relationship 
exists, but some evidence suggests that these outcomes are the result 
of reduced access to home health agencies with the highest scores for 
quality and health outcomes measures reported (subsequently referred to 
as high-quality HHAs).\35\ Research in long term care access has shown 
that neighborhoods with larger proportions of Black, Hispanic, and low-
income residents have lower access to a range of high-quality care 
including hospitals, primary care physicians, nursing homes, and 
community-based long-term services.36 37 38 A recent study 
found that Black and Hispanic home health patients were less likely to 
use high quality home health agencies than White patients who lived in 
the same neighborhoods.\39\ This difference in use of high quality HHAs 
persisted even after adjusting for patient health status, suggesting 
disparity in access to higher-quality home health agency was present. 
Disparities exist within neighborhoods, where Black, Hispanic, and 
lower-income home health patients that live in a neighborhood with 
higher-quality home health agencies still have less access to these 
HHAs.\40\ Disparities also persist across neighborhoods where the 
researchers found that 40-77 percent of disparities in high-quality 
agency use was attributable to neighborhood-level

[[Page 37665]]

factors.\41\ The issue of disparity in access is especially critical to 
address currently with the COVID-19 public health emergency (PHE). The 
PHE has increased demand for home health services instead of nursing 
home care for many patients seeking post-acute care.\42\ Factors 
outside of neighborhood effects that could affect inequities in home 
health care and access to care may include a provider's selection of 
patients with higher socioeconomic status (SES) who are perceived to 
have a lower likelihood of reducing provider quality ratings \43\ or a 
provider's biased perception of a patient's risk behavior and adherence 
to care plans.\44\ These findings suggest the need to address issues 
related to care and access when striving to improve health equity.
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    \30\ https://www.minorityhealth.hhs.gov/assets/PDF/Update_HHS_Disparities_Dept-FY2020.pdf.
    \31\ www.cdc.gov/mmwr/volumes/70/wr/mm7005a1.htm.
    \32\ Poteat TC, Reisner SL, Miller M, Wirtz AL. COVID-19 
Vulnerability of Transgender Women With and Without HIV Infection in 
the Eastern and Southern U.S. Preprint. medRxiv. 
2020;2020.07.21.20159327. Published 2020 Jul 24. doi:10.1101/
2020.07.21.20159327.
    \33\ Milkie Vu et al. Predictors of Delayed Healthcare Seeking 
Among American Muslim Women, Journal of Women's Health 26(6) (2016) 
at 58; S.B. Nadimpalli, et al., The Association between 
Discrimination and the Health of Sikh Asian Indians Health Psychol. 
2016 Apr; 35(4): 351-355.
    \34\ Joynt Maddox KE, Chen LM, Zuckerman R, Epstein AM. 
Association between race, neighborhood, and Medicaid enrollment and 
outcomes in Medicare home health care. J Am Geriatr Soc. 
2018;66(2):239-46.
    \35\ IBID.
    \36\ Smith DB, Feng Z, Fennell ML, Zinn J, Mor V. Racial 
disparities in access to long-term care: the illusive pursuit of 
equity. J Health Polit Policy Law. 2008;33(5):861-81.
    \37\ Gaskin DJ, Dinwiddie GY, Chan KS, McCleary R. Residential 
segregation and disparities in health care services utilization. Med 
Care Res Rev. 2012;69(2):158-75.
    \38\ Rahman M, Foster AD. Racial segregation and quality of care 
disparity in U.S. nursing homes. J Health Econ. 2015;39:1-16.
    \39\ Fashaw-Walters, SA. Rahman, M., Gee, G. et al. Out Of 
Reach: Inequities In The Use Of High-Quality Home Health Agencies. 
Health Affairs 2022 41(2):247-255.
    \40\ IBID.
    \41\ Fashaw-Walters, SA. Rahman, M., Gee, G. et al. Out Of 
Reach: Inequities In The Use Of High-Quality Home Health Agencies. 
Health Affairs 2022 41(2):247-255.
    \42\ Werner RM, Bressman E. Trends in post-acute care 
utilization during the COVID-19 pandemic. J Am Med Dir Assoc. 
2021;22(12):2496-9.
    \43\ Werner RM, Asch DA. The unintended consequences of publicly 
reporting quality information. JAMA. 2005;293(10):1239-44.
    \44\ Davitt JK, Bourjolly J, Frasso R. Understanding inequities 
in home health care outcomes: staff views on agency and system 
factors. Res Gerontol Nurs. 2015;8(3):119-29.
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    We are committed to achieving equity in health care outcomes for 
beneficiaries by supporting providers in quality improvement activities 
to reduce health disparities, enabling beneficiaries to make more 
informed decisions, and promoting provider accountability for health 
care disparities.45 46 CMS is committed to closing the 
equity gap in CMS quality programs.
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    \45\ https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/Downloads/CMS-Quality-Strategy.pdf.
    \46\ Report to Congress: Improving Medicare PostAcute Care 
Transformation (IMPACT) Act of 2014 Strategic Plan for Accessing 
Race and Ethnicity Data. January 5, 2017. Available at https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/Research-Reports-2017-Report-to-Congress-IMPACT-ACT-of-2014.pdf.
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    We thank commenters for previous input to our request for 
information on closing the health equity gap in home health care in the 
CY 2022 HH PPS final rule (86 FR 62240). Many commenters shared that 
relevant data collection and appropriate stratification are very 
important in addressing any health equity gaps. These commenters noted 
that CMS should consider potential stratification of health outcomes. 
Stakeholders, including providers, also shared their strategies for 
addressing health disparities, noting that this was an important 
commitment for many health provider organizations. Commenters also 
shared recommendations for additional social determinants of health 
(SDOH) data elements that could strengthen their assessment of 
disparities and issues of health equity. SDOH are the conditions in the 
environments where people are born, live, learn, work, play, worship, 
and age that affect a wide range of health, functioning, and quality-
of-life outcomes and risks.\47\ Many commenters suggested capturing 
information related to food insecurity, income, education, 
transportation, and housing. We will continue to take all comments and 
suggestions into account as we work to develop policies on this 
important topic. We appreciate home health agencies and other 
stakeholders sharing their support and commitment to addressing health 
disparities and offering meaningful comments for consideration. As we 
continue to consider health equity within the HH QRP, we are soliciting 
public comment on the following questions:
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    \47\ Healthy People 2030, U.S. Department of Health and Human 
Services, Office of Disease Prevention and Health Promotion. 
Retrieved 06/09/22.
---------------------------------------------------------------------------

     What efforts does your HHA employ to recruit staff, 
volunteers, and board members from diverse populations to represent and 
serve underserved populations? How does your HHA attempt to bridge any 
cultural gaps between your personnel and beneficiaries/clients? How 
does your HHA measure whether this has an impact on health equity?
     How does your HHA currently identify barriers to access to 
care in your community or service area?
     What are the barriers to collecting data related to 
disparities, SDOH, and equity? What steps does your HHA take to address 
these barriers?
     How does your HHA collect self-reported demographic 
information such as information on race and ethnicity, disability, 
sexual orientation, gender identity, veteran status, socioeconomic 
status, and language preference?
     How is your HHA using collected information such as 
housing, food security, access to interpreter services, caregiving 
status, and marital status to inform its health equity initiatives?
    In addition, we are considering the adoption of a structural 
composite measure for the HH QRP, which could include organizational 
activities to address access to and quality of home health care for 
underserved populations. The composite structural measure concept could 
include HHA reported data on HHA activities to address underserved 
populations' access to home health care. An HHA could receive a point 
(for a total of three points for the three domains) for each domain 
where data are submitted to a CMS portal, regardless of the action in 
that domain.
    HHAs could submit information such as documentation, examples, or 
narratives to qualify for the measure numerator. The domains under 
consideration for the measure, as well as how an HHA could satisfy each 
of those domains and earn a point for that domain, are the following:
    Domain 1: HHAs' commitment to reducing disparities is strengthened 
when equity is a key organizational priority. Candidate domain 1 could 
be satisfied if an HHA submits data on actions it is taking with 
respect to health equity and community engagement in their strategic 
plan. HHAs could report data in the reporting year about their actions 
in each of the following areas, and submission of data for all elements 
could be required to qualify for the measure numerator.
     HHAs attest to whether their strategic plan includes 
approaches to address health equity in the reporting year.
     HHAs report community engagement and key stakeholder 
activities in the reporting year.
     HHAs report on any attempts to measure input they solicit 
from patients and caregivers about care disparities they may experience 
as well as recommendations or suggestions for improvement.
    Domain 2: Training HHA board members, HHA leaders, and other HHA 
staff in culturally and linguistically appropriate services (CLAS),\48\ 
health equity, and implicit bias is an important step the HHA can take 
to provide quality care to diverse populations. Candidate domain 2 
could focus on HHAs' diversity, equity, inclusion training for board 
members and staff by capturing the following reported actions in the 
reporting year. Submission of relevant data for all elements could be 
required to qualify for the measure numerator.
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    \48\ https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/CLAS-Toolkit-12-7-16.pdf.
---------------------------------------------------------------------------

     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

[[Page 37666]]

as the materials provided or other documentation of the learning 
opportunities.
    Domain 3: HHA leaders and staff can improve their capacity to 
address health disparities by demonstrating routine and thorough 
attention to equity and setting an organizational culture of equity. 
This candidate domain could capture activities related to 
organizational inclusion initiatives and capacity to promote health 
equity. Examples of equity-focused factors include proficiency in 
languages other than English, experience working with diverse 
populations in the service area, and experience working with 
individuals with disabilities. Submission of relevant data for all 
elements could be required to qualify for the measure numerator.
     HHAs attest as to whether they considered equity-focused 
factors in the hiring of HHA senior leadership, including chief 
executives and board of trustees, in the applicable reporting year.
     HHAs attest as to whether equity-focused factors were 
included in the hiring of direct patient care staff (for example, 
therapists, nurses, social workers, physicians, or aides) in the 
applicable reporting year.
     HHAs attest as to whether equity focused factors were 
included in the hiring of indirect care or support staff (for example, 
administrative, clerical, or human resources) in the applicable 
reporting year.
    We are interested in developing health equity measures based on 
information collected by HHAs not currently available on claims, 
assessments, or other publicly available data sources to support 
development of future quality measures. We are soliciting public 
comment on the conceptual domains and quality measures described in 
this section. Furthermore, we are soliciting public comments on 
publicly reporting a composite structural health equity quality 
measure; displaying descriptive information on Care Compare from the 
data HHAs provide to support health equity measures; and the impact of 
the domains and quality measure concepts on organizational culture 
change.

G. Advancing Health Information Exchange

    The Department of Health and Human Services (HHS) has a number of 
initiatives designed to encourage and support the adoption of 
interoperable health information technology and to promote nationwide 
health information exchange to improve health care and patient access 
to their digital health information.
    To further interoperability in post-acute care settings, CMS and 
the Office of the National Coordinator for Health Information 
Technology (ONC) participate in the Post-Acute Care Interoperability 
Workgroup (PACIO) to facilitate collaboration with industry 
stakeholders to develop Health Level Seven International[supreg] (HL7) 
Fast Healthcare Interoperability Resources[supreg] (FHIR) 
standards.\49\ These standards could support the exchange and reuse of 
patient assessment data derived from the Minimum Data Set (MDS), 
Inpatient Rehabilitation Facility-Patient Assessment Instrument (IRF-
PAI), LTCH Continuity Assessment Record and Evaluation (CARE) Data Set 
(LCDS), Outcome and Assessment Information Set (OASIS), and other 
sources. The PACIO Project has focused on HL7 FHIR implementation 
guides for functional status, cognitive status and new use cases on 
advance directives, re-assessment timepoints, and Speech, Language, 
Swallowing, Cognitive communication and Hearing (SPLASCH) pathology. We 
encourage PAC provider and health IT vendor participation as the 
efforts advance.
---------------------------------------------------------------------------

    \49\ http://www.pacioproject.org/.
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    The CMS Data Element Library (DEL) continues to be updated and 
serves as a resource for PAC assessment data elements and their 
associated mappings to health IT standards, such as Logical Observation 
Identifiers Names and Codes (LOINC) and Systematized Nomenclature of 
Medicine Clinical Terms (SNOMED). The DEL furthers CMS' goal of data 
standardization and interoperability. Standards in the DEL (https://www.del.cms.gov/DELWeb/pubHome) can be referenced on the CMS website 
and in the ONC Interoperability Standards Advisory (ISA). The 2022 ISA 
is available at https://www.healthit.gov/isa.
    The 21st Century Cures Act (Cures Act) (Pub. L. 114-255, enacted 
December 13, 2016) required HHS and ONC to take steps to further 
interoperability for providers in settings across the care continuum. 
Section 4003(b) of the Cures Act required ONC to take steps to advance 
interoperability through the development of a trusted exchange 
framework and common agreement aimed at establishing a universal floor 
of interoperability across the country. On January 18, 2022, ONC 
announced a significant milestone by releasing the Trusted Exchange 
Framework \50\ and Common Agreement Version 1.\51\ The Trusted Exchange 
Framework is a set of non-binding principles for health information 
exchange, and the Common Agreement is a contract that advances those 
principles. The Common Agreement and the Qualified Health Information 
Network Technical Framework Version 1 \52\ (incorporated by reference 
into the Common Agreement) establish the technical infrastructure model 
and governing approach for different health information networks and 
their users to securely share clinical information with each other--all 
under commonly agreed to terms. The technical and policy architecture 
of how exchange occurs under the Trusted Exchange Framework and the 
Common Agreement follows a network-of-networks structure, which allows 
for connections at different levels and is inclusive of many different 
types of entities at those different levels, such as health information 
networks, healthcare practices, hospitals, public health agencies, and 
Individual Access Services (IAS) Providers.\53\ For more information, 
we refer readers to https://www.healthit.gov/topic/interoperability/trusted-exchange-framework-and-common-agreement.
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    \50\ The Trusted Exchange Framework (TEF): Principles for 
Trusted Exchange (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Trusted_Exchange_Framework_0122.pdf.
    \51\ Common Agreement for Nationwide Health Information 
Interoperability Version 1 (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
    \52\ Qualified Health Information Network (QHIN) Technical 
Framework (QTF) Version 1.0 (Jan. 2022),https://www.rce.sequoiaproject.org/wp-content/uploads/2022/01/QTF_0122.pdf.
    \53\ The Common Agreement defines Individual Access Services 
(IAS) as ``with respect to the Exchange Purposes definition, the 
services provided utilizing the Connectivity Services, to the extent 
consistent with Applicable Law, to an Individual with whom the QHIN, 
Participant, or Subparticipant has a Direct Relationship to satisfy 
that Individual's ability to access, inspect, or obtain a copy of 
that Individual's Required Information that is then maintained by or 
for any QHIN, Participant, or Subparticipant.'' The Common Agreement 
defines ``IAS Provider'' as: ``Each QHIN, Participant, and 
Subparticipant that offers Individual Access Services.'' See Common 
Agreement for Nationwide Health Information Interoperability Version 
1, at 7 (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
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    We invite readers to learn more about these important developments 
and how they are likely to affect HHAs.

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

A. Background

    As authorized by section 1115A of the Act and finalized in the CY 
2016 HH PPS final rule (80 FR 68624), the Center for Medicare and 
Medicaid Innovation (Innovation Center) implemented the

[[Page 37667]]

Home Health Value-Based Purchasing (HHVBP) Model (``original Model'') 
in nine states on January 1, 2016. The design of the original HHVBP 
Model leveraged the successes and lessons learned from other CMS value-
based purchasing programs and demonstrations to shift from volume-based 
payments to a model designed to promote the delivery of higher quality 
care to Medicare beneficiaries. The specific goals of the original 
HHVBP Model were to--
     Provide incentives for better quality care with greater 
efficiency;
     Study new potential quality and efficiency measures for 
appropriateness in the home health setting; and,
     Enhance the current public reporting process.
    The original HHVBP Model resulted in an average 4.6 percent 
improvement in HHAs' total performance scores (TPS) and an average 
annual savings of $141 million to Medicare without evidence of adverse 
risks.\54\ The evaluation of the original model also found reductions 
in unplanned acute care hospitalizations and skilled nursing facility 
(SNF) stays, resulting in reductions in inpatient and SNF spending. The 
U.S. Secretary of Health and Human Services determined that expansion 
of the original HHVBP Model would further reduce Medicare spending and 
improve the quality of care. In October 2020, the CMS Chief Actuary 
certified that expansion of the HHVBP Model would produce Medicare 
savings if expanded to all states.\55\
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    \54\ https://innovation.cms.gov/data-and-reports/2020/hhvbp-thirdann-rpt.
    \55\ https://www.cms.gov/files/document/certificationhome-health-value-based-purchasing-hhvbpmodel.pdf.
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    On January 8, 2021, CMS announced the certification of the HHVBP 
Model for expansion nationwide, as well as the intent to expand the 
Model through notice and comment rulemaking.\56\
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    \56\ https://www.cms.gov/newsroom/press-releases/cms-takes-action-improve-home-health-care-seniors-announces-intent-expand-home-health-value-based.
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    In the CY 2022 HH PPS final rule (86 FR 62292 through 62336) and 
codified at 42 CFR part 484, subpart F, we finalized the decision to 
expand the HHVBP Model to all Medicare certified HHAs in the 50 States, 
territories, and District of Columbia beginning January 1, 2022. We 
finalized that the expanded Model will generally use benchmarks, 
achievement thresholds, and improvement thresholds based on CY 2019 
data to assess achievement or improvement of HHA performance on 
applicable quality measures and that HHAs will compete nationally in 
their applicable size cohort, smaller-volume HHAs or larger-volume 
HHAs, as defined by the number of complete unique beneficiary episodes 
for each HHA in the year prior to the performance year. All HHAs 
certified to participate in the Medicare program prior to January 1, 
2022, will be required to participate and will be eligible to receive 
an annual Total Performance Score based on their CY 2023 performance.
    We finalized the quality measure set for the expanded Model, as 
well as policies related to the removal, modification, and suspension 
of applicable measures, and the addition of new measures and the form, 
manner and timing of the OASIS-based, Home Health Consumer Assessment 
of Healthcare Providers and Systems (HHCAHPS) survey-based, and claims-
based measures submission in the applicable measure set beginning CY 
2022 and subsequent years. We also finalized an appeals process, an 
extraordinary circumstances exception policy, and public reporting of 
annual performance data under the expanded Model.
    Additionally, in the CY 2022 HH PPS proposed rule (86 FR 35929) we 
solicited comments on the challenges unique to value-based purchasing 
frameworks in terms of health equity and ways in which we could 
incorporate health equity goals into the expanded HHVBP Model. We 
received comments related to the use of stabilization measures to 
promote access to care for individuals with chronic illness or limited 
ability to improve; collection of patient level demographic information 
for existing measures; and stratification of outcome measures by 
various patient populations to determine how they are affected by 
social determinants of health (SDOH). In the CY 2022 HHPPS final rule 
(86 FR 62312) we summarized and responded to these comments received.
    In this proposed rule, we are proposing to replace the term 
baseline year with the terms HHA baseline year and Model baseline year 
and to change the calendar years associated with each of those baseline 
years, and soliciting comment on future approaches to health equity in 
the expanded HHVBP Model.

B. Proposed Changes to the Baseline Years and New Definitions

1. Definitions
a. Background
    Benchmarks, achievement thresholds, and improvement thresholds are 
used to assess achievement or improvement of HHA performance on 
applicable quality measures. As codified at Sec.  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 Sec.  484.350(b), that 
for a new HHA that is certified by Medicare on or after January 1, 
2019, the baseline year is the first full calendar year of services 
beginning after the date of Medicare certification, with the exception 
of HHAs certified on January 1, 2019, through December 31, 2019, for 
which the baseline year is calendar year (CY) 2021, and the first 
performance year is the first full calendar year (beginning with CY 
2023) following the baseline year.
b. Proposals To Amend Definitions
    Since that final rule, it has come to our attention that there 
could be some confusion and we would like to explain our terminology 
more clearly by proposing to differentiate between two types of 
baseline years used in the expanded HHVBP Model. The Model baseline 
year is used to determine the benchmark and achievement threshold for 
each measure for all HHAs. For example, as finalized, CY 2019 data is 
used in the calculation of the achievement thresholds and benchmarks 
for all applicable measures for both the small cohort and for the large 
cohort. The HHA baseline year is used to determine the HHA improvement 
threshold for each measure for each individual competing HHA. For 
example, if an HHA is certified in CY 2021, CY 2022 data would be used 
in the calculation of the improvement thresholds for all applicable 
measures for that HHA.
    Therefore, we are proposing to amend Sec.  484.345 to remove the 
existing baseline year definition: means the year against which measure 
performance in a performance year will be compared. In its place, we 
are proposing to define: (1) HHA baseline year as the calendar year 
used to determine the improvement threshold for each measure for each 
individual competing HHA, and (2) Model baseline year as the calendar 
year used to determine the benchmark and achievement threshold for each 
measure for all competing HHAs. In line with these proposed 
definitions, we are proposing to make conforming revisions toto the 
definitions of achievement threshold and benchmark to indicate that 
they are calculated using the Model baseline year, and the definition 
of improvement threshold to indicate that it is calculated using the 
HHA baseline

[[Page 37668]]

year. Additionally, we are proposing to amend paragraph (a) of Sec.  
484.370 to remove the phrase ``for the baseline year'' because the 
calculation of the TPS using the applicable benchmarks and achievement 
thresholds (determined usingusing the Model baseline year) and 
improvement thresholds (determined using the HHA baseline year) is 
described at Sec.  484.360.
    We invite public comments on these proposals.
2. Proposed Change of HHA Baseline Years
a. Background--New and Existing HHAs Baseline Years
    As previously discussed, in the CY 2022 HH PPS final rule (86 FR 
62300), we finalized our proposal to use CY 2019 as the baseline year 
for the expanded HHVBP Model. Our intent was that the Model baseline 
year used to determine achievement thresholds and benchmarks is CY 2019 
for all HHAs and the HHA baseline year used to determine an individual 
HHA's improvement threshold is 2019 for HHAs certified prior to January 
1, 2019. As discussed in the section IV.B.1.b. of this rule, we are 
proposing to replace the term baseline year with the terms Model 
baseline year and HHA baseline year to differentiate between two types 
of baseline years used in the expanded HHVBP Model.
    As mentioned earlier, in that same rule (86 FR 62423), we codified 
at Sec.  484.350(b), that for a new HHA that is certified by Medicare 
on or after January 1, 2019, the baseline year is the first full 
calendar year of services beginning after the date of Medicare 
certification, with the exception of HHAs certified on January 1, 2019, 
through December 31, 2019, for which the baseline year is calendar year 
(CY) 2021, and the first performance year is the first full calendar 
year (beginning with CY 2023) following the baseline year. Table D1 
depicts what was finalized in the CY 2022 HH PPS final rule.
[GRAPHIC] [TIFF OMITTED] TP23JN22.055

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

[[Page 37669]]

[GRAPHIC] [TIFF OMITTED] TP23JN22.056

[GRAPHIC] [TIFF OMITTED] TP23JN22.057


[[Page 37670]]


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

    \57\ Derived from data at https://data.cms.gov/provider-data/archived-data/home-health-services.
[GRAPHIC] [TIFF OMITTED] TP23JN22.058

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

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

    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

[[Page 37671]]

2019 baseline year data in advance of the first performance year under 
the expanded Model (CY 2023). If we were to finalize this proposal to 
instead use CY 2022 data for the HHA baseline year, we would intend to 
continue to make these baseline data available as soon as 
administratively possible, and would anticipate providing HHAs with 
their final individual improvement thresholds in the summer of CY 2023. 
We note that this would be consistent with the original HHVBP Model, 
for which improvement thresholds using CY 2015 data were made available 
HHAs in the first interim performance report (IPR) in the summer of the 
first performance year (CY 2016).
    This proposal is made in conjunction with our proposal to add the 
definition of the term HHA baseline year discussed previously. We 
believe that this proposal would allow all eligible HHAs, starting with 
the CY 2023 performance year, to compete on a level playing field with 
all HHA baseline data being after the peak of the pandemic. 
Accordingly, we are proposing to amend Sec.  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 Sec.  484.350(c) to reflect that for an existing HHA, 
specifically an HHA that is certified by Medicare before January 1, 
2022, the HHA baseline year is CY 2022. Table D3 depicts these 
proposals.
[GRAPHIC] [TIFF OMITTED] TP23JN22.059

    In developing this proposal, we considered changing the HHA 
baseline year to CY 2021 for all HHAs for all of the applicable 
measures or, alternatively, not changing the HHA baseline year for any 
of the applicable measures. We decided against those alternatives for 
the reasons explained previously in support of our proposal to change 
the HHA baseline year to CY 2022. We also considered changing the HHA 
baseline for only some of the applicable measures. For example, we 
considered changing the HHA baseline to CY 2022 only for the claims-
based measures and using the HHA baseline of CY 2019 or CY 2021 (see 
Table D1) for applicable HHAs for the OASIS-based and HHCAHPS-based 
measures. However, for the reasons previously discussed, we are instead 
proposing to change the HHA baseline year to CY 2022 for all applicable 
measures used in the expanded HHVBP Model, which would allow all HHAs 
certified by Medicare prior to CY 2022 to have the same baseline period 
for all measures, using the most recent available data, for the 
performance year beginning CY 2023.
    We invite public comments on these proposals.
3. Proposal to Change the Model Baseline Year
    As mentioned earlier, under the policy finalized in the CY 2022 HH 
PPS final rule (86 FR 62300), we previously adopted CY 2019 as the 
Model baseline year for the expanded HHVBP Model for all HHAs. This 
baseline year is used to determine the benchmarks and achievement 
threshold for each measure for all HHAs.
    Consistent with our proposal to update the HHA baseline year to CY 
2022 for all HHAs that are certified by Medicare before January 1, 
2022, and in conjunction with our proposal to more clearly define the 
Model baseline year in previous section IV.B.1.b., we are also 
proposing to change the Model baseline year from CY 2019 to CY 2022 for 
the CY 2023 performance year and subsequent years. This would enable us 
to measure competing HHAs' performance using benchmarks and achievement 
thresholds that are based on the most recent data available. This would 
also allow the benchmarks and achievement thresholds to be set using 
data from after the most acute phase of the COVID-19 PHE, which we 
believe would provide a more appropriate basis for assessing 
performance under the expanded Model than the CY 2019 pre-PHE period. 
As previously discussed, CY 2022 is the first year where the vast 
majority of beneficiaries are vaccinated, there are viable treatments 
available and healthcare providers had nearly two years of experience 
managing COVID-19 patients. We anticipate that this more recent data 
from the CY 2022 time period would more likely be aligned with 
performance years' data under the expanded Model. As discussed in 
connection with our proposal to use CY 2022 data for the HHA baseline 
year, if we were to finalize this proposal to use CY 2022 rather than 
CY 2019 data for the Model baseline year, we would anticipate providing 
HHAs with the final achievement thresholds and benchmarks in the July 
2023 IPR in the summer of CY 2023. This would be consistent with the 
rollout of the original HHVBP Model in which benchmarks and achievement 
thresholds using 2015 data were made available to HHAs during the 
summer of the first performance year (CY 2016).
    We invite public comments on this proposal.

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

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

[[Page 37672]]

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

    \59\ Joynt KE, Orav E, Jha AK. (2011). Thirty-day readmission 
rates for Medicare beneficiaries by race and site of care. JAMA, 
305(7):675-681.
    \60\ Lindenauer PK, Lagu T, Rothberg MB, et al. (2013). Income 
inequality and 30 day outcomes after acute myocardial infarction, 
heart failure, and pneumonia: Retrospective cohort study. British 
Medical Journal, 346.
    \61\ Trivedi AN, Nsa W, Hausmann LRM, et al. (2014). Quality and 
equity of care in U.S. hospitals. New England Journal of Medicine, 
371(24):2298-2308.
    \62\ Polyakova, M., et al. (2021). Racial disparities in excess 
all-cause mortality during the early COVID-19 pandemic varied 
substantially across states. Health Affairs, 40(2): 307-316.
    \63\ Rural Health Research Gateway. (2018). Rural communities: 
age, income, and health status. Rural Health Research Recap. https://www.ruralhealthresearch.org/assets/2200-8536/rural-communities-age-incomehealth-status-recap.pdf.
    \64\ https://www.minorityhealth.hhs.gov/assets/PDF/Update_HHS_Disparities_Dept-FY2020.pdf.
    \65\ www.cdc.gov/mmwr/volumes/70/wr/mm7005a1.htm.
    \66\ Milkie Vu et al. Predictors of Delayed Healthcare Seeking 
Among American Muslim Women, Journal of Women's Health 26(6) (2016) 
at 58; S.B. Nadimpalli, et al., The Association between 
Discrimination and the Health of Sikh Asian Indians Health Psychol. 
2016 Apr; 35(4): 351-355.
    \67\ Poteat TC, Reisner SL, Miller M, Wirtz AL. (2020). COVID-19 
vulnerability of transgender women with and without HIV infection in 
the Eastern and Southern U.S. preprint. medRxiv. 2020;2020.07.21. 
20159327. doi:10.1101/2020.07.21.20159327.
    \68\ 86 FR 7009 (January 25, 2021); https://www.whitehouse.gov/briefing-room/presidential-actions/2021/01/20/executive-order-advancing-racial-equity-and-support-for-underserved-communities-through-the-federal-government/.
    \69\ https://www.cms.gov/pillar/health-equity.
    \70\ https://www.cms.gov/About-CMS/Agency-Information/OMH/OMH-Mapping-Medicare-Disparities.
    \71\ https://innovation.cms.gov/innovation-models/ahcm.
    \72\ https://qualitynet.cms.gov/inpatient/measures/disparity-methods.
    \73\ https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/-IMPACT-Act-Standardized-Patient-Assessment-Data-Elements.
    \74\ https://www.cms.gov/sites/default/files/2022-04/CMS%20Framework%20for%20Health%20Equity_2022%2004%2006.pdf.
---------------------------------------------------------------------------

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

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

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

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

    In accordance with section 1834(u)(3) of the Act and 42 CFR 
414.1550, our national home infusion therapy (HIT) services payment 
rates for the initial and subsequent visits in each of the home 
infusion therapy payment categories for CY 2023 are required to be the 
CY 2022 rate adjusted by the percentage increase in the Consumer Price 
Index (CPI) for all urban consumers (United States city average) for 
the 12 month period ending with June of the preceding year reduced by a 
productivity adjustment described in section 1886(b)(3)(B)(xi)(II) of 
the Act as the 10-year moving average of changes in annual economy-wide 
private nonfarm business multifactor productivity. Section 1834(u)(3) 
of the Act further states that the application of the productivity 
adjustment may result in a percentage being less than 0.0 for a given 
year, and may result in payment being less than such payment rates for 
the preceding year. We note that Sec.  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

[[Page 37673]]

(84 FR 62568). The next full update to the GPCIs and the GAFs will be 
proposed in the CY 2023 PFS proposed rule. The CY 2023 PFS proposed 
rule and the CY 2023 proposed GAFs will be available on the PFS website 
at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/PhysicianFeeSched after publication in the Federal Register.
    The updated GAFs, national home infusion therapy payment rates, and 
locality-adjusted home infusion therapy payment rates will be posted on 
CMS' Home Infusion Therapy Services web page \76\ once these rates are 
finalized. In the future, we will no longer include a section in the HH 
PPS rule on home infusion therapy if no changes are being proposed to 
the payment methodology. Instead, the rates will be updated each year 
in a Change Request and posted on the website. For more in-depth 
information regarding the finalized policies associated with the scope 
of the home infusion therapy services benefit and conditions for 
payment, we refer readers to the CY 2020 HH PPS final rule with comment 
period (84 FR 60544).
---------------------------------------------------------------------------

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

VI. Collection of Information Requirements

A. Statutory Requirement for Solicitation of Comments

    Under the Paperwork Reduction Act of 1995, we are required to 
provide a 60-day notice in the Federal Register and solicit public 
comment before a collection of information requirement is submitted to 
the Office of Management and Budget (OMB) for review and approval. In 
order to fairly evaluate whether an information collection should be 
approved by OMB, section 3506(c)(2)(A) of the Paperwork Reduction Act 
of 1995 requires that we solicit comment on the following issues:
     The need for the information collection and its usefulness 
in carrying out the proper functions of our agency.
     The accuracy of our estimate of the information collection 
burden.
     The quality, utility, and clarity of the information to be 
collected.
     Recommendations to minimize the information collection 
burden on the affected public, including automated collection 
techniques.
    In this proposed rule, we are soliciting public comment on each of 
these issues for the following sections of this document that contain 
information collection requirements (ICRs).

B. Collection of Information Requirement

1. ICRs for HH QRP
    In section III. of this proposed rule, we are proposing to end the 
suspension of the collection of OASIS data on non-Medicare and non-
Medicaid patients and to require HHAs to submit all-payer OASIS data 
for purposes of the HH QRP, beginning with the CY 2025 program year. We 
believe that the burden associated with this proposal is the time and 
effort associated with the submission of non-Medicare and non-Medicaid 
OASIS data. The submission of OASIS data on HH patients regardless of 
payor source will ensure that CMS can appropriately assess the quality 
of care provided to all patients receiving skilled care by all 
Medicare-certified HHAs that participate in the HH QRP. As of January 
1, 2022, there are approximately 11,354 HHAs reporting OASIS data to 
CMS under the HH QRP.
    The OASIS is completed by RNs or PTs, or very occasionally by 
occupational therapists (OT) or speech language pathologists (SLP/ST). 
Data from 2020 show that the SOC/ROC OASIS is completed by RNs 
(approximately 76.50 percent of the time), PTs (approximately 20.78 
percent of the time), and other therapists, including OTs and SLP/STs 
(approximately 2.72 percent of the time). Based on this analysis, we 
estimated a weighted clinician average hourly wage of $79.41, inclusive 
of fringe benefits, using the hourly wage data in Table F1. Individual 
providers determine the staffing resources necessary.
    For purposes of calculating the costs associated with the 
information collection requirements, we obtained mean hourly wages for 
these from the U.S. Bureau of Labor Statistics' May 2020 National 
Occupational Employment and Wage Estimates (https://www.bls.gov/oes/current/oes_nat.htm). To account for overhead and fringe benefits (100 
percent), we have doubled the hourly wage. These amounts are detailed 
in Table F1.
[GRAPHIC] [TIFF OMITTED] TP23JN22.060

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

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

    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.

[[Page 37674]]

[GRAPHIC] [TIFF OMITTED] TP23JN22.061

    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.
[GRAPHIC] [TIFF OMITTED] TP23JN22.062

    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 x 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 x 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 x 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 x 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 x 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 x 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 x 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

[[Page 37675]]

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

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

Death at Home

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

9 data elements x 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 x 65,640 DAH assessments = 177,228 minutes/60 
minutes = 2,954 hours

Discharge

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

146 data elements x 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 x 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.
[GRAPHIC] [TIFF OMITTED] TP23JN22.063

    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 x 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 x 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 x 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 x 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 x 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 x 4,534,626 hours = $360,094,650.66 for all HHAs

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

C. Submission of PRA-Related Comments

    We have submitted a copy of this proposed rule to OMB for its 
review of the rule's information collection requirements. The 
requirements are not effective until they have been approved by OMB.
    We invite public comments on these information collection 
requirements. If you wish to comment, please identify the rule (CMS-
1766-P) and, where applicable, the preamble section, and the ICR 
section. See this rule's DATES and ADDRESSES sections for the

[[Page 37676]]

comment due date and for additional instructions.

VII. Regulatory Impact Analysis

A. Statement of Need

1. HH PPS
    Section 1895(b)(1) of the Act requires the Secretary to establish a 
HH PPS for all costs of home health services paid under Medicare. In 
addition, section 1895(b) of the Act requires: (1) the computation of a 
standard prospective payment amount include all costs for home health 
services covered and paid for on a reasonable cost basis and that such 
amounts be initially based on the most recent audited cost report data 
available to the Secretary; (2) the prospective payment amount under 
the HH PPS to be an appropriate unit of service based on the number, 
type, and duration of visits provided within that unit; and (3) the 
standardized prospective payment amount be adjusted to account for the 
effects of case-mix and wage levels among HHAs. Section 1895(b)(3)(B) 
of the Act addresses the annual update to the standard prospective 
payment amounts by the home health applicable percentage increase. 
Section 1895(b)(4) of the Act governs the payment computation. Sections 
1895(b)(4)(A)(i) and (b)(4)(A)(ii) of the Act requires the standard 
prospective payment amount be adjusted for case-mix and geographic 
differences in wage levels. Section 1895(b)(4)(B) of the Act requires 
the establishment of appropriate case-mix adjustment factors for 
significant variation in costs among different units of services. 
Lastly, section 1895(b)(4)(C) of the Act requires the establishment of 
wage adjustment factors that reflect the relative level of wages, and 
wage-related costs applicable to home health services furnished in a 
geographic area compared to the applicable national average level.
    Section 1895(b)(3)(B)(iv) of the Act provides the Secretary with 
the authority to implement adjustments to the standard prospective 
payment amount (or amounts) for subsequent years to eliminate the 
effect of changes in aggregate payments during a previous year or years 
that were the result of changes in the coding or classification of 
different units of services that do not reflect real changes in case-
mix. Section 1895(b)(5) of the Act provides the Secretary with the 
option to make changes to the payment amount otherwise paid in the case 
of outliers because of unusual variations in the type or amount of 
medically necessary care. Section 1895(b)(3)(B)(v) of the Act requires 
HHAs to submit data for purposes of measuring health care quality, and 
links the quality data submission to the annual applicable percentage 
increase. Section 50208 of the BBA of 2018 (Pub. L. 115-123) requires 
the Secretary to implement a new methodology used to determine rural 
add-on payments for CYs 2019 through 2022.
    Sections 1895(b)(2) and 1895(b)(3)(A) of the Act, as amended by 
section 51001(a)(1) and 51001(a)(2) of the BBA of 2018 respectively, 
required the Secretary to implement a 30-day unit of service, for 30-
day periods beginning on and after January 1, 2020. The HH PPS wage 
index utilizes the wage adjustment factors used by the Secretary for 
purposes of sections 1895(b)(4)(A)(ii) and (b)(4)(C) of the Act for 
hospital wage adjustments.
2. HH QRP
    Section 1895(b)(3)(B)(v) of the Act authorizes the HH QRP, which 
requires HHAs to submit data in accordance with the requirements 
specified by CMS. Failure to submit data required under section 
1895(b)(3)(B)(v) of the Act with respect to a program year will result 
in the reduction of the annual home health market basket percentage 
increase otherwise applicable to an HHA for the corresponding calendar 
year by 2 percentage points.
3. Expanded HHVBP Model
    In the CY 2022 HH PPS final rule (86 FR 62292 through 62336) and 
codified at 42 CFR part 484, subpart F, we finalized our policy to 
expand the HHVBP Model to all Medicare certified HHAs in the 50 States, 
territories, and District of Columbia beginning January 1, 2022. CY 
2022 was designated as a pre-implementation year during which CMS will 
provide HHAs with resources and training. This pre-implementation year 
as intended to allow HHAs time to prepare and learn about the 
expectations and requirements of the expanded HHVBP Model without risk 
to payments.
    We also finalized that the expanded Model will use a baseline year 
to establish the benchmarks and achievement thresholds for each cohort 
on each measure for HHAs. The baseline year is currently 2019. In this 
rule, we are proposing to establish a separate HHA baseline year to 
determine HHA improvement thresholds by measure for each individual 
agency to assess achievement or improvement of HHA performance on 
applicable quality measures. As codified at Sec.  484.350(b), for an 
HHA that is certified by Medicare on or after January 1, 2019, the 
baseline year is the first full calendar year of services beginning 
after the date of Medicare certification, with the exception of HHAs 
certified on January 1, 2019, through December 31, 2019, for which the 
baseline year is calendar year (CY) 2021, and the first performance 
year is the first full calendar year (beginning with CY 2023) following 
the baseline year. As discussed in that final rule, we stated that we 
may conduct analyses of the impact of using various baseline periods 
and consider any changes for future rulemaking.
    Due to the continuation of the COVID-19 PHE through CY 2021 and its 
effects on the quality measures in the expanded HHVBP Model used to 
determine payment adjustments for eligible HHAs (as described in 
section IV.B.2.b. of this proposed rule), we believe an HHA's baseline 
year that would be CY 2021 should be adjusted to CY 2022. This policy 
aligns with similar proposals in the Hospital VBP and SNF VBP Programs 
to account for the continued effects of the PHE on measures in 2021. 
Additionally, amending the HHA baseline year (and defining this term) 
for HHAs certified prior to 2022 starting in the CY 2023 performance 
year as well as changing the Model baseline year (and defining this 
term) to CY 2022 starting in the CY 2023 performance year allows 
eligible HHAs to be scored on measure data that is more current and is 
intended to compare HHAs to a base year that is 2 years after the peak 
of the pandemic.
4. Medicare Coverage of Home Infusion Therapy
    Section 1834(u)(1) of the Act, as added by section 5012 of the 21st 
Century Cures Act, requires the Secretary to establish a home infusion 
therapy services payment system under Medicare. This payment system 
requires a single payment to be made to a qualified home infusion 
therapy supplier for items and services furnished by a qualified home 
infusion therapy supplier in coordination with the furnishing of home 
infusion drugs. Section 1834(u)(1)(A)(ii) of the Act states that a unit 
of single payment is for each infusion drug administration calendar day 
in the individual's home. The Secretary shall, as appropriate, 
establish single payment amounts for types of infusion therapy, 
including to consider variation in utilization of nursing services by 
therapy type. Section 1834(u)(1)(A)(iii) of the Act provides a 
limitation to the single payment amount, requiring that it shall not 
exceed the amount determined under the Physician Fee Schedule (under 
section 1848 of the Act) for infusion therapy services furnished in a

[[Page 37677]]

calendar day if furnished in a physician office setting, except such 
single payment shall not reflect more than 5 hours of infusion for a 
particular therapy in a calendar day. Section 1834(u)(1)(B)(i) of the 
Act requires that the single payment amount be adjusted by a geographic 
wage index. Finally, section 1834(u)(1)(C) of the Act allows for 
discretionary adjustments which may include outlier payments and other 
factors as deemed appropriate by the Secretary, and are required to be 
made in a budget neutral manner. Section 1834(u)(3) of the Act 
specifies that annual updates to the single payment are required to be 
made beginning January 1, 2022, by increasing the single payment amount 
by the percentage increase in the CPI-U for all urban consumers for the 
12 month period ending with June of the preceding year, reduced by the 
productivity adjustment. The unit of single payment for each infusion 
drug administration calendar day, including the required adjustments 
and the annual update, cannot exceed the amount determined under the 
fee schedule under section 1848 of the Act for infusion therapy 
services if furnished in a physician's office, and the single payment 
amount cannot reflect more than 5 hours of infusion for a particular 
therapy per calendar day. Finally, Division N, section 101 of CAA 2021 
amended section 1848(t)(1) of the Act and modified the CY 2021 PFS 
rates by providing a 3.75 percent increase in PFS payments only for CY 
2021.

B. Overall Impact

    We have examined the impacts of this rule as required by Executive 
Order 12866 on Regulatory Planning and Review (September 30, 1993), 
Executive Order 13563 on Improving Regulation and Regulatory Review 
(January 18, 2011), the Regulatory Flexibility Act (RFA) (September 19, 
1980, Pub. L. 96 354), section 1102(b) of the Act, section 202 of the 
Unfunded Mandates Reform Act of 1995 (March 22, 1995; Pub. L. 104-4), 
Executive Order 13132 on Federalism (August 4, 1999), and the 
Congressional Review Act (5 U.S.C. 804(2))
    Executive Orders 12866 and 13563 direct agencies to assess all 
costs and benefits of available regulatory alternatives and, if 
regulation is necessary, to select regulatory approaches that maximize 
net benefits (including potential economic, environmental, public 
health and safety effects, distributive impacts, and equity). Section 
3(f) of Executive Order 12866 defines a ``significant regulatory 
action'' as an action that is likely to result in a rule: (1) having an 
annual effect on the economy of $100 million or more in any 1 year, or 
adversely and materially affecting a sector of the economy, 
productivity, competition, jobs, the environment, public health or 
safety, or state, local or tribal governments or communities (also 
referred to as ``economically significant''); (2) creating a serious 
inconsistency or otherwise interfering with an action taken or planned 
by another agency; (3) materially altering the budgetary impacts of 
entitlement grants, user fees, or loan programs or the rights and 
obligations of recipients thereof; or (4) raising novel legal or policy 
issues arising out of legal mandates, the President's priorities, or 
the principles set forth in the Executive order. Therefore, we estimate 
that this rule is ``economically significant'' as measured by the $100 
million threshold, and hence also a major rule under the Congressional 
Review Act. Accordingly, we have prepared a Regulatory Impact Analysis 
that presents our best estimate of the costs and benefits of this rule.

C. Detailed Economic Analysis

    This rule proposes updates to Medicare payments under the HH PPS 
for CY 2023. The net transfer impact related to the changes in payments 
under the HH PPS for CY 2023 is estimated to be -$810 million (-4.2 
percent). The $810 million decrease in estimated payments for CY 2023 
reflects the effects of the proposed CY 2023 home health payment update 
percentage of 2.9 percent ($560 million increase), an estimated 6.9 
percent decrease that reflects the effects of the permanent behavioral 
adjustment ($1.33 billion decrease) and an estimated 0.2 percent 
decrease that reflects the effects of an updated FDL ($40 million 
decrease).
    We use the latest data and analysis available, however, we do not 
adjust for future changes in such variables as number of visits or 
case-mix. This analysis incorporates the latest estimates of growth in 
service use and payments under the Medicare home health benefit, based 
primarily on Medicare claims data for periods that ended on or before 
December 31, 2021. We note that certain events may combine to limit the 
scope or accuracy of our impact analysis, because such an analysis is 
future-oriented and, thus, susceptible to errors resulting from other 
changes in the impact time period assessed. Some examples of such 
possible events are newly-legislated general Medicare program funding 
changes made by the Congress or changes specifically related to HHAs. 
In addition, changes to the Medicare program may continue to be made as 
a result of new statutory provisions. Although these changes may not be 
specific to the HH PPS, the nature of the Medicare program is such that 
the changes may interact, and the complexity of the interaction of 
these changes could make it difficult to predict accurately the full 
scope of the impact upon HHAs.
    Table F5 represents how HHA revenues are likely to be affected by 
the finalized policy changes for CY 2023. For this analysis, we used an 
analytic file with linked CY 2021 OASIS assessments and home health 
claims data for dates of service that ended on or before December 31, 
2021. The first column of Table F5 classifies HHAs according to a 
number of characteristics including provider type, geographic region, 
and urban and rural locations. The second column shows the number of 
facilities in the impact analysis. The third column shows the payment 
effects of the permanent behavioral adjustment on all payments. The 
fourth column shows the payment effects of the recalibration of the 
case-mix weights offset by the case-mix weights budget neutrality 
factor. The fifth column shows the payment effects of updating to the 
CY 2023 wage index with a 5-percent cap on wage index decreases. The 
sixth column shows the payment effects of the final CY 2023 home health 
payment update percentage. The seventh column shows the payment effects 
of the new FDL, and the last column shows the combined effects of all 
the finalized provisions.
    Overall, it is projected that aggregate payments in CY 2023 would 
decrease by 4.2 percent which reflects the 6.9 percent decrease from 
the permanent behavioral adjustment, the 2.9 payment update percentage 
increase, and the 0.2 percent decrease from increasing the FDL. As 
illustrated in Table F5, the combined effects of all of the changes 
vary by specific types of providers and by location. We note that some 
individual HHAs within the same group may experience different impacts 
on payments than others due to the distributional impact of the CY 2023 
wage index, the percentage of total HH PPS payments that were subject 
to the LUPA or paid as outlier payments, and the degree of Medicare 
utilization.
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BILLING CODE 4120-01-C
2. Impacts for the HH QRP for CY 2023
    Failure to submit HH QRP data required under section 
1895(b)(3)(B)(v) of the Act with respect to a program year will result 
in the reduction of the annual home health market basket percentage 
increase otherwise applicable to an HHA for the corresponding calendar 
year by 2 percentage points. For the CY 2022 program year, 1,169 of the 
11,128 active Medicare-certified HHAs, or approximately 10.4 percent, 
did not receive the full annual percentage increase because they did 
not meet assessment submission requirements. The 1,169 HHAs that did 
not satisfy the reporting requirements of the HH QRP for the CY 2022 
program year represent $437 million in home health claims payment 
dollars during the reporting period out of a total $17.3 billion for 
all HHAs.
    As discussed in section III. of this proposed rule, we are 
proposing to end the temporary suspension of non-Medicare/Medicaid data 
under section 704 of the Medicare Prescription Drug, Improvement, and 
Modernization Act of 2003 and, in accordance with section 
1895(b)(3)(B)(v) of the Act, to require HHAs to report all-payer OASIS 
data for purposes of the HH QRP, beginning with the CY 2025 program 
year.
    Section III. of this proposed rule provides a detailed description 
of the net increase in burdens associated with these proposed changes. 
We are proposing that HHAs would be required to begin reporting all-
payer OASIS data beginning with January 1, 2024, discharges. The cost 
impact of this proposal is estimated to be a net increase of 
$267,157,680.3 in annualized cost to HHAs, discounted at 7 percent 
relative to year 2020, over a perpetual time horizon beginning in CY 
2025. We described the estimated burden and cost reductions for these 
measures in section V1V1.B.1. of this proposed rule. In summary, the 
submission of data on non-Medicare/Medicaid patients for the HH QRP is 
estimated to increase the burden on HHAs to $23,529.82 per HHA 
annually, or $267,157,680.3 for all HHAs annually.
3. Impacts for the Expanded HHVBP Model
    In the CY 2022 HHPPS final rule (86 FR 62402 through 62410), we 
estimated that the expanded HHVBP Model would generate a total 
projected 5-year gross FFS savings, CYs 2023 through 2027, of 
$3,376,000,000. The proposed changes to the baseline years in this 
proposed rule will not change those estimates because they do not 
change the number of HHAs in the Model or the payment methodology.
4. Impact of the CY 2023 Payment for Home Infusion Therapy Services
    There are no new proposals in this rule related to payments for 
home infusion therapy services in CY 2023. The CY 2023 home infusion 
therapy service payments will be updated by the CPI-U reduced by the 
productivity adjustment and geographically adjusted in a budget neutral 
manner using the GAF standardization factor. The CY 2023 final GAF 
values (and the CPI-U as of June 2022) were not available at the time 
of rulemaking, therefore, we are unable to estimate the impact of these 
adjustments on the CY 2023 HIT service payment amounts compared to the 
CY 2022 HIT service payment amounts.

D. Regulatory Review Cost Estimation

    If regulations impose administrative costs on private entities, 
such as the time needed to read and interpret this proposed or final 
rule, we should estimate the cost associated with regulatory review. 
Due to the uncertainty involved with accurately quantifying the number 
of entities that will review the rule, we assume that the total number 
of unique commenters on last year's proposed rule will be the number of 
reviewers of this proposed rule. We acknowledge that this assumption 
may understate or overstate the costs of reviewing this rule. It is 
possible that not all commenters reviewed last year's rule in detail, 
and it is also possible that some reviewers chose not to comment on the 
proposed rule. For these reasons we thought that the number of past 
commenters would be a fair estimate of the number of reviewers of this 
rule. We seek comments on the approach used in estimating the number of 
entities reviewing this proposed rule.
    We also recognize that different types of entities are in many 
cases affected by mutually exclusive sections of this proposed rule, 
and therefore for the purposes of our estimate we assume that each 
reviewer reads approximately 50 percent of the rule. We seek comments 
on this assumption. Using the wage information from the BLS for medical 
and health service managers (Code 11-9111), we estimate that the cost 
of reviewing this rule is $115.22 per hour, including overhead and 
fringe benefits https://www.bls.gov/oes/current/oes_nat.htm. Assuming 
an average reading speed, we estimate that it would take approximately 
2.32 hours for the staff to review half of this proposed rule. For each 
entity that reviews the rule, the estimated cost is $267 (2.32 hours x 
$115.22). Therefore, we estimate that the total cost of reviewing this 
regulation is $ 55,269 ($267 x 207) [207

[[Page 37680]]

is the number of estimated reviewers, which is based on the total 
number of unique commenters from last year's proposed rule].

E. Alternatives Considered

1. HH PPS
    For the CY 2023 HH PPS proposed rule, we considered alternatives to 
the provisions articulated in section II.B.2. of this proposed rule. 
Specifically, we considered other potential methodologies to determine 
the difference between assumed versus actual behavior change on 
estimated aggregate expenditures in response to the comment 
solicitation in the CY 2022 HH PPS proposed rule (86 FR 35892). 
However, most of the alternate methodologies controlled for certain 
actual behavior changes (for example, the reduction in therapy visits) 
and this is not in alignment with what the statute requires at section 
1895(b)(3)(D)(i) of the Act where we must examine actual behavior 
change. Therefore, any method that would control for an actual behavior 
change would be counter to what is required by law. Additionally, we 
considered alternative approaches to the implementation of the 
permanent and temporary behavior assumption adjustments. As described 
in section II.B.2. of this rule, to help prevent future over or 
underpayments, we calculated a permanent prospective adjustment by 
determining what the 30-day base payment amount should have been in CYs 
2020 and 2021 in order to achieve the same estimated aggregate 
expenditures as obtained from the simulated 60-day episodes. One 
alternative to the proposed -7.69 percent permanent payment adjustment 
included a phase-in approach, where we could reduce the permanent 
adjustment, by spreading out the adjustment over a period of a few 
years. Another alternative would be to delay the permanent adjustment 
to a future year. However, we believe that a phase-in approach or delay 
for the permanent adjustment would not be appropriate, as phasing in or 
delaying the permanent adjustment would further impact budget 
neutrality and likely lead to a compounding effect creating the need 
for a larger reduction to the payment rate in future years.
    Finally, we considered proposing to implement the one-time 
temporary adjustment to reconcile retrospective overpayments in CYs 
2020 and 2021. We note that MedPAC's March 2022 Report to Congress \78\ 
has found that in 2020, the aggregate Medicare margin for freestanding 
HHAs was 20.2 percent, a nearly 5 percentage point increase from the 
previous year. However, as stated previously in this rule, we believe 
that implementing both the permanent and temporary adjustments to the 
CY 2023 payment rate may adversely affect HHAs. Likewise, section 
1895(b)(3)(D)(iii) of the Act gives CMS the authority to make any 
temporary adjustment in a time and manner appropriate though notice and 
comment rulemaking. Therefore, we believe it is best to propose only 
the implementation of the permanent decrease of 7.69 percent to the CY 
2023 base payment rate, while soliciting comments on the best approach 
to implement the temporary adjustment for overpayments to HHAs for CYs 
2020 and 2021.
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    \78\ Home Health Services. MedPAC Report to Congress- 2022. 
https://www.medpac.gov/wp-content/uploads/2022/03/Mar22_MedPAC_ReportToCongress_Ch8_SEC.pdf.
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2. HHQRP
    We did not consider any alternatives in this proposed rule.
3. Expanded HHVBP Model
    We discuss the alternative we considered to the proposed change to 
the HHA baseline year for each applicable measure in the expanded HHVBP 
Model in section IV.B.2.b. of this proposed rule.
4. Home Infusion Therapy
    We did not consider any alternatives in this proposed rule.

F. Accounting Statements and Tables

1. HH PPS
    As required by OMB Circular A-4 (available at https://www.whitehouse.gov/wp-content/uploads/legacy_drupal_files/omb/circulars/A4/a-4.pdf), in Table F7, we have prepared an accounting 
statement showing the classification of the transfers and benefits 
associated with the CY 2023 HH PPS provisions of this rule.
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2. HHQRP
    As required by OMB Circular A-4 (available at https://www.whitehouse.gov/sites/whitehouse.gov/files/omb/circulars/A4/a-4.pdf), in Table F8, we have prepared an accounting statement showing 
the classification of the expenditures associated with this proposed 
rule as they relate to HHAs. Table F8 provides our best estimate of the 
increase in burden for OASIS submission.
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[[Page 37681]]


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.
[GRAPHIC] [TIFF OMITTED] TP23JN22.068

G. Regulatory Flexibility Act (RFA)

    The RFA requires agencies to analyze options for regulatory relief 
of small entities, if a rule has a significant impact on a substantial 
number of small entities. For purposes of the RFA, small entities 
include small businesses, nonprofit organizations, and small 
governmental jurisdictions. In addition, HHAs and home infusion therapy 
suppliers are small entities, as that is the term used in the RFA. 
Individuals and States are not included in the definition of a small 
entity.
    The North American Industry Classification System (NAICS) was 
adopted in 1997 and is the current standard used by the Federal 
statistical agencies related to the U.S. business economy. We utilized 
the NAICS U.S. industry title ``Home Health Care Services'' and 
corresponding NAICS code 621610 in determining impacts for small 
entities. The NAICS code 621610 has a size standard of $16.5 million 
\79\ and approximately 96 percent of HHAs and home infusion therapy 
suppliers are considered small entities. Table F10 shows the number of 
firms, revenue, and estimated impact per home health care service 
category.
[GRAPHIC] [TIFF OMITTED] TP23JN22.069

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

[[Page 37682]]

1895(b)(3)(D)(i) of the Act requires CMS to annually determine the 
impact of differences between the assumed behavior changes finalized in 
the CY 2019 HH PPS final rule (83 FR 56455) and actual behavior changes 
on estimated aggregate expenditures under the HH PPS with respect to 
years beginning with 2020 and ending with 2026. Additionally, section 
1895(b)(3)(D)(ii) and (iii) of the Act requires that CMS make permanent 
and temporary adjustments to the payment rate to offset for such 
increases or decreases in estimated aggregate expenditures through 
notice and comment rulemaking. Since the permanent and temporary 
adjustments are mandated by statute, we cannot offer HHAs relief from 
these adjustments. While we are not proposing to implement the 
temporary payment adjustments in CY 2023, we believe that the -7.69 
percent permanent payment adjustment, described in section II.B.2.c. of 
this proposed rule, is necessary to offset the increase in estimated 
aggregate expenditures for CYs 2020 and 2021 based on the impact of the 
differences between assumed behavior changes and actual behavior 
changes. In the alternatives considered previously, we noted that we 
considered a phase-in approach to the permanent adjustment. However, we 
believe that a phase-in of the permanent adjustment is not appropriate 
for CY 2023 because it would further impact budget neutrality and 
likely lead to a compounding effect creating the need for a larger 
reduction to the payment rate in future years. As mentioned previously, 
we recognize that implementing both the permanent and temporary 
adjustments to the CY 2023 payment rate may adversely affect HHAs, 
including small entities. Therefore, we are soliciting comments on the 
best approach to collect the temporary payment adjustment of $2.0 
billion for CYs 2020 and 2021. We solicit comments on the overall HH 
PPS RFA analysis.
    Guidance issued by HHS interpreting the Regulatory Flexibility Act 
considers the effects economically `significant' only if greater than 5 
percent of providers reach a threshold of 3- to 5-percent or more of 
total revenue or total costs. Among the over 7,500 HHAs that are 
estimated to qualify to compete in the expanded HHVBP Model, we 
estimate that the percent payment adjustment resulting from this rule 
would be larger than 3 percent, in magnitude, for about 28 percent of 
competing HHAs (estimated by applying the proposed 5-percent maximum 
payment adjustment under the expanded Model to CY 2019 data). As a 
result, more than the RFA threshold of 5-percent of HHA providers 
nationally would be significantly impacted. We refer readers to Tables 
43 and 44 in the CY 2022 HH PPS final rule (86 FR 62407 through 62410) 
for our analysis of payment adjustment distributions by State, HHA 
characteristics, HHA size and percentiles.
    Thus, the Secretary has certified that this proposed rule would 
have a significant economic impact on a substantial number of small 
entities. Though the RFA requires consideration of alternatives to 
avoid economic impacts on small entities, the intent of the rule, 
itself, is to encourage quality improvement by HHAs through the use of 
economic incentives. As a result, alternatives to mitigate the payment 
reductions would be contrary to the intent of the rule, which is to 
test the effect on quality and costs of care of applying payment 
adjustments based on HHAs' performance on quality measures.
    In addition, section 1102(b) of the Act requires us to prepare a 
Regulatory Impact Analysis (RIA) if a rule may have a significant 
impact on the operations of a substantial number of small rural 
hospitals. This analysis must conform to the provisions of section 603 
of RFA. For purposes of section 1102(b) of the Act, we define a small 
rural hospital as a hospital that is located outside of a metropolitan 
statistical area and has fewer than 100 beds. This rule is not 
applicable to hospitals. Therefore, the Secretary has certified that 
this proposed rule would not have a significant economic impact on the 
operations of small rural hospitals.

I. Unfunded Mandates Reform Act (UMRA)

    Section 202 of UMRA of 1995 UMRA also requires that agencies assess 
anticipated costs and benefits before issuing any rule whose mandates 
require spending in any 1 year of $100 million in 1995 dollars, updated 
annually for inflation. In 2022, that threshold is approximately $165 
million. This proposed rule would not impose a mandate that will result 
in the expenditure by State, local, and Tribal Governments, in the 
aggregate, or by the private sector, of more than $165 million in any 
one year.

J. Federalism

    Executive Order 13132 establishes certain requirements that an 
agency must meet when it promulgates a proposed rule (and subsequent 
final rule) that imposes substantial direct requirement costs on State 
and local governments, preempts State law, or otherwise has federalism 
implications. We have reviewed this proposed rule under these criteria 
of Executive Order 13132, and have determined that it would not impose 
substantial direct costs on State or local governments.
    Chiquita Brooks-LaSure, Administrator of the Centers for Medicare & 
Medicaid Services, approved this document on June 10, 2022.

List of Subjects in 42 CFR Part 484

    Health facilities, Health professions, Medicare, and Reporting and 
recordkeeping requirements.

    For the reasons set forth in the preamble, the Centers for Medicare 
& Medicaid Services proposes to amend 42 CFR chapter IV as follows:

PART 484--HOME HEALTH SERVICES

0
1. The authority citation for part 484 continues to read as follows:

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

0
2. Section 484.220 is amended by adding paragraph (c) to read as 
follows:


Sec.  484.220  Calculation of the case-mix and wage area adjusted 
prospective payment rates.

* * * * *
    (c) Beginning on January 1, 2023, CMS applies a cap on decreases to 
the home health wage index such that the wage index applied to a 
geographic area is not less than 95 percent of the wage index applied 
to that geographic area in the prior calendar year. The 5-percent cap 
on negative wage index changes is implemented in a budget neutral 
manner through the use of wage index budget neutrality factors.
0
3. Section 484.245 is amended--
0
a. In paragraph (b)(1)(i) by removing the reference ``sections 
1899B(c)(1) and 1899B(d)(1) of the Act'' and adding in its place the 
reference ``sections 1895(b)(3)(B)(v)(II), 1899B(c)(1), and 1899B(d)(1) 
of the Act'';
0
b. In paragraph (b)(1)(iii) by removing the first sentence; and
0
c. By adding paragraph (b)(3).
    The addition reads as follows:


Sec.  484.245  Requirements under the Home Health Quality Reporting 
Program (HH QRP).

* * * * *
    (b) * * *
    (3) CMS may remove a quality measure from the HH QRP based on one 
or more of the following factors:
    (i) Measure performance among HHAs is so high and unvarying that 
meaningful distinctions in improvements in performance can no longer be 
made.

[[Page 37683]]

    (ii) Performance or improvement on a measure does not result in 
better patient outcomes.
    (iii) A measure does not align with current clinical guidelines or 
practice.
    (iv) The availability of a more broadly applicable (across 
settings, populations, or conditions) measure for the particular topic.
    (v) The availability of a measure that is more proximal in time to 
desired patient outcomes for the particular topic.
    (vi) The availability of a measure that is more strongly associated 
with desired patient outcomes for the particular topic.
    (vii) Collection or public reporting of a measure leads to negative 
unintended consequences other than patient harm.
    (viii) The costs associated with a measure outweigh the benefit of 
its continued use in the program.
* * * * *
0
4. Section 484.345 is amended--
0
a. In the definition of ``Achievement threshold'' by removing the 
phrase ``during a baseline year'' and adding in its place the phrase 
``during a Model baseline year'';
0
b. By removing the definition of ``Baseline year'';
0
c. In the definition of ``Benchmark'' by removing the phrase ``during 
the baseline year'' and adding in its place the phrase ``during the 
Model baseline year'';
0
d. By adding the definition of ``HHA baseline year'' in alphabetical 
order;
0
e. In the definition of ``Improvement threshold'' by removing the 
phrase ``during the baseline year'' and adding in its place the phrase 
``during the HHA baseline year''; and
0
f. By adding the definition of ``Model baseline year'' in alphabetical 
order.
    The additions read as follows:


Sec.  484.345  Definitions.

* * * * *
    HHA baseline year means the calendar year used to determine the 
improvement threshold for each measure for each individual competing 
HHA.
* * * * *
    Model baseline year means the calendar year used to determine the 
benchmark and achievement threshold for each measure for all competing 
HHAs.
* * * * *
0
5. Section 484.350 is amended by revising paragraph (b) and adding 
paragraph (c) to read as follows:
* * * * *
    (b) New HHAs. A new HHA is certified by Medicare on or after 
January 1, 2022. For new HHAs, the following apply:
    (1) The HHA baseline year is the first full calendar year of 
services beginning after the date of Medicare certification.
    (2) The first performance year is the first full calendar year 
following the HHA baseline year.
    (c) Existing HHAs. An existing HHA is certified by Medicare before 
January 1, 2022 and the HHA baseline year is calendar year (CY) 2022.


Sec.  484.370  [Amended]

0
6. Section 484.370 is amended in paragraph (a) by removing the phrase 
``Model for the baseline year, and CMS'' and adding in its place the 
phrase ``Model, and CMS''.

    Dated: June 16, 2022.
Xavier Becerra,
Secretary, Department of Health and Human Services.
[FR Doc. 2022-13376 Filed 6-17-22; 4:15 pm]
BILLING CODE 4120-01-P