[Federal Register Volume 86, Number 129 (Friday, July 9, 2021)]
[Proposed Rules]
[Pages 36322-36437]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2021-14250]
[[Page 36321]]
Vol. 86
Friday,
No. 129
July 9, 2021
Part II
Department of Health and Human Services
-----------------------------------------------------------------------
Centers for Medicare & Medicaid Services
-----------------------------------------------------------------------
42 CFR Parts 413 and 512
Medicare Program; End-Stage Renal Disease Prospective Payment System,
Payment for Renal Dialysis Services Furnished to Individuals With Acute
Kidney Injury, End-Stage Renal Disease Quality Incentive Program, and
End-Stage Renal Disease Treatment Choices Model; Proposed Rule
Federal Register / Vol. 86 , No. 129 / Friday, July 9, 2021 /
Proposed Rules
[[Page 36322]]
-----------------------------------------------------------------------
DEPARTMENT OF HEALTH AND HUMAN SERVICES
Centers for Medicare & Medicaid Services
42 CFR Parts 413 and 512
[CMS-1749-P]
RIN 0938-AU39
Medicare Program; End-Stage Renal Disease Prospective Payment
System, Payment for Renal Dialysis Services Furnished to Individuals
With Acute Kidney Injury, End-Stage Renal Disease Quality Incentive
Program, and End-Stage Renal Disease Treatment Choices Model
AGENCY: Centers for Medicare & Medicaid Services (CMS), HHS.
ACTION: Proposed rule.
-----------------------------------------------------------------------
SUMMARY: This proposed rule would update the End-Stage Renal Disease
(ESRD) Prospective Payment System (PPS) for calendar year (CY) 2022.
This rulemaking also proposes to update the payment rate for renal
dialysis services furnished by an ESRD facility to individuals with
acute kidney injury (AKI). In addition, this rulemaking proposes to
update requirements for the ESRD Quality Incentive Program (QIP),
including a proposed measure suppression policy for the duration of the
coronavirus disease 2019 (COVID-19) public health emergency (PHE) and
as well as proposals to suppress individual ESRD QIP measures under
that proposed measure suppression policy. This proposed rule also
announces an extension of time for facilities to report September
through December 2020 ESRD QIP data under our Extraordinary
Circumstances Exception (ECE) policy due to CMS operational issues, and
proposes to not score facilities or reduce payment to any facility in
PY 2022. In addition, this proposed rule includes requests for
information on topics that are relevant to the ESRD QIP. Further, this
rule also proposes changes to the ESRD Treatment Choices (ETC) Model,
which is a mandatory payment model that is focused on encouraging
greater use of home dialysis and kidney transplants, to reduce Medicare
expenditures while preserving or enhancing the quality of care
furnished to Medicare beneficiaries. Finally, this proposed rule
includes several requests for information to inform payment reform
under the ESRD PPS.
DATES: To be assured consideration, comments must be submitted at one
of the addresses provided below, by August 31, 2021.
ADDRESSES: In commenting, please refer to file code CMS-1749-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 http://www.regulations.gov. Follow the ``Submit a
comment'' instructions.
2. By regular mail. You may mail written comments to the following
address ONLY: Centers for Medicare & Medicaid Services, Department of
Health and Human Services, Attention: CMS-1749-P, P.O. Box 8010,
Baltimore, MD 21244-8010.
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-1749-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:
[email protected], for issues related to the ESRD PPS and
coverage and payment for renal dialysis services furnished to
individuals with AKI.
[email protected], for issues related to the
Transitional Add-On Payment Adjustment for New and Innovative Equipment
and Supplies (TPNIES).
Delia Houseal, (410) 786-2724, for issues related to the ESRD QIP.
[email protected], for issues related to the ESRD Treatment
Choices (ETC) Model.
SUPPLEMENTARY INFORMATION:
Inspection of Public Comments: All comments received before the
close of the comment period are available for viewing by the public,
including any personally identifiable or confidential business
information that is included in a comment. We post all comments
received before the close of the comment period on the following
website as soon as possible after they have been received: http://www.regulations.gov. Follow the search instructions on that website to
view public comments. CMS will not post on Regulations.gov public
comments that make threats to individuals or institutions or suggest
that the individual will take actions to harm the individual. CMS
continues to encourage individuals not to submit duplicative comments.
We will post acceptable comments from multiple unique commenters even
if the content is identical or nearly identical to other comments.
Current Procedural Terminology (CPT) Copyright Notice: Throughout
this proposed rule, we use CPT[supreg] codes and descriptions to refer
to a variety of services. We note that CPT[supreg] codes and
descriptions are copyright 2020 American Medical Association (AMA). All
Rights Reserved. CPT[supreg] is a registered trademark of the AMA.
Applicable Federal Acquisition Regulations (FAR) and Defense Federal
Acquisition Regulations (DFAR) apply.
Table of Contents
To assist readers in referencing sections contained in this
preamble, we are providing a Table of Contents.
I. Executive Summary
A. Purpose
B. Summary of the Major Provisions
C. Summary of Cost and Benefits
II. Calendar Year (CY) 2022 End-Stage Renal Disease (ESRD)
Prospective Payment System (PPS)
A. Background
B. Provisions of the Proposed Rule
C. Proposed Transitional Add-On Payment Adjustment for New and
Innovative Equipment and Supplies (TPNIES) for CY 2022 Payment
III. Calendar Year (CY) 2022 Payment for Renal Dialysis Services
Furnished to Individuals With Acute Kidney Injury (AKI)
A. Background
B. Proposed Annual Payment Rate Update for CY 2022
IV. End-Stage Renal Disease Quality Incentive Program (ESRD QIP)
A. Background
B. Extraordinary Circumstances Exception (ECE) Previously
Granted for the ESRD QIP and Notification of ECE Due to ESRD Quality
Reporting System Issues
C. Proposed Flexibilities for the ESRD QIP in Response to the
COVID-19 PHE
D. Proposed Special Scoring Methodology and Payment Policy for
the PY 2022 ESRD QIP
E. Proposed Updates to Requirements Beginning With the PY 2024
ESRD QIP
F. Updates for the PY 2025 ESRD QIP
G. Requests for Information (RFIs) on Topics Relevant to ESRD
QIP
V. End-Stage Renal Disease Treatment Choices (ETC) Model
A. Background
B. Provisions of the Proposed Rule
C. Requests for Information (RFIs) on Topics Relevant to ETC
Model
VI. Requests for Information
A. Informing Payment Reform Under the ESRD PPS
[[Page 36323]]
B. Technical Expert Panels (TEPs)
C. Calculation of the Low-Volume Payment Adjustment (LVPA)
D. Calculation of the Case-Mix Adjustments
E. Calculation of the Outlier Payment Adjustment
F. Calculation of the Pediatric Dialysis Payment Adjustment
G. Modifying the ESRD PPS and Hospital Cost Reports
H. Modifying the Pediatric Cost Report
I. Modifying Site of Services Provided to Medicare Beneficiaries
with Acute Kidney Injury (AKI)
VII. Collection of Information Requirements
A. Legislative Requirement for Solicitation of Comments
B. Requirements in Regulation Text
C. Additional Information Collection Requirements
VIII. Response to Comments
IX. Economic Analyses
A. Regulatory Impact Analysis
B. Detailed Economic Analysis
C. Accounting Statement
D. Regulatory Flexibility Act Analysis (RFA)
E. Unfunded Mandates Reform Act Analysis (UMRA)
F. Federalism
G. Congressional Review Act
X. Files Available to the Public via the Internet
Regulations Text
I. Executive Summary
A. Purpose
1. End-Stage Renal Disease (ESRD) Prospective Payment System (PPS)
On January 1, 2011, we implemented the End-Stage Renal Disease
(ESRD) Prospective Payment System (PPS), a case-mix adjusted, bundled
PPS for renal dialysis services furnished by ESRD facilities as
required by section 1881(b)(14) of the Social Security Act (the Act),
as added by section 153(b) of the Medicare Improvements for Patients
and Providers Act of 2008 (MIPPA) (Pub. L. 110-275). Section
1881(b)(14)(F) of the Act, as added by section 153(b) of MIPPA, and
amended by section 3401(h) of the Patient Protection and Affordable
Care Act (the Affordable Care Act) (Pub. L. 111-148), established that
beginning calendar year (CY) 2012, and each subsequent year, the
Secretary of the Department of Health and Human Services (the
Secretary) shall annually increase payment amounts by an ESRD market
basket increase factor, reduced by the productivity adjustment
described in section 1886(b)(3)(B)(xi)(II) of the Act. This rule
proposes updates to the ESRD PPS for CY 2022.
2. Coverage and Payment for Renal Dialysis Services Furnished to
Individuals With Acute Kidney Injury (AKI)
On June 29, 2015, the President signed the Trade Preferences
Extension Act of 2015 (TPEA) (Pub. L. 114-27). Section 808(a) of the
TPEA amended section 1861(s)(2)(F) of the Act to provide coverage for
renal dialysis services furnished on or after January 1, 2017, by a
renal dialysis facility or a provider of services paid under section
1881(b)(14) of the Act to an individual with acute kidney injury (AKI).
Section 808(b) of the TPEA amended section 1834 of the Act by adding a
new subsection (r) that provides for payment for renal dialysis
services furnished by renal dialysis facilities or providers of
services paid under section 1881(b)(14) of the Act to individuals with
AKI at the ESRD PPS base rate beginning January 1, 2017. This rule
proposes to update the AKI payment rate for CY 2022.
3. End-Stage Renal Disease Quality Incentive Program (ESRD QIP)
The End-Stage Renal Disease Quality Incentive Program (ESRD QIP) is
authorized by section 1881(h) of the Act. The Program fosters improved
patient outcomes by establishing incentives for dialysis facilities to
meet or exceed performance standards established by the Centers for
Medicare & Medicaid Services (CMS). This rule proposes to suppress the
use of certain ESRD QIP measure data for scoring and payment adjustment
purposes in the PY 2022 ESRD QIP because we have determined that
circumstances caused by the Public Health Emergency (PHE) for the
coronavirus disease 2019 (COVID-19) pandemic have significantly
affected the validity and reliability of the measures and resulting
performance scores, as well as special scoring and payment policies for
PY 2022. We are also announcing an extension of time for facilities to
report September-December 2020 ESRD QIP data under our Extraordinary
Circumstances Exception (ECE) policy due to CMS operational issues.
Beginning with the PY 2024 ESRD QIP, we are proposing to update the
specifications for the SHR clinical measure. We are also proposing for
the PY 2024 ESRD QIP to adopt CY 2019 as the baseline period for
purposes of calculating the achievement thresholds, benchmarks, and
performance standard values. Although no new requirements are proposed
for the PY 2025 ESRD QIP, this proposed rule includes policies that
would apply in PY 2025. This proposed rule also includes requests for
information on several important topics, including strategies that CMS
can use to address the gap in existing health inequities, the addition
of COVID-19 vaccination measures in future rulemaking, and the use of
digital quality measurement.
4. End-Stage Renal Disease Treatment Choices (ETC) Model
This rulemaking proposes to implement changes to the End-Stage
Renal Disease (ESRD) Treatment Choices Model (ETC) Model, a mandatory
Medicare payment model tested under the authority of section 1115A of
the Act. The ETC Model is operated by the Center for Medicare and
Medicaid Innovation (Innovation Center), and tests the use of payment
adjustments to encourage greater utilization of home dialysis and
kidney transplants, in order to preserve or enhance the quality of care
furnished to Medicare beneficiaries while reducing Medicare
expenditures. The ETC Model includes ESRD facilities and certain
clinicians caring for beneficiaries with ESRD--or Managing Clinicians--
located in Selected Geographic Areas as participants.
The ETC Model was finalized as part of a final rule published in
the Federal Register on September 29, 2020, titled, ``Medicare Program;
Specialty Care Models to Improve Quality of Care and Reduce
Expenditures'' (85 FR 61114), referred to herein as the ``Specialty
Care Models final rule.'' The ETC Model is designed to test the
effectiveness of adjusting certain Medicare payments to ETC
Participants (ESRD facilities and Managing Clinicians--clinicians who
furnish and bill the Monthly Capitation Payment (MCP) for managing ESRD
Beneficiaries--who have been selected to participate in the ETC Model)
to encourage greater utilization of home dialysis and kidney
transplantation, support beneficiary modality choice, reduce Medicare
expenditures, and preserve or enhance the quality of care. In the
Specialty Care Models final rule, we established that the ETC Model
adjusts payments for home dialysis and home dialysis-related claims
with claim service dates from January 1, 2021 through December 31, 2023
through the Home Dialysis Payment Adjustment (HDPA). We are assessing
the rates of home dialysis and of kidney transplant waitlisting and
living donor transplantation, among beneficiaries attributed to ETC
Participants during the period beginning January 1, 2021, and ending
June 30, 2026. Based on those rates, we are applying the Performance
Payment Adjustment (PPA) to claims for dialysis and dialysis-
[[Page 36324]]
related services with claim service dates beginning July 1, 2022, and
ending June 30, 2027. We codified these provisions in a new subpart of
the Code of Federal Regulations (CFR) 42 CFR part 512, subpart C.
This rulemaking proposes modifications to the ETC Model, including
changes to the home dialysis rate and transplant rate, the PPA
achievement benchmarking methodology, and the PPA improvement
benchmarking and scoring methodology. We are also proposing to add
processes and requirements for ETC Participants to receive certain data
from CMS and to include certain additional waivers and flexibilities as
part of the ETC Model test. This proposed rule also includes requests
for information regarding the placement of peritoneal dialysis
catheters and the development of a home dialysis beneficiary experience
measure.
B. Summary of the Major Provisions
1. ESRD PPS
Update to the ESRD PPS base rate for CY 2022: The proposed
CY 2022 ESRD PPS base rate is $255.55. This proposed amount reflects
the application of the wage index budget-neutrality adjustment factor
(.999546) and a productivity-adjusted market basket increase of 1.0
percent as required by section 1881(b)(14)(F)(i)(I) of the Act,
equaling $255.55 (($253.13 x .999546) x 1.010 = $255.55).
Annual update to the wage index: We adjust wage indices on
an annual basis using the most current hospital wage data and the
latest core-based statistical area (CBSA) delineations to account for
differing wage levels in areas in which ESRD facilities are located.
For CY 2022, we are proposing to update the wage index values based on
the latest available data and continuing the 2-year transition to the
Office of Management and Budget (OMB) delineations as described in the
September 14, 2018 OMB Bulletin No. 18-04.
Update to the outlier policy: We are proposing to update
the outlier policy using the most current data, as well as update the
outlier services fixed-dollar loss (FDL) amounts for adult and
pediatric patients and Medicare allowable payment (MAP) amounts for
adult and pediatric patients for CY 2022 using CY 2020 claims data.
Based on the use of the latest available data, the proposed FDL amount
for pediatric beneficiaries would decrease from $44.78 to $30.38, and
the MAP amount would decrease from $30.88 to $28.73, as compared to CY
2021 values. For adult beneficiaries, the proposed FDL amount would
decrease from $122.49 to $111.18, and the MAP amount would decrease
from $50.92 to $47.87. The 1.0 percent target for outlier payments was
not achieved in CY 2020. Outlier payments represented approximately 0.6
percent of total payments rather than 1.0 percent.
Update to the offset amount for the transitional add-on
payment adjustment for new and innovative equipment and supplies
(TPNIES) for CY 2022: The proposed CY 2022 average per treatment offset
amount for the transitional add-on payment adjustment for new and
innovative equipment and supplies (TPNIES) for capital-related assets
that are home dialysis machines is $9.41. This proposed offset amount
reflects the application of the productivity-adjusted market basket
increase of 1.0 percent ($9.32 x 1.010 = $9.41).
TPNIES applications received for CY 2022: This proposed
rule presents a summary of the two CY 2022 TPNIES applications that we
received by the February 1, 2021 deadline and our analysis of the
applicants' claims related to substantial clinical improvement (SCI)
and other eligibility criteria for the TPNIES.
2. Payment for Renal Dialysis Services Furnished to Individuals With
AKI
We are proposing to update the AKI payment rate for CY 2022 to
$255.55, which is the same as the base rate proposed under the ESRD PPS
for CY 2022.
3. ESRD QIP
We are announcing an extension of time for facilities to report
September through December 2020 ESRD QIP data under our Extraordinary
Circumstances Exception (ECE) policy due to CMS operational issues. We
are proposing to adopt a measure suppression policy for the duration of
the COVID-19 PHE that would enable us to suppress the use of one or
more measures in the ESRD QIP for scoring and payment adjustment
purposes if we determine that circumstances caused by the COVID-19 PHE
have significantly affected the measures and resulting performance
scores. We are also proposing to suppress the Standardized
Hospitalization Ratio (SHR) clinical measure, the Standardized
Readmission Ratio (SRR) clinical measure, the In-Center Hemodialysis
Consumer Assessment of Healthcare Providers and Systems (ICH CAHPS)
clinical measure, and the Long-Term Catheter Rate clinical measure for
PY 2022 under the proposed measure suppression policy. Finally, we are
proposing to not score or reduce payment to any facility in PY 2022.
Beginning with the PY 2024 ESRD QIP, we are proposing to update the
specifications for the SHR clinical measure. We are also proposing for
the PY 2024 ESRD QIP to adopt CY 2019 as the baseline period for
purposes of calculating the achievement thresholds, benchmarks, and
performance standard values. This proposed rule also announces the
performance standards and payment reductions that would apply for PY
2024. This proposed rule describes several policies continuing for PY
2025, but does not propose any new requirements beginning with the PY
2025 ESRD QIP.
This proposed rule includes requests for public comment on several
important topics, including closing the gap in health equity, adding a
COVID-19 vaccination measure for health care personnel (HCP) and a
COVID-19 vaccination measure for ESRD patients to the ESRD QIP measure
set in future rulemaking, and potential actions and priority areas that
would enable the continued transformation of our quality measurement
enterprise toward greater digital capture of data and use of the Fast
Healthcare Interoperability Resources (FHIR[supreg]) standard.
4. ETC Model
We are proposing to implement the following changes to the ETC
Model beginning for the third Measurement Year (MY3) of the Model,
which begins January 1, 2022.
Beneficiary Attribution for Living Kidney Donor
Transplants: To better reflect the care relationship between
beneficiaries who receive pre-emptive living donor transplants (LDT)
and the Managing Clinicians who provide their care, we propose to
modify the methodology for attributing Pre-emptive LDT Beneficiaries to
Managing Clinicians, such that a Pre-emptive LDT Beneficiary would be
attributed to the Managing Clinician who submitted the most claims for
services furnished to the beneficiary during the 365 days prior to the
transplant date.
Home Dialysis Rate Calculation: To incentivize additional
alternative renal replacement modalities under the ETC Model, we
propose adding nocturnal in-center dialysis to the calculation of the
home dialysis rate for ESRD facilities not owned in whole or in part by
a large dialysis organization (LDO) as well as Managing Clinicians.
Transplant Rate Beneficiary Exclusion: To better align
with common reasons transplant centers do not place patients on the
transplant waitlist, we propose to exclude beneficiaries with a
diagnosis of, and who are receiving
[[Page 36325]]
treatment with chemotherapy or radiation for, vital solid organ cancers
from the calculation of the transplant rate.
Performance Payment Adjustment Achievement Benchmarking
Methodology: When we originally finalized the ETC Model, we stated our
intent to increase achievement benchmarks above rates observed in
Comparison Geographic Areas for future model years. As such, we propose
to increase achievement benchmarks by 10 percent over rates observed in
Comparison Geographic Areas every two MYs, beginning in MY3 (2022). We
also propose to stratify achievement benchmarks based on the proportion
of attributed beneficiaries who are dually-eligible for Medicare and
Medicaid or receive the Low Income Subsidy (LIS) during the MY, in
recognition that beneficiaries with lower socioeconomic status have
lower rates of home dialysis and transplant than those with higher
socioeconomic status.
Performance Payment Adjustment Improvement Benchmarking
and Scoring: In conjunction with our proposal to stratify achievement
benchmarks based on the proportion of beneficiaries who are dual-
eligible or LIS recipients, we propose to introduce the Health Equity
Incentive to the improvement scoring methodology used in calculating
the PPA. CMS expects that the Health Equity Incentive would encourage
ETC Participants to decrease disparities in renal replacement modality
choice among beneficiaries with lower socioeconomic status by rewarding
ETC Participants that demonstrate significant improvement in the home
dialysis rate or transplant rate among their attributed beneficiaries
who are dual-eligible or LIS recipients. We also propose to adjust the
improvement scoring calculation to avoid the scenario where an ETC
Participant cannot receive an improvement score because its home
dialysis rate or transplant rate was zero during the Benchmark Year.
Performance Payment Adjustment Reports and Related Data
Sharing: To ensure that ETC Participants have timely access to ETC
Model reports, we are proposing a process by which CMS would share
certain model data with ETC Participants.
Medicare Waivers: We are proposing an additional
programmatic waiver to provide Managing Clinicians who are ETC
Participants additional flexibility in furnishing the kidney disease
patient education services described in Sec. 410.48: A waiver of
certain telehealth requirements as necessary solely for purposes of
allowing ETC Participants to furnish kidney disease patient education
services via telehealth under the ETC Model.
Kidney Disease Patient Education Services Coinsurance
Waivers: We are proposing to permit Managing Clinicians who are ETC
Participants to reduce or waive the beneficiary coinsurance for kidney
disease patient education services, subject to certain requirements. We
anticipate making the determination that the anti-kickback statute safe
harbor for CMS-sponsored model patient incentives (42 CFR
1001.952(ii)), would be available to protect the reduction or
elimination of coinsurance performed in accordance with our proposed
policy, if finalized.
C. Summary of Costs and Benefits
In section IX.B of this proposed rule, we set forth a detailed
analysis of the impacts that the proposed changes would have on
affected entities and beneficiaries. The impacts include the following:
1. Impacts of the Proposed ESRD PPS
The impact table in section IX.B.1.a of this proposed rule displays
the estimated change in payments to ESRD facilities in CY 2022 compared
to estimated payments in CY 2021. The overall impact of the proposed CY
2022 changes is projected to be a 1.2 percent increase in payments.
Hospital-based ESRD facilities have an estimated 1.3 percent increase
in payments compared with freestanding facilities with an estimated 1.2
percent increase. We estimate that the aggregate ESRD PPS expenditures
would increase by approximately $140 million in CY 2022 compared to CY
2021. This reflects a $120 million increase from the payment rate
update and a $20 million increase due to the updates to the outlier
threshold amounts. Because of the projected 1.2 percent overall payment
increase, we estimate there would be an increase in beneficiary
coinsurance payments of 1.2 percent in CY 2022, which translates to
approximately $30 million.
2. Impacts of the Proposed Payment for Renal Dialysis Services
Furnished to Individuals With AKI
The impact table in section IX.B.2.a of this proposed rule displays
the estimated change in payments to ESRD facilities in CY 2022 compared
to estimated payments in CY 2021. The overall impact of the proposed CY
2022 changes is projected to be a 1.0 percent increase in payments for
individuals with AKI. Hospital-based ESRD facilities have an estimated
1.1 percent increase in payments compared with freestanding ESRD
facilities with an estimated 1.0 percent increase. The overall impact
reflects the effects of the updated wage index and the proposed payment
rate update. We estimate that the aggregate payments made to ESRD
facilities for renal dialysis services furnished to patients with AKI,
at the proposed CY 2022 ESRD PPS base rate, would increase by $1
million in CY 2022 compared to CY 2021.
3. Impacts of the Proposed ESRD QIP
Our proposals to suppress measures for the PY 2022 ESRD QIP and to
revise the scoring and payment methodology such that no facility will
receive a payment reduction necessitates a modification to our previous
estimated overall economic impact of the PY 2022 ESRD QIP (84 FR
60651). In the CY 2020 ESRD PPS final rule, we estimated that the
overall economic impact of the PY 2022 ESRD QIP would be approximately
$229 million as a result of the policies we had finalized at that time.
The $229 million figure for PY 2022 included costs associated with the
collection of information requirements, which we estimated would be
approximately $211 million, and $18 million in estimated payment
reductions across all facilities. However, as a result of the proposals
impacting the PY 2022 ESRD QIP we are making in this proposed rule, we
are modifying our previous estimate. We now estimate that the overall
economic impact of the PY 2022 ESRD QIP would be approximately $215
million. The $215 million figure for PY 2022 includes costs associated
with the collection of information requirements. If our proposals are
finalized as proposed, there would be no payment reductions in PY 2022.
We estimate that the overall economic impact of the PY 2024 ESRD QIP
would be approximately $232 million as a result of the policies we have
previously finalized and the proposals in this proposed rule. The $232
million figure for PY 2024 includes costs associated with the
collection of information requirements, which we estimate would be
approximately $215 million, and $17 million in estimated payment
reductions across all facilities. We also estimate that the overall
economic impact of the PY 2025 ESRD QIP would be approximately $232
million as a result of the policies we have previously finalized.
4. Impacts of Proposed Changes to the ETC Model
The impact estimate in section IX.B.4 of this proposed rule
describes the estimated change in anticipated Medicare program savings
arising from
[[Page 36326]]
the ETC Model over the duration of the ETC Model as a result of the
changes proposed in this proposed rule. We estimate that the ETC Model
would result in $38 million in net savings over the 6.5-year duration
of the ETC Model. We also estimate that $7 million of the estimated $38
million in net savings would be attributable to changes proposed in
this proposed rule.
II. Calendar Year (CY) 2022 End-Stage Renal Disease (ESRD) Prospective
Payment System (PPS)
A. Background
1. Statutory Background
On January 1, 2011, the Centers for Medicare & Medicaid Services
(CMS) implemented the End-Stage Renal Disease (ESRD) Prospective
Payment System (PPS), a case-mix adjusted bundled PPS for renal
dialysis services furnished by ESRD facilities, as required by section
1881(b)(14) of the Social Security Act (the Act), as added by section
153(b) of the Medicare Improvements for Patients and Providers Act of
2008 (MIPPA). Section 1881(b)(14)(F) of the Act, as added by section
153(b) of MIPPA and amended by section 3401(h) of the Patient
Protection and Affordable Care Act (the Affordable Care Act),
established that beginning with CY 2012, and each subsequent year, the
Secretary of the Department of Health and Human Services (the
Secretary) shall annually increase payment amounts by an ESRD market
basket increase factor reduced by the productivity adjustment described
in section 1886(b)(3)(B)(xi)(II) of the Act.
Section 632 of the American Taxpayer Relief Act of 2012 (ATRA)
(Pub. L. 112-240) included several provisions that apply to the ESRD
PPS. Section 632(a) of ATRA added section 1881(b)(14)(I) to the Act,
which required the Secretary, by comparing per patient utilization data
from 2007 with such data from 2012, to reduce the single payment for
renal dialysis services furnished on or after January 1, 2014 to
reflect the Secretary's estimate of the change in the utilization of
ESRD-related drugs and biologicals (excluding oral-only ESRD-related
drugs). Consistent with this requirement, in the CY 2014 ESRD PPS final
rule we finalized $29.93 as the total drug utilization reduction and
finalized a policy to implement the amount over a 3- to 4-year
transition period (78 FR 72161 through 72170).
Section 632(b) of ATRA prohibited the Secretary from paying for
oral-only ESRD-related drugs and biologicals under the ESRD PPS prior
to January 1, 2016. Section 632(c) of ATRA required the Secretary, by
no later than January 1, 2016, to analyze the case-mix payment
adjustments under section 1881(b)(14)(D)(i) of the Act and make
appropriate revisions to those adjustments.
On April 1, 2014, the Protecting Access to Medicare Act of 2014
(PAMA) (Pub. L. 113-93) was enacted. Section 217 of PAMA included
several provisions that apply to the ESRD PPS. Specifically, sections
217(b)(1) and (2) of PAMA amended sections 1881(b)(14)(F) and (I) of
the Act and replaced the drug utilization adjustment that was finalized
in the CY 2014 ESRD PPS final rule (78 FR 72161 through 72170) with
specific provisions that dictated the market basket update for CY 2015
(0.0 percent) and how the market basket should be reduced in CY 2016
through CY 2018.
Section 217(a)(1) of PAMA amended section 632(b)(1) of ATRA to
provide that the Secretary may not pay for oral-only ESRD-related drugs
under the ESRD PPS prior to January 1, 2024. Section 217(a)(2) of PAMA
further amended section 632(b)(1) of ATRA by requiring that in
establishing payment for oral-only drugs under the ESRD PPS, the
Secretary must use data from the most recent year available. Section
217(c) of PAMA provided that as part of the CY 2016 ESRD PPS
rulemaking, the Secretary shall establish a process for (1) determining
when a product is no longer an oral-only drug; and (2) including new
injectable and intravenous products into the ESRD PPS bundled payment.
Finally, on December 19, 2014, the President signed the Stephen
Beck, Jr., Achieving a Better Life Experience Act of 2014 (ABLE) (Pub.
L. 113-295). Section 204 of ABLE amended section 632(b)(1) of ATRA, as
amended by section 217(a)(1) of PAMA, to provide that payment for oral-
only renal dialysis services cannot be made under the ESRD PPS bundled
payment prior to January 1, 2025.
2. System for Payment of Renal Dialysis Services
Under the ESRD PPS, a single per-treatment payment is made to an
ESRD facility for all of the renal dialysis services defined in section
1881(b)(14)(B) of the Act and furnished to individuals for the
treatment of ESRD in the ESRD facility or in a patient's home. We have
codified our definitions of renal dialysis services at Sec. 413.171,
which is in 42 CFR part 413, subpart H, along with other ESRD PPS
payment policies. The ESRD PPS base rate is adjusted for
characteristics of both adult and pediatric patients and accounts for
patient case-mix variability. The adult case-mix adjusters include five
categories of age, body surface area, low body mass index, onset of
dialysis, and four comorbidity categories (that is, pericarditis,
gastrointestinal tract bleeding, hereditary hemolytic or sickle cell
anemia, myelodysplastic syndrome). A different set of case-mix
adjusters are applied for the pediatric population. Pediatric patient-
level adjusters include two age categories (under age 22, or age 22-26)
and two dialysis modalities (that is, peritoneal or hemodialysis)
(Sec. 413.235(a) and (b)).
The ESRD PPS provides for three facility-level adjustments. The
first payment adjustment accounts for ESRD facilities furnishing a low
volume of dialysis treatments (Sec. 413.232). The second adjustment
reflects differences in area wage levels developed from core-based
statistical areas (CBSAs) (Sec. 413.231). The third payment adjustment
accounts for ESRD facilities furnishing renal dialysis services in a
rural area (Sec. 413.233).
There are four additional payment adjustments under the ESRD PPS.
The ESRD PPS provides adjustments, when applicable, for: (1) A training
add-on for home and self-dialysis modalities (Sec. 413.235(c)); (2) an
additional payment for high cost outliers due to unusual variations in
the type or amount of medically necessary care (Sec. 413.237); (3) a
transitional drug add-on payment adjustment (TDAPA) for certain new
renal dialysis drugs and biological products (Sec. 413.234(c)); and
(4) a transitional add-on payment adjustment for new and innovative
equipment and supplies (TPNIES) for certain qualifying, new and
innovative renal dialysis equipment and supplies (Sec. 413.236(d)).
3. Updates to the ESRD PPS
Policy changes to the ESRD PPS are proposed and finalized annually
in the Federal Register. The CY 2011 ESRD PPS final rule was published
on August 12, 2010 in the Federal Register (75 FR 49030 through 49214).
That rule implemented the ESRD PPS beginning on January 1, 2011 in
accordance with section 1881(b)(14) of the Act, as added by section
153(b) of MIPPA, over a 4-year transition period. Since the
implementation of the ESRD PPS, we have published annual rules to make
routine updates, policy changes, and clarifications.
On November 9, 2020, we published a final rule in the Federal
Register titled, ``Medicare Program; End-Stage Renal Disease
Prospective Payment System, Payment for Renal Dialysis Services
Furnished to Individuals With Acute Kidney Injury, and End-Stage
[[Page 36327]]
Renal Disease Quality Incentive Program,'' referred to herein as the
``CY 2021 ESRD PPS final rule''. In that rule, we updated the ESRD PPS
base rate, wage index, and outlier policy, for CY 2021. We also
finalized an update to the ESRD PPS wage index to adopt the 2018 OMB
delineations with a transition period, changes to the eligibility
criteria and determination process for the TPNIES, an expansion of the
TPNIES to include certain new and innovative capital-related assets
that are home dialysis machines, an addition to the ESRD PPS base rate
to include calcimimetics in the ESRD PPS bundled payment, and a change
to the low-volume payment adjustment eligibility criteria and
attestation requirement to account for the coronavirus disease 2019
(COVID-19) Public Health Emergency (PHE). For further detailed
information regarding these updates, see 85 FR 71398.
B. Provisions of the Proposed Rule
1. Proposed CY 2022 ESRD PPS Update
a. Proposed CY 2022 ESRD Bundled (ESRDB) Market Basket Update,
Productivity Adjustment, and Labor-Related Share
In accordance with section 1881(b)(14)(F)(i) of the Act, as added
by section 153(b) of MIPPA and amended by section 3401(h) of the
Affordable Care Act, beginning in 2012, the ESRD PPS payment amounts
are required to be annually increased by an ESRD market basket increase
factor and reduced by the productivity adjustment described in section
1886(b)(3)(B)(xi)(II) of the Act. The application of the productivity
adjustment may result in the increase factor being less than 0.0
percent for a year and may result in payment rates for a year being
less than the payment rates for the preceding year. The statute also
provides that the market basket increase factor should reflect the
changes over time in the prices of an appropriate mix of goods and
services used to furnish renal dialysis services.
As required under section 1881(b)(14)(F)(i) of the Act, CMS
developed an all-inclusive ESRD Bundled (ESRDB) input price index (75
FR 49151 through 49162). In the CY 2015 ESRD PPS final rule we rebased
and revised the ESRDB input price index to reflect a 2012 base year (79
FR 66129 through 66136). Subsequently, in the CY 2019 ESRD PPS final
rule, we finalized a rebased ESRDB input price index to reflect a 2016
base year (83 FR 56951 through 56962).
Although ``market basket'' technically describes the mix of goods
and services used for ESRD treatment, this term is also commonly used
to denote the input price index (that is, cost categories, their
respective weights, and price proxies combined) derived from a market
basket. Accordingly, the term ``ESRDB market basket,'' as used in this
document, refers to the ESRDB input price index.
We propose to use the CY 2016-based ESRDB market basket as
finalized and described in the CY 2019 ESRD PPS final rule (83 FR 56951
through 56962) to compute the CY 2022 ESRDB market basket increase
factor based on the best available data. Consistent with historical
practice, we propose to estimate the ESRDB market basket update based
on IHS Global Inc.'s (IGI's) forecast using the most recently available
data. IGI is a nationally recognized economic and financial forecasting
firm with which we contract to forecast the components of the market
baskets. Using this methodology and the IGI first quarter 2021 forecast
of the CY 2016-based ESRDB market basket (with historical data through
the fourth quarter of 2020), the proposed CY 2022 ESRDB market basket
increase factor is 1.6 percent.
Under section 1881(b)(14)(F)(i) of the Act, for CY 2012 and each
subsequent year, the ESRD market basket percentage increase factor
shall be reduced by the productivity adjustment described in section
1886(b)(3)(B)(xi)(II) of the Act. The productivity adjustment is
calculated using a projection of multifactor productivity (MFP), which
is derived by subtracting the contribution of labor and capital input
growth from output growth. We finalized the detailed methodology for
deriving the projection of MFP in the CY 2012 ESRD PPS final rule (76
FR 40503 through 40504). The most up-to-date MFP projection methodology
is available on the CMS website at https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/MedicareProgramRatesStats/Downloads/MFPMethodology.pdf. We note that
for CY 2022 and beyond, CMS is changing the name of this adjustment to
refer to it as the productivity adjustment, which is the term used in
sections 1881(b)(14)(F)(i) and 1886(b)(3)(B)(xi)(II) of the Act, rather
than the multifactor productivity or MFP adjustment. This is not a
change in policy, as we will continue to use the same methodology for
deriving the adjustment and rely on the same underlying data. Using
this methodology and the IGI first quarter 2021 forecast, the proposed
productivity adjustment for CY 2022 (the 10-year moving average of MFP
for the period ending CY 2022) is projected to be 0.6 percent.
As a result of these provisions, the proposed CY 2022 ESRD market
basket increase factor reduced by the productivity adjustment is 1.0
percent. The proposed market basket increase factor is calculated by
starting with the proposed CY 2022 ESRDB market basket percentage
increase factor of 1.6 percent and reducing it by the proposed
productivity adjustment (the 10-year moving average of MFP for the
period ending CY 2022) of 0.6 percent.
As is our general practice, we are proposing that if more recent
data become available after the publication of this proposed rule and
before the publication of the final rule (for example, a more recent
estimate of the CY 2016-based ESRD market basket increase factor or
productivity adjustment), we would use such data, if appropriate, to
determine the final CY 2022 market basket update and productivity
adjustment.
For the CY 2022 ESRD payment update, we propose to continue using a
labor-related share of 52.3 percent for the ESRD PPS payment, which was
finalized in the CY 2019 ESRD PPS final rule (83 FR 56963).
b. The Proposed CY 2022 ESRD PPS Wage Indices
(1) Background
Section 1881(b)(14)(D)(iv)(II) of the Act provides that the ESRD
PPS may include a geographic wage index payment adjustment, such as the
index referred to in section 1881(b)(12)(D) of the Act, as the
Secretary determines to be appropriate. In the CY 2011 ESRD PPS final
rule (75 FR 49200), we finalized an adjustment for wages at Sec.
413.231. Specifically, CMS adjusts the labor-related portion of the
base rate to account for geographic differences in the area wage levels
using an appropriate wage index, which reflects the relative level of
hospital wages and wage-related costs in the geographic area in which
the ESRD facility is located. We use OMB's CBSA-based geographic area
designations to define urban and rural areas and their corresponding
wage index values (75 FR 49117). OMB publishes bulletins regarding CBSA
changes, including changes to CBSA numbers and titles. The bulletins
are available online at https://www.whitehouse.gov/omb/information-for-agencies/bulletins/.
For CY 2022, we would update the wage indices to account for
updated wage levels in areas in which ESRD facilities are located using
our existing methodology. We use the most recent
[[Page 36328]]
pre-floor, pre-reclassified hospital wage data collected annually under
the inpatient PPS. The ESRD PPS wage index values are calculated
without regard to geographic reclassifications authorized under
sections 1886(d)(8) and (d)(10) of the Act and utilize prefloor
hospital data that are unadjusted for occupational mix. For CY 2022,
the updated wage data are for hospital cost reporting periods beginning
on or after October 1, 2017, and before October 1, 2018 (fiscal year
[FY] 2018 cost report data).
We have also adopted methodologies for calculating wage index
values for ESRD facilities that are located in urban and rural areas
where there is no hospital data. For a full discussion, see CY 2011 and
CY 2012 ESRD PPS final rules at 75 FR 49116 through 49117 and 76 FR
70239 through 70241, respectively. For urban areas with no hospital
data, we compute the average wage index value of all urban areas within
the state to serve as a reasonable proxy for the wage index of that
urban CBSA, that is, we use that value as the wage index. For rural
areas with no hospital data, we compute the wage index using the
average wage index values from all contiguous CBSAs to represent a
reasonable proxy for that rural area. We apply the statewide urban
average based on the average of all urban areas within the state to
Hinesville-Fort Stewart, Georgia (78 FR 72173), and we apply the wage
index for Guam to American Samoa and the Northern Mariana Islands (78
FR 72172).\1\
---------------------------------------------------------------------------
\1\ We note that for the CY 2020 ESRD PPS final rule, we did not
apply the statewide urban average to Carson City, Nevada because
hospital data was available to compute the wage index.
---------------------------------------------------------------------------
A wage index floor value (0.5000) is applied under the ESRD PPS as
a substitute wage index for areas with very low wage index values.
Currently, all areas with wage index values that fall below the floor
are located in Puerto Rico. However, the wage index floor value is
applicable for any area that may fall below the floor. A description of
the history of the wage index floor under the ESRD PPS can be found in
the CY 2019 ESRD PPS final rule (83 FR 56964 through 56967).
An ESRD facility's wage index is applied to the labor-related share
of the ESRD PPS base rate. In the CY 2019 ESRD PPS final rule (83 FR
56963), we finalized a labor-related share of 52.3 percent, which is
based on the 2016-based ESRDB market basket. In the CY 2021 ESRD PPS
final rule (85 FR 71436), we updated the OMB delineations as described
in the September 14, 2018 OMB Bulletin No. 18-04, beginning with the CY
2021 ESRD PPS wage index. In addition, we finalized the application of
a 5 percent cap on any decrease in an ESRD facility's wage index from
the ESRD facility's wage index from the prior CY. We finalized that the
transition would be phased in over 2 years, such that the reduction in
an ESRD facility's wage index would be capped at 5 percent in CY 2021,
and no cap would be applied to the reduction in the wage index for the
second year, CY 2022. Thus, for CY 2022, the labor-related share to
which a facility's wage index would be applied is 52.3 percent.
For CY 2022, we are proposing to update the ESRD PPS wage index to
use the most recent hospital wage data. The proposed CY 2022 ESRD PPS
wage index is set forth in Addendum A and is available on the CMS
website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/ESRDpayment/End-Stage-Renal-Disease-ESRD-Payment-Regulations-and-Notices. Addendum A provides a crosswalk between the CY 2021 wage
index and the proposed CY 2022 wage index. Addendum B provides an ESRD
facility level impact analysis. Addendum B is available on the CMS
website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/ESRDpayment/End-Stage-Renal-Disease-ESRD-Payment-Regulations-and-Notices.
c. Proposed CY 2022 Update to the Outlier Policy
Section 1881(b)(14)(D)(ii) of the Act requires that the ESRD PPS
include a payment adjustment for high cost outliers due to unusual
variations in the type or amount of medically necessary care, including
variability in the amount of erythropoiesis-stimulating agents (ESAs)
necessary for anemia management. Some examples of the patient
conditions that may be reflective of higher facility costs when
furnishing dialysis care would be frailty, obesity, and comorbidities,
such as secondary hyperparathyroidism. The ESRD PPS recognizes high
cost patients, and we have codified the outlier policy and our
methodology for calculating outlier payments at Sec. 413.237.
The policy provides that the following ESRD outlier items and
services are included in the ESRD PPS bundle: (1) Renal dialysis drugs
and biological products that were or would have been, prior to January
1, 2011, separately billable under Medicare Part B; (2) renal dialysis
laboratory tests that were or would have been, prior to January 1,
2011, separately billable under Medicare Part B ; (3) renal dialysis
medical/surgical supplies, including syringes, used to administer renal
dialysis drugs and biological products that were or would have been,
prior to January 1, 2011, separately billable under Medicare Part B;
(4) renal dialysis drugs and biological products that were or would
have been, prior to January 1, 2011, covered under Medicare Part D,
including renal dialysis oral-only drugs effective January 1, 2025; and
(5) renal dialysis equipment and supplies, except for capital-related
assets that are home dialysis machines(as defined in Sec.
413.236(a)(2)), that receive the transitional add-on payment adjustment
as specified in Sec. 413.236 after the payment period has ended.
In the CY 2011 ESRD PPS final rule (75 FR 49142), CMS stated that
for purposes of determining whether an ESRD facility would be eligible
for an outlier payment, it would be necessary for the facility to
identify the actual ESRD outlier services furnished to the patient by
line item (that is, date of service) on the monthly claim. Renal
dialysis drugs, laboratory tests, and medical/surgical supplies that
are recognized as outlier services were specified in Transmittal 2134,
dated January 14, 2011.\2\ https://www.cms.gov/Regulations-and-Guidance/Guidance/Transmittals/downloads/R2134CP.pdf. Furthermore, CMS
uses administrative issuances to update the renal dialysis service
items available for outlier payment via our quarterly update CMS Change
Requests, when applicable. For example, we use these updates to
identify renal dialysis service drugs that were or would have been
covered under Medicare Part D for outlier eligibility purposes and
items and services that have been incorrectly identified as eligible
outlier services.
---------------------------------------------------------------------------
\2\ Transmittal 2033 issued August 20, 2010, was rescinded and
replaced by Transmittal 2094, dated November 17, 2010. Transmittal
2094 identified additional drugs and laboratory tests that may also
be eligible for ESRD outlier payment. Transmittal 2094 was rescinded
and replaced by Transmittal 2134, dated January 14, 2011, which
included one technical correction.
---------------------------------------------------------------------------
Under Sec. 413.237, an ESRD facility is eligible for an outlier
payment if its actual or imputed Medicare Allowable Payment (MAP)
amount per treatment for ESRD outlier services exceeds a threshold. The
MAP amount represents the average incurred amount per treatment for
services that were or would have been considered separately billable
services prior to January 1, 2011. The threshold is equal to the ESRD
facility's predicted ESRD outlier services MAP amount per treatment
(which is case-mix adjusted and described in the following paragraphs)
[[Page 36329]]
plus the fixed-dollar loss (FDL) amount. In accordance with Sec.
413.237(c), facilities are paid 80 percent of the per treatment amount
by which the imputed MAP amount for outlier services (that is, the
actual incurred amount) exceeds this threshold. ESRD facilities are
eligible to receive outlier payments for treating both adult and
pediatric dialysis patients.
In the CY 2011 ESRD PPS final rule and codified in Sec.
413.220(b)(4), using 2007 data, we established the outlier percentage,
which is used to reduce the per treatment base rate to account for the
proportion of the estimated total payments under the ESRD PPS that are
outlier payments, at 1.0 percent of total payments (75 FR 49142 through
49143). We also established the FDL amounts that are added to the
predicted outlier services MAP amounts. The outlier services MAP
amounts and FDL amounts are different for adult and pediatric patients
due to differences in the utilization of separately billable services
among adult and pediatric patients (75 FR 49140). As we explained in
the CY 2011 ESRD PPS final rule (75 FR 49138 through 49139), the
predicted outlier services MAP amounts for a patient are determined by
multiplying the adjusted average outlier services MAP amount by the
product of the patient-specific case-mix adjusters applicable using the
outlier services payment multipliers developed from the regression
analysis used to compute the payment adjustments.
For CY 2022, we propose that the outlier services MAP amounts and
FDL amounts would be derived from claims data from CY 2020. Because we
believe that any adjustments made to the MAP amounts under the ESRD PPS
should be based upon the most recent data year available in order to
best predict any future outlier payments, we propose the outlier
thresholds for CY 2022 would be based on utilization of renal dialysis
items and services furnished under the ESRD PPS in CY 2020.
We recognize that the utilization of ESAs and other outlier
services have continued to decline under the ESRD PPS, and that we have
lowered the MAP amounts and FDL amounts every year under the ESRD PPS.
As discussed in the CY 2021 ESRD PPS final rule (85 FR 71438), CY 2019
claims data show outlier payments represented approximately 0.5 percent
of total payments. As discussed in section II.B.1.c.(1) of this
proposed rule, CY 2020 claims data show outlier payments represent
approximately 0.6 percent of total payments.
(1) CY 2022 Update to the Outlier Services MAP Amounts and FDL Amounts
For CY 2022, we propose to update the outlier services MAP amounts
and FDL amounts to reflect the utilization of outlier services reported
on 2020 claims. For this proposed rule, the outlier services MAP
amounts and FDL amounts were updated using 2020 claims data. The impact
of this update is shown in Table 1, which compares the outlier services
MAP amounts and FDL amounts used for the outlier policy in CY 2021 with
the updated proposed estimates for this rule. The estimates for the
proposed CY 2022 outlier policy, which are included in Column II of
Table 1, were inflation adjusted to reflect projected 2022 prices for
outlier services.
[GRAPHIC] [TIFF OMITTED] TP09JY21.000
The estimated FDL amount per treatment that determines the CY 2022
outlier threshold amount for adults (Column II; $111.18) is lower than
that used for the CY 2021 outlier policy (Column I; $122.49). The lower
threshold is accompanied by a decrease in the adjusted average MAP for
outlier services from $50.92 to $47.87. For
[[Page 36330]]
pediatric patients, there is a decrease in the FDL amount from $44.78
to $30.38. There is a corresponding decrease in the adjusted average
MAP for outlier services among pediatric patients, from $30.08 to
$28.73.
We estimate that the percentage of patient months qualifying for
outlier payments in CY 2022 would be 5.45 percent for adult patients
and 11.37 percent for pediatric patients, based on the 2020 claims
data. The outlier MAP and FDL amounts continue to be lower for
pediatric patients than adults due to the continued lower use of
outlier services (primarily reflecting lower use of ESAs and other
injectable drugs).
(2) Outlier Percentage
In the CY 2011 ESRD PPS final rule (75 FR 49081) and under Sec.
413.220(b)(4), we reduced the per treatment base rate by 1 percent to
account for the proportion of the estimated total payments under the
ESRD PPS that are outlier payments as described in Sec. 413.237. Based
on the 2020 claims, outlier payments represented approximately 0.6
percent of total payments, which is below the 1 percent target due to
declines in the use of outlier services. As noted in past rulemaking,
recalibration of the thresholds using 2020 data is expected to result
in aggregate outlier payments close to the 1 percent target in CY 2022.
We believe the update to the outlier MAP and FDL amounts for CY 2022
would increase payments for ESRD beneficiaries requiring higher
resource utilization. This would move us closer to meeting our 1
percent outlier policy goal, because we are using more current data for
computing the MAP and FDL, which is more in line with current outlier
services utilization rates. We note that recalibration of the FDL
amounts in this proposed rule would result in no change in payments to
ESRD facilities for beneficiaries with renal dialysis items and
services that are not eligible for outlier payments.
d. Proposed Impacts to the CY 2022 ESRD PPS Base Rate
(1) ESRD PPS Base Rate
In the CY 2011 ESRD PPS final rule (75 FR 49071 through 49083), CMS
established the methodology for calculating the ESRD PPS per-treatment
base rate, that is, ESRD PPS base rate, and calculating the per
treatment payment amount, which are codified at Sec. Sec. 413.220 and
413.230. The CY 2011 ESRD PPS final rule also provides a detailed
discussion of the methodology used to calculate the ESRD PPS base rate
and the computation of factors used to adjust the ESRD PPS base rate
for projected outlier payments and budget neutrality in accordance with
sections 1881(b)(14)(D)(ii) and 1881(b)(14)(A)(ii) of the Act,
respectively. Specifically, the ESRD PPS base rate was developed from
CY 2007 claims (that is, the lowest per patient utilization year as
required by section 1881(b)(14)(A)(ii) of the Act), updated to CY 2011,
and represented the average per treatment MAP for composite rate and
separately billable services. In accordance with section 1881(b)(14)(D)
of the Act and our regulation at Sec. 413.230, the per-treatment
payment amount is the sum of the ESRD PPS base rate, adjusted for the
patient specific case-mix adjustments, applicable facility adjustments,
geographic differences in area wage levels using an area wage index,
and any applicable outlier payment, training adjustment add-on, TDAPA,
and TPNIES.
(2) Annual Payment Rate Update for CY 2022
We are proposing an ESRD PPS base rate for CY 2022 of $255.55. This
update reflects several factors, described in more detail as follows:
Wage Index Budget-Neutrality Adjustment Factor: We compute a wage
index budget-neutrality adjustment factor that is applied to the ESRD
PPS base rate. For CY 2022, we are not proposing any changes to the
methodology used to calculate this factor, which is described in detail
in the CY 2014 ESRD PPS final rule (78 FR 72174). We computed the
proposed CY 2022 wage index budget-neutrality adjustment factor using
treatment counts from the 2020 claims and facility-specific CY 2021
payment rates to estimate the total dollar amount that each ESRD
facility would have received in CY 2021. The total of these payments
became the target amount of expenditures for all ESRD facilities for CY
2022. Next, we computed the estimated dollar amount that would have
been paid for the same ESRD facilities using the ESRD PPS wage index
for CY 2022. As discussed in section II.B.1.b of this proposed rule,
the proposed ESRD PPS wage index for CY 2022 includes an update to the
most recent hospital wage data, use of the 2018 OMB delineations, and
no cap on wage index decreases applied for CY 2022. The total of these
payments becomes the new CY 2022 amount of wage-adjusted expenditures
for all ESRD facilities. The wage index budget-neutrality factor is
calculated as the target amount divided by the new CY 2022 amount. When
we multiplied the wage index budget neutrality factor by the applicable
CY 2022 estimated payments, aggregate payments to ESRD facilities would
remain budget neutral when compared to the target amount of
expenditures. That is, the wage index budget neutrality adjustment
factor ensures that wage index adjustments do not increase or decrease
aggregate Medicare payments with respect to changes in wage index
updates. The CY 2022 proposed wage index budget-neutrality adjustment
factor is .999546. This application would yield a CY 2022 ESRD PPS
proposed base rate of $253.02 prior to the application of the proposed
market basket increase ($253.13 x .999546 = $253.02).
Market Basket Increase: Section 1881(b)(14)(F)(i)(I) of the Act
provides that, beginning in 2012, the ESRD PPS payment amounts are
required to be annually increased by the ESRD market basket percentage
increase factor. The latest CY 2022 projection of the proposed ESRDB
market basket percentage increase factor is 1.6 percent. In CY 2022,
this amount must be reduced by the productivity adjustment described in
section 1886(b)(3)(B)(xi)(II) of the Act, as required by section
1881(b)(14)(F)(i)(II) of the Act. As discussed previously, the proposed
productivity adjustment for CY 2021 is 0.6 percent, thus yielding a
proposed update to the base rate of 1.0 percent for CY 2022. Therefore,
the CY 2022 ESRD PPS proposed base rate is $255.55 ($253.02 x 1.010 =
$255.55).
In summary, we are proposing a CY 2022 ESRD PPS base rate of
$255.55. This amount reflects a proposed CY 2022 wage index budget-
neutrality adjustment factor of .999546, and the CY 2022 ESRD PPS
productivity-adjusted market basket update of 1.0 percent.
e. Update to the Offset Amount for TPNIES
In the CY 2021 ESRD PPS final rule (85 FR 71427), we expanded
eligibility for the TPNIES under Sec. 413.236 to include certain
capital-related assets that are home dialysis machines when used in the
home for a single patient. We finalized the additional steps that the
Medicare Administrative Contractors (MACs) must follow to establish the
basis of payment of the TPNIES for these capital-related assets that
are home dialysis machines when used in the home, including an offset
to the pre-adjusted per treatment amount to account for the cost of the
home dialysis machine that is already in the ESRD PPS base rate. We
will pay 65 percent of the MAC-determined preadjusted per treatment
amount reduced by an offset for 2-calendar
[[Page 36331]]
years. Section Sec. 413.236(f)(3)(v) states that effective January 1,
2022, CMS will annually update the amount determined in paragraph
(f)(3)(iv) of Sec. 413.236 by the ESRD bundled market basket
percentage increase factor minus the productivity adjustment factor.
The CY 2021 offset amount for TPNIES for capital-related equipment
that are home dialysis machines used in the home is $9.32. As discussed
previously in section II.B.1.a of this proposed rule, the proposed CY
2022 ESRD bundled market basket increase factor minus the productivity
adjustment is 1.0 percent (1.6 percent minus 0.6 percent). Applying the
proposed update factor of 1.010 to the CY 2021 offset amount results in
a proposed CY 2022 offset amount of $9.41($9.32 x 1.010). We will
update this calculation to use the most recent data available in the CY
2022 ESRD PPS final rule.
C. Proposed Transitional Add-On Payment Adjustment for New and
Innovative Equipment and Supplies (TPNIES) for CY 2022 Payment
1. Background
In the CY 2020 ESRD PPS final rule (84 FR 60681 through 60698), CMS
established the transitional add-on payment adjustment for new and
innovative equipment and supplies (TPNIES) under the ESRD PPS, under
the authority of section 1881(b)(14)(D)(iv) of the Act, in order to
support ESRD facility use and beneficiary access to these new
technologies. We established this add-on payment adjustment to help
address the unique circumstances experienced by ESRD facilities when
incorporating new and innovative equipment and supplies into their
businesses and to support ESRD facilities transitioning or testing
these products during the period when they are new to market. We added
Sec. 413.236 to establish the eligibility criteria and payment
policies for the TPNIES.
In the CY 2020 ESRD PPS final rule (84 FR 60650), we established in
Sec. 413.236(b) that for dates of service occurring on or after
January 1, 2020, we will provide the TPNIES to an ESRD facility for
furnishing a covered equipment or supply only if the item: (1) Has been
designated by CMS as a renal dialysis service under Sec. 413.171; (2)
is new, meaning granted marketing authorization by the Food and Drug
Administration (FDA) on or after January 1, 2020; (3) is commercially
available by January 1 of the particular calendar year, meaning the
year in which the payment adjustment would take effect; (4) has a
Healthcare Common Procedure Coding System (HCPCS) application submitted
in accordance with the official Level II HCPCS coding procedures by
September 1 of the particular calendar year; (5) is innovative, meaning
it meets the SCI criteria specified in the Inpatient Prospective
Payment System (IPPS) regulations at 42 CFR 412.87(b)(1) and related
guidance, and (6) is not a capital related asset that an ESRD facility
has an economic interest in through ownership (regardless of the manner
in which it was acquired).
Regarding the innovation requirement in Sec. 413.236(b)(5), in the
CY 2020 ESRD PPS final rule (84 FR 60690), we stated that we will use
the following criteria to evaluate SCI for purposes of the TPNIES under
the ESRD PPS based on the IPPS SCI criteria in Sec. 412.87(b)(1) and
related guidance:
A new technology represents an advance that substantially improves,
relative to renal dialysis services previously available, the diagnosis
or treatment of Medicare beneficiaries. First, CMS considers the
totality of the circumstances when making a determination that a new
renal dialysis equipment or supply represents an advance that
substantially improves, relative to renal dialysis services previously
available, the diagnosis or treatment of Medicare beneficiaries.
Second, a determination that a new renal dialysis equipment or supply
represents an advance that substantially improves, relative to renal
dialysis services previously available, the diagnosis or treatment of
Medicare beneficiaries means one of the following:
The new renal dialysis equipment or supply offers a
treatment option for a patient population unresponsive to, or
ineligible for, currently available treatments; or
The new renal dialysis equipment or supply offers the
ability to diagnose a medical condition in a patient population where
that medical condition is currently undetectable, or offers the ability
to diagnose a medical condition earlier in a patient population than
allowed by currently available methods, and there must also be evidence
that use of the new renal dialysis service to make a diagnosis affects
the management of the patient; or
The use of the new renal dialysis equipment or supply
significantly improves clinical outcomes relative to renal dialysis
services previously available as demonstrated by one or more of the
following: A reduction in at least one clinically significant adverse
event, including a reduction in mortality or a clinically significant
complication; a decreased rate of at least one subsequent diagnostic or
therapeutic intervention; a decreased number of future hospitalizations
or physician visits; a more rapid beneficial resolution of the disease
process treatment including, but not limited to, a reduced length of
stay or recovery time; an improvement in one or more activities of
daily living; an improved quality of life; or, a demonstrated greater
medication adherence or compliance; or,
The totality of the circumstances otherwise demonstrates
that the new renal dialysis equipment or supply substantially improves,
relative to renal dialysis services previously available, the diagnosis
or treatment of Medicare beneficiaries.
Third, evidence from the following published or unpublished
information sources from within the U.S. or elsewhere may be sufficient
to establish that a new renal dialysis equipment or supply represents
an advance that substantially improves, relative to renal dialysis
services previously available, the diagnosis or treatment of Medicare
beneficiaries: Clinical trials, peer reviewed journal articles; study
results; meta-analyses; consensus statements; white papers; patient
surveys; case studies; reports; systematic literature reviews; letters
from major healthcare associations; editorials and letters to the
editor; and public comments. Other appropriate information sources may
be considered.
Fourth, the medical condition diagnosed or treated by the new renal
dialysis equipment or supply may have a low prevalence among Medicare
beneficiaries. Fifth, the new renal dialysis equipment or supply may
represent an advance that substantially improves, relative to services
or technologies previously available, the diagnosis or treatment of a
subpopulation of patients with the medical condition diagnosed or
treated by the new renal dialysis equipment or supply.
In the CY 2020 ESRD PPS final rule (84 FR 60681 through 60698), we
also established a process modeled after IPPS's process of determining
if a new medical service or technology meets the SCI criteria specified
in Sec. 412.87(b)(1). Specifically, similar to the IPPS New Technology
Add-On Payment, we wanted to align our goals with the agency's efforts
to transform the healthcare delivery system for the ESRD beneficiary
through competition and innovation to provide patients with better
value and results. As we discuss in the CY 2020 ESRD PPS final rule (84
[[Page 36332]]
FR 60682), we believe it is appropriate to facilitate access to new and
innovative equipment and supplies through add-on payments similar to
the IPPS New Technology Add-On Payment and to provide stakeholders with
standard criteria for both inpatient and outpatient settings. In Sec.
413.236(c), we established a process for our announcement of TPNIES
determinations and a deadline for consideration of new renal dialysis
equipment or supply applications under the ESRD PPS. CMS will consider
whether a new renal dialysis equipment or supply meets the eligibility
criteria specified in Sec. 413.236(b) and summarize the applications
received in the annual ESRD PPS proposed rules. Then, after
consideration of public comments, we will announce the results in the
Federal Register as part of our annual updates and changes to the ESRD
PPS in the ESRD PPS final rule. In the CY 2020 ESRD PPS final rule, we
also specified certain deadlines for the application requirements. We
noted that we would only consider a complete application received by
February 1 prior to the particular calendar year. In addition, we
required that FDA marketing authorization for the equipment or supply
must occur by September 1 prior to the particular calendar year. We
also stated in the CY 2020 ESRD PPS final rule (84 FR 60690 through
60691) that we would establish a workgroup of CMS medical and other
staff to review the materials submitted as part of the TPNIES
application, public comments, FDA marketing authorization, and HCPCS
application information and assess the extent to which the product
provides SCI over current technologies.
In the CY 2020 ESRD PPS final rule, we established Sec. 413.236(d)
to provide a payment adjustment for a new and innovative renal dialysis
equipment or supply. We stated that the TPNIES is paid for 2-calendar
years. Following payment of the TPNIES, the ESRD PPS base rate will not
be modified and the new and innovative renal dialysis equipment or
supply will become an eligible outlier service as provided in Sec.
413.237.
Regarding the basis of payment for the TPNIES, in the CY 2020 ESRD
PPS final rule, we finalized at Sec. 413.236(e) that the TPNIES is
based on 65 percent of the price established by the MACs, using the
information from the invoice and other specified sources of
information. In the CY 2021 ESRD PPS final rule (85 FR 71410 through
71464), we made several changes to the TPNIES eligibility criteria at
Sec. 413.236. First, we revised the definition of new at Sec.
413.236(b)(2) as within 3 years beginning on the date of the FDA
marketing authorization. Second, we changed the deadline for TPNIES
applicants' HCPCS Level II code application submission from September 1
of the particular calendar year to the HCPCS Level II code application
deadline for biannual Coding Cycle 2 for durable medical equipment,
orthotics, prosthetics, and supplies (DMEPOS) items and services as
specified in the HCPCS Level II coding guidance on the CMS website
prior to the calendar year. In addition, a copy of the applicable FDA
marketing authorization must be submitted to CMS by the HCPCS Level II
code application deadline for biannual Coding Cycle 2 for DMEPOS items
and services as specified in the HCPCS Level II coding guidance on the
CMS website in order for the equipment or supply to be eligible for the
TPNIES the following year. Third, we revised Sec. 413.236(b)(5) to
remove a reference to related guidance on the SCI criterion, as the
guidance has already been codified.
Finally, in the CY 2021 ESRD PPS final rule, we expanded the TPNIES
policy to include certain capital-related assets that are home dialysis
machines when used in the home for a single patient. We explained that
capital-related assets are defined in the Provider Reimbursement Manual
(chapter 1, section 104.1) as assets that a provider has an economic
interest in through ownership (regardless of the manner in which they
were acquired). We noted that examples of capital-related assets for
ESRD facilities are dialysis machines and water purification systems.
We explained that while in the CY 2020 ESRD PPS proposed rule (84 FR
38354), we stated that we did not believe capital-related assets should
be eligible for additional payment through the TPNIES because the cost
of these items is captured in cost reports, they depreciate over time,
and are generally used for multiple patients, there were a number of
other factors we considered that led us to consider expanding
eligibility for these technologies in the CY 2021 ESRD PPS rulemaking.
We explained that, following publication of the CY 2020 ESRD PPS final
rule, we continued to study the issue of payment for capital-related
assets under the ESRD PPS, taking into account information from a wide
variety of stakeholders and recent developments and initiatives
regarding kidney care. For example, we considered various HHS home
dialysis initiatives, Executive Orders to transform kidney care, and
how the risk of COVID-19 for particularly vulnerable ESRD beneficiaries
could be mitigated by encouraging home dialysis. After closely
considering these issues, we proposed a revision to Sec. 413.236(b)(6)
in the CY 2021 ESRD PPS proposed rule to provide an exception to the
general exclusion for capital-related assets from eligibility for the
TPNIES for capital-related assets that are home dialysis machines when
used in the home for a single patient and that meet the other
eligibility criteria in Sec. 413.235(b), and finalized the exception
as proposed. We finalized the same determination process for TPNIES
applications for capital-related assets that are home dialysis machines
as for all other TPNIES applications; that we will provide a
description of the new home dialysis machine and pertinent facts in the
ESRD PPS proposed rule so the public may comment and then publish the
results in the ESRD PPS final rule. We will consider whether the new
home dialysis machine meets the eligibility criteria specified in the
proposed revisions to Sec. 413.236(b) and announce the results in the
Federal Register as part of our annual updates and changes to the ESRD
PPS. Per Sec. 413.236(c), we will only consider, for additional
payment using the TPNIES for a particular calendar year, an application
for a capital-related asset that is a home dialysis machine received by
February 1 prior to the particular calendar year. If the application is
not received by February 1, the application will be denied and the
applicant will need to reapply within 3 years beginning on the date of
FDA marketing authorization in order to be considered for the TPNIES,
in accordance with the proposed revisions to Sec. 413.236(b)(2).
In the CY 2021 ESRD PPS final rule, at Sec. 413.236(f), we
finalized a pricing methodology for capital-related assets that are
home dialysis machines when used in the home for a single patient by
requiring MACs to calculate the annual allowance and the preadjusted
per treatment amount. The pre-adjusted per treatment amount is reduced
by an estimated average per treatment offset amount to account for the
costs already paid through the ESRD PPS base rate. The CY 2021 TPNIES
offset amount was $9.32, and we finalized that this amount will be
updated on an annual basis so that it is consistent with how the ESRD
PPS base rate is updated.
We revised Sec. 413.236(d) to reflect that we would pay 65 percent
of the pre-adjusted per treatment amount minus the offset for capital-
related assets that are home dialysis machines when used in the home
for a single patient.
We revised Sec. 413.236(d)(2) to reflect that following payment of
the TPNIES, the ESRD PPS base rate will not be
[[Page 36333]]
modified and the new and innovative renal dialysis equipment or supply
will be an eligible outlier service as provided in Sec. 413.237,
except a capital-related asset that is a home dialysis machine will not
be an eligible outlier service as provided in Sec. 413.237. In
summary, under the current eligibility requirements in Sec.
413.236(b), CMS provides for a TPNIES to an ESRD facility for
furnishing a covered equipment or supply only if the item: (1) Has been
designated by CMS as a renal dialysis service under Sec. 413.171; (2)
Is new, meaning within 3 years beginning on the date of the FDA
marketing authorization; (3) Is commercially available by January 1 of
the particular calendar year, meaning the year in which the payment
adjustment would take effect; (4) Has a complete HCPCS Level II code
application submitted in accordance with the HCPCS Level II coding
procedures on the CMS website, by the HCPCS Level II code application
deadline for biannual Coding Cycle 2 for DMEPOS items and services as
specified in the HCPCS Level II coding guidance on the CMS website
prior to the calendar year; (5) Is innovative, meaning it meets the
criteria specified in Sec. 412.87(b)(1) of this chapter; and (6) Is
not a capital-related asset, except for capital-related assets that are
home dialysis machines.
We received two applications for the TPNIES for CY 2022. A
discussion of these applications is presented below. The applications
received are for technologies commonly used for the treatment of ESRD:
Hemodialysis (HD) and peritoneal dialysis (PD). Detailed definitions
for HD and PD are found in Chapter 11, Section 10 of the Medicare
Benefits Policy Manual (Pub. L. 100-02).\3\ In brief, HD is a process
that involves blood passing through an artificial kidney machine and
the waste products diffusing across a manmade membrane into a bath
solution known as dialysate after which the cleansed blood is returned
to the patient's body. HD is accomplished usually in 3 to 5 hour
sessions, 3 times a week. PD is a process that involves waste products
passing from the patient's body through the peritoneal membrane into
the peritoneal (abdominal) cavity where the bath solution (dialysate)
is introduced and removed periodically.
---------------------------------------------------------------------------
\3\ Medicare Benefits Policy Manual (Pub. L. 100-102), available
at: https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Downloads/bp102c11.pdf.
---------------------------------------------------------------------------
a. Tablo[supreg] System
Outset Medical, Inc. submitted an application for the TPNIES for
the Tablo[supreg] System (Tablo[supreg]) for CY 2022. According to the
applicant, the technology is an HD machine that has been designed for
patient-driven self-care and to minimize system training time. The
applicant also stated that the system is intended to substantially
improve the treatment of people with ESRD by removing barriers to home
dialysis. The applicant explained that the Tablo[supreg] System is
comprised of (1) the Tablo[supreg] Console with integrated water
purification, on-demand dialysate production, and a simple-to-use
touchscreen interface; (2) a proprietary, disposable, single-use pre-
strung cartridge that easily clicks into place, minimizing steps, touch
points, and connections; and (3) the Tablo[supreg] Connectivity and
Data Ecosystem. Per the applicant, the system is built to function in a
connected setting with cloud-based system monitoring, patient analytics
and clinical recordkeeping.
The applicant stated that the Tablo[supreg] System's unique
features combine to provide a significantly differentiated HD solution
with many benefits. First, the applicant stated that the Tablo[supreg]
System's intuitive touchscreen interface makes it easy to learn and
use, guiding users through treatment from start to finish using step-
by-step instructions with simple words and animation. The applicant
also stated that instructions include non-technical language and color-
coded parts to enable easier training, faster set-up, and simpler
management including clear alarm explanations and resolution
instructions.
Second, the applicant stated that the Tablo[supreg] System can
accommodate treatments at home allowing for flexibility in treatment
frequencies, durations, and flow rates. Per the applicant, the
Tablo[supreg] System does not have a pre-configured dialyzer, which
allows clinicians to use a broad range of dialyzer types and
manufactures, allowing for greater customization of treatment for the
patient. The applicant stated that this is an improvement over the
incumbent home device, which requires a separate device component and
complex process to switch to another dialyzer.
Third, the applicant stated that the Tablo[supreg] System is an
all-in-one system with integrated water purification and on-demand
dialysate production, eliminating the need for industrial water
treatment rooms that are required to operate traditional HD machines.
The applicant also stated that electronic data capture and automatic
wireless transmission eliminate the need for manual record keeping by
the patient, care partner, or nurse. Per the applicant, a single-use
Tablo[supreg] Cartridge with user-friendly pre-strung blood, saline,
and infusion tubing and a series of sensor-receptors mounted to a user-
friendly organizer snaps easily into the system minimizing difficult
connections that require additional training. The applicant stated that
automated features, including an integrated blood pressure monitor, air
removal, priming, and blood return, minimize user errors, save time,
and streamline the user experience.
Fourth, the applicant stated that the Tablo[supreg] System's two-
way wireless connectivity and data analytics provide the ability to
continuously activate new capabilities and enhancements through
wireless software updates, while also enabling predictive preventative
maintenance to maximize machine uptime.
The applicant stated that currently 88 percent of patients receive
HD in a clinic 3 times per week, for 3.0 to 4.5 hours a day and fewer
than 2 percent perform HD treatment at home.\4\ The applicant stated
that 25 to 36 percent of home HD patients return to in-center care
within 1 year of initiating HD at home.5 6 Per the
applicant, barriers to home dialysis adoption and retention have been
well studied and include treatment burden for patients and care partner
fatigue; technical challenges with operating a HD machine; space, home
modifications, and supplies management; patients not wanting medical
equipment in the home; and safety concerns.7 8
---------------------------------------------------------------------------
\4\ United States Renal Data System. 2020 USRDS Annual Data
Report: Epidemiology of kidney disease in the United States, End-
Stage Renal Disease Chapter 2. National Institutes of Health,
National Institute of Diabetes and Digestive and Kidney Diseases,
Bethesda, MD, 2020. Available at: https://adr.usrds.org/2020/end-stage-renaldisease/introduction-to-volume-2. Accessed on Jan. 21,
2021.
\5\ Seshasai, R.K., et al. (2019). The home hemodialysis patient
experience: A qualitative assessment of modality use and
discontinuation. Hemodialysis International, 23: 139-150, 2019.
doi:10.1111/hdi.12713.
\6\ Weinhandl, Eric D., Collins Allan, Incidence of Therapy
Cessation among Home Hemodialysis Patients in the United States,
Abstract presented, American Society of Nephrology Kidney Week 2016.
\7\ Seshasai, R.K., et al. (2019). The home hemodialysis patient
experience: A qualitative assessment of modality use and
discontinuation. Hemodialysis International, 23: 139-150, 2019.
doi:10.1111/hdi.12713.
\8\ Chan, Christopher T. et al. (2018). Exploring Barriers and
Potential Solutions in Home Dialysis: An NKF-KDOQI Conference
Outcomes Report American Journal of Kidney Diseases, Volume 73,
Issue 3, 363-371.
---------------------------------------------------------------------------
[[Page 36334]]
The applicant stated that innovation in making home dialysis more
accessible to patients has been lacking due to a lack of investment
funding, limited incremental reimbursement for new technology, and a
consolidated, price-sensitive dialysis provider market where the lack
of market competition is costly and has been associated with increased
hospitalizations in dialysis patients.\9\ The applicant stated that the
Tablo[supreg] System was designed to address many system-related
barriers that result in patients resigning themselves to in-center care
and/or stopping home modalities due to the burden of self-managed
therapy.
---------------------------------------------------------------------------
\9\ Erickson, K.F., Zheng, Y., Ho, V., Winkelmayer, W.C.,
Bhattacharya, J., & Chertow, G.M. (2018). Market Competition and
Health Outcomes in Hemodialysis. Health services research, 53(5),
3680-3703. https://doi.org/10.1111/1475-6773.12835.
---------------------------------------------------------------------------
The applicant stated that while PD, like HD, removes excess fluid
and waste from the body, it has a different mechanism of action and
relies on the body's own membrane, the peritoneum, to act as the
``dialyzer''. Per the applicant, PD requires surgical placement of a
catheter in the abdomen and utilizes a cleansing fluid, dialysate, that
must be infused and dwell in the abdomen to remove waste products from
the blood. The applicant stated that PD must be conducted daily to
achieve adequate dialysis and can be conducted manually or via a
cycler; while in contrast, HD directly cleanses the blood with the use
of a HD machine, dialysate and a dialyzer, which acts as an artificial
kidney in removing excess fluid and toxins. The applicant stated that
HD also requires surgical placement of a dialysis access, which is
usually in the form of a catheter or a more permanent arteriovenous
fistula.\10\
---------------------------------------------------------------------------
\10\ Blake, P.G., Quinn, R.R., & Oliver, M.J. (2013). Peritoneal
dialysis and the process of modality selection. Peritoneal dialysis
international: journal of the International Society for Peritoneal
Dialysis, 33(3), 233-241. https://doi.org/10.3747/pdi.2012.00119.
---------------------------------------------------------------------------
The applicant asserted that PD is the dominant home therapy used
around the world, but should not be solely relied upon to increase
growth in home dialysis, as there are physiological
contraindications.\11\ The applicant also stated that there is recent
evidence that post 90-day mortality is higher in PD patients than in HD
patients. Per the applicant, multivariable risk-adjusted analyses
demonstrate that the mortality hazard ratio of HD versus PD is 0.74 (95
percent confidence interval (CI), 0.68-0.80) in the 270 to 360-day
period after starting dialysis.\12\ The applicant stated that patients
and clinicians should weigh the risks and benefits of both options and
select the one that meets the individual patient's preferences, goals,
values and physiology. Per the applicant, because PD relies on the
patient's own membrane, physiologic changes can occur and result in
patients who are unable to continue PD due to loss of the ability to
achieve adequacy. The applicant stated that these home patients could
consider home HD rather than a return to in-center and noted that the
practice of transitioning from one home modality to another is
acknowledged by experts to be underutilized and is particularly
pronounced in the U.S., where the ratio of PD use to home HD is
6:1,\13\ as compared to 4:1 in Canada.\14\
---------------------------------------------------------------------------
\11\ Ibid.
\12\ Mukhopadhyay, P., Woodside, K.J., Schaubel, D.E., Repeck,
K., McCullough, K., Shahinian, V.B., . . . & Saran, R. (2020).
Survival among incident peritoneal dialysis versus hemodialysis
patients who initiate with an arteriovenous fistula. Kidney
Medicine, 2(6), 732-741.
\13\ United States Renal Data System. 2020 USRDS Annual Data
Report: Epidemiology of kidney disease in the United States, End-
Stage Renal Disease Chapter 2. National Institutes of Health,
National Institute of Diabetes and Digestive and Kidney Diseases,
Bethesda, MD, 2020. Available at: https://adr.usrds.org/2020/end-stage-renaldisease/introduction-to-volume-2. Accessed on Jan 21,
2021.
\14\ Canada Institute for Health Information (2020): Annual
Statistics. Available at: https://secure.cihi.ca/estore/productSeries.htm?locale=en&pc=PCC24&_ga=2.265337481.729263172.1612199530-510791291.1610562424. Accessed on Jan. 31, 2021.
---------------------------------------------------------------------------
The applicant asserted that that the Tablo[supreg] System presents
a significant clinical improvement over NxStage[supreg] System One
(NxStage[supreg]), the current standard of home HD care, with the goal
of getting patients access to easier to use technology and increasing
the number of patients who can do dialysis at home. Per the applicant,
NxStage[supreg] is the only other mobile HD machine that is approved
for home use.
(1) Renal Dialysis Service Criterion (Sec. 413.236(b)(1))
With respect to the first TPNIES eligibility criterion under Sec.
413.236(b)(1), whether the item has been designated by CMS as a renal
dialysis service under Sec. 413.171, maintenance dialysis treatments
and all associated services, including historically defined dialysis-
related drugs, laboratory tests, equipment, supplies, and staff time,
were included in the composite rate for renal dialysis services as of
December 31, 2010 (75 FR 49036). An in-home HD machine would be
considered equipment necessary for the provision of maintenance
dialysis and, therefore, we would consider this a renal dialysis
service under Sec. 413.171.
(2) Newness Criterion (Sec. 413.236(b)(2))
With respect to the second TPNIES eligibility criterion under Sec.
413.236(b)(2), whether the item is new, meaning within 3 years
beginning on the date of the FDA marketing authorization, the applicant
stated that the Tablo[supreg] System received FDA marketing
authorization for home use on March 31, 2020. Therefore, the
Tablo[supreg] System is considered new. We note that, in reviewing the
enclosure to which the March 31, 2020 FDA authorization letter refers,
the applicant's Section 510(k) submission indicates that the
Tablo[supreg] Cartridge was reviewed separately from the Tablo[supreg]
System and has its own separate 510(k) clearance. As discussed in the
CY 2021 ESRD PPS final rule, CMS determined that the cartridge did not
meet the newness criterion for the TPNIES (85 FR 71464) and as such,
the cartridge is not new.
(3) Commercial Availability Criterion (Sec. 413.236(b)(3))
With respect to the third TPNIES eligibility criterion under Sec.
413.236(b)(3), whether the item is commercial available by January 1 of
the particular calendar year, meaning the year in which the payment
adjustment would take effect, the applicant stated that the
Tablo[supreg] System became available for home use on April 1, 2020.
Therefore, the Tablo[supreg] System is commercially available.
(4) HCPCS Level II Application Criterion (Sec. 413.236(b)(4))
With respect to the fourth TPNIES eligibility criterion under Sec.
413.236(b)(4), whether the applicant submitted a HCPCS Level II code
application by the July 6, 2021 deadline, the applicant stated that it
intends to submit a HCPCS Level II code application by the deadline.
(5) Innovation Criterion (Sec. Sec. 413.236(b)(5) and 412.87(b)(1))
With respect to the fifth TPNIES eligibility criterion under Sec.
413.236(b)(5), that the item is innovative, meaning it meets the SCI
criteria specified in Sec. 412.87(b)(1), the applicant claimed that
the Tablo[supreg] System significantly improves clinical outcomes
relative to the current standard of care for home HD services, which it
identified as the incumbent NxStage[supreg] home dialysis machine. The
applicant presented the following SCI claims: (1) Decreased treatment
frequency with adequate dialysis clearance; (2) increased adherence to
dialysis treatment and retention to home therapy; and (3) improved
patient
[[Page 36335]]
quality of life. The applicant supported these claims with the
Tablo[supreg] Investigational Device Exemption (IDE) Study \15\ and
secondary support from four papers 16 17 18 19 and two
posters.20 21 The applicant also provided comparison data
from three studies directly related to the incumbent
22 23 24 and an additional study that, based on the
timeframe of the study, likely involved participants undergoing
treatment with NxStage[supreg] although the article does not directly
reference the incumbent.\25\
---------------------------------------------------------------------------
\15\ Clinicaltrials.gov website. https://www.clinicaltrials.gov/ct2/show/NCT02460263. Last Updated July 1, 2020. https://www.clinicaltrials.gov/ProvidedDocs/63/NCT02460263/Prot_000.pdf.
\16\ Chertow, G.M., Alvarez, L., Plumb, T.J., Prichard, S.S., &
Aragon, M. (2020). Patient-reported outcomes from the
investigational device exemption study of the Tablo hemodialysis
system. Hemodialysis International, 24(4), 480-486.
\17\ Leypoldt, J.K., Prichard, S., Chertow, G.M., & Alvarez, L.
(2019). Differential molecular modeling predictions of mid and
conventional dialysate flows. Blood purification, 47(4), 369-376.
\18\ Safety and efficacy of the Tablo hemodialysis system for
in-center and home hemodialysis Plumb, T.J., Alvarez, L., Ross,
D.L., Lee, J.J., Mulhern, J.G., Bell, J.L., Abra, G., Prichard,
S.S., Chertow, G.M. and Aragon, M.A. (2019), Hemodialysis
International.
\19\ Plumb, Troy J., Luis Alvarez, Dennis L. Ross, Joseph J.
Lee, Jeffrey G. Mulhern, Jeffrey L. Bell, Graham E. Abra, Sarah S.
Prichard, Glenn M. Chertow, and Michael A. Aragon. ``Self-care
training using the Tablo hemodialysis system.'' Hemodialysis
International (2020).
\20\ Alvarez, Luis et al. Urea Clearance Results in Patients
Dialyzed Thrice Weekly Using a Dialysate Flow of 300 mL/min,
clinical abstract, presented March 2019, Annual Dialysis Conference,
Dallas, TX.
\21\ Chahal, Y., Plumb, T., Aragon M. (2020). Patient Device
Preference for Home Hemodialysis: A Subset Analysis of the Tablo
Home IDE Trial. Poster Presentation at National Kidney Foundation
Spring Clinical Conference, March 2020.
\22\ Kraus, M., et al., A comparison of center-based vs. home-
based daily hemodialysis for patients with end-stage renal disease.
Hemodialysis International, 11: 468-477, (2007).
\23\ Finkelstein, F.O., et al. (2012). At-home short daily
hemodialysis improves the long-term health-related quality of life.
Kidney international, 82(5), 561-569.
\24\ Weinhandl, E.D., Gilbertson, D.T., & Collins, A.J. (2016).
Mortality, hospitalization, and technique failure in daily home
hemodialysis and matched peritoneal dialysis patients: A matched
cohort study. American Journal of Kidney Diseases, 67(1), 98-110.
\25\ Suri, R.S., Li, L., & Nesrallah, G.E. (2015). The risk of
hospitalization and modality failure with home dialysis. Kidney
international, 88(2), 360-368.
---------------------------------------------------------------------------
We provide an overview of these ten sources below, followed by the
applicant's summary of how the data support each claim of SCI. We
conclude with a discussion of the way in which we have applied the
requirements of Sec. 413.236(b)(5) to our review of the application
and a summary of our concerns. We have not included detailed summaries
of the remaining supplemental content included with the application.
Specifically, the applicant submitted numerous supplemental background
materials related to the dialysis industry, reimbursement patterns,
modalities, treatment frequencies, patient adherence, hospitalization
rates, and quality of life. The applicant also submitted several
letters of support for the Tablo[supreg] System; three from dialysis
patients, three from nephrologists, and one from a dialysis clinic
nurse. These letters emphasized benefits of the Tablo[supreg] System,
including reduced frequency of dialysis treatment, improved home
dialysis retention, reduced patient and caregiver burden, reduced
patient fatigue, and improved patient quality of life.
(a) Applicant SCI Sources
As stated previously, the applicant's primary support for its three
SCI claims comes from a prospective, multicenter, open-label, non-
randomized crossover study that compared in-center and in-home HD
performance using the Tablo[supreg] System. Per the applicant, this
study is referred to as the Tablo[supreg] Investigational Device
Exemption (IDE) Study and the original study protocol and amendments
were approved by FDA and registered on http://www.clinicaltrials.gov as
ID: NCT02460263. The applicant stated that of the 30 participants
enrolled (17 White and 13 Black or African American), 28 (18 men and 10
women) completed the study. Thirteen of the participants had previous
home HD experience with NxStage[supreg], and the remainder had
previously received conventional in-center HD care. The applicant also
noted that the Tablo[supreg] IDE study sample was comprised of a
representative cohort of dialysis patients and reports that it was
similar to the population studied for the IDE study for the incumbent
NxStage[supreg]. As described in the study protocol, the primary and
secondary efficacy endpoints were a standardized weekly Kt/V of greater
than or equal to 2.1 and ultrafiltration (fluid removal) value as
reported by the device within ten percent of the expected fluid removal
based on the ultrafiltration prescription and the Tablo[supreg] Console
fluid removal algorithm, respectively.\26\ We clarify that Kt/V is a
value used to quantify dialysis treatment adequacy and ``K'' = dialyzer
clearance, ``t'' = time, and ``V'' = Volume of distribution of urea.
The applicant stated that each participant served as his or her own
control and remained in the trial for approximately 21 weeks, during
which time they were prescribed HD with the Tablo[supreg] System on a 4
times per week schedule. The applicant explained that the trial
consisted of 4 treatment periods: (1) A 1 week, in-center run-in
period; (2) an in-center period of 32 treatments (approximately 8
weeks) during which ESRD facility staff managed the dialysis
treatments; (3) a transition period of up to 4 weeks to train the
patient and care partner in managing the dialysis; and (4) a final in-
home period of 32 treatments (approximately 8 weeks).
---------------------------------------------------------------------------
\26\ Clinicaltrials.gov website. https://www.clinicaltrials.gov/ct2/show/NCT02460263. Last Updated July 1, 2020. https://www.clinicaltrials.gov/ProvidedDocs/63/NCT02460263/Prot_000.pdf.
---------------------------------------------------------------------------
With respect to the applicant's secondary sources of support, a
poster presentation from Alvarez, et al., presented dialysis adequacy
data collected from a retrospective review of 29 patients' (18 males,
11 females and 17 percent Black, 10 percent Hispanic) dialysis records.
The study compared Kt/V results of patients aged 34-84 receiving
dialysis using the Tablo[supreg] System to patients receiving dialysis
from a conventional HD machine. The majority of patients used a fistula
or graft (59 percent fistula, 28 percent graft, 10 percent catheter).
One hundred ninety two dialysis treatments were conducted on a thrice-
weekly schedule using the Tablo[supreg] System with a dialysate flow
rate of 300 mL per minute. A single pool Kt/V of greater than 1.2 was
achieved in 94 percent of treatments in patients less than 90 kg with
an average duration of treatment at 224 +/-29 minutes and in 79 percent
of treatments in patients greater than 90 kg with an average duration
of treatment at 249 +/-27 minutes. The average achieved Kt/V was 1.4 +/
-0.2 among treatments provided with the Tablo[supreg] System. Eighty-
eight treatments were conducted using a conventional HD machine with a
dialysate flow rate of 500 mL per minute. A single pool Kt/V of greater
than 1.2 was achieved in 93 percent of treatments in patients less than
90 kg with an average duration of treatment at 227 +/-21 minutes and in
83 percent of treatments in patients greater than 90 kg with an average
duration of treatment at 249 +/-14 minutes. The average achieved Kt/V
was 1.6 +/-0.4 among the conventional HD treatments.\27\
---------------------------------------------------------------------------
\27\ Alvarez, Luis et al. Urea Clearance Results in Patients
Dialyzed Thrice Weekly Using a Dialysate Flow of 300 mL/min,
clinical abstract, presented March 2019, Annual Dialysis Conference,
Dallas, TX.
---------------------------------------------------------------------------
Next, an article from Chertow, et al., described additional data
from the Tablo[supreg] IDE study (discussed previously), including
health-related quality of life, to further assess the safety of home HD
with the Tablo[supreg]
[[Page 36336]]
System. Demographic information identified the mean age as 49.8 13 years, 62 percent male, 62 percent White, 38 percent Black or
African American, 23 percent Hispanic or Latino, 68 percent Not
Hispanic or Latino, and 8 percent not reported, among patients
established on home HD. Among the patients new to home HD, the mean age
was identified as 54.2 10.4 years, 65 percent male, 53
percent White, 47 percent Black or African American, 29 percent
Hispanic or Latino, 71 percent Not Hispanic or Latino, and 0 percent
not reported. Twenty-eight of 30 patients (93 percent) completed all
trial periods. Adherence to the prescribed 4 treatments per week
schedule was 96 percent in-center and 99 percent in-home. The median
time to recovery was 1.5 hours during the in-center and 2 hours during
the at-home phase of the trial. Median index values on the 5-level
EuroQol-5 Dimension (EQ-5D-5L) (a self-assessed, health related,
quality of life questionnaire) were similar during the in-center as
compared to in-home dialysis at 0.832 and 0.826, respectively. Patients
new to home HD had lower median values (0.751) for both in-center and
in-home periods. Patients who had used home dialysis prior to the trial
had higher median values during both in-center (0.903) and in-home
(0.906) periods. Patients reported feeling alert or well-rested with
little difficulty falling or staying asleep or feeling tired and worn
out when using the Tablo[supreg] System in either environment. The
authors concluded that when using the Tablo[supreg] System in-home,
patients reported similar time to recovery, general health status, and
sleep quality compared to using the Tablo[supreg] System in-center.\28\
---------------------------------------------------------------------------
\28\ Chertow, G.M., Alvarez, L., Plumb, T.J., Prichard, S.S., &
Aragon, M. (2020). Patient-reported outcomes from the
investigational device exemption study of the Tablo hemodialysis
system. Hemodialysis International, 24(4), 480-486.
---------------------------------------------------------------------------
Next, an article from Leypoldt, et al., described the use of uremic
solute kinetic models to assess dialysis adequacy via theoretical
single pool Kt/V levels when varying the dialysis blood flow rates and
the patient urea volume of distribution. A comparison was made between
dialysate flows of 300 and 500 mL/min at blood flows of both 300 and
400 mL/min. The patient urea volume of distribution range modeled by
the authors ranged from 25 to 45 L. Under ideal conditions, the authors
demonstrate that with a blood flow of 300 mL per minute, a single pool
Kt/V of greater than 1.2 could be achieved in patients with a urea
volume of distribution of 35 L and 240 minutes of dialysis. Patients
with a urea volume of distribution of 40 L would require 255 minutes of
dialysis. Patients with a urea volume of distribution of 45 L would
require over 270 minutes of dialysis. With a blood flow of 400 mL per
minute, patients with a urea volume of distribution of 40 L could
achieve the target single pool Kt/V of greater than 1.2 with 240
minutes of dialysis. Patients with a volume of distribution of 45 L
could achieve the target with 270 minutes of dialysis. The authors did
not model urea kinetics for patients with volumes of distribution
greater than 45 L.\29\
---------------------------------------------------------------------------
\29\ Leypoldt, J.K., Prichard, S., Chertow, G.M., & Alvarez, L.
(2019). Differential molecular modeling predictions of mid and
conventional dialysate flows. Blood purification, 47(4), 369-376.
---------------------------------------------------------------------------
Next, an article by Plumb, et al., described the Tablo[supreg] IDE
study (discussed previously). Demographic information reflected the
mean age as 52.3 11.6 years, 19 men and the following
racial and ethnic representation: 17 White, 13 Black or African
American, 8 Hispanic or Latino, and 21 Not Hispanic or Latino.
Comparisons among the 28 patients in this study and subsequent
secondary analyses were either made between the 8 weeks of using the
Tablo[supreg] System for in-center HD and the 8 weeks of the
Tablo[supreg] System for in-home HD or between using the Tablo[supreg]
System in-home HD and the treatment provided prior to study enrollment.
In both settings, patients dialyzed using the Tablo[supreg] System 4
times per week. The primary efficacy endpoint was achievement of a
weekly standard Kt/V greater than or equal to 2.1 in both the 8-week
in-center phase of the study and the 8-week in-home phase of the study.
This endpoint was achieved in 199 of 200 weeks in the in-center
dialysis period and in 168 of 171 weeks in the in-home dialysis period.
The primary safety endpoint of adverse event rates were similar at 1.9
percent in the in-center dialysis period and 1.8 percent in the in-home
dialysis period. The secondary efficacy endpoint was whether the
ultrafiltration volume and rate achieved the prescribed levels. In both
in-center and in-home dialysis, 94 percent of treatments achieved
successful delivery of ultrafiltration, defined as a rate within ten
percent of the prescribed value. Of 960 in-center dialysis services and
896 in-home dialysis services, 922 and 884 were completed respectively,
yielding adherence rates of 96 percent and 99 percent.\30\
---------------------------------------------------------------------------
\30\ Safety and efficacy of the Tablo hemodialysis system for
in-center and home hemodialysis Plumb, T.J., Alvarez, L., Ross,
D.L., Lee, J.J., Mulhern, J.G., Bell, J.L., Abra, G., Prichard,
S.S., Chertow, G.M. and Aragon, M.A. (2019), Hemodialysis
International.
---------------------------------------------------------------------------
Next, a separate article by Plumb et al., reports additional data
from the Tablo[supreg] IDE study (previously discussed) regarding
participants' assessment of the Tablo[supreg] System's ease-of-use, the
degree of dependence on health care workers and caregivers after
training with the system was complete, and the training time required
for a participant to be competent in self-care. Demographic information
reflected the mean age as 52.6 years, 18 men, 10 women, 16 White, 7
Hispanic or Latino, 9 Not Hispanic or Latino, and 12 Black or African
American. Participants were stratified according to whether they were
previously on self-care dialysis at home or conventional in-center HD.
Thirteen participants had previous experience performing self-care HD.
The remaining 15 participants had previous experience with in-center HD
only. All participants rated the Tablo[supreg] System's setup,
treatment, and takedown on a scale from 1 (very difficult) to 5 (very
simple) and indicated whether they had required assistance with
treatment over the prior 7 days. Set up times were similar regardless
of whether the participants were previously on self-care HD or
conventional in-center HD. For the participants previously on in-center
HD, the average set up time for the concentrates was 0.93 minutes and
for the cartridge, 9.35 minutes. For participants previously on self-
care home HD, the average set up time for the concentrates was 1.22
minutes and for the cartridge, 10.28 minutes. The average rating of the
Tablo[supreg] System's ease of use for setup was 4.5, treatment 4.6,
and take down 4.6 among the participants previously on self-care home
HD. In comparison, based on recollection (not based on rating during
time of use) these participants' average rating of their previous
device's ease of use for setup was 3.5, treatment 3.3, and take down
3.8. The average rating of the Tablo[supreg] System's ease of use for
setup and treatment was 4.6 and 4.7 for take down among participants
without prior self-care experience.
Among patients surveyed, caregiver assistance was required in 62
percent of patient-weeks during home self-care. Participants previously
on self-care home HD required some caregiver assistance in 42 percent
of the in-home dialysis treatment weeks. Participants previously on
conventional in-center dialysis required some caregiver assistance in
35 percent of the in-home dialysis treatment weeks. The requirement for
some form of assistance
[[Page 36337]]
among participants with or without previous self-care experience was
not meaningfully different. Finally, the authors noted that a protocol
amendment allowed for the recording of the number of training sessions
necessary to deem a patient competent to do self-care dialysis. This
recording was limited to the last 15 participants enrolled into the
study. Five of these participants had previous self-care dialysis at
home experience. The average number of training sessions required to be
deemed competent was 3.6 for participants with previous self-care
dialysis at home experience and 3.9 sessions for participants with only
conventional in-center HD experience.\31\
---------------------------------------------------------------------------
\31\ Plumb, Troy J., Luis Alvarez, Dennis L. Ross, Joseph J.
Lee, Jeffrey G. Mulhern, Jeffrey L. Bell, Graham E. Abra, Sarah S.
Prichard, Glenn M. Chertow, and Michael A. Aragon. ``Self-care
training using the Tablo hemodialysis system.'' Hemodialysis
International (2020).
---------------------------------------------------------------------------
Next, a poster presentation from Chahal et al., reported patient
device preference of prior in-home HD patients based on data from the
Tablo[supreg] IDE study (previously discussed). The authors noted that
13 of the 30 participants in the Tablo[supreg] IDE trial were
performing in-home HD at the time of enrollment and that prior to the
study, dialysis prescriptions averaged 4.5 treatments per week with an
average time of 3.1 hours per session. Trial prescriptions were for 4
days per week and an average of 3.4 hours per session. Adherence to the
study regimen was 97 percent and 92 percent of surveys were completed.
The authors concluded that participants with prior home HD experience
preferred the Tablo[supreg] System compared to their prior device and
85.6 percent found that the Tablo[supreg] System was easier to use.\32\
---------------------------------------------------------------------------
\32\ Chahal, Y., Plumb, T., Aragon M. (2020). Patient Device
Preference for Home Hemodialysis: A Subset Analysis of the Tablo
Home IDE Trial. Poster Presentation at National Kidney Foundation
Spring Clinical Conference, March 2020.
---------------------------------------------------------------------------
As stated previously in this section of the proposed rule, the
applicant submitted several sources pertaining to the incumbent,
NxStage.[supreg] First, an article from Kraus et al., describes a
feasibility study to demonstrate the safety of center-based versus
home-based daily HD with the NxStage[supreg] portable HD device. This
retrospective analysis examined the extent to which clinical effects
previously associated with short-daily dialysis were also seen using
the NxStage[supreg] device. The authors conducted a prospective, two-
treatment, two-period, open-label, crossover study of in-center HD vs.
home HD in 32 patients treated at six U.S. centers. Demographic
information reflected the mean age as 51 years, 63 percent male, 38
percent female, 24 White, 6 Black or African American, 1 American
Indian or Alaskan native, and 1 Asian. The 8-week In-Center Phase (6
days/week) was followed by a 2-week transition period and then followed
by the 8-week Home Phase (6 days/week). Data was collected
retrospectively on HD treatment parameters immediately preceding the
study in a subset of patients. Twenty-six out of 32 patients (81
percent) successfully completed the study. Treatment compliance
(defined as completing 43 to 48 treatments in a given phase) was
comparable between the 2 treatment environments (88 percent In-Center
vs. 89 percent Home). Successful delivery of at least 90 percent of
prescribed fluid volume (primary endpoint) was achieved in 98.5 percent
of treatments in-center and 97.3 percent at home. Total effluent volume
as a percentage of prescribed volume was between 94 percent and 100
percent for all study weeks. The composite rate of intradialytic and
interdialytic adverse events per 100 treatments was significantly
higher for the In-Center Phase (5.30) compared with the Home Phase
(2.10; p=0.007). Compared with the period immediately preceding the
study, there were reductions in blood pressure, antihypertensive
medications, and interdialytic weight gain. The study concluded that
daily home HD with a small, easy-to-use HD device is a viable dialysis
option for ESRD patients capable of self/partner administered
dialysis.\33\
---------------------------------------------------------------------------
\33\ Kraus, M., et al., A comparison of center-based vs. home-
based daily hemodialysis for patients with end-stage renal disease.
Hemodialysis International, 11: 468-477, (2007).
---------------------------------------------------------------------------
Second, an article from Finkelstein et al., reports on interim
results of the Following Rehabilitation, Economics and Everyday-
Dialysis Outcome Measurements (FREEDOM) study, a multi-center,
prospective, cohort study of at-home short daily HD with a planned 12-
month follow-up (ClinicalTrials.gov identifier, NCT00288613). Eligible
patients were adults with ESRD requiring dialysis who were being
initiated on short daily HD (prescribed 6 times per week) at home using
the NxStage[supreg] cycler and who had Medicare as their primary
insurance payer. The authors examined the long-term effect of short
daily HD on health-related quality of life, as measured by the Short
Form-36 (SF-36) health survey. The survey was administered at baseline,
4 and 12 months after initiation of short daily HD to 291 (total
cohort) participants. Demographic information reflected the mean age as
53 years, 66 percent male and 70 percent White. Of the 291
participants, 154 completed the 12-month follow-up (as-treated cohort).
In the total cohort analysis, both the physical- and mental-
component summary scores improved over the 12-month period, as did all
8 individual domains of the SF-36. The as-treated cohort analysis
showed similar improvements with the exception of the role-emotional
domain. Significantly, in the as-treated cohort, the percentage of
patients achieving a physical component summary score at least
equivalent to the general population more than doubled. The authors
concluded by noting that at-home short daily HD is associated with
long-term improvements in various physical and mental health-related
quality of life measures.\34\
---------------------------------------------------------------------------
\34\ Finkelstein, F.O., et al. (2012). At-home short daily
hemodialysis improves the long-term health-related quality of life.
Kidney International, 82(5), 561-569.
---------------------------------------------------------------------------
Third, in Weinhandl et al., authors described a cohort study in
which 4,201 new home HD patients in 2007 were matched with 4,201 new PD
patients in 2010 from the United States Renal Data System (USRDS)
database to assess relative mortality, hospitalization, and technique
failure. Demographic information reflected the mean age as 53.8 14.9 years, 67 percent male, 33 percent female, 24.4 percent
Black, and 75.6 percent Nonblack. Daily home HD patients initiated use
of NxStage[supreg] from 2007 through 2010. Authors reported home HD was
associated with 20 percent lower risk for all-cause mortality, 8
percent lower risk for all-cause hospitalization, and 37 percent lower
risk for technique failure, all relative to PD. Regarding
hospitalization, risk comparisons favored home HD for cardiovascular
disease and dialysis access infection and PD for bloodstream infection.
Authors noted that matching was unlikely to reduce confounding
attributable to unmeasured factors, including residual kidney function;
lack of data regarding dialysis frequency, duration, and dose in daily
home HD patients and frequency and solution in PD patients; and
diagnosis codes used to classify admissions. The authors concluded that
these data suggest that relative to peritoneal dialysis, daily home HD
is associated with decreased mortality, hospitalization, and technique
failure but that risks for mortality and hospitalization were similar
with these modalities in new dialysis patients.\35\
---------------------------------------------------------------------------
\35\ Weinhandl, E.D., Gilbertson, D.T., & Collins, A.J. (2016).
Mortality, hospitalization, and technique failure in daily home
hemodialysis and matched peritoneal dialysis patients: A matched
cohort study. American Journal of Kidney Diseases, 67(1), 98-110.
---------------------------------------------------------------------------
[[Page 36338]]
Fourth, in Suri et al., 1116, daily home HD patients were matched
by propensity scores to 2784, contemporaneous USRDS patients receiving
home peritoneal dialysis. The authors compared hospitalization rates
from cardiovascular, infectious, access-related or bleeding causes, and
modality failure risk. Similar analyses were performed for 1187, daily
home HD patients matched to 3173, USRDS patients receiving in-center
conventional HD. Demographic information identified the mean age as
50.5 years, 67.3 percent male, 70.9 percent White, 26.6 percent Black,
and 2.5 percent Other, among the daily home HD patients. Among the home
PD patients, the mean age was identified as 50.9 years, 66.9 percent
male, 73.1 percent White, 25.1 percent Black and 1.2 percent Other. The
composite hospitalization rate was significantly lower with daily home
HD than with PD (0.93 vs. 1.35/patient-year). Daily home HD patients
spent significantly fewer days in the hospital than PD patients (5.2
vs. 9.2 days/patient-year), and significantly more daily home HD
patients remained admission-free (52 percent daily home dialysis vs. 32
percent peritoneal dialysis). In contrast, there was no significant
difference in hospitalizations between daily home HD and conventional
HD (0.93 vs. 1.10/patient-year). Cardiovascular hospitalizations were
lower with daily home HD than with conventional HD (0.68) while
infectious and access hospitalizations were higher (1.15) and 1.25
respectively). Significantly more PD than daily home HD patients
switched back to in-center HD (44 percent vs. 15 percent). In this
prevalent cohort, daily home HD was associated with fewer admissions
and hospital days than PD, and a substantially lower risk of modality
failure.\36\
---------------------------------------------------------------------------
\36\ Suri, R.S., Li, L., & Nesrallah, G.E. (2015). The risk of
hospitalization and modality failure with home dialysis. Kidney
International, 88(2), 360-368.
---------------------------------------------------------------------------
(b) Applicant SCI Claims
Regarding the applicant's first claim that the Tablo[supreg] System
decreases treatment frequency with adequate dialysis clearance, the
applicant stated that the Tablo[supreg] System is the only mobile HD
device approved for use in the home that can achieve adequate dialysis
in as little as 3 treatments per week, while also providing flexibility
for more frequent dialysis and thus greater personalization of care.
The applicant stated that adequate dialysis for a standard, thrice
weekly treatment schedule is a single treatment clearance of urea,
expressed as a single-pool Kt/V (spKt/V) of greater than 1.2 where
``K'' = dialyzer clearance, ``t'' = time, and ``V'' = Volume of
distribution of urea. The applicant also stated that dialyzer
clearance, or ``K'', is dependent on the mass transfer coefficient
(KoA) characteristics of the prescribed dialyzer and prescribed blood
and dialysate flow rates. The applicant further noted that limitations
in ``K'' or ``t'' affect the ability of a patient to achieve adequate
clearance during a dialysis treatment. Per the applicant, across a
broad range of weights, patients using the Tablo[supreg] System can
achieve the target of dialysis adequacy, a single pool Kt/V of 1.2,
with 3 treatments per week in less than 4 hours.\37\ The applicant also
stated that when used 4 times per week, patients using the
Tablo[supreg] System had a higher mean weekly standard Kt/V with
equivalent or better dialysis-related hospitalization rates,\38\ as
compared to NxStage[supreg] IDE patients prescribed therapy at 6 days
per week.\39\
---------------------------------------------------------------------------
\37\ Alvarez, Luis et al. Urea Clearance Results in Patients
Dialyzed Thrice Weekly Using a Dialysate Flow of 300 mL/min,
clinical abstract, presented March 2019, Annual Dialysis Conference,
Dallas, TX.
\38\ Plumb, T.J., Alvarez, L., Ross, D.L., Lee, J.J., Mulhern,
J.G., Bell, J.L., Abra, G., Prichard, S.S., Chertow, G.M. and
Aragon, M.A. (2019). Safety and efficacy of the Tablo hemodialysis
system for in-center and home hemodialysis. Hemodialysis
International.
\39\ NxStage Clearance Calculator. Available at: https://dosingcalculator.nxstage.com/DosingCalculator/. Accessed on Jan 21,
2021.
---------------------------------------------------------------------------
The applicant stated that the Tablo[supreg] System's on-demand
dialysate production has no limitation to the volume of dialysate that
can be produced and used during a single treatment. The applicant
further stated that this facilitates the delivery of adequate dialysis
clearance (Kt/V) in a standard duration and target frequency of 3 times
per week, as well as alternate frequencies and durations as preferred
by a patient or recommended by a health care provider.
The applicant asserted that NxStage,[supreg] when attached to its
Pureflow device, requires users to batch a set amount of dialysate
(maximum of 60 liters) in advance of a treatment or use sterile
dialysate bags (maximum of 30 liters). The applicant also stated that
at its maximum dialysate flow rate (Qd) of 300ml/min, NxStage[supreg]
greatly limits time by restricting treatment to a maximum of 200
minutes before exhausting its dialysate capacity (200 min = 60L/300ml/
min).
The applicant stated that Dialysis Outcomes and Practice Patterns
Study (DOPPS) data demonstrate that the current U.S. practice for
thrice weekly dialysis occurs at an average treatment time of greater
than 220 minutes, and has increased in the last 25 years.\40\ Per the
applicant, with the limited ``t'', a single-pooled Kt/V of >1.2 cannot
be expected to be achieved for the majority of U.S. patients with ESRD
on a thrice weekly schedule, requiring increased treatment frequency
\41\ at home for these patients to meet the desired clearance level.
---------------------------------------------------------------------------
\40\ Tentori F, Zhang J, Li Y, Karaboyas A, Kerr P, Saran R,
Bommer J, Port F, Akiba T, Pisoni R, Robinson B. Longer dialysis
session length is associated with better intermediate outcomes and
survival among patients on in-center three times per week
hemodialysis: results from the Dialysis Outcomes and Practice
Patterns Study (DOPPS). Nephrol Dial Transplant. 2012
Nov;27(11):4180-8. doi: 10.1093/ndt/gfs021. Epub 2012 Mar 19. PMID:
22431708; PMCID: PMC3529546.
\41\ Health Management Associates (HMA) analysis of 2018 100%
Medicare Outpatient file.
---------------------------------------------------------------------------
In citing Leypoldt et al., the applicant stated that data from the
Hemodialysis (HEMO) trial combined with modeling results from Leypoldt
et al.,\42\ allow for an estimation of the patients with ESRD, based on
weight, that cannot be expected to achieve target clearance with
standard thrice weekly dialysis at this treatment duration. The
applicant explained that because urea is evenly distributed throughout
a body's water, the volume of distribution of urea is equal to a
patient's total volume of water. The applicant also stated that total
body water and volume of distribution of urea can be expressed as a
volume or as a percentage of total weight and can vary based on
numerous factors including disease state. The applicant stated that it
is possible to estimate the percent of water for the ESRD population
from the HEMO trial as summarized in Leypoldt et al.\43\ The applicant
stated that in the trial, the mean patient weight was 69.8kg and the
mean patient volume of body water (V) was 30.9L. The applicant further
explained that from this, total body water (and volume of distribution
of urea) are calculated as 44.3 percent of the mean weight of patients
with ESRD (44.3 = 30.9L/69.8kg x 100). Per the applicant, applying this
44.3 percent of total body weight to the volumes of distribution in
Leypoldt et al.\44\ allows the conversion of the kinetic model
described into anticipated patient weights. The applicant further
stated
[[Page 36339]]
that in calculating with standard blood flow and a higher dialyzer mass
transfer area coefficient for urea (KoA) diayzer, a 200 minute
treatment at a dialysate flow rate (Qd) of 300ml/min would not achieve
what the applicant refers to as the CMS target spKt/V target 1.2 for
patients with a volume of distribution of urea (V) of 35L or greater.
The applicant stated that these assumptions were drawn from
NxStage[supreg] technical specifications.45 46 The applicant
stated that at 44.3 percent of total weight, this volume of
distribution of urea correlates to patients with ESRD with a mean
weight above 79 kg (79 = 35L/.443) or approximately 174 pounds. Per the
applicant, patients at or above this weight cannot be expected to
achieve a spKt/V urea of 1.2 on a thrice weekly schedule using the
NxStage[supreg] system at its maximal dialysate flow rate.
---------------------------------------------------------------------------
\42\ Leypoldt, J.K., Prichard, S., Chertow, G.M., & Alvarez, L.
(2019). Differential molecular modeling predictions of mid and
conventional dialysate flows. Blood Purification, 47(4), 369-376.
\43\ Ibid.
\44\ Ibid.
\45\ Leypoldt, J.K., Prichard, S., Chertow, G.M., & Alvarez, L.
(2019). Differential molecular modeling predictions of mid and
conventional dialysate flows. Blood Purification, 47(4), 369-376.
\46\ Daugirdas JT, Greene T, Depner TA, Chumela C, Rocco, MJ,
Chertow, GM for the Hemodialysis (HEMO) Study Group.
Anthropometrically Estimated Total Body Water Volumes are Larger
than Modeled Urea Volume in Chronic Hemodialysis Patients: Effects
of Age, Race and Gender. 2003. Kidney Int. 64:1108-1119.
---------------------------------------------------------------------------
The applicant stated that for the majority of the U.S. prevalent
ESRD population between the ages of 22-74, whose mean weight is between
84.3-89.1 kg by age group,\47\ thrice weekly therapy at home on
NxStage[supreg] would not achieve the Medicare coverage standard.
Specifically, per the applicant, Medicare's national coverage policy is
to reimburse for dialysis care 3 times per week, regardless of the
modality that is used and health care providers are expected to ensure
that patients receive adequate clearance with the 3 times per week
cadence. The applicant also stated that Medicare Administrative
Contractors (MACs) have discretion in reimbursing additional treatments
with medical justification.\48\ Per the applicant, an analysis of
Medicare claims data from 2018 finds that despite the limitations of
the reimbursement policy, Medicare is paying for 5 or more treatments
per week in 50 percent of home HD patients nationwide, amounting to an
estimated annual cost to Medicare of $122 to $126 million.\49\ However,
based on CMS review of dialysis facility claims data, among all
beneficiaries who had home dialysis treatments in 2018, 39.1 percent
had 5 or more dialysis sessions at least once during any week. The
overall percentage of beneficiary-weeks that had 5 or more home HD
sessions in 2018 was 20.9 percent. Medicare payment for these
additional sessions totaled $17 million. We note that, as indicated in
Local Coverage Determination ID L35014, ``Frequency of Dialysis''
(revised effective September 26, 2019),\50\ CMS established payment for
HD based on conventional treatment which is defined as 3 times per
week. Sessions in excess of 3 times per week must be both reasonable
and necessary in order to receive payment. Covered indications include
metabolic conditions (acidosis, hyperkalemia, hyperphosphatemia), fluid
positive status not controlled with routine dialysis, pregnancy, heart
failure, pericarditis, and incomplete dialysis secondary to hypotension
or access issues. The applicant asserted that the use of the
Tablo[supreg] System would decrease the number of necessary dialysis
treatments, without affecting patient outcomes such as clearance or
hospitalizations.
---------------------------------------------------------------------------
\47\ United States Renal Data System. 2020 USRDS Annual Data
Report: Epidemiology of kidney disease in the United States, End-
Stage Renal Disease Chapter 2. National Institutes of Health,
National Institute of Diabetes and Digestive and Kidney Diseases,
Bethesda, MD, 2020. Available at: https://adr.usrds.org/2020/end-stage-renaldisease/introduction-to-volume-2. Accessed on Jan 21,
2021.
\48\ Wilk, A.S., Hirth, R.A., Zhang, W., Wheeler, J.R., Turenne,
M.N., Nahra, T.A., . . . & Messana, J.M. (2018). Persistent
variation in Medicare payment authorization for home hemodialysis
treatments. Health services research, 53(2), 649-670.
\49\ Health Management Associates (HMA) analysis of 2018 100
percent Medicare Outpatient file.
\50\ Medicare Coverage Database. Retrieved May 24, 2021 from:
https://www.cms.gov/medicare-coverage-database/details/lcd-details.aspx?LCDId=35014&ver=39&NCDId=79&ncdver=1&SearchType=Advanced&CoverageSelection=Both&NCSelection=NCA%7CCAL%7CNCD%7CMEDCAC%7CTA%7CMCD&ArticleType=Ed%7CKey%7CSAD%7CFAQ&PolicyType=Final&s=-%7C5%7C6%7C66%7C67%7C9%7C38%7C63%7C41%7C64%7C65%7C44&KeyWord=transplant&KeyWordLookUp=Doc&KeyWordSearchType=Exact&kq=true&bc=IAAAADgAAAAA&
.
---------------------------------------------------------------------------
The applicant stated that there is clinical evidence and expert
consensus that as treatment frequency increases, native residual kidney
function drops, patient and care partner burden increases, and vascular
access complications increase.51 52 Per the applicant, home
use of the Tablo[supreg] System can reduce the need for a fifth or
sixth weekly treatment without increasing patients' symptom burden.\53\
The applicant stated that by achieving adequacy targets with fewer
treatments, Tablo[supreg] System patients can be expected to have fewer
vascular access interventions and health care providers will have
increased flexibility in personalizing the frequency and duration of
patient treatments.54 55 The applicant stated that reducing
treatment frequency while maintaining adequate patient clearance levels
may also reduce complications that lead to hospitalizations. The
applicant stated that during the Tablo[supreg] IDE study, patients
using the Tablo[supreg] System 4 times per week, for an average
duration of less than 4 hours per treatment, had an all-cause hospital
admission rate of 426 per 1,000 patient-years whereas in the general
dialysis population, the all-cause admission rate is 1,688 per 1,000
patient-years, and for patients who utilize peritoneal dialysis, the
hospitalization rate is 1,460 per 1,000 patient years.\56\
---------------------------------------------------------------------------
\51\ National Kidney Foundation. KDOQI clinical practice
guideline for hemodialysis adequacy: 2015 update. Am J Kidney Dis.
2015;66(5):884-930.
\52\ Shafi T, Wilson RF, Greer R, Zhang A, Sozio S, Tan M, Bass
EB. End-stage Renal Disease in the Medicare Population: Frequency
and Duration of Hemodialysis and Quality of Life Assessment.
Technology Assessment Program Project ID No. JHE51000. (Prepared by
the Johns Hopkins University Evidence-based Practice Center under
contract number HHSA 290-2015-00006I) Rockville, MD: Agency for
Healthcare Research and Quality. July 2020. Available at: http://www.ahrq.gov/research/findings/ta/index.html.
\53\ Safety and efficacy of the Tablo hemodialysis system for
in-center and home hemodialysis Plumb, T.J., Alvarez, L., Ross,
D.L., Lee, J.J., Mulhern, J.G., Bell, J.L., Abra, G., Prichard,
S.S., Chertow, G.M. and Aragon, M.A. (2019), Hemodialysis
International.
\54\ FHN Trial Group. (2010). In-center hemodialysis six times
per week versus three times per week. New England Journal of
Medicine, 363(24), 2287-2300.
\55\ Kuo, T.H., Tseng, C.T., Lin, W.H., Chao, J.Y., Wang, W.M.,
Li, C.Y., & Wang, M.C. (2015). Association Between Vascular Access
Dysfunction and Subsequent Major Adverse Cardiovascular Events in
Patients on Hemodialysis: A Population-Based Nested Case-Control
Study. Medicine, 94(26).
\56\ United States Renal Data System. 2020 USRDS Annual Data
Report: Epidemiology of kidney disease in the United States, End-
Stage Renal Disease Chapter 2. National Institutes of Health,
National Institute of Diabetes and Digestive and Kidney Diseases,
Bethesda, MD, 2020. Available at: https://adr.usrds.org/2020/end-stage-renaldisease/introduction-to-volume-2. Reference Table G2.
---------------------------------------------------------------------------
The applicant stated that while NxStage[supreg] has not
specifically reported the hospitalization rates per patient-year from
its IDE study, published data from Weinhandl et al.,\57\ and Suri et
al.,\58\ report hospital admission rates amongst patients on daily home
HD ranging from 930 to 1,663 per 1,000 patient-years, using a national
sample of dialysis patients matched for comparison to similar
peritoneal and in-center dialysis patients. We clarify that this would
represent 930 to 1,663 cases observed
[[Page 36340]]
among 1,000 persons during 1 year. The applicant also noted that all
data on home patients in Weinhandl et al. came from a matched cohort of
NxStage[supreg] patients. Per the applicant, in Suri et al., data were
collected prior to 2015 and that during this timeframe, it can be
reasonably assumed that home HD patients were using NxStage[supreg] for
treatment. The applicant stated that the results from these studies
suggest that patients receiving treatment at home with NxStage[supreg]
5 to 6 times per week do not have a lower all-cause hospitalization
rate, relative to matched in-center HD patients. The applicant
concluded by stating that because of the clinical and demographic
diversity of the Tablo[supreg] System's patient population, the
applicant's results show incremental improvement over the
hospitalization rate of the current home HD population.
---------------------------------------------------------------------------
\57\ Weinhandl, E.D., Gilbertson, D.T., & Collins, A.J. (2016).
Mortality, hospitalization, and technique failure in daily home
hemodialysis and matched peritoneal dialysis patients: A matched
cohort study. American Journal of Kidney Diseases, 67(1), 98-110.
\58\ Suri, R.S., Li, L., & Nesrallah, G.E. (2015). The risk of
hospitalization and modality failure with home dialysis. Kidney
international, 88(2), 360-368.
---------------------------------------------------------------------------
Regarding the applicant's second claim that the Tablo[supreg]
System increases adherence to dialysis treatment and retention to home
therapy, the applicant stated that patients using the Tablo[supreg]
System have improved adherence to prescribed treatments and a higher
rate of retention to home therapy. The applicant further stated that
this increased adherence and retention is likely to improve patient
outcomes by reducing the rate of dialysis-related hospitalizations and
other adverse events associated with missing treatment in this patient
population.\59\
---------------------------------------------------------------------------
\59\ Chan, K.E., Thadhani, R.I., & Maddux, F.W. (2014).
Adherence barriers to chronic dialysis in the United States. Journal
of the American Society of Nephrology, 25(11), 2642-2648. Supporting
evidence of association between decreased dialysis adherence and
poor patient health and utilization outcomes.
---------------------------------------------------------------------------
The applicant stated that adherence to prescribed dialysis
treatments is crucial for dialysis patients because missed treatments
increases the risk of dialysis dropout, hospitalization, and death.\60\
Per the applicant, the Tablo[supreg] IDE study demonstrated a 99
percent treatment adherence rate to all prescribed home treatments \61\
among both prior in-center participants and prior self-care home HD
participants who used NxStage[supreg]. The applicant also stated that
the Tablo[supreg] System's adherence rates were similar among both the
prior in-center and prior self-care participants. The applicant stated
that these results represent a significant improvement over the
treatment adherence rate reported in the NxStage[supreg] IDE, where the
treatment compliance rate was defined less stringently as missing 5 or
fewer treatments of the 48 possible treatments and was only 89 percent
among patients at home and during the study period.\62\ Per the
applicant, using a comparable metric of missing 5 or fewer of all
possible treatments at home, Tablo[supreg] IDE patients at home had a
100 percent treatment compliance rate.
---------------------------------------------------------------------------
\60\ Weinhandl, Eric D., Collins Allan, Incidence of Therapy
Cessation among Home Hemodialysis Patients in the United States,
Abstract presented, American Society of Nephrology Kidney Week 2016.
\61\ Safety and efficacy of the Tablo hemodialysis system for
in-center and home hemodialysis Plumb, T.J., Alvarez, L., Ross,
D.L., Lee, J.J., Mulhern, J.G., Bell, J.L., Abra, G., Prichard,
S.S., Chertow, G.M. and Aragon, M.A. (2019), Hemodialysis
International.
\62\ Kraus, M., et al., A comparison of center-based vs. home-
based daily hemodialysis for patients with end-stage renal disease.
Hemodialysis International,11: 468-477, (2007). The authors
performed a feasibility study to demonstrate the safety of center-
based vs. home-based daily hemodialysis with the NxStage System One
portable hemodialysis device.
---------------------------------------------------------------------------
The applicant stated that technique failure in home HD, defined as
reduced retention at home and a return to in-center care, has been high
with NxStage[supreg]. Per the applicant, real world data show that
technique failure occurs in 36 percent of home HD patients using
NxStage[supreg] within 1 year of initiating treatment.\63\ The
applicant stated that this is challenging for the patient and taxing on
the healthcare system that has invested in providing patients with home
dialysis training and in paying for more frequent therapy.
---------------------------------------------------------------------------
\63\ Weinhandl, Eric D., Collins Allan, Incidence of Therapy
Cessation among Home Hemodialysis Patients in the United States,
Abstract presented, American Society of Nephrology Kidney Week 2016.
---------------------------------------------------------------------------
The applicant stated that by directly comparing the Tablo[supreg]
System's retention to that of NxStage[supreg], the applicant assessed
rates in the analogous IDE populations while excluding those who exited
either study for reasons unrelated to the device such as receipt of a
transplant or death. The applicant stated that the Tablo[supreg] System
demonstrated a 97 percent (28 of 29) patient retention rate for the
entire IDE study and a 100 percent retention rate in the in-home phase
of the trial among both prior NxStage[supreg] users and prior in-center
patients.\64\ The applicant stated that in comparison, 81 percent of
participants completed the NxStage[supreg] IDE study.\65\
---------------------------------------------------------------------------
\64\ Safety and efficacy of the Tablo hemodialysis system for
in-center and home hemodialysis Plumb, T.J., Alvarez, L., Ross,
D.L., Lee, J.J., Mulhern, J.G., Bell, J.L., Abra, G., Prichard,
S.S., Chertow, G.M. and Aragon, M.A. (2019), Hemodialysis
International.
\65\ Kraus M, Burkart J, Hegeman R, Solomon R, Coplon N, Moran
J. A comparison of center-based vs. home-based daily hemodialysis
for patients with end-stage renal disease. Hemodial Int. 2007
Oct;11(4):468-77. doi: 10.1111/j.1542-4758.2007.00229.x. PMID:
17922746.
---------------------------------------------------------------------------
The applicant stated that the Tablo[supreg] System's ease of use
contributed to the improved adherence and retention rates and that the
Tablo[supreg] System is designed to enable patients to become
proficient and independent in using the Tablo[supreg] System after an
average of 3.9 days.\66\ Per the applicant, published NxStage[supreg]
IDE data \67\ reported an average of 14.5 days ``to complete device
training on NxStage[supreg].'' The applicant stated that, in
comparison, device-related training time is reduced by at least 50
percent on the Tablo[supreg] System. Per the applicant, the reduced
training time and ease of use will likely improve retention and
potentially reduce the number of reimbursable training sessions. The
applicant stated that because of the significant role that caregivers
play in supporting home dialysis treatments,\68\ care partner burnout
and a patient's perception of being a burden is associated with
discontinuation of home therapy.69 70 Per the applicant, the
28 patients who entered the home phase of the Tablo[supreg] IDE study
were asked weekly if they needed help with their dialysis treatments
during the prior 7 days. The applicant stated that a 96 percent
response rate (216 of 224 possible) was achieved at the end of the
study and that for both prior-in-center and NxStage[supreg] study
participants, in 79 percent of the treatment weeks, patients reported
needing no assistance from their care partner in performing dialysis
set-up, treatment, or breakdown. The applicant explained that among the
13 prior in-home patients, all of whom were formerly NxStage[supreg]
users, participants reported needing help from a trained individual
with dialysis treatment in 69 percent of treatment weeks, with 46
percent of instances involving a need for device-related help. We
clarify that per Plumb, et al.,\71\ this
[[Page 36341]]
is the baseline percentage and reflects 9 of the 13 patients with
previous self-care experience. The applicant stated that patients
reported needing help with treatment in only 42 percent of treatment
weeks while using the Tablo[supreg] System, which is a 39 percent
reduction from baseline NxStage[supreg] use; and only 18 percent of
these instances related to use of the Tablo[supreg] System, which is a
61 percent reduction in rate from baseline NxStage[supreg] use.\72\
---------------------------------------------------------------------------
\66\ Plumb, Troy J., Luis Alvarez, Dennis L. Ross, Joseph J.
Lee, Jeffrey G. Mulhern, Jeffrey L. Bell, Graham E. Abra, Sarah S.
Prichard, Glenn M. Chertow, and Michael A. Aragon. ``Self-care
training using the Tablo hemodialysis system.'' Hemodialysis
International (2020).
\67\ Kraus, M., et al., A comparison of center-based vs. home-
based daily hemodialysis for patients with end-stage renal disease.
Hemodialysis International,11: 468-477, (2007).
\68\ Seshasai, R.K., et al. (2019) The home hemodialysis patient
experience: A qualitative assessment of modality use and
discontinuation. Hemodialysis International, 23: 139-150 (2019).
\69\ Suri, R.S., Larive, B., Hall, Y., Kimmel, P.L., Kliger,
A.S., Levin, N., . . . & Frequent Hemodialysis Network (FHN) Trial
Group. (2014). Effects of frequent hemodialysis on perceived
caregiver burden in the Frequent Hemodialysis Network trials.
Clinical Journal of the American Society of Nephrology, 9(5), 936-
942.
\70\ Jacquet, S., & Trinh, E. (2019). The potential burden of
home dialysis on patients and caregivers: A narrative review.
Canadian journal of kidney health and disease, 6, 2054358119893335.
\71\ Plumb, Troy J., Luis Alvarez, Dennis L. Ross, Joseph J.
Lee, Jeffrey G. Mulhern, Jeffrey L. Bell, Graham E. Abra, Sarah S.
Prichard, Glenn M. Chertow, and Michael A. Aragon. ``Self-care
training using the Tablo hemodialysis system.'' Hemodialysis
International (2020).
\72\ Ibid.
---------------------------------------------------------------------------
The applicant stated that it collected weekly data from patients by
asking them to rate the extent to which they believed that they were a
burden on a scale of 1 to 5, with 1 representing never and 5
representing always. The applicant stated that this measure was adapted
from an instrument used in assessing terminally ill patients.\73\ The
applicant stated that the subpopulation of study participants who had
previously used NxStage[supreg] reported an average score of 3.1 for
self-perceived burden on their care partner when using their prior
device, which subsequently reduced to 2.4 when using the Tablo[supreg]
System (a 23 percent reduction in score from baseline NxStage[supreg]
use).\74\ Per the applicant, these data underscore that a significant
increase in patients' confidence, ability to achieve treatment
independence at home, and subsequent reduction in the sense of self
burden can positively contribute to success in the home setting. The
applicant further noted that the ease of use, reduced training time,
and substantial reduction in care partner assistance required for the
Tablo[supreg] System correlated to the improved retention and adherence
rates in the Tablo[supreg] IDE study. The applicant stated that on a
population level, this likely translates to reduced barriers to
continuing home HD once initiated, and ultimately, a reduced risk of
adverse outcomes due to missed treatments. The applicant also stated
that the Tablo[supreg] System's electronic data capture and automatic
wireless transmission eliminates the need for manual record keeping,
which represents an improvement with respect to burden and monitoring
as compared to NxStage[supreg].
---------------------------------------------------------------------------
\73\ Chochinov, H.M., Kristjanson, L.J., Hack, T.F., Hassard,
T., McClement, S., & Harlos, M. (2007). Burden to others and the
terminally ill. Journal of pain and symptom management, 34(5), 463-
471.
\74\ Chertow, G.M., Alvarez, L., Plumb, T.J., Prichard, S.S., &
Aragon, M. (2020). Patient-reported outcomes from the
investigational device exemption study of the Tablo hemodialysis
system. Hemodialysis International, 24(4), 480-486.
---------------------------------------------------------------------------
Regarding the applicant's third claim that the Tablo[supreg] System
improves patient quality of life, the applicant stated that patients on
the Tablo[supreg] System experience reduced disease burden, dialysis
related symptoms, and an improved quality of life at home as compared
to in-center and existing home care options. Per the applicant,
patients with ESRD experience significant dialysis-related symptoms
including difficulty sleeping, dizziness, and pain associated with
recovery time that affect mental and physical health and lead to
decreased overall quality of life.\75\ Per the applicant, the
Tablo[supreg] IDE study assessed several validated Patient-Reported
Outcome Measures (PROMs) to better understand overall health-related
quality of life (HR-QoL). The applicant explained that the overall
measure was the EQ-5D-5L, a validated, preference-based PROM in which
patients self-assess mobility, self-care, usual activities, pain/
discomfort, and anxiety/depression.\76\ The applicant stated that from
these domains, an index value is calculated to report a summary score
that ranges from 0 (death) to 1 (full health).
---------------------------------------------------------------------------
\75\ Gabbay, E., Meyer, K.B., Griffith, J.L., Richardson, M.M.,
& Miskulin, D.C. (2010). Temporal trends in healthrelated quality of
life among hemodialysis patients in the United States. Clinical
journal of the American Society of Nephrology, 5(2), 261-267.
\76\ Yang, F., Wong, C.K., Luo, N., Piercy, J., Moon, R., &
Jackson, J. (2019). Mapping the kidney disease quality of life 36-
item short form survey (KDQOL-36) to the EQ-5D-3L and the EQ-5D-5L
in patients undergoing dialysis. The European Journal of Health
Economics, 20(8), 1195-1206.
---------------------------------------------------------------------------
Per the applicant, while the NxStage[supreg] IDE study did not
report results for a quality-of-life instrument, HR-QoL was assessed in
NxStage[supreg] patients in a prospective multicenter observational
study referred to as the FREEDOM trial, which examined the effects of
at-home dialysis 6 times per week with the NxStage[supreg] System on
costs and HR-QoL using the SF-36 instrument. The applicant further
stated that the reported results at 4-month follow-up among these
patients \77\ translates to a mean EQ-5D score of 0.70. The applicant
included an appendix describing the Methodology to Derive EQ-5D Scores
from the FREEDOM Study Results in its application and derived a
predicted mean EQ-5D score of 0.695-0.70 at follow up for the FREEDOM
study. The applicant further noted that because this estimate is based
on the average aggregate change for an adjusted measure that was then
translated to the EQ-5D scale, and the applicant did not have access to
standard error estimates for the Mental Component Score (MCS) and
Physical Component Score (PCS), its interpretation of this estimate and
its variance is limited. Per the applicant, nonetheless, it provides a
sense of the comparable HR-QoL of this sample of NxStage[supreg]
patients at follow-up. The applicant further noted that mean EQ-5D
index values for traditional HD and PD patients reported from a meta-
analysis of existing studies in the literature are 0.56 (95 percent CI:
0.49-0.62) and 0.58 (95 percent CI: 0.5-0.67), respectively.\78\
---------------------------------------------------------------------------
\77\ Finkelstein, F.O., et al. (2012). At-home short daily
hemodialysis improves the long-term health-related quality of life.
Kidney international, 82(5), 561-569.
\78\ Liem, Y.S., Bosch, J.L., & Hunink, M.M. (2008). Preference-
based quality of life of patients on renal replacement therapy: A
systematic review and meta-analysis. Value in Health, 11(4), 733-
741.
---------------------------------------------------------------------------
Per the applicant, patients in the Tablo[supreg] IDE study reported
mean EQ-5D index values of 0.821 (SD: 0.163) \79\ in the
home phase of the study with final measures taken at approximately 5
months from trial start. The applicant stated that this is a
significant improvement when using traditional HD patients as a
comparator, and higher overall HR-QoL as compared to NxStage[supreg]
patients. The applicant emphasized that participants in the
Tablo[supreg] IDE trial underwent a reduced treatment frequency as
compared to participants in the FREEDOM study who were prescribed 6
treatments per week on NxStage[supreg]. The applicant stated that among
patients in the Tablo[supreg] IDE study who had previously been using
NxStage[supreg], the mean EQ-5D score during the in-home phase of the
study was 0.906 (SD: 0.119) and asserted that this is
significantly greater than index population values for HD and
peritoneal dialysis.
---------------------------------------------------------------------------
\79\ Chertow, G.M., Alvarez, L., Plumb, T.J., Prichard, S.S., &
Aragon, M. (2020). Patient-reported outcomes from the
investigational device exemption study of the Tablo hemodialysis
system. Hemodialysis International, 24(4), 480-486.
---------------------------------------------------------------------------
The applicant stated that sleep problems are present in 60 percent
of patients with chronic kidney disease (CKD) and ESRD \80\ and that
patients rank fatigue and lack of energy as the most important
contributor to their decreased quality of life.\81\ Per the
[[Page 36342]]
applicant, the frequency of sleep-related symptoms among the
Tablo[supreg] System's patients was assessed by a survey that was
administered weekly during the Tablo[supreg] IDE study. The applicant
stated that, in the absence of a well-validated sleep survey specific
to the ESRD population, study investigators selected survey questions
from previously validated sleep questionnaires in the non-ESRD
population, based on their relevance to the study
population.82 83 The applicant explained that questions were
designed to focus on quality of sleep and restfulness and noted that
these measures are validated for use among chronically ill populations
and measure the frequency of 4 key sleep-related symptoms. The
applicant stated that, while at home, patients on the Tablo[supreg]
System reported improved quality of sleep, with a measurable reduction
in rate of patient-reported sleep symptoms ranging from a 10-60 percent
reduction, depending on symptom.\84\ The applicant stated that this
reduction was observed among study participants who were previously
receiving dialysis in-center (average magnitude of reduction in rate
across symptoms: 42 percent) and among study participants who were
previously receiving in-home dialysis on NxStage[supreg] (average
magnitude of reduction in rate across symptoms: 27 percent). Per the
applicant, on average, sleep-related difficulties reduced from being
reported in 33 percent of treatment weeks while on NxStage[supreg] to
23 percent of treatment weeks while on the Tablo[supreg] System.
---------------------------------------------------------------------------
\80\ Davison SN, Levin A, Moss AH, Jha V, Brown EA, Brennan F,
Murtagh FE, Naicker S, Germain MJ, O'Donoghue DJ, Morton RL, Obrador
GT; Kidney Disease: Improving Global Outcomes. Executive summary of
the KDIGO Controversies Conference on Supportive Care in Chronic
Kidney Disease: Developing a roadmap to improving quality care.
Kidney Int. 2015 Sep;88(3):447-59.
\81\ Urquhart-Secord, Rachel et al. (2016). Patient and
Caregiver Priorities for Outcomes in Hemodialysis: An International
Nominal Group Technique Study American Journal of Kidney Diseases,
Volume 68, Issue 3, 444-454.
\82\ Morin, C.M., Belleville, G., B[eacute]langer, L., & Ivers,
H. (2011). The Insomnia Severity Index: Psychometric indicators to
detect insomnia cases and evaluate treatment response. Sleep, 34(5),
601-608.
\83\ Natale, V., Fabbri, M., Tonetti, L., & Martoni, M. (2014).
Psychometric goodness of the mini sleep questionnaire. Psychiatry
and clinical neurosciences, 68(7), 568-573.
\84\ Chertow, G.M., Alvarez, L., Plumb, T.J., Prichard, S.S., &
Aragon, M. (2020). Patient-reported outcomes from the
investigational device exemption study of the Tablo hemodialysis
system. Hemodialysis International, 24(4), 480-486.
---------------------------------------------------------------------------
The applicant stated that hypotensive symptoms such as feelings of
dizziness and lightheadedness are associated with the drops in blood
pressure that can occur during dialysis and are also among the top ten
symptoms dialysis patients report that impact their quality of
life.\85\ Per the applicant, participants in the Tablo[supreg] IDE
study were asked at the time of enrollment regarding symptoms
previously experienced during dialysis. The applicant also stated that
at the end of each study treatment, participants were surveyed
regarding the presence of any symptoms during that treatment on the
Tablo[supreg] System. Per the applicant, a total of 8 (26.7 percent)
subjects reported hypotensive symptoms during the Tablo[supreg] System
treatments during the in-home treatment period, compared to 27 (90
percent) subjects reporting hypotensive symptoms at baseline (prior to
initiating care on the Tablo[supreg] System). The applicant reported a
70 percent reduction in the rate of patient-reported hypotensive
symptoms while on the Tablo[supreg] System, though we were unable to
validate the source of this statement.
---------------------------------------------------------------------------
\85\ Urquhart-Secord, Rachel et al. (2016). Patient and
Caregiver Priorities for Outcomes in Hemodialysis: An International
Nominal Group Technique Study American Journal of Kidney Diseases,
Volume 68, Issue 3, 444-454.
---------------------------------------------------------------------------
The applicant stated that currently, ESRD patients on dialysis
report meaningfully lower quality of life compared to those with other
chronic illnesses.\86\ The applicant further noted that decreased
quality of life is associated with a meaningful decline in continuation
of home therapy, dialysis frequency, and worse clinical and health care
utilization outcomes.\87\
---------------------------------------------------------------------------
\86\ Liem, Y.S., Bosch, J.L., Arends, L.R., Heijenbrok-Kal,
M.H., & Hunink, M.M. (2007). Quality of life assessed with the
Medical Outcomes Study Short Form 36-Item Health Survey of patients
on renal replacement therapy: A systematic review and meta-analysis.
Value in Health, 10(5), 390-397.
\87\ Lowrie, E.G., Curtin, R.B., LePain, N., & Schatell, D.
(2003). Medical outcomes study short form-36: A consistent and
powerful predictor of morbidity and mortality in dialysis patients.
American Journal of Kidney Diseases, 41(6), 1286-1292.
---------------------------------------------------------------------------
The applicant concluded by asserting that the totality of evidence
submitted in support of the Tablo[supreg] System demonstrates SCI over
the current standard of home dialysis care. The applicant also stated
that patient preference for devices is currently used by FDA to guide
marketing authorization decisions and provides important information on
the benefit and risks that some patients are willing to trade when
choosing a device.\88\ Per the applicant, patients may be more likely
to choose home dialysis to the extent that the device is both
accessible and easy to use. The applicant also stated that 86 percent
of prior NxStage[supreg] patients in the Tablo[supreg] IDE study found
the Tablo[supreg] System easier to use than their incumbent device and
preferred to remain on the Tablo[supreg] System at the end of the
study.\89\
---------------------------------------------------------------------------
\88\ Food and Drug Administration Center for Devices and
Radiological Health (2020). ``Patient Preference-Sensitive Areas:
Using Patient Preference Information in Medical Device Evaluation''
Available at: https://www.fda.gov/about-fda/cdrh-patient-engagement/patient-preference-sensitive-areas-using-patientpreference-information-medical-device-evaluation. Accessed Jan 21, 2021.
\89\ Chahal, Y., Plumb, T., Aragon M. (2020). Patient Device
Preference for Home Hemodialysis: A Subset Analysis of the Tablo
Home IDE Trial. Poster Presentation at National Kidney Foundation
Spring Clinical Conference, March 2020.
---------------------------------------------------------------------------
In summary, the applicant claimed that the Tablo[supreg] System
improves the treatment of Medicare beneficiaries relative to the
incumbent by focusing on outcomes set forth in Sec.
412.87(b)(1)(ii)(C), including a decreased number of treatments to
achieve dialysis adequacy, which the applicant stated leads to greater
adherence to prescribed therapy, and improved quality of life.
(c) CMS Preliminary Assessment of SCI Claims and Sources
After a review of the information provided by the applicant, we
have identified the following concerns regarding the SCI eligibility
criterion for the TPNIES. We note that, consistent with Sec.
413.236(c), CMS will announce its final determination regarding whether
Tablo[supreg] meets the SCI criterion and other eligibility criteria
for the TPNIES in the CY 2022 ESRD PPS final rule.
With respect to the applicant's claim that patients can achieve
dialysis adequacy in as little as 3 treatments per week, we note that
the Tablo[supreg] IDE study did not test whether patients receive
adequate dialysis on a thrice-weekly schedule. Instead, data published
from the Tablo[supreg] IDE study address a weekly measure of dialysis
adequacy among patients treated on a 4 times per week schedule. The
applicant relied on modeling and unpublished data on patients receiving
thrice-weekly dialysis in making the conclusion that dialysis adequacy
can be reached on a thrice-weekly schedule. Specifically, the applicant
referred to a theoretical modeling study based on historical data from
the USRDS, Medicare claims, and historical outcomes from
NxStage[supreg] observational studies. The applicant also stated that
findings from a retrospective review of 29 patients receiving treatment
with the Tablo[supreg] System on a thrice-weekly schedule affirm the
results from the modeling study. We also note that the authors in
Alvarez et al.\90\ stated that conclusions about fluid removal could
not be made from their study. We would be interested in whether
additional studies are available that address issues related to
effective fluid removal using home
[[Page 36343]]
self-care dialysis thrice-weekly with the Tablo[supreg] System. We
invite comments on whether less frequent dialysis sessions would
represent SCI over shorter, more frequent sessions that, according to
the applicant, are common among users of the incumbent technology.
---------------------------------------------------------------------------
\90\ Alvarez, Luis et al. Urea Clearance Results in Patients
Dialyzed Thrice Weekly Using a Dialysate Flow of 300 mL/min,
clinical abstract, presented March 2019, Annual Dialysis Conference,
Dallas, Texas.
---------------------------------------------------------------------------
The applicant's second claim was that the Tablo[supreg] System
increases adherence to dialysis treatment and retention to home
therapy, which may reduce dialysis-related hospitalizations and other
adverse events associated with missing treatment. This claim was
supported by the Tablo[supreg] IDE study (28 participants completed the
study) and the use of historical comparisons to prior studies involving
the NxStage[supreg] System. The applicant noted that hospitalization
rates from the Tablo[supreg] IDE trial were lower than rates in the
general dialysis population and rates reported in two observational
studies of patients using the NxStage[supreg] device. While the
applicant cited an all-cause hospitalization rate of 426 per 1000
patient years in the Tablo[supreg] IDE study, it does not appear that
the sources 91 92 published these hospitalization rates. We
further note that the applicant relied on historical comparisons in
asserting that that patients treated with the Tablo[supreg] System
experience reduced disease burden and improved quality of life.
---------------------------------------------------------------------------
\91\ Safety and efficacy of the Tablo hemodialysis system for
in-center and home hemodialysis Plumb, T.J., Alvarez, L., Ross,
D.L., Lee, J.J., Mulhern, J.G., Bell, J.L., Abra, G., Prichard,
S.S., Chertow, G.M. and Aragon, M.A. (2019), Hemodialysis
International.
\92\ Chertow, G.M., Alvarez, L., Plumb, T.J., Prichard, S. S., &
Aragon, M. (2020). Patient-reported outcomes from the
investigational device exemption study of the Tablo hemodialysis
system. Hemodialysis International, 24(4), 480-486.
---------------------------------------------------------------------------
We note that in the Tablo[supreg] IDE study, the before-after
comparisons in patients with NxStage[supreg] regarding improved sleep
compared to prior to the Tablo[supreg] System may be prone to recall
bias in that participants' experiences with NxStage[supreg] were not
recorded at the time they were receiving NxStage[supreg] treatments,
but rather, were based on recall at the time of the Tablo[supreg] IDE
study.
We understand that greater flexibility for patients in the way that
they receive their dialysis treatments may represent a benefit to
Medicare beneficiaries who are candidates to receive this treatment in
the home setting. We invite comments on whether this potential benefit
represents SCI, including whether the Tablo[supreg] System represents
an advance that substantially improves, relative to renal dialysis
services previously available, the treatment of Medicare beneficiaries.
(6) Capital Related Assets Criterion (Sec. 413.236(b)(6))
With respect to the sixth TPNIES eligibility criterion under Sec.
413.236(b)(6), whether the item is a capital-related asset and home
dialysis machine, Sec. 413.236(a)(2) defines these terms. First, a
capital-related asset is an asset that an ESRD facility has an economic
interest in through ownership (regardless of the manner in which it was
acquired) and is subject to depreciation. Equipment obtained by the
ESRD facility through operating leases are not considered capital-
related assets. Second, home dialysis machines are HD machines and PD
cyclers in their entirety (meaning that one new part of a machine does
not make the entire capital-related asset new) that receive FDA
marketing authorization for home use and when used in the home for a
single patient. The applicant identified the Tablo[supreg] System as an
asset that an ESRD facility has an economic interest in through
ownership, is subject to depreciation, and is an HD machine that
received FDA marketing authorization for home use. Therefore, the
Tablo[supreg] System is a capital-related asset that is a home dialysis
machine. We welcome comments on the Tablo[supreg] System's status as a
capital related asset that is a home dialysis machine.
b. CloudCath Peritoneal Dialysis Drain Set Monitoring System (CloudCath
System)
CloudCath submitted an application for the TPNIES for the CloudCath
Peritoneal Dialysis Drain Set Monitoring System (CloudCath System) for
CY 2022. According to the application, the CloudCath System is a
tabletop passive drainage system that detects and monitors solid
particles in dialysate effluent during PD treatments. Solid particles
in dialysate effluent, manifesting itself as cloudy dialysate, may
indicate that the patient has peritonitis, the inflammation of the
peritoneum in the abdominal wall usually due to a bacterial or fungal
infection.\93\ PD therapy is a common cause of peritonitis.\94\ If left
untreated, the condition can be life threatening.\95\
---------------------------------------------------------------------------
\93\ Mayo Clinic Staff, ``Peritonitis,'' June 18, 2020,
available at: https://www.mayoclinic.org/diseases-conditions/peritonitis/symptoms-causes/syc-20376247.
\94\ Ibid.
\95\ Ibid.
---------------------------------------------------------------------------
PD-related peritonitis is a major complication and challenge to the
long-term success and adherence of patients on PD therapy.\96\ The
applicant stated that only about 12 percent of eligible patients are on
PD therapy.\97\ The applicant claimed that the risk of PD-related
peritonitis, and the challenges to detect it, are the main reasons for
these figures. The guidelines for diagnosis of PD-related peritonitis,
as outlined by the International Society for Peritoneal Dialysis
(ISPD), recommend that peritonitis be diagnosed when at least 2 of the
following criteria are present: (1) The patient experiences clinical
features consistent with peritonitis (abdominal pain and/or cloudy
dialysate effluent); (2) the patient's dialysate effluent has a whole
blood count (WBC) >100 cells/[mu]L or >0.1 x 10/L with
polymorphonuclear (PMN) cells >50 percent; and (3) positive dialysis
effluent culture is identified.\98\ Additionally, the guidelines
recommend that PD patients presenting with cloudy effluent be presumed
to have peritonitis and treated as such until the diagnosis can be
confirmed or excluded.\99\ Per the guidelines, this means that for
patients undergoing PD treatments at home, it is recommended that they
self-monitor for symptoms of peritonitis, cloudy dialysate and/or
abdominal pain, and seek medical attention for additional testing and
treatment upon experiencing any or both of these symptoms. According to
the applicant, despite the fact that peritonitis is highly prevalent,
symptom monitoring is insensitive and non-specific, which can
contribute to late presentation for medical attention and treatment.
The applicant asserted that under the current standard of care, PD
patients face the following challenges in detecting peritonitis. First,
the applicant stated that patients' fluid observation has low
compliance rates as it relies on patients' close examination of their
own dialysate effluent during PD treatments, which often occur while
patients are asleep. Second, the applicant noted that it can be
difficult for patients to visually detect peritonitis in dialysate
effluent using a ``newspaper test'' for cloudiness, and can be even
more difficult to see when the fluid is drained into a toilet, where it
is diluted by water. The applicant stated that, as a result of these
challenges, patients with ESRD suffer unsatisfactorily high mortality
and morbidity from
[[Page 36344]]
peritonitis, as well as high rates of PD modality loss, meaning they
must discontinue PD and begin a different type of dialysis treatment.
Per the applicant, the CloudCath System addresses these challenges by
detecting changes in dialysate effluent at much lower levels of
particle concentrations than the amount needed to accumulate for visual
detection by patients.
---------------------------------------------------------------------------
\96\ Kam-Tao Li, Philip, et al., ``ISPD Peritonitis
recommendations: 2016 Update on Prevention and Treatment,''
Peritoneal Dialysis International 2016; 36(5):481-508, June 9, 2016,
available at: http://dx.doi.org/10.3747/pdi.2016.00078.
\97\ Briggs, et al., ``Early Detection of Peritonitis in
Patients Undergoing Peritoneal Dialysis: A Device and Cloud-Based
Algorithmic Solution,'' unpublished report.
\98\ Kam-Tao Li, Philip, et al., ``ISPD Peritonitis
recommendations: 2016 Update on Prevention and Treatment,''
Peritoneal Dialysis International 2016; 36(5):481-508, June 9, 2016,
available at: http://dx.doi.org/10.3747/pdi.2016.00078.
\99\ Ibid.
---------------------------------------------------------------------------
Per the applicant, the CloudCath System consists of three
components: (1) Drain set, (2) sensor, and (3) patient monitoring
software. As explained in the application, the CloudCath System's drain
set connects to a compatible PD cycler's drain line to enable draining
and monitoring of dialysate effluent before routing the fluid to the
drainage receptacle. Per the CloudCath System User Guide, included in
the application, the CloudCath System is compatible with the following
PD cyclers: Baxter Healthcare Home Choice PROTM, Baxter
Healthcare AMIATM Automated PD System, and Fresenius
Liberty[supreg] Select Cycler. Per the applicant, once the CloudCath
System is attached to a compatible cycler, the dialysate effluent runs
through the drain set, through the CloudCath System's optical sensor.
The applicant explained that the CloudCath System's optical sensor
detects and monitors changing concentrations of solid particles in the
dialysate effluent during each dialysis cycle and reports the
concentrations in a turbidity score. Per the applicant, the CloudCath
System will indicate whether dialysate effluent has normal turbidity
and will notify the patient and/or health care professional if the
dialysate effluent turbidity has exceeded the notification threshold
set by the patient's dialysis provider. The applicant stated that the
optical sensor's hardware and software components allow for data
trending over time and remote monitoring by a healthcare professional.
(1) Renal Dialysis Service Criterion (Sec. 413.236(b)(1))
Regarding the first TPNIES eligibility criterion in Sec.
413.236(b)(1), that the item has been designated by CMS as a renal
dialysis service under Sec. 413.171, monitoring for peritonitis is a
service that is essential for dialysis, and therefore would be
considered a renal dialysis service under Sec. 413.171.
(2) Newness Criterion (Sec. 413.236(b)(2))
With respect to the second TPNIES eligibility criterion in Sec.
413.236(b)(2), that the item is new, meaning within 3 years beginning
on the date of the FDA marketing authorization, the applicant stated
that it is seeking 510(k) marketing authorization from the FDA. To be
eligible for the TPNIES, the applicant must apply within three years of
the FDA marketing authorization date and receive FDA marketing
authorization by the HCPCS Level II deadline of July 6, 2021. The
applicant stated that it anticipates the CloudCath System will receive
FDA marketing authorization by the HCPCS Level II deadline.
(3) Commercial Availability Criterion (Sec. 413.236(b)(3))
Regarding the third TPNIES eligibility criterion in Sec.
413.236(b)(3), that the item is commercially available by January 1 of
the particular calendar year, meaning the year in which the payment
adjustment would take effect, the applicant stated that the CloudCath
System is not currently commercially available because it has not
received FDA marketing authorization. The applicant noted that it
expects the CloudCath System will be commercially available immediately
after receiving FDA marketing authorization.
(4) HCPCS Level II Application Criterion (Sec. 413.236(b)(4))
Regarding the fourth TPNIES eligibility criterion in Sec.
413.236(b)(4) requiring that the applicant submit a complete HCPCS
Level II code application by the HCPCS Level II application deadline of
July 6, 2021, the applicant stated that it has not submitted an
application yet, but intends to apply by the deadline.
(5) Innovation Criteria (Sec. Sec. 413.236(b)(5) and 412.87(b)(1))
(a) SCI Claims and Sources
With regard to the fifth TPNIES eligibility criterion under Sec.
413.236(b)(5), that the item is innovative, meaning it meets the SCI
criteria specified in Sec. 412.87(b)(1), the applicant asserted that
the CloudCath System offers SCI over technologies currently available
for the Medicare patient population by offering the ability to monitor
changes in turbidity of peritoneal dialysate effluent through
continuous remote monitoring in patients with ESRD receiving PD
therapy, earlier than the current standard of care. By allowing the
clinical standard of care to be initiated earlier, per the applicant,
the use of the CloudCath System changes the management of peritonitis
patients by enabling clinicians to both diagnose peritonitis and
initiate antibiotic treatment earlier.
The applicant submitted two studies on the technology in support of
the SCI claims. The applicant included a preliminary, unpublished
report by Briggs, et al. on a clinical study that tested the ability of
the CloudCath System and its dialysate effluent monitoring algorithm to
detect indicators of peritonitis.\100\ The proof of principle
observational study consisted of 70 PD patients outside of the U.S. who
had been on PD for a long interval of time (>10 days), and thus were at
an increased risk of developing peritonitis. Out of the 64 PD patients
whose data were included in the study, over 40 PD patients were
receiving intermittent PD, which is not commonly used in the U.S. The
remainder of the participants were receiving Continuous Ambulatory
Peritoneal Dialysis. The report states that in the U.S., PD is
generally performed in a modality called Continuous Cycling Peritoneal
Dialysis (CCPD), in which a cycler automatically administers multiple
dialysis exchange cycles, typically while patients sleep. Samples were
collected from patients' PD effluent drainage bags and measured in the
CloudCath System against a proprietary Turbidity Score threshold value
and also tested for reference laboratory measurements according to ISPD
guidelines for WBC count and differential (>100 cells/[mu]L, >50
percent PMN).\101\ Regarding the Turbidity Score threshold value, the
study set a score to determine if the effluent sample in the CloudCath
System was infected or not; samples greater than or equal to the
Turbidity Score threshold value would be classified as infected, and
samples less than the Turbidity Score threshold value would be
classified as non-infected. The crude sensitivity and specificity of
the CloudCath System was 96.2 percent and 91.2 percent, respectively. A
majority of false positives (44 of 77 samples) occurred among patients
already receiving antibiotic treatment for peritonitis, and another 20
false positive reports occurred because the patient had elevated
turbidity due to a cause other than peritonitis. The investigators
subsequently removed samples from patients already receiving treatment
for peritonitis, setting the sensitivity for detecting peritonitis
using the CloudCath System at 99 percent and the specificity at 97.6
percent.
---------------------------------------------------------------------------
\100\ Briggs, et al., ``Early Detection of Peritonitis in
Patients Undergoing Peritoneal Dialysis: A Device and Cloud-Based
Algorithmic Solution,'' unpublished report.
\101\ Kam-Tao Li, Philip, et al., ``ISPD Peritonitis
recommendations: 2016 Update on Prevention and Treatment,''
Peritoneal Dialysis International 2016; 36(5):481-508, June 9, 2016,
available at: http://dx.doi.org/10.3747/pdi.2016.00078.
---------------------------------------------------------------------------
The second study the applicant submitted is the Prospective
Clinical Study to Evaluate the Ability of the CloudCath System to
Detect Peritonitis
[[Page 36345]]
Compared to Standard of Care during In-Home Peritoneal Dialysis
(CATCH).\102\ CloudCath initiated this ongoing single-arm, open-label,
multi-center study to demonstrate that the CloudCath System is able to
detect changes in turbidity associated with peritonitis in PD patients
prior to laboratory diagnosis of peritonitis with a high degree of
specificity and sensitivity. The target enrollment is 186 participants
over 18 years of age using CCPD as their PD modality, with at least 2
exchanges per night.\103\ Patients with active infection and/or cancer
are excluded from the trial.\104\ The primary endpoint is time of
peritonitis detection by the CloudCath System (defined as two
consecutive Turbidity Scores >7.0) as compared to laboratory evidence
of peritonitis (defined as WBC count >100 cells/[mu]L or >0.1 x 109/L
with percentage of PMN >50 percent).\105\ While the study is ongoing,
the applicant included the study protocol and preliminary results with
its application.\106\ The preliminary results demonstrate that as of
December 29, 2020, 132 participants have been enrolled in the CATCH
Study at 13 sites.\107\ Of the 132 enrolled participants, 59.1 percent
of participants were male, 65.9 percent of participants were White and
29.6 percent of participants were Black or African American.\108\
Enrolled participants underwent an average of 4.5 exchanges per
night.\109\ The preliminary results indicate that, as of December 29,
2020, there have been 7 peritonitis events that met the ISPD peritoneal
fluid cell counts and differentials standard.\110\ All 7 of the
peritonitis events were also detected by the CloudCath System.\111\ In
5 out of the 7 peritonitis events, the CloudCath System detected
peritonitis 44 to 368 hours prior to the time of detection from a
clinical laboratory.\112\ The CloudCath System also detected
peritonitis 27 to 344 hours prior to participants presenting to the
hospital or clinic with signs or symptoms of peritonitis.\113\ The
applicant stated that these results support the claim that the
CloudCath System would enable diagnosis of peritonitis earlier than the
current standard of care through turbidity monitoring.
---------------------------------------------------------------------------
\102\ CloudCath, ``A Prospective Clinical Study to Evaluate the
Ability of the CloudCath System to Detect Peritonitis Compared to
Standard of Care during In-Home Peritoneal Dialysis (CATCH),''
Preliminary Clinical Study Report (NCT04515498), Jan 27, 2020.
\103\ CloudCath, ``A Prospective Clinical Study to Evaluate the
Ability of the CloudCath System to Detect Peritonitis Compared to
Standard of Care during In-Home Peritoneal Dialysis (CATCH),'' Study
Protocol (CC-P-001), June 24, 2020.
\104\ Ibid.
\105\ Ibid.
\106\ CloudCath, ``A Prospective Clinical Study to Evaluate the
Ability of the CloudCath System to Detect Peritonitis Compared to
Standard of Care during In-Home Peritoneal Dialysis (CATCH),''
Preliminary Clinical Study Report (NCT04515498), Jan 27, 2020.
\107\ Ibid.
\108\ Ibid.
\109\ Ibid.
\110\ Ibid.
\111\ Ibid.
\112\ Ibid.
\113\ Ibid.
---------------------------------------------------------------------------
In addition to the studies on the technology, the applicant
submitted an article by Muthucumarana, et al. on the impact of time-to-
treatment on clinical outcomes of PD-related peritonitis.\114\ The
article includes data from the Presentation and the Time of Initial
Administration of Antibiotics With Outcomes of Peritonitis (PROMPT)
Study, a prospective multicenter from 2012 to 2014 that observed
symptom-to-contact time, contact-to-treatment time, defined as the time
from health care presentation to initial antibiotic, and symptom-to-
treatment time in Australian PD patients. 116 patients participated in
the survey, 83 of which were caucasian and 14 were aboriginal.\115\ Out
of the sample size of 116 survey participants, there were 159 episodes
of PD-related peritonitis. Of these, 38 patient episodes met the
primary outcome of PD failure (defined as catheter removal or death) at
30 days.\116\ The median symptom-to-treatment time was 9.0 hours in all
patients, 13.6 hours in the PD-fail group, and 8.0 hours in the PD-cure
group.\117\ The study found that the risk of PD-failure increased by
5.5 percent for each hour of delay of administration of antibiotics
once patients presented to a health care provider.\118\ However,
neither symptom-to-contact nor symptom-to-treatment was associated with
PD-failure in non-adjusted analyses, and the time from presentation to
a health care provider to treatment was only associated with PD-failure
outcomes in multivariable-adjusted analyses in a subset of patients who
presented to hospital-based facilities. In addition to the
Muthucumarana et al. article, the applicant cited to other studies that
have found that antibiotic treatment should begin as soon as possible
in order to effectively treat infections other than
peritonitis.119 120 121 Per the applicant, these articles on
time-to-treatment demonstrate that the CloudCath System's ability to
detect effluent changes substantially earlier improves the standard of
care, enabling PD-related peritonitis diagnosis and antibiotic
treatment earlier while decreasing the likelihood of PD-failure due to
PD-related peritonitis.
---------------------------------------------------------------------------
\114\ Muthucumarana, et al., ``The Relationship Between
Presentation and the Time of Initial Administration of Antibiotics
With Outcomes of Peritonitis in Peritoneal Dialysis Patients: The
PROMPT Study.,'' Kidney Int Rep. 2016 Jun 11;1(2):65-72. doi:
10.1016/j.ekir.2016.05.003. PMID: 29142915; PMCID: PMC5678844.
\115\ Ibid.
\116\ Ibid.
\117\ Ibid.
\118\ Ibid.
\119\ Gacouin, A. et al., ``Severe pneumonia due to Legionella
pneumophila: prognostic factors, impact of delayed appropriate
antimicrobial therapy,'' Intensive Care Medicine 28, 686-691 (2002),
https://doi.org/10.1007/s00134-002-1304-8.
\120\ Houck, PM. et al., ``Timing of antibiotic administration
and outcomes for Medicare patients hospitalized with community-
acquired pneumonia,'' Arch Intern Med. 2004 Mar 22;164(6):637-44.
doi: 10.1001/archinte.164.6.637. PMID: 15037492.
\121\ Lodise TP, et al., ``Outcomes analysis of delayed
antibiotic treatment for hospital-acquired Staphylococcus aureus
bacteremia,''Clin Infect Dis. 2003 Jun 1;36(11):1418-23. doi:
10.1086/375057. Epub 2003 May 20. PMID: 12766837.
---------------------------------------------------------------------------
The applicant also submitted letters of support from a nephrologist
at an academic institution and the following ESRD patient advocacy
groups: The American Kidney Fund, the American Association of Kidney
Patients, and the International Society of Nephrology. The letter of
support from Dr. Thomas A. Golper, president-elect of the International
Society of Nephrology, endorsed the CloudCath System's ability to
detect peritonitis and enable clinicians to begin to treat the
infection earlier, preventing hospitalizations and related
complications such as the abandonment of home dialysis. The letter also
stated that the CloudCath System helps address the challenge of
peritonitis as the main reason for abandonment of PD for HD, and will
encourage a greater number of patients to select PD as their dialysis
modality of choice. The letters from the American Association of Kidney
Patients and the International Society of Nephrology encouraged CMS to
consider the CloudCath System's application, explaining that the
technology would have several benefits to patients, for example, by
reducing peritonitis-related hospitalizations, increasing adherence to
PD, and encouraging higher utilization of PD as a viable alternative to
in-center HD. The American Kidney Fund's letter emphasized that
peritonitis is a significant concern for PD patients \122\ and
requested CMS support of all efforts that ensure patients
[[Page 36346]]
with ESRD undergoing PD treatments can quickly detect and treat
infections.
---------------------------------------------------------------------------
\122\ Mehrotra, Rajnish et al., ``The Current State of
Peritoneal Dialysis,'' Journal of the American Society of Nephrology
27: 3238-3252, 2016. doi: 10.1681/ASN.2016010112, available at:
https://jasn.asnjournals.org/content/jnephrol/27/11/3238.full.pdf?with-ds=yes.
---------------------------------------------------------------------------
(b) CMS Preliminary Assessment of SCI Claims and Sources
After a review of the information provided by the applicant, we
note the following concerns with regard to the SCI criterion under
Sec. 413.236(b)(5) and Sec. 412.87(b)(1). We note that, consistent
with Sec. 413.236(c), CMS will announce its final determination
regarding whether the CloudCath System meets the SCI criterion and
other eligibility criteria for the TPNIES in the CY 2022 ESRD PPS final
rule.
Because the applicant claims to offer the ability to diagnose a
medical condition, PD-related peritonitis, earlier in a patient
population than allowed by currently available methods, the applicant
must also include evidence that use of the new technology to make a
diagnosis affects the management of the patient, as required under the
SCI criterion at Sec. 412.87(b)(1)(ii)(B). Specifically, Sec.
412.87(b)(1)(ii)(B) states that a determination that a technology
represents SCI over existing technology means: The new medical service
or technology offers the ability to diagnose a medical condition in a
patient population where that medical condition is currently
undetectable, or offers the ability to diagnose a medical condition
earlier in a patient population than allowed by currently available
methods and there must also be evidence that use of the new medical
service or technology to make a diagnosis affects the management of the
patient.
It is not clear to us whether the studies submitted demonstrate or
examine the impacts of using the technology on patients with ESRD such
that we can determine whether it represents an advance that
substantially improves the treatment of Medicare beneficiaries compared
to renal dialysis services previously available. We note that the
studies submitted serve as ``proof of concept,'' as they provide
evidence that the CloudCath System detects solid particles in dialysate
effluent that may indicate PD-related peritonitis, and, may do so
earlier than patient observation and a cell count test. However, the
studies are limited in that they do not observe how the CloudCath
System, in detecting the solid particles in dialysate effluent and
doing so earlier than a cell count test, affects the management of the
patient, as required under the SCI criterion at Sec.
412.87(b)(1)(ii)(B). For example, as part of the CATCH Study,
investigators deactivated the notification capability of the CloudCath
System for the duration of the study, so that neither the participants
nor the investigators would be aware of the device measurements.\123\
Therefore, the CATCH study did not examine patient and clinician
behavior, including the medical management of the patient, after the
CloudCath System detected the solid particles in the dialysate
effluent. The Briggs et al. study also did not examine how use of the
CloudCath System impacted management of the patient. The investigators
in that study stated, ``none of the data from our device was used for
clinical decision making,'' meaning that the study did not test how or
if the CloudCath System offered the ability to diagnose a medical
condition and how use of the CloudCath System to make a diagnosis
affected the management of the patient.\124\ Because the studies
submitted did not observe how patients and clinicians use the CloudCath
System's monitoring to make decisions regarding patient management, we
are concerned that we will not be able to make a determination on
whether early detection of PD-related peritonitis by the CloudCath
System meets the SCI criterion at Sec. 412.87(b)(1)(ii)(B). Similarly,
while the applicant submitted evidence to show that time-to-treatment
plays a role in preventing PD failure in patients with ESRD with PD-
related peritonitis,\125\ CMS has not received any information
regarding how the CloudCath System would affect management of the
patient by reducing time-to-treatment for patients with ESRD receiving
PD therapy. CMS also notes that the applicant referenced studies that
support beginning antibacterial therapy for infections other than PD-
related peritonitis, like pneumonia, and, therefore do not directly
demonstrate the importance of time-to-treatment for PD-related
peritonitis.
---------------------------------------------------------------------------
\123\ CloudCath, ``A Prospective Clinical Study to Evaluate the
Ability of the CloudCath System to Detect Peritonitis Compared to
Standard of Care during In-Home Peritoneal Dialysis (CATCH),''
Preliminary Clinical Study Report, NCT04515498, Jan 27, 2020.
\124\ Briggs, et al., ``Early Detection of Peritonitis in
Patients Undergoing Peritoneal Dialysis: A Device and Cloud-Based
Algorithmic Solution,'' unpublished report.
\125\ Muthucumarana, et al., ``The Relationship Between
Presentation and the Time of Initial Administration of Antibiotics
With Outcomes of Peritonitis in Peritoneal Dialysis Patients: The
PROMPT Study.,'' Kidney Int Rep. 2016 Jun 11;1(2):65-72. doi:
10.1016/j.ekir.2016.05.003. PMID: 29142915; PMCID: PMC5678844.
---------------------------------------------------------------------------
Additionally, it is not clear to us whether the CloudCath System
would affect medical management of the patient because use of the
technology may potentially detect solid particles in dialysate effluent
so early, that, in some cases, healthcare providers may decide to wait
for confirmation via patient symptoms, cell count, or positive culture
as stated in the ISPD guidelines on diagnosis.\126\ The preliminary
results of the CATCH study demonstrate that in 5 out of 7 PD-related
peritonitis events, the CloudCath System detected PD-related
peritonitis 33 to 367 hours prior to the time of detection from a
clinical laboratory.\127\ The CloudCath System also detected PD-related
peritonitis 27 to 344 hours prior to participants presenting to a
healthcare facility with symptoms of PD-related peritonitis.\128\ We
note that no evidence was submitted to show that clinicians would begin
to treat suspected peritonitis if the CloudCath System alerted the
patient and clinician of possible PD-related peritonitis that was too
early to detect via any of the ISPD guidelines.\129\ In other words, we
have not received evidence to demonstrate that the CloudCath System
would affect medical management of the patient by replacing one of the
ISPD guidelines for diagnosis.\130\
---------------------------------------------------------------------------
\126\ Kam-Tao Li, Philip, et al., ``ISPD Peritonitis
recommendations: 2016 Update on Prevention and Treatment,''
Peritoneal Dialysis International 2016; 36(5):481-508, June 9, 2016,
available at: http://dx.doi.org/10.3747/pdi.2016.00078.
\127\ CloudCath, ``A Prospective Clinical Study to Evaluate the
Ability of the CloudCath System to Detect Peritonitis Compared to
Standard of Care during In-Home Peritoneal Dialysis (CATCH),''
Preliminary Clinical Study Report (NCT04515498), Jan 27, 2020.
\128\ Ibid.
\129\ Kam-Tao Li, Philip, et al., ``ISPD Peritonitis
recommendations: 2016 Update on Prevention and Treatment,''
Peritoneal Dialysis International 2016; 36(5):481-508, June 9, 2016,
available at: http://dx.doi.org/10.3747/pdi.2016.00078.
\130\ Ibid.
---------------------------------------------------------------------------
Additionally, CMS notes that the applicant has not submitted
evidence to show that beginning treatment for presumed PD-related
peritonitis in patients with ESRD prior to the occurrence of any of the
ISPD guidelines would not be harmful to patients. In the Briggs et al.
study, the CloudCath System identified 20 false positives that occurred
because the patient had elevated turbidity due to some cause other than
PD-related peritonitis.\131\ However, the applicant did not explain or
provide evidence on whether beginning treatment for PD-related
peritonitis for a group of patients with ESRD who tested positive, but
were in fact negative for the condition, was clinically advisable. CMS
is concerned that the CloudCath System's potential for false positive
results may lead to
[[Page 36347]]
clinicians beginning treatment for PD-related peritonitis when not
necessary in an already vulnerable group of Medicare beneficiaries. We
welcome public comment on these issues.
---------------------------------------------------------------------------
\131\ Briggs, et al., ``Early Detection of Peritonitis in
Patients Undergoing Peritoneal Dialysis: A Device and Cloud-Based
Algorithmic Solution,'' unpublished report.
---------------------------------------------------------------------------
(6) Capital Related Assets Criterion (Sec. 413.236(b)(6))
Regarding the sixth TPNIES eligibility criterion in Sec.
413.236(b)(6), limiting capital-related assets from being eligible for
the TPNIES, except those that are home dialysis machines, the applicant
stated that the CloudCath System is not a capital-related asset. The
applicant explained that the CloudCath System does not meet the
definition of a capital-related asset, as defined in the Provider
Reimbursement Manual (chapter 1, section 104.1), because the device is
not subject to depreciation, nor is used by a provider as part of a
regular lease agreement.\132\
---------------------------------------------------------------------------
\132\ CMS Provider Reimbursement Manual, Chapter 1, Section
104.1. Available at: https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Paper-Based-Manuals-Items/CMS021929.
---------------------------------------------------------------------------
III. Calendar Year (CY) 2022 Payment for Renal Dialysis Services
Furnished to Individuals With Acute Kidney Injury (AKI)
A. Background
The Trade Preferences Extension Act of 2015 (TPEA) (Pub. L. 114-27)
was enacted on June 29, 2015, and amended the Act to provide coverage
and payment for dialysis furnished by an ESRD facility to an individual
with acute kidney injury (AKI). Specifically, section 808(a) of the
TPEA amended section 1861(s)(2)(F) of the Act to provide coverage for
renal dialysis services furnished on or after January 1, 2017, by a
renal dialysis facility or a provider of services paid under section
1881(b)(14) of the Act to an individual with AKI. Section 808(b) of the
TPEA amended section 1834 of the Act by adding a subsection (r) to
provide payment, beginning January 1, 2017, for renal dialysis services
furnished by renal dialysis facilities or providers of services paid
under section 1881(b)(14) of the Act to individuals with AKI at the
ESRD PPS base rate, as adjusted by any applicable geographic adjustment
applied under section 1881(b)(14)(D)(iv)(II) of the Act and adjusted
(on a budget neutral basis for payments under section 1834(r) of the
Act) by any other adjustment factor under section 1881(b)(14)(D) of the
Act that the Secretary elects.
In the CY 2017 ESRD PPS final rule, we finalized several coverage
and payment policies in order to implement subsection (r) of section
1834 of the Act and the amendments to section 1881(s)(2)(F) of the Act,
including the payment rate for AKI dialysis (81 FR 77866 through 77872,
and 77965). We interpret section 1834(r)(1) of the Act as requiring the
amount of payment for AKI dialysis services to be the base rate for
renal dialysis services determined for a year under the ESRD PPS base
rate as set forth in Sec. 413.220, updated by the ESRD bundled market
basket percentage increase factor minus a productivity adjustment as
set forth in Sec. 413.196(d)(1), adjusted for wages as set forth in
Sec. 413.231, and adjusted by any other amounts deemed appropriate by
the Secretary under Sec. 413.373. We codified this policy in Sec.
413.372 (81 FR 77965).
B. Proposed Annual Payment Rate Update for CY 2022
1. CY 2022 AKI Dialysis Payment Rate
The payment rate for AKI dialysis is the ESRD PPS base rate
determined for a year under section 1881(b)(14) of the Act, which is
the finalized ESRD PPS base rate, including the applicable annual
productivity-adjusted market basket payment update, geographic wage
adjustments, and any other discretionary adjustments, for such year. We
note that ESRD facilities have the ability to bill Medicare for non-
renal dialysis items and services and receive separate payment in
addition to the payment rate for AKI dialysis.
As discussed in section II.B.1.d of this proposed rule, the CY 2022
proposed ESRD PPS base rate is $255.55, which reflects the application
of the proposed CY 2022 wage index budget-neutrality adjustment factor
of .999546 and the CY 2022 proposed ESRDB market basket increase of 1.6
percent reduced by the productivity adjustment of 0.6 percentage point,
that is, 1.0 percent. Accordingly, we are proposing a CY 2022 per
treatment payment rate of $255.55 for renal dialysis services furnished
by ESRD facilities to individuals with AKI. This payment rate is
further adjusted by the wage index, as discussed in the next section of
this proposed rule.
2. Geographic Adjustment Factor
Under section 1834(r)(1) of the Act and Sec. 413.372, the amount
of payment for AKI dialysis services is the base rate for renal
dialysis services determined for a year under section 1881(b)(14) of
the Act (updated by the ESRD bundled market basket and reduced by the
productivity adjustment), as adjusted by any applicable geographic
adjustment factor applied under section 1881(b)(14)(D)(iv)(II) of the
Act.\133\ Accordingly, we apply the same wage index under Sec. 413.231
that is used under the ESRD PPS and discussed in section II.B.1.b of
this proposed rule. The AKI dialysis payment rate is adjusted by the
wage index for a particular ESRD facility in the same way that the ESRD
PPS base rate is adjusted by the wage index for that facility (81 FR
77868). Specifically, we apply the wage index to the labor-related
share of the ESRD PPS base rate that we utilize for AKI dialysis to
compute the wage adjusted per-treatment AKI dialysis payment rate. As
stated previously, we are proposing a CY 2022 AKI dialysis payment rate
of $255.55, adjusted by the ESRD facility's wage index.
---------------------------------------------------------------------------
\133\ Section 1881(b)(14)(D)(iv)(II) of the Act.
---------------------------------------------------------------------------
IV. End-Stage Renal Disease Quality Incentive Program (ESRD QIP)
A. Background
For a detailed discussion of the End-Stage Renal Disease Quality
Incentive Program's (ESRD QIP's) background and history, including a
description of the Program's authorizing statute and the policies that
we have adopted in previous final rules, we refer readers to the
following final rules:
CY 2011 ESRD PPS final rule (75 FR 49030),
CY 2012 ESRD PPS final rule (76 FR 628),
CY 2012 ESRD PPS final rule (76 FR 70228),
CY 2013 ESRD PPS final rule (77 FR 67450),
CY 2014 ESRD PPS final rule (78 FR 72156),
CY 2015 ESRD PPS final rule (79 FR 66120),
CY 2016 ESRD PPS final rule (80 FR 68968),
CY 2017 ESRD PPS final rule (81 FR 77834),
CY 2018 ESRD PPS final rule (82 FR 50738),
CY 2019 ESRD PPS final rule (83 FR 56922),
CY 2020 ESRD PPS final rule (84 FR 60648), and
CY 2021 ESRD PPS final rule (85 FR 71398).
We have also codified many of our policies for the ESRD QIP at 42
CFR 413.177 and 413.178.
[[Page 36348]]
B. Extraordinary Circumstances Exception (ECE) Previously Granted for
the ESRD QIP and Notification of ECE Due to ESRD Quality Reporting
System Issues
1. Extraordinary Circumstance Exception (ECE) Previously Granted in
Response to the COVID-19 PHE
On March 22, 2020, in response to the COVID-19 PHE, we announced
relief for clinicians, providers, hospitals, and facilities
participating in Medicare quality reporting and value-based purchasing
programs.\134\ On March 27, 2020, we published a supplemental guidance
memorandum that described the scope and duration of the ECEs we were
granting under each Medicare quality reporting and VBP program.\135\
Each of these ECEs relieved these providers and facilities of their
obligation to report data for Q4 CY 2019, Q1 and Q2 CY 2020, but we
stated that we would score such data if optionally reported.
---------------------------------------------------------------------------
\134\ CMS, Press Release, CMS Announces Relief for Clinicians,
Providers, Hospitals and Facilities Participating in Quality
Reporting Programs in Response to COVID-19 (Mar. 22, 2020), https://www.cms.gov/newsroom/press-releases/cms-announces-relief-clinicians-providers-hospitals-and-facilities-participating-quality-reporting.
\135\ CMS, Exceptions and Extensions for Quality Reporting
Requirements for Acute Care Hospitals, PPS-Exempt Cancer Hospitals,
Inpatient Psychiatric Facilities, Skilled Nursing Facilities, Home
Health Agencies, Hospices, Inpatient Rehabilitation Facilities,
Long-Term Care Hospitals, Ambulatory Surgical Centers, Renal
Dialysis Facilities, and MIPS Eligible Clinicians Affected by COVID-
19 (Mar. 27, 2020), https://www.cms.gov/files/document/guidance-memo-exceptions-and-extensions-quality-reporting-and-value-based-purchasing-programs.pdf.
---------------------------------------------------------------------------
The September 2020 IFC updated the ECE we granted in response to
the COVID-19 PHE for the ESRD QIP and several other quality reporting
programs (85 FR 54827 through 54838).
In the IFC, we updated the ECE policy for the ESRD QIP (85 FR 54828
through 54830). First, we updated our regulations at Sec.
413.178(d)(7) to state that a facility has opted out of the ECE for
COVID-19 with respect to the reporting of Q4 CY 2019 NHSN data if the
facility actually reported the data by the March 31, 2020 deadline but
did not notify CMS that it would do so. Additionally, we finalized that
facilities would not have the option to opt-out of the ECE we granted
with respect to Q1 and Q2 2020 ESRD QIP data. We stated that measures
calculated using excepted data could affect the national comparability
of these data due to the geographic differences of COVID-19 incidence
rates and hospitalizations along with different impacts resulting from
different state and local law and policy changes implemented in
response to COVID-19, and therefore may not provide a nationally
comparable assessment of performance in keeping with the program goal
of national comparison.
In the September 2020 IFC, we welcomed public comments on our
policy to update our regulations at Sec. 413.178(d)(7) to consider a
facility as having opted out of the ECE with respect to NHSN data
reported for Q4 2019 if the facility actually reported the data by the
submission deadline, without notifying CMS, and on the exception we
finalized to the ECE opt out policy for the ESRD QIP to exclude any
ESRD QIP data that facilities optionally reported during Q1 and Q2 2020
from our calculation of PY 2022 TPSs and from the baseline for PY 2023.
We will respond to the public comments we received in the CY 2022 ESRD
PPS final rule.
2. Notification of ECE Due to ESRD Quality Reporting System (EQRS)
Issues
On November 9, 2020,\136\ we launched the ESRD Quality Reporting
System (EQRS). The EQRS contains the functionalities of the following
three legacy ESRD Systems in one global application: (1) A quality
measure and VBP performance score review system (ESRD QIP System); (2)
an ESRD patient registry and quality measure reporting system through
CROWNWeb; and (3) Medicare coverage determination support through the
Renal Management Information System (REMIS). The transition to EQRS
supports our efforts to consolidate the functionalities of the
CROWNWeb, ESRD QIP System, and REMIS applications into a single system,
and aims to provide ongoing support to the ESRD user community to
foster accurate and timely monthly data submission. This migration
eliminates the need for multiple user accounts, and will in the long-
term also improve the overall user experience and reduce burden due to
enhanced navigation features.
---------------------------------------------------------------------------
\136\ https://mycrownweb.org/2020/11/november-2020-newsletter/.
---------------------------------------------------------------------------
In order to access EQRS, all authorized users must create an
account with the Health Care Quality Information Systems (HCQIS) Access
Roles and Profile, known as HARP, which is a secure identity management
portal provided by CMS. Previously, users created separate accounts for
each ESRD application through CMS' Enterprise Identity Data Management
(EIDM) system. Creating an account via HARP provides users with a user
ID and password that can be used to access many CMS applications. It
also provides a single location for users to modify their profile,
change their password, update their challenge question, and add or
remove two-factor authentication devices. Users can register for a HARP
account by going to the QualityNet HARP Registration page, available at
https://harp.cms.gov/register/profile-info.
Since the launch of EQRS, several critical data submission issues
have been identified that impact the overall quality and accuracy of
data available to support the implementation of the ESRD QIP, and we
suspended all clinical data submissions into EQRS to allow time to
resolve the issue.\137\ Based on our assessment, the data submission
issues only impact ESRD QIP, Dialysis Star Ratings, Dialysis Facility
Compare and data submitted for ESRD Network quality improvement
activities. We have analyzed the data submission issues and believe
that the data systems issues will be resolved on or about July 12,
2021.
---------------------------------------------------------------------------
\137\ https://mycrownweb.org/2021/02/eqrs-data-reporting-update-feb-2021/.
---------------------------------------------------------------------------
We recognize that these operational systems issues will prevent
facilities from submitting ESRD QIP clinical data until the data
systems issues are resolved. Therefore, we are announcing a blanket
extension of remaining CY 2020 clinical reporting deadlines. Under this
extension, facilities will have until September 1, 2021 to submit
September through December 2020 ESRD QIP clinical data. We believe this
reporting extension aligns with the time estimated for resolution of
our operational systems issues and will give dialysis facilities nearly
seven weeks to submit their data to EQRS. We will provide further
details to facilities when the EQRS issues are resolved, as well as
when facilities can begin submitting their data for CY 2020 and CY
2021, through routine communication channels to facilities, vendors,
Quality Improvement Organizations (QIOs) and ESRD Networks. The
communications could include memos, emails, and notices on the public
QualityNet website (https://www.qualitynet.org/). We discuss the
treatment of impacted CY 2020 data in this proposed rule. As this
situation is ongoing, we will announce any relevant extension deadlines
and data submission requirements for impacted CY 2021 data through the
routine communication channels discussed above.
Because the current data submissions issue will not be resolved
until on or about July 12, 2021 and has impacted all facilities that
participate in ESRD QIP, we believe that granting a blanket ECE
[[Page 36349]]
to all facilities without a request under 42 CFR 413.178(d)(6)(ii) is
the appropriate remedy under these circumstances. We also believe that
requiring facilities to report the CY 2020 data impacted by this ECE by
September 1, 2021 is reasonable. In our data suspension announcements,
we noted that facilities are expected to continue to use EQRS to
collect clinical data to complete tasks such as admit and discharge
patients, complete CMS forms (such as the CMS-2728: End Stage Renal
Disease Medical Evidence Report Medicare Entitlement and/or Patient
Registration, CMS-2744: End Stage Renal Disease Annual Facillity Survey
Form, and CMS-2746: ESRD Death Notification), add or update treatment
summaries, resolve notifications within a timely manner, and should
also continue to keep facilities' information up-to-date. In other
words, although facilities were unable to submit clinical data through
EQRS, facilities were advised that they must continue to collect the
clinical data.
While we are working to resolve all known systems issues by on or
about July 12, 2021 and reopen submissions so that facilities may
submit their September through December 2020 ESRD QIP data no later
than September 1, 2021, we will only be able to ensure the validity of
the impacted data after they are submitted. Given that the system
issues experienced during the initial implementation of the EQRS, if
not fully resolved, could potentially impact the accuracy and
reliability of the data reported, we are concerned that facilities may
be unfairly penalized because the current systems issues may impact the
quality of the data. The EQRS system issues have resulted in multiple
or incorrect dates of patient admissions and/or discharges, as well as
showing duplicate patient records. Facilities have also expressed
concerns about their experience with EQRS issues, noting that there is
no way for a facility to verify accuracy or completeness. They have
reported issues including missing record status in response files,
which means that facilities do not know if the records were accepted or
received an error response, and issues with determining whether
clinical data are accepted because the information does not show in the
user interface or the reports that facilities are receiving from EQRS.
We recognize stakeholders' concerns about the potential impact to
the quality of data for CY 2020. We believe the observed system issues,
and any unresolved issues that may be identified only after data
submissions are resumed, could impact the quality and accuracy of the
data needed to calculate accurate ESRD QIP scores used for PY 2022 ESRD
QIP calculations because patient admittance dates, discharge dates,
record status in response files, clinical data, and the number of
active patient cases are data points that are included in measure
calculations for all of the PY 2022 ESRD QIP measures. If these data
points are incorrect, then this would impact our ability to accurately
calculate measures and would distort a facility's measure performance.
Therefore, because of the EQRS system issues described above, and
additionally, due to the impact of the COVID-19 PHE on some of the PY
2022 ESRD QIP measures, as described more fully in section IV.C. of
this proposed rule, we are proposing to not score or award a TPS to any
facility, or reduce payment to any facility, in PY 2022, as discussed
more fully in section IV.D.
Although we considered if there may be any alternative data sources
for the measures impacted by these EQRS system issues, we concluded
that this was not feasible for several reasons. First, all 14 ESRD QIP
measures for PY 2022 are impacted by these system issues. Although
certain measures do not require that facilities submit clinical data
into EQRS, we use EQRS data to determine whether a facility has treated
a sufficient number of patients in order to meet the measure's minimum
patient case threshold necessary to calculate the measure for ESRD QIP.
For example, the National Healthcare Safety Network (NHSN) Bloodstream
Infection (BSI) clinical measure requires that facilities report data
to NHSN. However, the measure also has a requirement to exclude
facilities that do not treat at least 11 eligible in-center
hemodialysis patients during the 12 month performance period. In order
to determine whether a facility has treated at least 11 eligible
patients, we use EQRS admission data and Medicare claims data in order
to determine whether the facility is eligible to receive a score on the
measure.\138\
---------------------------------------------------------------------------
\138\ https://www.cms.gov/files/document/cy-2021-final-technical-specifications-20201130.pdf.
---------------------------------------------------------------------------
We ultimately decided to propose the special rule for PY 2022, as
described further, because not only do these system issues impact all
ESRD QIP measures, which could lead to distorted performance scores and
unfair penalties, but we also want to provide facilities with the
business certainty they need regarding their PY 2022 payments. In order
to determine whether all data quality issues have been resolved when
EQRS reopens for data submissions, we will need time to validate the
impacted data after facilities are able to resume data submission. Due
to the timing of this reporting extension, we believe that there are no
feasible alternative data sources for PY 2022. Therefore, we believe
that the scoring and payment modifications for PY 2022 as proposed in
section IV.D in this proposed rule are appropriate in this situation.
C. Proposed Flexibilities for the ESRD QIP in Response to the COVID-19
PHE
1. Proposal To Adopt a Measure Suppression Policy for the Duration of
the COVID-19 PHE
In previous rules, we have identified the need for flexibility in
our quality measurement programs to account for changing conditions
that are beyond participating facilities' or practitioners' control. We
identified this need because we would like to ensure that participants
in our programs are not affected negatively when their quality
performance suffers for reasons not due to the care provided, but
instead due to external factors.
A significant example of the type of external factor that may
affect quality measurement is the COVID-19 PHE, which has had, and
continues to have, significant and ongoing effects on the provision of
medical care in the country and around the world. The COVID-19 pandemic
and associated PHE have impeded effective quality measurement in many
ways. Changes to clinical practices to accommodate safety protocols for
medical personnel and patients, as well as unpredicted changes in the
number of stays and facility-level case mixes, have affected the data
used in quality measurement and the resulting quality scores. Measures
used in the ESRD QIP need to be evaluated to determine whether their
specifications need to be updated to account for new clinical
guidelines, diagnosis or procedure codes, and medication changes that
we have observed during the PHE. Additionally, because COVID-19
prevalence is not consistent across the country, dialysis facilities
located in different areas have been affected differently at different
times throughout the pandemic. Under those circumstances, we remain
significantly concerned that the ESRD QIP's quality measure scores that
are calculated using data submitted during the PHE for COVID-19 will be
distorted and will result in skewed payment incentives and inequitable
payments, particularly for dialysis facilities that have treated more
COVID-19 patients than others.
It is not our intention to penalize dialysis facilities based on
measure
[[Page 36350]]
scores that we believe are distorted by the COVID-19 pandemic and,
thus, not reflective of the quality of care that the measures in the
ESRD QIP were designed to assess. As discussed above, the COVID-19
pandemic has had, and continues to have, significant and enduring
effects on health care systems around the world, and affects care
decisions, including those made on clinical topics covered by the ESRD
QIP's measures. As a result of the COVID-19 PHE, dialysis facilities
could provide care to their patients that meets the underlying clinical
standard but results in worse measured performance, and by extension,
payment penalties in the ESRD QIP. We are also concerned that regional
differences in COVID-19 prevalence during the performance period for PY
2022 have directly affected dialysis facilities' measure scores on the
ESRD QIP for PY 2022. Although these regional differences in COVID-19
prevalence rates do not reflect differences in the quality of care
furnished by dialysis facilities, they could directly affect the
payment penalties that these facilities could receive and could result
in an unfair and inequitable distribution of those penalties. These
inequities could be especially pronounced for dialysis facilities that
have treated a large number of COVID-19 patients.
We are therefore proposing to adopt a policy for the duration of
the COVID-19 PHE that would enable us to suppress the use of ESRD QIP
measure data for all facilities if we determine that circumstances
caused by the COVID-19 PHE have affected those measures and the
resulting total performance scores (TPSs) significantly. We are also
proposing, as described in more detail in section IV.C.2. of this
proposed rule, to suppress certain measures for the PY 2022 program
year because we have determined that circumstances caused by the COVID-
19 PHE have affected those measures significantly. In addition, due to
both the impacts of the COVID-19 PHE on certain measures and the EQRS
system issues described in section IV.B.2. we are proposing to adopt a
special scoring and payment rule for PY 2022, as described more fully
in section IV.D.
In developing this proposed policy, we considered what
circumstances caused by the COVID-19 PHE would affect a quality measure
significantly enough to warrant its suppression in a value-based
purchasing (VBP) program. We believe that a significant deviation in
measured performance that can be reasonably attributed to the COVID-19
PHE is a significant indicator of changes in clinical conditions that
affect quality measurement. Similarly, we believe that a measure may be
focused on a clinical topic or subject that is proximal to the disease,
pathogen, or other health impacts of the PHE. As has been the case
during the COVID-19 pandemic, we believe that rapid or unprecedented
changes in clinical guidelines and care delivery, potentially including
appropriate treatments, drugs, or other protocols may affect quality
measurement significantly and should not be attributed to the
participating facility positively or negatively. We also note that
scientific understanding of a particular disease or pathogen may evolve
quickly during an emergency, especially in cases of new disease or
conditions. Finally, we believe that, as evidenced during the COVID-19
pandemic, national or regional shortages or changes in health care
personnel, medical supplies, equipment, diagnostic tools, and patient
case volumes or case mix may result in significant distortions to
quality measurement.
Based on these considerations, we developed a number of Measure
Suppression Factors that we believe should guide our determination of
whether to propose to suppress ESRD QIP measures for one or more
payment years that overlap with the COVID-19 PHE. We are proposing to
adopt these Measure Suppression Factors for use in the ESRD QIP and,
for consistency, the following other VBP programs: Hospital VBP,
Hospital Readmissions Reduction Program, Hospital-Acquired Condition
(HAC) Reduction Program, and Skilled Nursing Facility VBP Program (see,
for example, 86 FR 25460 through 25462, 25470 through 25472, and 25497
through 25499). We believe that these Measure Suppression Factors will
help us evaluate measures in the ESRD QIP and that their adoption in
the other VBP programs noted above will help ensure consistency in our
measure evaluations across programs. The proposed Measure Suppression
Factors are:
Factor 1: Significant deviation in national performance on
the measure during the COVID-19 PHE, which could be significantly
better or significantly worse compared to historical performance during
the immediately preceding program years.
Factor 2: Clinical proximity of the measure's focus to the
relevant disease, pathogen, or health impacts of the COVID-19 PHE.
Factor 3: Rapid or unprecedented changes in:
++ Clinical guidelines, care delivery or practice, treatments,
drugs, or related protocols, or equipment or diagnostic tools or
materials; or
++ the generally accepted scientific understanding of the nature or
biological pathway of the disease or pathogen, particularly for a novel
disease or pathogen of unknown origin.
Factor 4: Significant national shortages or rapid or
unprecedented changes in:
++ Healthcare personnel;
++ medical supplies, equipment, or diagnostic tools or materials;
or
++ patient case volumes or facility-level case mix.
We also considered alternatives to this proposed policy that could
fulfill our objective to not penalize dialysis facilities for measure
results that are distorted due to the COVID-19 PHE. As noted above, the
country continues to grapple with the effects of the COVID-19 pandemic,
and in March 2020, CMS issued a nationwide, blanket Extraordinary
Circumstances Exception (ECE) for all hospitals and other facilities
participating in our quality reporting and VBP programs in response to
the COVID-19 PHE. This blanket ECE excepted all data reporting
requirements for Q1 and Q2 2020 data, including claims data and data
collected through the CDC's web-based surveillance system for this data
period, and quality data collection resumed on July 1, 2020. For
claims-based measures, we also stated that we would exclude all
qualifying Q1 and Q2 2020 claims from our measure calculations. We
considered extending this blanket ECE that we issued for Q1 and Q2 2020
to also include Q3 and Q4 2020. This alternative would protect
providers and suppliers from having their quality data used for quality
scoring purposes while those data are likely to have been affected
significantly by the COVID-19 PHE. However, this option would make
quality data collection and reporting to CMS no longer mandatory and
would leave no comprehensive data available for us to provide
confidential performance feedback to providers nor for monitoring and
to inform decision-making for potential future programmatic changes,
particularly as the PHE is extended.
As an alternative to the proposed quality measure suppression
policy, we also considered not suppressing any measures under the ESRD
QIP. However, this alternative would mean assessing dialysis facilities
using quality measure data that has been significantly affected by the
COVID-19 pandemic. Additionally, given the geographic disparities in
the COVID-19 pandemic's effects, implementation of the PY 2022 ESRD QIP
as previously finalized would place dialysis facilities in regions that
were more heavily impacted by the
[[Page 36351]]
pandemic in Q3 and Q4 of 2020 at a disadvantage compared to facilities
in regions that were more heavily impacted during the first two
quarters for CY 2020.
We view this measure suppression proposal as a necessity to ensure
that the ESRD QIP does not penalize facilities based on external
factors that were beyond the control of facilities. We intend for this
proposed policy to provide short-term relief to dialysis facilities
when we have determined that one or more of the Measure Suppression
Factors warrants the suppression of an ESRD QIP measure.
We welcome public comments on this proposal for the adoption of a
measure suppression policy for the duration of the COVID-19 PHE, and
also on the proposed Measure Suppression Factors that we developed for
purposes of this proposed policy.
2. Proposals To Suppress Four ESRD QIP Measures for PY 2022
a. Background
In response to the PHE for the COVID-19 pandemic, we have conducted
analyses of the fourteen current ESRD QIP measures to determine whether
and how COVID-19 may have impacted the validity of these measures. For
the reasons discussed below, we have concluded that COVID-19 has so
severely impacted the validity of four measures that we cannot fairly
and equitably score these measures for the PY 2022 program year, and we
are proposing to suppress these measures for the PY 2022 program year
for all ESRD QIP participants. Specifically, the measures we are
proposing to suppress for the PY 2022 ESRD QIP are as follows:
SHR clinical measure (under proposed Measure Suppression
Factor 1, Significant deviation in national performance on the measure
during the COVID-19 PHE, which could be significantly better or
significantly worse compared to historical performance during the
immediately preceding program years; and proposed Measure Suppression
Factor 4, Significant national shortages or rapid or unprecedented
changes in:
++ Healthcare personnel;
++ medical supplies, equipment, or diagnostic tools or materials;
or (iii) patient case volumes or facility-level case mix);
Standardized Readmission Ratio (SRR) clinical measure
(under proposed Measure Suppression Factor 1, Significant deviation in
national performance on the measure during the COVID-19 PHE, which
could be significantly better or significantly worse compared to
historical performance during the immediately preceding program years;
and proposed Measure Suppression Factor 4, Significant national
shortages or rapid or unprecedented changes in:
++ Healthcare personnel;
++ medical supplies, equipment, or diagnostic tools or materials;
or
++ patient case volumes or facility-level case mix);
In-Center Hemodialysis Consumer Assessment of Healthcare
Providers and Systems (ICH CAHPS) Survey Administration clinical
measure (under proposed Measure Suppression Factor 1, Significant
deviation in national performance on the measure during the COVID-19
PHE, which could be significantly better or significantly worse
compared to historical performance during the immediately preceding
program years); and
Long-Term Catheter Rate clinical measure (under proposed
Measure Suppression Factor 1, Significant deviation in national
performance on the measure during the COVID-19 PHE, which could be
significantly better or significantly worse compared to historical
performance during the immediately preceding program years).
b. Proposal To Suppress the SHR Clinical Measure for PY 2022
We are proposing to suppress the SHR clinical measure for the PY
2022 program year under proposed Measure Suppression Factor 1,
Significant deviation in national performance on the measure during the
COVID-19 PHE, which could be significantly better or significantly
worse as compared to historical performance during the immediately
preceding program years. The SHR clinical measure is an all-cause,
risk-standardized rate of hospitalizations during a 1-year observation
window. The standardized hospitalization ratio is defined as the ratio
of the number of hospital admissions that occur for Medicare ESRD
dialysis patients treated at a particular facility to the number of
hospitalizations that would be expected given the characteristics of
the dialysis facility's patients and the national norm for dialysis
facilities. This measure is calculated as a ratio but can also be
expressed as a rate. The intent of the SHR clinical measure is to
improve health care delivery and care coordination to help reduce
unplanned hospitalization among ESRD patients.
Based on our analysis of Medicare dialysis patient data from
January 2020 through August 2020, we found that hospitalizations
involving patients diagnosed with COVID-19 resulted in higher mortality
rates, higher rates of discharge to hospice or skilled nursing
facilities, and lower rates of discharge to home than hospitalizations
involving patients who are not diagnosed with COVID-19. Specifically,
the hospitalization rate for Medicare dialysis patients diagnosed with
COVID-19 was more than 7 times greater than the hospitalization rate
during the same period for Medicare dialysis patients who were not
diagnosed with COVID-19, which is much greater than the relative risk
of hospitalization for any other comorbidity. This indicates that
COVID-19 has had a significant impact on the hospitalization rate for
dialysis patients. Because COVID-19 Medicare dialysis patients are at
significantly greater risk of hospitalization, and the SHR clinical
measure was not developed to account for the impact of COVID-19 on this
patient population, we are concerned about the effects of the observed
COVID-19 hospitalizations on the SHR clinical measure. We also note
that COVID-19 affected different regions of the country at different
rates depending on factors like time of year, geographic density, state
and local policies, and health care system capacity. Because of the
increased hospitalization risk associated with COVID-19 and the
Medicare dialysis patient population, we are concerned that these
regional differences in COVID-19 rates has led to distorted
hospitalization rates such that we cannot reliably measure national
performance on the SHR clinical measure.
Our analysis of the available Medicare claims data indicates that
the COVID-19 PHE has had significant effects on hospital admissions of
dialysis patients, and will result in significant deviation in national
performance on the measure during the COVID-19 PHE which could be
significantly worse as compared to historical performance during the
immediately preceding program years. Not only are there effects on
patients diagnosed with COVID-19, but the presence of the virus
strongly affected hospital admission patterns of dialysis patients from
March 2020 to June 2020, and we are concerned that similar effects will
be seen in the balance of the calendar year (CY) as the PHE continued.
Because the COVID-19 pandemic swept through geographic regions of the
country unevenly, we are concerned that dialysis facilities in
different regions of the country would have been affected differently
throughout the 2020 year, thereby
[[Page 36352]]
skewing measure performance and affecting national comparability due to
significant and unprecedented changes in patient case volumes or
facility-level case mix. Given the limitations of the data available to
us for CY 2020, we believe the resulting performance measurement on the
SHR clinical measure would not be sufficiently reliable or valid for
use in the ESRD QIP.
We are proposing to suppress this measure for the PY 2022 program
year, rather than remove it, because we believe that the SHR clinical
measure is an important part of the ESRD QIP measure set. However, we
are concerned that the COVID-19 PHE affects measure performance on the
current SHR clinical measure such that we would not be able to score
facilities fairly or equitably on it. Additionally, we would continue
to collect the measure's claims data from participating facilities so
that we can monitor the effect of the circumstances on quality
measurement and determine the appropriate policies in the future. We
would also continue to provide confidential feedback reports to
facilities as part of program activities to ensure that they are made
aware of the changes in performance rates that we observe. We also
intend to publicly report PY 2022 data where feasible and appropriately
caveated.
We are currently exploring ways to adjust effectively for the
systematic effects of the COVID-19 PHE on hospital admissions for the
SHR clinical measure. However, we are still working to improve these
COVID-19 adjustments and verify the validity of a potential modified
version of the SHR clinical measure as additional data become
available. As an alternative, we considered whether we could exclude
patients with a diagnosis of COVID-19 from the SHR clinical measure
cohort, but we determined suppression will provide us with additional
time and additional months of data potentially impacted by COVID-19 to
more thoroughly evaluate a broader range of alternatives. We want to
ensure that the measure reflects care provided to Medicare dialysis
patients and we are concerned that excluding otherwise eligible
patients may not accurately reflect the care provided, particularly
given the unequal distribution of COVID-19 patients across facilities
and hospitals over time. As an alternative approach, we also might
consider updating the specifications for the SHR clinical measure to
eliminate any exposure time and events after infection for patients who
contract COVID-19, as COVID-19 symptoms may continue to affect patients
after infection. We believe this approach might help distinguish
between ESRD-related hospitalizations and COVID-19 related
hospitalizations that might otherwise impact SHR clinical measure
calculations.
We welcome public comment on our proposal to suppress the SHR
clinical measure for PY 2022.
c. Proposal To Suppress the SRR Clinical Measure for PY 2022
We are proposing to suppress the SRR clinical measure for the PY
2022 program year under proposed Measure Suppression Factor 1,
Significant deviation in national performance on the measure during the
COVID-19 PHE, which could be significantly better or significantly
worse compared to historical performance during the immediately
preceding program years. The SRR assesses the number of readmission
events for the patients at a facility, relative to the number of
readmission events that would be expected based on overall national
rates and the characteristics of the patients at that facility as well
as the number of discharges. The intent of the SRR clinical measure has
always been to improve care coordination between dialysis facilities
and hospitals to improve communication prior to and post discharge.
Based on our analysis, we found that index discharge
hospitalizations involving dialysis patients diagnosed with COVID-19
resulted in lower readmissions and higher mortality rates within the
first 7 days. We used index hospitalizations occurring from January 1,
2020 through June 30, 2020 to identify eligible index hospitalizations
and unplanned hospital readmissions. In an analysis of unadjusted
readmission and death rates by COVID-19 hospitalization status and days
since index discharge, during the first 4 to 7 days after discharge
there was a readmission rate of 81.3 percent of dialysis patients
hospitalized with COVID-19, as compared to 82.6 percent of dialysis
patients hospitalized without COVID-19. During that same 4 to 7 day
time period, the unadjusted mortality rate for dialysis patients
hospitalized with COVID-19 was 16.9 percent, compared with 10.9 percent
of patients hospitalized without COVID-19. Based on this discrepancy,
we are concerned about the effects of these observations on the
calculations for the SRR clinical measure. The denominator of SRR
reflects the expected number of index discharges followed by an
unplanned readmission within 4 to 30 days in each facility, which is
derived from a model that accounts for patient characteristics, the
dialysis facility to which the patient is discharged, and the
discharging acute care or critical access hospitals involved. Our
analysis indicates potential competing risks of higher mortality and
lower readmissions due to patient death or discharge to hospice, both
of which would remove them from the denominator for the SRR clinical
measure. If readmissions rates are lower because patient mortality is
higher due to the impact of COVID-19 on dialysis patients, then
readmission rates are distorted by appearing significantly better
compared to historical performance during the immediately preceding
program years. Based on the impact of COVID-19 on SRR results,
including the deviance in measurement, we concluded that the SRR
clinical measure meets our criteria for Factor 1 where performance data
would significantly deviate from historical data performance and would
be considered unreliable. Therefore, we believe the resulting
performance measurement on the SRR clinical measure would not be
sufficiently reliable or valid for use in the ESRD QIP.
We are proposing to suppress this measure for the PY 2022 program
year, rather than remove it, because we believe that the SRR clinical
measure is an important part of the ESRD QIP Program measure set.
However, we are concerned that the PHE for the COVID-19 pandemic
affects measure performance on the current SRR clinical measure such
that we will not be able to score facilities fairly or equitably on it.
Additionally, we would continue to collect the measure's claims data
from participating facilities so that we can monitor the effect of the
circumstances on quality measurement and determine the appropriate
policies in the future. We would also continue to provide confidential
feedback reports to facilities as part of program activities to ensure
that they are made aware of the changes in performance rates that we
observe. We also intend to publicly report PY 2022 data where feasible
and appropriately caveated.
We are currently exploring ways to adjust effectively for the
systematic effects of the COVID-19 PHE on hospital admissions for the
SRR clinical measure. However, we are still working to improve these
COVID-19 adjustments and verify the validity of a potential modified
version of the SRR clinical measure as additional data becomes
available. As an alternative approach, we might also consider
eliminating from the calculation of the SRR clinical measure any cases
of patients who had a COVID-19 event prior to or at the time of index
hospitalization. We believe this
[[Page 36353]]
approach might help distinguish between ESRD-related readmissions and
COVID-19 related readmissions that might otherwise impact SRR clinical
measure calculations.
We welcome public comment on our proposal to suppress the SRR
clinical measure for PY 2022.
d. Proposal To Suppress the ICH CAHPS Clinical Measure for PY 2022
We are proposing to suppress the ICH CAHPS clinical measure for the
PY 2022 program year under proposed Measure Suppression Factor 1,
Significant deviation in national performance on the measure during the
COVID-19 PHE, which could be significantly better or significantly
worse compared to historical performance during the immediately
preceding program years. Based on our analysis of CY 2020 ICH CAHPS
data, we have found a significant decrease in response scores as
compared to previous years.
The ICH CAHPS clinical measure is scored based on three composite
measures and three global ratings.\139\ Global ratings questions employ
a scale of 0 to 10, worst to best; each of the questions within a
composite measure use either ``Yes'' or ``No'' responses, or response
categories ranging from ``Never'' to ``Always'' to assess the patient's
experience of care at a facility. Facility performance on each
composite measure is determined by the percent of patients who choose
``top-box'' responses (that is, most positive or ``Always'') to the ICH
CAHPS survey questions in each domain. The ICH CAHPS survey is
administered twice yearly, once in the spring and once in the fall.
---------------------------------------------------------------------------
\139\ Groupings of questions and composite measures can be found
at https://ichcahps.org/Portals/0/ICH_Composites_English.pdf.
---------------------------------------------------------------------------
Because of the ECE we granted in response to the COVID-19 PHE,
facilities were not required to submit CY 2020 spring ICH CAHPS data
for purposes of the ESRD QIP. On September 2, 2020, we published an
interim final rule with comment (IFC) in the Federal Register titled,
``Medicare and Medicaid Programs, Clinical Laboratory Improvement
Amendments (CLIA), and Patient Protection and Affordable Care Act;
Additional Policy and Regulatory Revisions in Response to the COVID-19
Public Health Emergency'' (85 FR 54820) referred to herein as the
``September 2020 IFC''. In the September 2020 IFC, we noted that we
would not use any first or second quarter CY 2020 data to calculate
TPSs for the applicable performance period (85 FR 54829 through 54830).
Because the PY 2022 performance period for the ICH CAHPS measure is
January 1, 2020 through December 31, 2020, and the ICH CAHPS survey is
administered twice a year (once in the spring and once in the fall), we
only have data available from the fall CY 2020 survey to calculate
facility performance on this measure. Therefore, facilities would only
be scored on data based on one ICH CAHPS survey administration for CY
2020, rather than two. Even if we were to score facilities based on the
one ICH CAHPS survey administered in the fall, our preliminary data
indicates that 95 percent of facilities would not be eligible for
scoring on ICH CAHPS for CY 2020. By contrast, 58.9 percent of
facilities were not eligible for ICH CAHPS during CY 2018. If we were
to score the 5 percent of eligible facilities on ICH CAHPS, we believe
there would be a significant deviation in national performance on this
measure compared to the national performance based on 41.1 percent of
facilities eligible for scoring on ICH CAHPS during 2018. This is a
significant deviation in national performance on this measure compared
to historical performance during the immediately preceding program
years. Given this significant deviation in national performance during
the PHE, we believe the ICH CAHPS clinical measure meets the criteria
for Measure Suppression Factor 1.
We also believe that this significant change in performance may
unfairly penalize facilities and that suppressing this measure for the
PY 2022 program year will address concerns about the potential
unintended consequences of penalizing facilities that treat COVID-19
diagnosed patients in the ESRD QIP. As alternative approaches, we
considered changing the performance period or scoring facilities on one
survey administration, but otherwise meeting the 30 completed surveys
requirement. However, we found that neither of these approaches were
feasible; extending the performance period would not accurately reflect
ICH CAHPS performance during CY 2020, and as discussed above, an
estimated 95 percent of facilities would not be eligible for ICH CAHPS
scoring on one survey. Therefore, to avoid unfairly penalizing
facilities due to their performance on the ICH CAHPS survey for the PY
2022 ESRD QIP, we believe it is appropriate to suppress the ICH CAHPS
measure for CY 2020, which is the performance period for the PY 2022
ESRD QIP program year (83 FR 57010).
We are proposing to suppress this measure for the PY 2022 program
year, rather than remove it, because we believe that the ICH CAHPS
measure is an important part of the ESRD QIP measure set. However, we
are concerned that the COVID-19 PHE affects measure performance on the
current ICH CAHPS measure such that we will not be able to score
facilities fairly or equitably on it. Additionally, participating
facilities would continue to report the measure's data to CMS so that
we can monitor the effect of the circumstances on quality measurement
and determine the appropriate policies in the future. We would also
continue to provide confidential feedback reports to facilities as part
of program activities to ensure that they are made aware of the changes
in performance rates that we observe. We also intend to publicly report
PY 2022 data where feasible and appropriately caveated.
We welcome public comment on our proposal to suppress the ICH CAHPS
measure for the PY 2022 program year.
e. Proposal To Suppress Long-Term Catheter Rate Clinical Measure for PY
2022
Under the measure suppression policy discussion in section IV.C.1
of this proposed rule, we are proposing to suppress the Long-Term
Catheter Rate clinical measure for the PY 2022 program year under
proposed Measure Suppression Factor 1, Significant deviation in
national performance on the measure during the COVID-19 PHE, which
could be significantly better or significantly worse compared to
historical performance during the immediately preceding program years.
Based on our analysis of Long-Term Catheter Rate clinical measure data
during CY 2020, we have found a significant increase in long-term
catheter use as compared to previous years, which may be the result of
hesitancy to seek medical treatment among dialysis patients concerned
about being exposed to COVID-19 during the PHE.
In the CY 2018 ESRD PPS final rule, we finalized the inclusion of
the Hemodialysis Vascular Access: Long-Term Catheter Rate clinical
measure in the ESRD QIP measure set beginning with the PY 2021 program
(82 FR 50778). The Long-Term Catheter Rate clinical measure is defined
as the percentage of adult hemodialysis patient-months using a catheter
continuously for three months or longer for vascular access. The
measure is based on vascular access data reported in the Consolidated
Renal Operations in a Web-enabled Network (CROWNWeb) and excludes
patient-months where a patient has a catheter in place and has a
limited life expectancy.
[[Page 36354]]
Our analysis based on the available data indicates that long-term
catheter use rates have increased significantly during the COVID-19
PHE. Average long-term catheter rates were averaging around 12 percent
in CY 2017 and CY 2018. In CY 2019, rates increased to average around
12.25 percent. This increase continued into CY 2020, with rates
reaching a peak of 14.7 percent in June 2020 and declining slightly to
14.3 percent in July and August 2020. After remaining around 12 percent
for 3 consecutive years, we view a sudden 2 percent increase in average
long-term catheter rates as a significant deviation compared to
historical performance during immediately preceding years. We are
concerned that the COVID-PHE impacted the ability of ESRD patients to
seek treatment from medical providers regarding their catheter use,
either due to difficulty accessing treatment due to COVID-19
precautions at healthcare facilities, or due to increased patient
reluctance to seek medical treatment because of risk of COVID-19
exposure and increased health risks resulting therefrom, and that these
contributed to the significant increase in long-term catheter use
rates.
We are proposing to suppress this measure for the PY 2022 program
year, rather than remove it, because we believe that the Long-Term
Catheter Rate clinical measure is an important part of the ESRD QIP
measure set. However, we are concerned that the PHE for COVID-19
affects measure performance on the current Long-Term Catheter Rate
clinical measure such that we will not be able to score facilities
fairly or equitably on it. Additionally, participating facilities would
continue to report the measure's data to CMS so that we can monitor the
effect of the circumstances on quality measurement and determine the
appropriate policies in the future. We would also continue to provide
confidential feedback reports to facilities as part of program
activities to ensure that they are made aware of the changes in
performance rates that we observe. We also intend to publicly report PY
2022 data where feasible and appropriately caveated.
We welcome public comment on our proposal to suppress the Long-Term
Catheter Rate clinical measure for the PY 2022 program year.
D. Proposed Special Scoring Methodology and Payment Policy for the PY
2022 ESRD QIP
As described in section IV.B.2 of this proposed rule, we have
considered the impact of operational systems issues preventing
facilities from submitting September through December 2020 patient and
clinical data into the EQRS from November 1, 2020 through on or about
July 12, 2021. Even when facilities are able to submit the September
through December 2020 patient and clinical data by September 1, 2021,
we will need time to validate the quality and reliability of the
impacted data in order to determine whether all data quality issues
have been resolved. In addition, as described in section IV.C. we
believe four of the ESRD QIP measures have been impacted by the COVID-
19 PHE that could result in distorted measure performance for PY 2022.
It is not our intention to penalize dialysis facilities based on
the performance on data that are not reliable, thus, not reflective of
the quality of care that the measures in the program are designed to
assess. Therefore, we are proposing a special rule for PY 2022 scoring
for the ESRD QIP under which we would calculate measure rates for all
measures, but would not calculate achievement and improvement points
for any of them because they have all been impacted by the operational
systems issues and, as proposed above, we believe that four of them
have additionally been significantly impacted by COVID. Because we
would not calculate achievement and improvement scores for any
measures, we are also proposing under this special rule that we would
not score any of the measures in the four domains or calculate or award
Total Performance Scores for any facility. We are also proposing to not
apply any payment reductions to ESRD facilities for PY 2022.
In order to ensure that a facility is aware of any changes to its
measure rates that we have observed, we are proposing to provide
confidential feedback reports that contain the measure rates we
calculated for PY 2022. Performance scores for facilities would be
released on Dialysis Facility Compare and footnoted to indicate
potential accuracy concerns with the scores. Performance score
certificates would be generated with the TPS showing as ``Not
Applicable.''
We propose to codify these policies for PY 2022 at 42 CFR
413.177(a) and Sec. 413.178(h).
However if the policies in sections IV.C and IV.D of this proposed
rule are not finalized, the PY 2022 ESRD QIP payment would be as
implemented in accordance with our current policy, as well as the
payment reduction ranges finalized in the CY 2020 ESRD PPS final rule
(84 FR 60725 through 60727).
We invite public comment on this proposed special scoring and
payment policy for the PY 2022 ESRD QIP.
E. Proposed Updates to Requirements Beginning With the PY 2024 ESRD QIP
1. PY 2024 ESRD QIP Measure Set
Under our current policy, we retain all ESRD QIP measures from year
to year unless we propose through rulemaking to remove them or
otherwise provide notification of immediate removal if a measure raises
potential safety issues (77 FR 67475). Accordingly, the PY 2024 ESRD
QIP measure set will include the same 14 measures as the PY 2023 ESRD
QIP measure set (85 FR 71465 through 71466). These measures are
described in Table 2. For the most recent information on each measure's
technical specifications for PY 2024, we refer readers to the CMS ESRD
Measures Manual for the 2021 Performance Period.\140\
---------------------------------------------------------------------------
\140\ https://www.cms.gov/files/document/esrd-measures-manual-v61.pdf.
---------------------------------------------------------------------------
BILLING CODE 4120-01-P
[[Page 36355]]
[GRAPHIC] [TIFF OMITTED] TP09JY21.001
BILLING CODE 4120-01-C
We discuss our proposal to update the SHR clinical measure in the
following section.
a. Proposal To Update the Standardized Hospitalization Ratio (SHR)
Clinical Measure Beginning With the PY 2024 ESRD QIP
In the CY 2017 ESRD PPS final rule, we adopted the SHR clinical
measure under the authority of section 1881(h)(2)(B)(ii) of the Act (81
FR 77906 through 77911). The SHR clinical measure is a National Quality
Forum (NQF)-endorsed all-cause, risk-standardized rate of
hospitalizations during a 1-year observation window. The standardized
hospitalization ratio is defined as the ratio of the number of hospital
admissions that occur for Medicare ESRD dialysis patients treated at a
particular facility to the number of hospitalizations that would be
expected
[[Page 36356]]
given the characteristics of the dialysis facility's patients and the
national norm for dialysis facilities. This measure is calculated as a
ratio but can also be expressed as a rate.
Hospitalizations are an important indicator of patient morbidity
and quality of life. On average, dialysis patients are admitted to the
hospital nearly twice a year and spend an average of 11.2 days in the
hospital per year.\141\ Hospitalizations account for approximately 33
percent of total Medicare expenditures for ESRD patients.\142\ Studies
have shown that improved health care delivery and care coordination may
help reduce unplanned acute care including hospitalization.\143\
Hospitalization rates vary across dialysis facilities even after
adjustment for patient characteristics, suggesting that
hospitalizations might be influenced by dialysis facility practices. An
adjusted facility-level standardized hospitalization ratio, accounting
for differences in patients' characteristics, plays an important role
in identifying potential problems, and helps facilities provide cost-
effective quality health care to help limit escalating medical costs.
---------------------------------------------------------------------------
\141\ United States Renal Data System. 2018 United States Renal
Data System annual data report: Epidemiology of kidney disease in
the United States. National Institutes of Health, National Institute
of Diabetes and Digestive and Kidney Diseases, Bethesda, MD 2018.
\142\ Ibid.
\143\ Office of the Assistant Secretary for Planning and
Evaluation, U.S. Department of Health & Human Services. Advancing
American Kidney Health. 2019. Available at: https://aspe.hhs.gov/system/files/pdf/262046/AdvancingAmericanKidneyHealth.pdf.
---------------------------------------------------------------------------
In the CY 2017 ESRD PPS final rule, we finalized our proposal to
adopt the SHR clinical measure, which was a modified version of the
NQF-endorsed SHR clinical measure (NQF #1463), as part of the ESRD QIP
measure set (81 FR 77911). In that final rule, we stated that our
modified SHR clinical measure would incorporate 210 prevalent
comorbidities into our risk adjustment calculation, as our analyses
suggested that incorporating prevalent comorbidities would result in a
more robust and reliable measure of hospitalization (81 FR 77906
through 77907). In that final rule, we explained that data used to
calculate the SHR clinical measure are derived from an extensive
national ESRD patient database (81 FR 77908). We noted that the
database is comprehensive for Medicare Parts A and B patients, and that
non-Medicare patients are included in all sources except for the
Medicare payment records. In that final rule, we also stated that the
Standard Information Management System/CROWNWeb provides tracking by
dialysis provider and treatment modality for non-Medicare patients, and
information on hospitalizations and patient comorbidities are obtained
from Medicare Inpatient Claims Standard Analysis Files. In the CY 2019
ESRD PPS final rule, we increased the weight of the SHR clinical
measure from 8.25 percent to 14 percent of the TPS (83 FR 56992 through
56997).
On November 20, 2020, NQF completed its most recent review of the
SHR clinical measure, a measure maintenance review, and renewed the
measure's endorsement. As part of this review, the NQF endorsed
updating the prevalent comorbidity adjustment, which would group 210
individual ICD-9-CM prevalent comorbidities into 90 condition groups,
derived from the Agency for Healthcare Research and Quality (AHRQ)
Clinical Classifications Software (CCS) groups. The updated prevalent
comorbidity adjustment would also limit the source of prevalent
comorbidities to inpatient claims. The switch to using only Medicare
inpatient claims to identify prevalent comorbidities is due to the lack
of Medicare outpatient claims data for the growing Medicare Advantage
(MA) patient population. By using the original set of Medicare claims
datasets (inpatient, outpatient, hospice, skilled nursing, and home
health), the NQF stated its concern that MA patient prevalent
comorbidities would be systematically biased. These MA patient
prevalent comorbidities would only be populated by Medicare inpatient
claims, as compared to non-MA patient prevalent comorbidities that
would be populated by the aforementioned set of Medicare claim sources.
The updated NQF-endorsed SHR clinical measure would also include all
time at risk for MA patients, and added a MA indicator for adjustment
in the model. The NQF-endorsed specifications also included updates to
parameterization of existing adjustment factors and re-evaluation of
interactions, and also created three distinct groups of patients to use
in the SHR model based on time spent in a skilled nursing facility,
noting that nursing home residence is a marker of higher morbidity.
The updated SHR clinical measure was included on the publicly
available ``List of Measures under Consideration for December 21,
2020'' (MUC List), a list of measures under consideration for use in
various Medicare programs.\144\ When the Measure Applications
Partnership Hospital Workgroup convened on January 11, 2021, it
reviewed the MUC List, including the SHR clinical measure. The Measure
Applications Partnership Hospital Workgroup recognized that
hospitalization rates vary across dialysis facilities, even after
adjusting for patient characteristics, which suggests that
hospitalizations might be influenced by dialysis facility practices.
The Measure Applications Partnership Hospital Workgroup also noted that
the SHR clinical measure seeks to improve patient outcomes by measuring
hospitalization ratios among dialysis facilities, and that the measure
seeks to promote communication between the dialysis facilities and
other care settings to improve care transitions.\145\ In its final
report, the Measure Applications Partnership supported this measure for
rulemaking.\146\
---------------------------------------------------------------------------
\144\ National Quality Forum. List of Measures Under
Consideration for December 21, 2020. Accessed at: https://www.cms.gov/files/document/measures-under-consideration-list-2020-report.pdf on January 29 2021.
\145\ Measure Applications Partnership. Measure Applications
Partnership Preliminary Recommendations 2020-2021. Accessed on
January 24, 2021 at: http://www.qualityforum.org/Project_Pages/MAP_Hospital_Workgroup.aspx.
\146\ Measure Applications Partnership. Measure Applications
Partnership 2020-2021: Considerations for Implementing Measures in
Federal Programs: Clinician, Hospital & PAC/LTC. Accessed on April
28, 2021 at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=94893.
---------------------------------------------------------------------------
In this proposed rule, we are proposing to update the SHR clinical
measure specifications to align with the NQF-endorsed updates. These
include updates to the risk adjustment method of the measure, which
include a prevalent comorbidity adjustment, the addition of MA patients
and a MA indicator in the model, updates to parameterization of
existing adjustment factors and re-evaluation of interactions, and an
indicator for a patient's time spent in a skilled nursing facility.
We believe that adopting these updates would be consistent with our
stated goal of evaluating opportunities to more closely align ESRD QIP
measures with NQF measure specifications (84 FR 60724). The SHR
clinical measure seeks to improve patient outcomes by measuring
hospitalization ratios among dialysis facilities, and we believe that
these updates would result in a more reliable and robust SHR clinical
measure.
We seek comment on this proposal to update the SHR clinical measure
specifications for use in the ESRD QIP beginning with PY 2024.
[[Page 36357]]
2. Performance Standards for the PY 2024 ESRD QIP
Section 1881(h)(4)(A) of the Act requires the Secretary to
establish performance standards with respect to the measures selected
for the ESRD QIP for a performance period with respect to a year. The
performance standards must include levels of achievement and
improvement, as required by section 1881(h)(4)(B) of the Act, and must
be established prior to the beginning of the performance period for the
year involved, as required by section 1881(h)(4)(C) of the Act. We
refer readers to the CY 2013 ESRD PPS final rule (76 FR 70277) for a
discussion of the achievement and improvement standards that we have
established for clinical measures used in the ESRD QIP. We define the
terms ``achievement threshold,'' ``benchmark,'' ``improvement
threshold,'' and ``performance standard'' in our regulations at Sec.
413.178(a)(1), (3), (7), and (12), respectively.
a. Proposal To Update the Performance Standards Applicable to the PY
2024 Clinical Measures
Our current policy is to automatically adopt a performance and
baseline period for each year that is 1 year advanced from those
specified for the previous payment year (84 FR 60728). Under this
policy, CY 2022 is currently the performance period and CY 2020 is the
baseline period for the PY 2024 ESRD QIP. However, under the nationwide
ECE that we granted in response to the COVID-19 PHE, first and second
quarter data for CY 2020 are excluded from scoring for purposes of the
ESRD QIP. We are concerned that it will be difficult to assess levels
of achievement and improvement if the performance standards are based
on partial year data.\147\ Our preliminary analysis indicates that the
effect of the excluded data would create higher performance standards
for certain measures and lower performance standards for other
measures, which may skew achievement and improvement thresholds for
facilities and therefore may result in performance standards that do
not accurately reflect levels of achievement and improvement.
---------------------------------------------------------------------------
\147\ We note that for most ESRD QIP measures, this partial year
data would be measure data from July and August 2020.
---------------------------------------------------------------------------
Our current policy substitutes the performance standard,
achievement threshold, and/or benchmark for a measure for a performance
year if final numerical values for the performance standard,
achievement threshold, and/or benchmark are worse than the numerical
values for that measure in the previous year of the ESRD QIP (82 FR
50764). We adopted this policy because we believe that the ESRD QIP
should not have lower performance standards than in previous years.
However, our general policy provides flexibility to substitute the
performance standard, achievement threshold and benchmark in
appropriate cases (82 FR 50764).
Although the lower performance standards would be substituted with
those from the prior year, the higher performance standards would be
used to set performance standards for certain measures, even though
they would be based on partial year data. We are concerned that this
may create performance standards for certain measures that would be
difficult for facilities to attain with a full 12 months of data.
Therefore, in this proposed rule, we are proposing to calculate the
performance standards for PY 2024 using CY 2019 data, which is the most
recently available full calendar year of data we can use to calculate
those standards. Due to the impact of CY 2020 data that is excluded
from the ESRD QIP for scoring purposes, we believe that using CY 2019
data for performance standard setting purposes is appropriate.
Consistent with our established policy, we would continue to use the
prior year's numerical values for performance standard, achievement
threshold, and benchmark if the most recent full CY's final numerical
values are worse.
We welcome public comments on this proposal.
b. Performance Standards for the PY 2024 ESRD QIP if Proposal to Use CY
2019 as the Baseline Period is Finalized
Table 3 displays the achievement thresholds, 50th percentiles of
the national performance, and benchmarks for the PY 2024 clinical
measures, and we would use these standards if our proposal to use CY
2019 as the baseline period is finalized.
BILLING CODE 4120-01-P
[[Page 36358]]
[GRAPHIC] [TIFF OMITTED] TP09JY21.002
In addition, we have summarized in Table 4 existing requirements
for successful reporting on reporting measures in the PY 2024 ESRD QIP.
We are not making any proposals to change these standards as a result
of the COVID-19 PHE.
[[Page 36359]]
[GRAPHIC] [TIFF OMITTED] TP09JY21.003
3. Eligibility Requirements for the PY 2024 ESRD QIP
Our current minimum eligibility requirements for scoring the ESRD
QIP measures are described in Table 5.
[[Page 36360]]
[GRAPHIC] [TIFF OMITTED] TP09JY21.004
4. Payment Reduction Scale for the PY 2024 ESRD QIP
Under our current policy, a facility will not receive a payment
reduction for a payment year in connection with its performance for the
ESRD QIP if it achieves a TPS that is at or above the minimum TPS
(mTPS) that we establish for the payment year. We have defined the mTPS
in our regulations at Sec. 413.178(a)(8) as, with respect to a payment
year, the TPS that an ESRD facility would receive if, during the
baseline period it performed at the 50th percentile of national
performance on all clinical measures and the median of national ESRD
facility performance on all reporting measures.
Our current policy, which is codified at Sec. 413.177 of our
regulations, also implements the payment reductions on a sliding scale
using ranges that reflect payment reduction differentials of 0.5
percent for each 10 points that the facility's TPS falls below the mTPS
(76 FR 634 through 635).
For PY 2024, based on available data, a facility must meet or
exceed a mTPS of 57 in order to avoid a payment reduction. We note that
the mTPS in this proposed rule is based on data from CY 2019 instead of
the PY 2024 baseline period (CY 2020) because we have proposed to use
CY 2019 as the baseline period for that payment year.
We refer readers to Table 3 for the estimated values of the 50th
percentile of national performance for each clinical measure. Under our
current policy, a facility that achieves a TPS of 56 or below would
receive a payment reduction based on the TPS ranges indicated in Table
6.
[[Page 36361]]
[GRAPHIC] [TIFF OMITTED] TP09JY21.005
BILLING CODE 4120-01-C
If we do not finalize the proposed update to our performance
standards policy as described in section IV.E.2.a of this proposed
rule, then we would update the mTPS for PY 2024, as well as the payment
reduction ranges for that payment year, in the CY 2022 ESRD PPS final
rule using data from CY 2020.
F. Updates for the PY 2025 ESRD QIP
1. Continuing Measures for the PY 2025 ESRD QIP
Under our previously adopted policy, the PY 2024 ESRD QIP measure
set will also be used for PY 2025. At this time, we are not proposing
to adopt any new measures beginning with the PY 2025 ESRD QIP.
2. Performance Period for the PY 2025 ESRD QIP
We continue to believe that 12-month performance and baseline
periods provide us sufficiently reliable quality measure data for the
ESRD QIP. Under this policy, we would adopt CY 2023 as the performance
period and CY 2021 as the baseline period for the PY 2025 ESRD QIP.
In this proposed rule, we are not proposing any changes to this
policy.
3. Performance Standards for the PY 2025 ESRD QIP
Section 1881(h)(4)(A) of the Act requires the Secretary to
establish performance standards with respect to the measures selected
for the ESRD QIP for a performance period with respect to a year. The
performance standards must include levels of achievement and
improvement, as required by section 1881(h)(4)(B) of the Act, and must
be established prior to the beginning of the performance period for the
year involved, as required by section 1881(h)(4)(C) of the Act. We
refer readers to the CY 2012 ESRD PPS final rule (76 FR 70277) for a
discussion of the achievement and improvement standards that we have
established for clinical measures used in the ESRD QIP. We define the
terms ``achievement threshold,'' ``benchmark,'' ``improvement
threshold,'' and ``performance standard'' in our regulations at Sec.
413.178(a)(1), (3), (7), and (12), respectively. In section IV.E.2.a of
this proposed rule, we note that we are proposing to use CY 2019 data
for purposes of calculating the performance standards for PY 2024
because, due to the anticipated impact of CY 2020 data that is excluded
from the ESRD QIP for scoring purposes during CY 2020, we believe that
using CY 2019 data for performance standard setting purposes would be
appropriate.
a. Performance Standards for Clinical Measures in the PY 2025 ESRD QIP
At this time, we do not have the necessary data to assign numerical
values to the achievement thresholds, benchmarks, and 50th percentiles
of national performance for the clinical measures for the PY 2025 ESRD
QIP because we do not have CY 2021 data. We intend to publish these
numerical values, using CY 2021 data, in the CY 2023 ESRD PPS final
rule.
b. Performance Standards for the Reporting Measures in the PY 2025 ESRD
QIP
In the CY 2019 ESRD PPS final rule, we finalized the continued use
of existing performance standards for the Screening for Clinical
Depression and Follow-Up reporting measure, the Ultrafiltration Rate
reporting measure, the NHSN Dialysis Event reporting measure, and the
MedRec reporting measure (83 FR 57010 through 57011). We will continue
use of these performance standards in PY 2025.
4. Scoring the PY 2025 ESRD QIP
a. Scoring Facility Performance on Clinical Measures
In the CY 2014 ESRD PPS final rule, we finalized policies for
scoring performance on clinical measures based on achievement and
improvement (78 FR 72215 through 72216). In the CY 2019 ESRD PPS final
rule, we finalized a policy to continue use of this methodology for
future payment years (83 FR 57011) and we codified these scoring
policies at Sec. 413.178(e).
In this proposed rule, we are not proposing any changes to this
policy for PY 2025.
b. Scoring Facility Performance on Reporting Measures
Our policy for scoring performance on reporting measures is
codified at Sec. 413.178(e), and more information on our scoring
policy for reporting measures can be found in the CY 2020 ESRD PPS
final rule (84 FR 60728). We previously finalized policies for scoring
performance on the NHSN Dialysis Event reporting measure in the CY 2018
ESRD PPS final rule (82 FR 50780 through 50781), as well as policies
for scoring the MedRec reporting measure and Clinical Depression
Screening and Follow-up reporting measure in the CY 2019 ESRD PPS final
rule (83 FR 57011). We also previously finalized the scoring policy for
the STrR reporting measure in the CY 2020 ESRD PPS final rule (84 FR
60721 through 60723). In the CY 2021 ESRD PPS final rule, we finalized
our updated scoring methodology for the Ultrafiltration Rate reporting
measure (85 FR 71468 through 71470).
In this proposed rule, we are not proposing any changes to this
policy for PY 2025.
5. Weighting the Measure Domains and the TPS for PY 2025
Under our current policy, we assign the Patient & Family Engagement
[[Page 36362]]
Measure Domain a weight of 15 percent of the TPS, the Care Coordination
Measure Domain a weight of 30 percent of the TPS, the Clinical Care
Measure Domain a weight of 40 percent of the TPS, and the Safety
Measure domain a weight of 15 percent of the TPS.
In the CY 2019 ESRD PPS final rule, we finalized a policy to assign
weights to individual measures and a policy to redistribute the weight
of unscored measures (83 FR 57011 through 57012). In the CY 2020 ESRD
PPS final rule, we finalized a policy to use the measure weights we
finalized for PY 2022 for the PY 2023 ESRD QIP and subsequent payment
years, and also to use the PY 2022 measure weight redistribution policy
for the PY 2023 ESRD QIP and subsequent payment years (84 FR 60728
through 60729). We are not proposing any updates to these policies for
PY 2025.
G. Requests for Information (RFIs) on Topics Relevant to ESRD QIP
1. Closing the Health Equity Gap in CMS Quality Programs Request for
Information
Persistent inequities in health care outcomes exist in the United
States (U.S.), including among Medicare patients. In recognition of
persistent health disparities and the importance of closing the health
equity gap, we request information on expanding several related CMS
programs to make reporting of health disparities based on social risk
factors and race and ethnicity, and disability more comprehensive and
actionable for dialysis facilities, providers, and patients. The
following is part of an ongoing effort across CMS to evaluate
appropriate initiatives to reduce health disparities. Feedback will be
used to inform the creation of a future, comprehensive, request for
information (RFI) focused on closing the health equity gap in CMS
programs and policies. This RFI contains four parts:
Background. This section provides information on existing
statements describing our commitment to health equity, and existing
initiatives with an emphasis on reducing disparity.
Current CMS Disparity Methods. This section describes the
methods, measures, and indicators of social risk currently used with
the CMS Disparity Methods.
Future potential stratification of quality measure
results. This section describes four potential future expansions of the
CMS Disparity Methods, including (a) Future potential stratification of
quality measure results by dual eligibility; (b) Future potential
stratification of quality measure results by race and ethnicity; (c)
Improving Demographic Data Collection; and (d) Potential Creation of an
ESRD Facility Equity Score to Synthesize Results Across Multiple Social
Risk Factors.
Solicitation of public comment. This section specifies 11
requests for feedback on the topics specified in this RFI.
a. Background
Significant and persistent inequities in health care outcomes exist
in the U.S.\148\ 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, or
being near or below the poverty level, is often associated with worse
health outcomes.149 150 151 152 153 154 155 156 Such
disparities in health outcomes are the result of number of factors, but
importantly for CMS programs, although not the sole determinant, poor
access and provision of lower quality health care contribute to health
disparities. For instance, numerous studies have shown that among
Medicare beneficiaries, racial and ethnic minority individuals often
receive lower quality of care, report lower experiences of care, and
experience more frequent hospital readmissions and operative
complications.157 158 159 160 161 162 Readmission rates for
common conditions in the Hospital Readmissions Reduction Program are
higher for Black Medicare beneficiaries and higher for Hispanic
Medicare beneficiaries with Congestive Heart Failure and Acute
Myocardial Infarction.163 164 165 166 167 Although Black
Americans represent 7.5 percent of all older adult Medicare
beneficiaries, they represent 28 percent of those with ESRD.\168\ Among
individuals with ESRD the odds of 30-day hospital readmission are 19
percent higher for Black beneficiaries as compared with white
beneficiaries.\169\ Studies have also shown that African Americans are
significantly more likely than white Americans to die prematurely from
heart disease and stroke.\170\ The COVID-19 pandemic has further
illustrated many of these longstanding health inequities with higher
rates of infection, hospitalization, and mortality among Black, Latino,
and Indigenous and Native American
[[Page 36363]]
persons relative to white persons.171 172 In the ESRD
patient population, one study found that the rate of COVID-19
hospitalizations among dialysis patients peaked at 40 times higher than
the rate in the general population during the pandemic, with Black,
Latino, and Asian persons hospitalized at a higher rate than white
persons.\173\ As noted by the Centers for Disease Control ``long-
standing systemic health and social inequities have put many people
from racial and ethnic minority groups at increased risk of getting
sick and dying from COVID-19.'' \174\ One important strategy for
addressing these important inequities is by improving data collection
to allow for better measurement and reporting on equity across our
programs and policies.
---------------------------------------------------------------------------
\148\ United States Department of Health and Human Services.
``Healthy People 2020: Disparities. 2014.'' Available at: https://www.healthypeople.gov/2020/about/foundation-health-measures/Disparities.
\149\ 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.
\150\ 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.
\151\ 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.
\152\ 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.
\153\ Rural Health Research Gateway. Rural Communities: Age,
Income, and Health Status. Rural Health Research Recap. November
2018.
\154\ 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.
\155\ www.cdc.gov/mmwr/volumes/70/wr/mm7005a1.htm.
\156\ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7386532/.
\157\ Martino, SC, Elliott, MN, Dembosky, JW, Hambarsoomian, K.,
Burkhart, Q., Klein, DJ, Gildner, J., and Haviland, AM. Racial,
Ethnic, and Gender Disparities in Health Care in Medicare Advantage.
Baltimore, MD: CMS Office of Minority Health. 2020.
\158\ Guide to Reducing Disparities in Readmissions. CMS Office
of Minority Health. Revised August 2018. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/OMH_Readmissions_Guide.pdf.
\159\ Singh JA, Lu X., Rosenthal GE, Ibrahim S., Cram P. Racial
disparities in knee and hip total joint arthroplasty: An 18-year
analysis of national Medicare data. Ann Rheum Dis. 2014
Dec;73(12):2107-15.
\160\ Rivera-Hernandez M., Rahman M., Mor V., Trivedi AN. Racial
Disparities in Readmission Rates among Patients Discharged to
Skilled Nursing Facilities. J Am Geriatr Soc. 2019 Aug;67(8):1672-
1679.
\161\ 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.
\162\ Tsai TC, Orav EJ, Joynt KE. Disparities in surgical 30-day
readmission rates for Medicare beneficiaries by race and site of
care. Ann Surg. Jun 2014;259(6):1086-1090.
\163\ Rodriguez F., Joynt KE, Lopez L., Saldana F., Jha AK.
Readmission rates for Hispanic Medicare beneficiaries with heart
failure and acute myocardial infarction. Am Heart J. Aug
2011;162(2):254-261 e253.
\164\ Centers for Medicare and Medicaid Services. Medicare
Hospital Quality Chartbook: Performance Report on Outcome Measures;
2014.
\165\ Guide to Reducing Disparities in Readmissions. CMS Office
of Minority Health. Revised August 2018. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/OMH_Readmissions_Guide.pdf.
\166\ Prieto-Centurion V., Gussin HA, Rolle AJ, Krishnan JA.
Chronic obstructive pulmonary disease readmissions at minority-
serving institutions. Ann Am Thorac Soc. Dec 2013;10(6):680-684.
\167\ 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.
\168\ https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/ESRD-Infographic.pdf.
\169\ Ibid.
\170\ HHS. Heart disease and African Americans. (March 29,
2021). https://www.minorityhealth.hhs.gov/omh/browse.aspx?lvl=4&lvlid=19.
\171\ https://www.cms.gov/files/document/medicare-covid-19-data-snapshot-fact-sheet.pdf.
\172\ Ochieng N., Cubanski J., Neuman T., Artiga S., and Damico
A. Racial and Ethnic Health Inequities and Medicare. Kaiser Family
Foundation. February 2021. Available at: https://www.kff.org/medicare/report/racial-and-ethnic-health-inequities-and-medicare/.
\173\ Weinhandl ED, Wetmore, JB, Peng Y., et al. Initial effects
of COVID-19 on patients with ESKD. J Am Soc Nephrol. Published
online April 8, 2021.doi:10.1681/ASN.2021010009.
\174\ https://www.cdc.gov/coronavirus/2019-ncov/community/health-equity/race-ethnicity.html.
---------------------------------------------------------------------------
We are committed to achieving equity in health care outcomes for
our beneficiaries by supporting providers in quality improvement
activities to reduce health inequities, enabling them to make more
informed decisions, and promoting provider accountability for health
care disparities.\175\ For the purposes of this rule, we are using a
definition of equity established in Executive Order 13985, as ``the
consistent and systematic fair, just, and impartial treatment of all
individuals, including individuals who belong to underserved
communities that have been denied such treatment, such as Black,
Latino, and Indigenous and Native American persons, Asian Americans and
Pacific Islanders and other persons of color; members of religious
minorities; lesbian, gay, bisexual, transgender, and queer (LGBTQ+)
persons; persons with disabilities; persons who live in rural areas;
and persons otherwise adversely affected by persistent poverty or
inequality.'' \176\ We note that this definition was recently
established by the Biden administration, and provides a useful, common
definition for equity across different areas of government, although
numerous other definitions of equity exist.
---------------------------------------------------------------------------
\175\ https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/Downloads/CMS-Quality-Strategy.pdf.
\176\ https://www.federalregister.gov/documents/2021/01/25/2021-01753/advancing-racial-equity-and-support-for-underserved-communities-through-the-federal-government.
---------------------------------------------------------------------------
Our ongoing commitment to closing the equity gap in CMS quality
programs is demonstrated by a portfolio of programs aimed at making
information on the quality of health care providers and services,
including disparities, more transparent to consumers and providers. The
CMS Equity Plan for Improving Quality in Medicare outlines a path to
equity which aims to support Quality Improvement Networks and Quality
Improvement Organizations (QIN-QIOs); federal, state, local, and tribal
organizations; providers; researchers; policymakers; beneficiaries and
their families; and other stakeholders in activities to achieve health
equity.\177\ The CMS Equity Plan for Improving Quality in Medicare
focuses on three core priority areas which inform our policies and
programs: (1) Increasing understanding and awareness of disparities;
(2) developing and disseminating solutions to achieve health equity;
and (3) implementing sustainable actions to achieve health equity.\178\
The CMS Quality Strategy \179\ and Meaningful Measures Framework \180\
include elimination of racial and ethnic disparities as a central
principle. Our efforts aimed at closing the health equity gap to date
have included both providing transparency of health disparities,
supporting providers with evidence-informed solutions to achieve health
equity, and reporting to providers on gaps in quality in the following:
---------------------------------------------------------------------------
\177\ Centers for Medicare and Medicaid Services Office of
Minority Health. The CMS Equity Plan for Improving Quality in
Medicare. 2015. https://www.cms.gov/About-CMS/Agency-Information/OMH/OMH_Dwnld-CMS_EquityPlanforMedicare_090615.pdf.
\178\ Centers for Medicare and Medicaid Services Office of
Minority Health. Paving The Way To Equity: A Progress Report. 2015-
2021. https://www.cms.gov/files/document/paving-way-equity-cms-omh-progress-report.pdf.
\179\ Centers for Medicare Services. CMS Quality Strategy. 2016.
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/Downloads/CMS-Quality-Strategy.pdf.
\180\ https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/MMF/General-info-Sub-Page.
---------------------------------------------------------------------------
The CMS Mapping Medicare Disparities Tool which is an
interactive map that identifies areas of disparities and is a starting
point to understand and investigate geographic, racial and ethnic
differences in health outcomes for Medicare patients.\181\
---------------------------------------------------------------------------
\181\ https://www.cms.gov/About-CMS/Agency-Information/OMH/OMH-Mapping-Medicare-Disparities.
---------------------------------------------------------------------------
The Racial, Ethnic, and Gender Disparities in Health Care
in Medicare Advantage Stratified Report, which highlights racial and
ethnic differences in health care experiences and clinical care,
compares quality of care for women and men, and looks at racial and
ethnic differences in quality of care among women and men separately
for Medicare Advantage plans.\182\
---------------------------------------------------------------------------
\182\ https://www.cms.gov/About-CMS/Agency-Information/OMH/research-and-data/statistics-and-data/stratified-reporting.
---------------------------------------------------------------------------
The Rural-Urban Disparities in Health Care in Medicare
Report which details rural-urban differences in health care experiences
and clinical care.\183\
---------------------------------------------------------------------------
\183\ Centers for Medicare & Medicaid Services. Rural-Urban
Disparities in Health Care in Medicare. 2019. https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/Rural-Urban-Disparities-in-Health-Care-in-Medicare-Report.pdf.
---------------------------------------------------------------------------
The Standardized Patient Assessment Data Elements for
certain post-acute care Quality Reporting Programs, which now includes
data reporting for race and ethnicity and preferred language, in
addition to screening questions for social needs (84 FR 42536 through
42588).
The CMS Innovation Center's Accountable Health Communities
Model which includes standardized collection of health-related social
needs data.
The Guide to Reducing Disparities which provides an
overview of key issues related to disparities in readmissions and
reviews set of activities that can help hospital leaders reduce
readmissions in diverse populations.\184\
---------------------------------------------------------------------------
\184\ Guide to Reducing Disparities in Readmissions. CMS Office
of Minority Health. Revised August 2018. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/OMH_Readmissions_Guide.pdf.
---------------------------------------------------------------------------
The Chronic Kidney Disease Disparities: Educational Guide
for Primary Care, which is intended to foster the development of
primary care practice teams in order to enhance care for vulnerable
patients with chronic kidney disease (CKD) and are at risk of
progression of disease or complications. The guide provides information
about disparities in the care of patients with CKD, presents potential
actions that may improve care and suggests other available resources
that may be used by primary care practice teams in caring for
vulnerable patients.\185\
---------------------------------------------------------------------------
\185\ CMS. Chronic Kidney Disease Disparities: Educational Guide
for Primary Care. February 2020. Available at: https://www.cms.gov/files/document/chronic-kidney-disease-disparities-educational-guide-primary-care.pdf.
---------------------------------------------------------------------------
The CMS Disparity Methods which provide hospital-level
confidential results stratified by dual eligibility for condition-
specific readmission
[[Page 36364]]
measures currently included in the Hospital Readmissions Reduction
Program (see 84 FR 42496 through 42500 for a discussion of using
stratified data in additional measures).
These programs are informed by reports by the National Academies of
Science, Engineering and Medicine (NASEM) \186\ and the Office of the
Assistant Secretary for Planning and Evaluation (ASPE) \187\ which have
examined the influence of social risk factors on several of our quality
programs. In this request for public comment, we address only the
eighth initiative listed above, the CMS Disparity Methods, which we
have implemented for measures in the Hospital Readmissions Reduction
Program and are considering in other programs, including the ESRD QIP.
We discuss the implementation of these methods to date and present
considerations for continuing to improve and expand these methods.
---------------------------------------------------------------------------
\186\ National Academies of Sciences, Engineering, and Medicine.
2016. Accounting for Social Risk Factors in Medicare Payment:
Identifying Social Risk Factors. Washington, DC: The National
Academies Press. https://doi.org/10.17226/21858.
\187\ https://aspe.hhs.gov/pdf-report/report-congress-social-risk-factors-and-performance-under-medicares-value-based-purchasing-programs.
---------------------------------------------------------------------------
b. Current CMS Disparity Methods
We first sought public comment on potential confidential and public
reporting of ESRD QIP measure data stratified by social risk factors in
the CY 2018 ESRD PPS proposed rule (82 FR 31202). We initially focused
on stratification by dual eligibility, which is consistent with
recommendations from ASPE's First Report to Congress which was required
by the Improving Medicare Post-Acute Care Transformation (IMPACT) Act
of 2014 (Pub. L. 113-185).\188\ This report found that in the context
of value-based purchasing (VBP) programs, dual eligibility was among
the most powerful predictors of poor health outcomes among those social
risk factors that ASPE examined and tested. In the FY 2018 IPPS/LTCH
PPS final rule we also solicited feedback on two potential methods for
illuminating differences in outcomes rates among patient groups within
a provider's patient population that would also allow for a comparison
of those differences, or disparities, across providers for the Hospital
IQR program (82 FR 38403 through 38409). The first method (the Within-
Hospital disparity method) promotes quality improvement by calculating
differences in outcome rates among patient groups within a hospital
while accounting for their clinical risk factors. This method also
allows for a comparison of the magnitude of disparity across hospitals,
so hospitals could assess how well they are closing disparity gaps
compared to other hospitals. The second methodological approach (the
Across-Hospital method) is complementary and assesses hospitals'
outcome rates for dual-eligible patients only, across hospitals,
allowing for a comparison among hospitals on their performance caring
for their patients with social risk factors. In the CY 2018 ESRD PPS
proposed rule (82 FR 31202 through 31203), we also specifically
solicited feedback on which social risk factors provide the most
valuable information to stakeholders. In addition, feedback was
solicited on the methodology for illuminating differences in outcomes
rates among patient groups within a provider's patient population that
would also allow for a comparison of those differences, or disparities,
across providers. Overall, comments supported the use of dual
eligibility as a proxy for social risk, although commenters also
suggested investigation of additional social risk factors, and we
continue to consider commenter suggestions for which risk factors
provide the most valuable information to stakeholders.
---------------------------------------------------------------------------
\188\ https://aspe.hhs.gov/pdf-report/report-congress-social-risk-factors-and-performance-under-medicares-value-based-purchasing-programs.
---------------------------------------------------------------------------
c. Future Potential Expansion of the CMS Disparity Methods to the ESRD
QIP
We are committed to advancing health equity by improving data
collection to better measure and analyze disparities across programs
and policies.\189\ As we previously noted, we have been considering,
among other things, expanding our efforts to provide stratified data
for additional social risk factors and measures, optimizing the ease-
of-use of the results, enhancing public transparency of equity results,
and building towards provider accountability for health equity. We are
seeking public comment on the potential stratification of quality
measures in the ESRD QIP across two social risk factors: Dual
eligibility and race/ethnicity.
---------------------------------------------------------------------------
\189\ Centers for Medicare Services. CMS Quality Strategy. 2016.
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/Downloads/CMS-Quality-Strategy.pdf.
---------------------------------------------------------------------------
(1) Stratification of Quality Measure Results--Dual Eligibility
As described above, landmark reports by NASEM \190\ and ASPE,\191\
which have examined the influence of social risk factors on several of
our quality programs, have shown that in the context of VBP programs,
dual eligibility, as an indicator of social risk, is a powerful
predictor of poor health outcomes. We are considering stratification of
quality measure results in the ESRD QIP and are considering which
measures would be most appropriate for stratification and if dual
eligibility would be a meaningful social risk factor for
stratification.
---------------------------------------------------------------------------
\190\ National Academies of Sciences, Engineering, and Medicine.
2016. Accounting for Social Risk Factors in Medicare Payment:
Identifying Social Risk Factors. Washington, DC: The National
Academies Press. https://doi.org/10.17226/21858.
\191\ https://aspe.hhs.gov/pdf-report/report-congress-social-risk-factors-and-performance-under-medicares-value-based-purchasing-programs.
---------------------------------------------------------------------------
For the ESRD QIP, we would consider disparity reporting using two
disparity methods the Within-Facility and Across-Facility methods. The
first method (based on the Within-Hospital disparity method, described
above) would aim to promote quality improvement by calculating
differences in outcome rates between dual and non-dual eligible patient
groups within a facility while accounting for their clinical risk
factors. This method would allow for a comparison of those differences,
or disparities, across facilities, so facilities could assess how well
they are closing disparity gaps compared to other facilities. The
second approach (based on the Across-Hospital method) would be
complementary and assesses facilities' outcome rates for subgroups of
patients, such as dual eligible patients, across facilities, allowing
for a comparison among facilities on their performance caring for their
patients with social risk factors.
(2) Stratification of Quality Measure Results--Race and Ethnicity
The Administration's Executive Order on Advancing Racial Equity and
Support for Underserved Communities Through the Federal Government
directs agencies to assess potential barriers that underserved
communities and individuals may face to enrollment in and access to
benefits and services in federal programs. As summarized earlier in the
preamble, studies have shown that among Medicare beneficiaries, racial
and ethnic minority persons often experience worse health outcomes,
including more frequent hospital readmissions and procedural
[[Page 36365]]
complications.\192\ We also note that the prevalence of ESRD is higher
among racial minorities.\193\ For example, in 2016 ESRD prevalence was
approximately 9.5 times greater in Native Hawaiians and Pacific
Islanders, 3.7 times greater in African Americans, 1.5 times greater in
American Indians and Alaska Natives, and 1.3 times greater in
Asians.\194\ An important part of identifying and addressing inequities
in health care is improving data collection to allow us to better
measure and report on equity across our programs and policies. We are
considering stratification of quality measure results in the ESRD QIP
by race and ethnicity, and are identifying which measures would be most
appropriate for stratification.
---------------------------------------------------------------------------
\192\ https://www.kff.org/medicare/report/racial-and-ethnic-health-inequities-and-medicare/.
\193\ United States Renal Data System. 2018 Annual Data Report:
ESRD Incidence, Prevalence, Patient Characteristics, and Treatment
Modalities. Available online at https://www.usrds.org/2018/view/Default.aspx.
\194\ United States Renal Data System. 2018 Annual Data Report,
Vol 2, Figure 1.12. Available online at https://www.usrds.org/2018/view/Default.aspx.
---------------------------------------------------------------------------
As outlined in the 1997 Office of Management and Budget (OMB)
Revisions to the Standards for the Collection of Federal Data on Race
and Ethnicity, the racial and ethnic categories which may be used for
reporting the disparity methods are considered to be social and
cultural, not biological or genetic.\195\ The 1997 OMB Standard lists
five minimum categories of race: (1) American Indian or Alaska Native;
(2) Asian; (3) Black or African American; (4) Native Hawaiian or Other
Pacific Islander; (5) and White. In the OMB standards, Hispanic or
Latino is the only ethnicity category included, and since race and
ethnicity are two separate and distinct concepts, persons who report
themselves as Hispanic or Latino can be of any race.\196\ Another
example, the ``Race & Ethnicity--CDC'' code system in Public Health
Information Network (PHIN) Vocabulary Access and Distribution Systems
(VADS) \197\ permits a much more granular structured recording of a
patient's race and ethnicity with its inclusion of over 900 concepts
for race and ethnicity. The recording and exchange of patient race and
ethnicity at such a granular level can facilitate the accurate
identification and analysis of health disparities based on race and
ethnicity. Further, the ``Race & Ethnicity--CDC'' code system has a
hierarchy that rolls up to the OMB minimum categories for race and
ethnicity and, thus, supports aggregation and reporting using the OMB
standard. ONC includes both the CDC and OMB standards in its criterion
for certified health IT products.\198\ For race and ethnicity, a
certified health IT product must be able to express both detailed races
and ethnicities using any of the 900 plus concepts in the ``Race &
Ethnicity--CDC'' code system in PHIN VADS, as well as aggregate each
one of a patient's races and ethnicities to the categories in the OMB
standard for race and ethnicity. This approach can reduce burden on
providers recording demographics using certified products.
---------------------------------------------------------------------------
\195\ Executive Office of the President Office of Management and
Budget, Office of Information and Regulatory Affairs. Revisions to
the standards for the classification of federal data on race and
ethnicity. Vol 62. Federal Register. 1997:58782-58790.
\196\ https://www.census.gov/topics/population/hispanic-origin/about.html.
\197\ https://phinvads.cdc.gov/vads/ViewValueSet.action?id=67D34BBC-617F-DD11-B38D-00188B398520.
\198\ ONC criteria for certified health IT products: https://www.healthit.gov/isa/representing-patient-race-and-ethnicity.
---------------------------------------------------------------------------
Self-reported race and ethnicity data remain the gold standard for
classifying an individual according to race or ethnicity. However,
historical inaccuracies in federal data systems and limited collection
classifications have contributed to the limited quality of race and
ethnicity information in our administrative data systems.\199\ In
recent decades, to address these data quality issues, CMS has
undertaken numerous initiatives, including updating data taxonomies and
conducting direct mailings to some beneficiaries to enable more
comprehensive race and ethnic identification.200 201 Despite
those efforts, studies reveal varying data accuracy in identification
of racial and ethnic groups in Medicare administrative data, with
higher sensitivity for correctly identifying white and Black
individuals, and lower sensitivity for correctly identifying
individuals of Hispanic ethnicity or of Asian/Pacific Islander and
American Indian/Alaskan Native race.\202\ Incorrectly classified race
or ethnicity may result in overestimation or underestimation in the
quality of care received by certain groups of beneficiaries.
---------------------------------------------------------------------------
\199\ Eicheldinger, C., & Bonito, A. (2008). More accurate
racial and ethnic codes for Medicare administrative data. Health
Care Financing Review, 29(3), 27-42.
\200\ Filice CE, Joynt KE. Examining Race and Ethnicity
Information in Medicare Administrative Data. Med Care.
2017;55(12):e170-e176. doi:10.1097/MLR.0000000000000608.
\201\ Eicheldinger, C., & Bonito, A. (2008). More accurate
racial and ethnic codes for Medicare administrative data. Health
Care Financing Review, 29(3), 27-42.
\202\ Centers for Medicare and Medicaid Services. Building an
Organizational Response to Health Disparities Inventory of Resources
for Standardized Demographic and Language Data Collection. 2020.
https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/Data-Collection-Resources.pdf.
---------------------------------------------------------------------------
We continue to work with public and private partners to better
collect and leverage data on social risk to improve our understanding
of how these factors can be better measured in order to close the
health equity gap. Among other things, we have developed an Inventory
of Resources for Standardized Demographic and Language Data Collection
\203\ and supported collection of specialized International
Classification of Disease, 10th Edition, Clinical Modification (ICD-10-
CM) codes for describing the socioeconomic, cultural, and environmental
determinants of health, and sponsored several initiatives to
statistically estimate race and ethnicity information when it is
absent.\204\
---------------------------------------------------------------------------
\203\ Centers for Medicare and Medicaid Services. Building an
Organizational Response to Health Disparities Inventory of Resources
for Standardized Demographic and Language Data Collection. 2020.
https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/Data-Collection-Resources.pdf.
\204\ https://pubmed.ncbi.nlm.nih.gov/18567241/, https://pubmed.ncbi.nlm.nih.gov/30506674/, Eicheldinger C., Bonito A. More
accurate racial and ethnic codes for Medicare administrative data.
Health Care Finance Rev. 2008;29(3):27-42. Haas A., Elliott MN,
Dembosky JW, et al. Imputation of race/ethnicity to enable
measurement of HEDIS performance by race/ethnicity. Health Serv Res.
2019;54(1):13-23. doi:10.1111/1475-6773.13099.
---------------------------------------------------------------------------
The Office of the National Coordinator for Health Information
Technology (ONC) included social, psychological, and behavioral
standards in the 2015 Edition health information technology
certification criteria (2015 Edition), providing interoperability
standards LOINC (Logical Observation Identifiers Names and Codes) and
SNOMED CT (Systematized Nomenclature of Medicine--Clinical Terms) for
financial strain, education, social connection and isolation, and
others. Additional stakeholder efforts underway to expand capabilities
to capture additional social determinants of health data elements
include the Gravity Project to identify and harmonize social risk
factor data for interoperable electronic health information exchange
for EHR fields, as well as proposals to expand the ICD-10
(International Classification of Diseases, Tenth Revision) Z-codes, the
alphanumeric codes used worldwide to represent diagnoses.\205\
---------------------------------------------------------------------------
\205\ https://aspe.hhs.gov/pdf-report/second-impact-report-to-congress.
---------------------------------------------------------------------------
While development of sustainable and consistent programs to collect
data on social determinants of health can be considerable undertakings,
we recognize
[[Page 36366]]
that another method to identify better race and ethnicity data is
needed in the short term to address the need for reporting on health
equity. In working with our contractors, two algorithms have been
developed to indirectly estimate the race and ethnicity of Medicare
beneficiaries (as described further in the next section). We believe
that using indirect estimation can help to overcome the current
limitations of demographic information and enable timelier reporting of
equity results until longer term collaborations to improve demographic
data quality across the health care sector materialize. The use of
indirectly estimated race and ethnicity for conducting stratified
reporting does not place any additional collection or reporting burdens
on facilities as these data are derived using existing administrative
and Census-linked data.
Indirect estimation relies on a statistical imputation method for
inferring a missing variable or improving an imperfect administrative
variable using a related set of information that is more readily
available.\206\ Indirectly estimated data are most commonly used at the
population level (such as the facility or health plan-level), where
aggregated results form a more accurate description of the population
than existing, imperfect data sets. These methods often estimate race
and ethnicity using a combination of other data sources which are
predictive of self-identified race and ethnicity, such as language
preference, information about race and ethnicity in our administrative
records, first and last names matched to validated lists of names
correlated to specific national origin groups, and the racial and
ethnic composition of the surrounding neighborhood. Indirect estimation
has been used in other settings to support population-based equity
measurement when self-identified data are not available.\207\
---------------------------------------------------------------------------
\206\ IOM. 2009. Race, Ethnicity, and Language Data:
Standardization for Health Care Quality Improvement. Washington, DC:
The National Academies Press.
\207\ IOM. 2009. Race, Ethnicity, and Language Data:
Standardization for Health Care Quality Improvement. Washington, DC:
The National Academies Press.
---------------------------------------------------------------------------
As discussed earlier in the preamble, we have previously supported
the development of two such methods of indirect estimation of race and
ethnicity of Medicare beneficiaries. One indirect estimation approach,
developed by our contractor, uses Medicare administrative data, first
name and surname matching, derived from the U.S. Census and other
sources, with beneficiary language preference, state of residence, and
the source of the race and ethnicity code in Medicare administrative
data to reclassify some beneficiaries as Hispanic or Asian Pacific
Islander (API).\208\ In recent years, we have also worked with another
contractor to develop a new approach, the Medicare Bayesian Improved
Surname Geocoding (MBISG), which combines Medicare administrative data,
first and surname matching, geocoded residential address linked to the
2010 U.S. Census, and uses both Bayesian updating and multinomial
logistic regression to estimate the probability of belonging to each of
six racial/ethnic groups.\209\
---------------------------------------------------------------------------
\208\ Eicheldinger, C., & Bonito, A. (2008). More accurate
racial and ethnic codes for Medicare administrative data. Health
Care Financing Review, 29(3), 27-42.
\209\ Haas, A., Elliott, M. et al., (2018). Imputation of race/
ethnicity to enable measurement of HEDIS performance by race/
ethnicity. Health Services Research, 54:13-23.
---------------------------------------------------------------------------
The MBISG model is currently used to conduct the national,
contract-level, stratified reporting of Medicare Part C & D performance
data for Medicare Advantage Plans by race and ethnicity.\210\
Validation testing reveals concordances of 0.88-0.95 between indirectly
estimated and self-report among individuals who identify as White,
Black, Hispanic, and Asian Pacific Islander for the MBISG version 2.0
and concordances with self-reported race and ethnicity of 0.96-0.99 for
these same groups for MBISG version 2.1.211 212 The
algorithms under consideration are considerably less accurate for
individuals who self-identify as American Indian or Alaskan Native as
well as for those who self-identify as multiracial.\213\
---------------------------------------------------------------------------
\210\ https://www.cms.gov/About-CMS/Agency-Information/OMH/research-and-data/statistics-and-data/stratified-reporting.
\211\ Haas, A., Elliott, M. et al., (2018). Imputation of race/
ethnicity to enable measurement of HEDIS performance by race/
ethnicity. Health Services Research, 54:13-23.
\212\ https://www.cms.gov/files/document/racial-ethnic-gender-disparities-health-care-medicare-advantage.pdf.
\213\ Haas, A., Elliott, M. et al., (2018). Imputation of race/
ethnicity to enable measurement of HEDIS performance by race/
ethnicity. Health Services Research, 54:13-23 and Bonito AJ, Bann
C., Eicheldinger C., Carpenter L. Creation of New Race-Ethnicity
Codes and Socioeconomic Status (SES) Indicators for Medicare
Beneficiaries. Final Report, Sub-Task 2. (Prepared by RTI
International for the Centers for Medicare and Medicaid Services
through an interagency agreement with the Agency for Healthcare
Research and Policy, under Contract No. 500-00-0024, Task No. 21)
AHRQ Publication No. 08-0029-EF. Rockville, MD, Agency for
Healthcare Research and Quality. January 2008.
---------------------------------------------------------------------------
Indirect estimation can be a statistically reliable approach for
calculating population-level equity results for groups of individuals
(such as the facility-level) and is not intended, nor being considered,
as an approach for inferring the race and ethnicity of an individual.
However, despite the high degree of statistical accuracy of the
indirect estimation algorithms under consideration there remains the
small risk of unintentionally introducing bias. For example, if the
indirect estimation is not as accurate in correctly estimating race and
ethnicity in certain geographies or populations it could lead to some
bias in the method results. Such bias might result in slight
overestimation or underestimation of the quality of care received by a
given group. We feel this amount of bias is considerably less than
would be expected if stratified reporting was conducted using the race
and ethnicity currently contained in our administrative data. Indirect
estimation of race and ethnicity is envisioned as an intermediate step,
filling the pressing need for more accurate demographic information for
the purposes of exploring inequities in service delivery, while
allowing newer approaches, as described in the next section, for
enhancing demographic data collection. We are interested in learning
more about, and soliciting comments, about the potential benefits and
challenges associated with measuring facility equity using an
imputation algorithm to enhance existing administrative data quality
for race and ethnicity until self-reported information is sufficiently
available.
(3) Improving Demographic Data Collection
Stratified facility-level reporting using indirectly estimated race
and ethnicity and dual eligibility would represent an important advance
in our ability to provide equity reports to facilities. However, self-
reported disability status, race and ethnicity data remain the gold
standard for classifying an individual according to disability status,
race or ethnicity. The CMS Quality Strategy outlines our commitment to
strengthening infrastructure and data systems by ensuring that
standardized demographic information is collected to identify
disparities in health care delivery outcomes.\214\ Collection and
sharing of a standardized set of social, psychological, and behavioral
data by facilities, including disability status and race and ethnicity,
using electronic data definitions which permit nationwide,
interoperable health information
[[Page 36367]]
exchange, can significantly enhance the accuracy and robustness of our
equity reporting.\215\ This could potentially include expansion to
additional social risk factors, such as language preference and
disability status, where accuracy of administrative data is currently
limited. We are mindful that additional resources, including data
collection and staff training may be necessary to ensure that
conditions are created whereby all patients are comfortable answering
all demographic questions, and that individual preferences for non-
response are maintained.
---------------------------------------------------------------------------
\214\ The Centers for Medicare & Medicaid Services. CMS Quality
Strategy. 2016. https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/Downloads/CMS-Quality-Strategy.pdf.
\215\ The Office of the National Coordinator for Health
Information Technology. United State Core Data for Interoperability
Draft Version 2. 2021. https://www.healthit.gov/isa/sites/isa/files/2021-01/Draft-USCDI-Version-2-January-2021-Final.pdf.
---------------------------------------------------------------------------
We are also interested in learning about and are soliciting
comments on current data collection practices by facilities to capture
demographic data elements (such as race, ethnicity, sex, sexual
orientation and gender identity (SOGI), language preference, and
disability status). Further, we are interested in potential challenges
facing facility collection of a minimum set of demographic data
elements in alignment with national data collection standards (such as
the standards finalized by the Affordable Care Act) \216\ and standards
for interoperable exchange (such as the U.S. Core Data for
Interoperability put forth by the Office of the National Coordinator
for Health Information Technology for incorporation in certified health
IT products as part of the 2015 Edition of health IT certification
criteria.) \217\ Advancing data interoperability through collection of
a minimum set of demographic data collection has the potential for
improving the robustness of the disparity methods results, potentially
permitting reporting using more accurate, self-reported, information,
such as race and ethnicity, and expanding reporting to additional
dimensions of equity, including stratified reporting by disability
status.
---------------------------------------------------------------------------
\216\ https://minorityhealth.hhs.gov/assets/pdf/checked/1/Fact_Sheet_Section_4302.pdf.
\217\ https://www.healthit.gov/sites/default/files/2020-08/2015EdCures_Update_CCG_USCDI.pdf.
---------------------------------------------------------------------------
(4) Potential Creation of an ESRD Facility Equity Score to Synthesize
Results Across Multiple Social Risk Factors
As we describe above, we are considering expanding the disparity
methods to include two social risk factors (dual eligibility and race/
ethnicity). This approach would improve the comprehensiveness of health
equity information provided to facilities. Aggregated results from
multiple measures and multiple social risk factors, from the CMS
Disparity Methods, in the format of a summary score, can improve the
usefulness of the equity results. In working with our contractors, we
recently developed an equity summary score for Medicare Advantage
contract/plans, the Health Equity Summary Score (HESS), with
application to stratified reporting using two social risk factors: Dual
eligibility and race and as described in Incentivizing Excellent Care
to At-Risk Groups with a Health Equity Summary Score.\218\
---------------------------------------------------------------------------
\218\ Agniel D., Martino S.C., Burkhart Q., et al. Incentivizing
Excellent Care to At-Risk Groups with a Health Equity Summary Score.
J Gen Intern Med. Published online November 11, 2019 Nov 11. doi:
10.1007/s11606-019-05473-x.
---------------------------------------------------------------------------
The HESS calculates standardized and combined performance scores
blended across the two social risk factors. The HESS also combines
results of the within-plan (similar to the Within-Facility method) and
across-plan method (similar to the Across-Facility method) across
multiple performance measures.
We are considering building an ESRD Facility Equity Score, not yet
developed, which would be modeled off the HESS but adapted to the
context of risk-adjusted facility outcome measures and potentially
other ESRD QIP quality measures. We envision that the ESRD Facility
Equity Score would synthesize results for a range of measures and using
multiple social risk factors, using measures and social risk factors
which would be reported to facilities as part of the CMS Disparity
Methods. We believe that creation of the ESRD Facility Equity Score has
the potential to supplement the overall measure data already reporting
on the Care Compare or successor website, by providing easy to
interpret information regarding disparities measured within individual
facilities and across facilities nationally. A summary score would
decrease burden by minimizing the number of measure results provided
and providing an overall indicator of equity.
The ESRD Facility Equity Score under consideration would
potentially:
Summarize facility performance across multiple social risk
factors (initially dual eligibility and indirectly estimated race and
ethnicity, as described above).
Summarize facility performance across the two disparity
methods (that is, the Within-Facility Disparity Method and the Across-
Facility Disparity Method) and potentially multiple measures.
Prior to any future public reporting of stratified measure data
using indirectly estimated race and ethnicity information, if we
determine that an ESRD Facility Equity Score can be feasibly and
accurately calculated, we would provide results of the ESRD Facility
Equity Score, in confidential facility specific reports which
facilities and their QIN-QIOs would be able to download. Any potential
future proposal to display the ESRD Facility Equity Score on the Care
Compare or successor website would be made through future RFI or
rulemaking.
d. Solicitation of Public Comment
We are seeking comment on the possibility of stratifying ESRD QIP
measures by dual eligibility and race and ethnicity. We are soliciting
public comments on the application of the within-facility or across-
facility disparities methods if we were to stratify ESRD QIP measures.
We are also seeking comment on the possibility of facility collection
of standardized demographic information for the purposes of potential
future quality reporting and measure stratification. In addition, we
are seeking comment on the potential design of a facility equity score
for calculating results across multiple social risk factors and
measures, including race and disability. Any data pertaining to these
areas that are recommended for collection for measure reporting for a
CMS program and any potential public disclosure on Care Compare or
successor website would be addressed through a separate and future
notice- and-comment rulemaking. We plan to continue working with ASPE,
facilities, the public, and other key stakeholders on this important
issue to identify policy solutions that achieve the goals of attaining
health equity for all patients and minimizing unintended consequences.
We look forward to receiving feedback on these topics and note for
readers that responses to the RFI will not directly impact payment
decisions. We also note our intention for additional RFI or rulemaking
on this topic in the future.
Specifically, we are inviting public comment on the following:
Future Potential Stratification of Quality Measure Results
The possible stratification of facility-specific reports
for ESRD QIP measure data by dual-eligibility status, including which
measures would be most appropriate for stratification;
The potential future application of indirect estimation of
race and ethnicity information to permit stratification of
[[Page 36368]]
measure data for reporting ESRD facility-level disparity results;
Appropriate privacy safeguards with respect to data
produced from the indirect estimation of race and ethnicity to ensure
that such data is properly identified if/when it is shared with
facilities.
Ways to address the challenges of defining and collecting,
accurate and standardized self-identified demographic information,
including information on race and ethnicity, disability, and language
preference for the purposes of reporting, measure stratification and
other data collection efforts relating to quality.
Recommendations for other types of readily available data
elements for measuring disadvantage and discrimination for the purposes
of reporting, measure stratification and other data collection efforts
relating to quality, in addition, or in combination with race and
ethnicity.
Recommendations for types of quality measures or
measurement domains to prioritize for stratified reporting by dual
eligibility, race and ethnicity, and disability.
Examples of approaches, methods, research, and/or
considerations for use of data-driven technologies that do not
facilitate exacerbation of health inequities, recognizing that biases
may occur in methodology or be encoded in datasets.
Improving Demographic Data Collection
Experiences of users of certified health IT regarding
local adoption of practices for collection of social, psychological,
and behavioral data elements, the perceived value of using these data
for improving decision-making and care delivery, and the potential
challenges and benefits of collecting more granular, structured
demographic information, such as the ``Race & Ethnicity--CDC'' code
system.
The possible collection of a minimum set of social,
psychological, and behavioral data elements by ESRD facilities at the
time of admission using structured, interoperable electronic data
standards, for the purposes of reporting, measure stratification and
other data collection efforts relating to quality.
Potential Creation of an ESRD Facility Equity Score To Synthesize
Results Across Multiple Social Risk Factors
The possible creation and confidential reporting of an
ESRD Facility Equity Score to synthesize results across multiple social
risk factors and disparity measures.
Interventions ESRD facilities could institute to improve a
low facility equity score and how improved demographic data could
assist with these efforts.
2. COVID-19 Vaccination Measures Request for Information
a. Background
On January 31, 2020, the Secretary declared a PHE for the U.S. in
response to the global outbreak of SARS-CoV-2, a novel (new)
coronavirus that causes a disease named ``coronavirus disease 2019''
(COVID-19).\219\ COVID-19 is a contagious respiratory infection \220\
that can cause serious illness and death. Older individuals and those
with underlying medical conditions are considered to be at higher risk
for more serious complications from COVID-19.\221\
---------------------------------------------------------------------------
\219\ U.S. Dept of Health and Human Services, Office of the
Assistant Secretary for Preparedness and Response. (2020).
Determination that a Public Health Emergency Exists. Available at:
https://www.phe.gov/emergency/news/healthactions/phe/Pages/2019-nCoV.aspx.
\220\ Centers for Disease Control and Prevention. (2020). Your
Health: Symptoms of Coronavirus. Available at: https://www.cdc.gov/coronavirus/2019-ncov/symptoms-testing/symptoms.html.
\221\ Ibid.
---------------------------------------------------------------------------
As of April 2, 2021, the U.S. reported over 30 million cases of
COVID-19 and over 550,000 COVID-19 deaths.\222\ Hospitals and health
systems saw significant surges of COVID-19 patients as community
infection levels increased.\223\ From December 2, 2020 through January
30, 2021, more than 100,000 Americans were in the hospital with COVID-
19 at the same time.\224\
---------------------------------------------------------------------------
\222\ Centers for Disease Control and Prevention. (2020). CDC
COVID Data Tracker. Available at: https://covid.cdc.gov/covid-data-tracker/#cases_casesper100klast7days.
\223\ Associated Press. Tired to the Bone. Hospitals Overwhelmed
with Virus Cases. November 18, 2020. Accessed on December 16, 2020,
at https://apnews.com/article/hospitals-overwhelmed-coronavirus-cases-74a1f0dc3634917a5dc13408455cd895. Also see: New York Times.
Just how full are U.S. intensive care units? New data paints an
alarming picture. November 18, 2020. Accessed on December 16, 2020,
at: https://www.nytimes.com/2020/12/09/world/just-how-full-are-us-intensive-care-units-new-data-paints-an-alarming-picture.html.
\224\ U.S. Currently Hospitalized [bond] The COVID Tracking
Project. Accessed January 31, 2021 at: https://covidtracking.com/data/charts/us-currently-hospitalized.
---------------------------------------------------------------------------
Evidence indicates that COVID-19 primarily spreads when individuals
are in close contact with one another.\225\ The virus is typically
transmitted through respiratory droplets or small particles created
when someone who is infected with the virus coughs, sneezes, sings,
talks or breathes.\226\ Thus, the CDC advises that infections mainly
occur through exposure to respiratory droplets when a person is in
close contact with someone who has COVID-19.\227\ Although less common,
COVID-19 can also spread when individuals are not in close contact if
small droplets or particles containing the virus linger in the air
after the person who is infected has left the space.\228\ Another means
of less common transmission is contact with a contaminated
surface.\229\ According to the CDC, those at greatest risk of infection
are persons who have had prolonged, unprotected close contact (that is,
within 6 feet for 15 minutes or longer) with an individual with
confirmed SARS-CoV-2 infection, regardless of whether the individual
has symptoms.\230\ Although personal protective equipment (PPE) and
other infection-control precautions can reduce the likelihood of
transmission in health care settings, COVID-19 can spread between
healthcare personnel (HCP) and patients, or from patient to patient
given the close contact that may occur during the provision of
care.\231\ The CDC has emphasized that health care settings can be
high-risk places for COVID-19 exposure and transmission.\232\
---------------------------------------------------------------------------
\225\ Centers for Disease Control and Prevention. (2021). How
COVID-19 Spreads. Accessed on April 3, 2021 at: https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/how-covid-spreads.html.
\226\ Ibid.
\227\ Ibid.
\228\ Ibid.
\229\ Ibid.
\230\ Centers for Disease Control and Prevention. (2021). When
to Quarantine. Accessed on April 2, 2021 at: https://www.cdc.gov/coronavirus/2019-ncov/if-you-are-sick/quarantine.html.
\231\ Centers for Disease Control and Prevention. (2021).
Interim U.S. Guidance for Risk Assessment and Work Restrictions for
Healthcare Personnel with Potential Exposure to COVID-19. Accessed
on April 2 at: https://www.cdc.gov/coronavirus/2019-ncov/hcp/faq.html#Transmission.
\232\ Dooling, K, McClung, M, et al. ``The Advisory Committee on
Immunization Practices' Interim Recommendations for Allocating
Initial Supplies of COVID-19 Vaccine--United States, 2020.'' Morb
Mortal Wkly Rep. 2020; 69(49): 1857-1859.
---------------------------------------------------------------------------
As part of its national strategy to address COVID-19, the Biden
Administration stated that it would work with states and the private
sector to execute an aggressive vaccination strategy and outlined a
goal of administering 200 million shots in 100 days.\233\ After
achieving this goal,\234\ the Biden Administration announced a new goal
to administer at least one COVID-
[[Page 36369]]
19 vaccine shot to 70 percent of the U.S. adult population by July 4th,
2021.\235\ Although the goal of the U.S. government is to ensure that
every American who wants to receive a COVID-19 vaccine can receive one,
federal agencies recommended that early vaccination efforts focus on
those critical to the PHE response, including HCP providing direct care
to patients with COVID-19, and individuals at highest risk for
developing severe illness from COVID-19.\236\ For example, the CDC's
Advisory Committee on Immunization Practices (ACIP) recommended that
HCP should be among those individuals prioritized to receive the
initial, limited supply of the COVID-19 vaccination, given the
potential for transmission in health care settings and the need to
preserve health care system capacity.\237\ Research suggests most
states followed this recommendation,\238\ and HCP began receiving the
vaccine in mid-December of 2020.\239\ Although the vaccination strategy
for individuals at highest risk for developing severe illness from
COVID-19, including ESRD patients, has varied from state to state,\240\
ACIP recommendations indicated that ESRD patients would be offered the
COVID-19 vaccine based on their high-risk status as part of phase
1c.\241\
---------------------------------------------------------------------------
\233\ The White House. Remarks by President Biden on the COVID-
19 Response and the State of Vaccinations. Accessed on April 3, 2021
at: https://www.whitehouse.gov/briefing-room/speeches-remarks/2021/03/29/remarks-by-president-biden-on-the-covid-19-response-and-the-state-of-vaccinations/.
\234\ The White House. Remarks by President Biden on the COVID-
19 Response and the State of Vaccinations. Accessed on June 2, 2021
at: https://www.whitehouse.gov/briefing-room/speeches-remarks/2021/04/21/remarks-by-president-biden-on-the-covid-19-response-and-the-state-of-vaccinations-2/.
\235\ The White House. Remarks by President Biden on the COVID-
19 Response and the State of Vaccinations. Accessed on June 4, 2021,
at: https://www.whitehouse.gov/briefing-room/statements-releases/2021/05/04/fact-sheet-president-biden-to-announce-goal-to-administer-at-least-one-vaccine-shot-to-70-of-the-u-s-adult-population-by-july-4th/.
\236\ Health and Human Services, Department of Defense. (2020)
From the Factory to the Frontlines: The Operation Warp Speed
Strategy for Distributing a COVID-19 Vaccine. Accessed December 18
at: https://www.hhs.gov/sites/default/files/strategy-for-distributing-covid-19-vaccine.pdf; Centers for Disease Control
(2020). COVID-19 Vaccination Program Interim Playbook for
Jurisdiction Operations. Accessed December 18 at: https://www.cdc.gov/vaccines/imz-managers/downloads/COVID-19-Vaccination-Program-Interim_Playbook.pdf.
\237\ Dooling, K, McClung, M, et al. ``The Advisory Committee on
Immunization Practices' Interim Recommendations for Allocating
Initial Supplies of COVID-19 Vaccine--United States, 2020.'' Morb.
Mortal Wkly Rep. 2020; 69(49): 1857-1859. ACIP also recommended that
long-term care residents be prioritized to receive the vaccine,
given their age, high levels of underlying medical conditions, and
congregate living situations make them high risk for severe illness
from COVID-19.
\238\ Kates, J, Michaud, J, Tolbert, J. ``How Are States
Prioritizing Who Will Get the COVID-19 Vaccine First?'' Kaiser
Family Foundation. December 14, 2020. Accessed on December 16 at
https://www.kff.org/policy-watch/how-are-states-prioritizing-who-will-get-the-covid-19-vaccine-first/.
\239\ Associated Press. `Healing is Coming:' U.S. Health Workers
Start Getting Vaccine. December 15, 2020. Accessed on December 16
at: https://apnews.com/article/us-health-workers-coronavirus-vaccine-56df745388a9fc12ae93c6f9a0d0e81f.
\240\ Kates, J, Michaud, J, Tolbert, J. ``The COVID-19 Vaccine
Priority Line Continues to Change as States Make Further Updates.''
Kaiser Family Foundation. January 21, 2021. Accessed on January 29
at https://www.kff.org/policy-watch/the-covid-19-vaccine-priority-line-continues-to-change-as-states-make-further-updates/.
\241\ Dooling K, Marin M, Wallace M, et al. ``The Advisory
Committee on Immunization Practices' Updated Interim Recommendation
for Allocation of COVID-19 Vaccine--United States, December 2020.''
MMWR Morb Mortal Wkly Rep 2021; 69:1657-1660. ACIP recommended that
the COVID-19 vaccine should be offered to persons aged >=75 years
and non-health care frontline essential workers in Phase 1b, and to
persons aged 16-64 years with high-risk medical conditions in Phase
1c.
---------------------------------------------------------------------------
As of June 22, 2021 the CDC reported that over 319 million doses of
COVID-19 vaccine had been administered, and approximately 150.4 million
people had received a complete vaccination course.\242\ President Biden
indicated on April 6, 2021 that the U.S. has sufficient vaccine supply
to make every adult eligible to receive a vaccine beginning April 19,
2021.\243\ Furthermore, on March 25, 2021, the Biden Administration
announced a new partnership with dialysis facilities to provide COVID-
19 vaccinations directly to people receiving dialysis and HCP in
dialysis facilities.\244\
---------------------------------------------------------------------------
\242\ Centers for Disease Control and Prevention. COVID Data
Tracker. COVID-19 Vaccinations in the United States. Accessed June
23, 2021 at: https://covid.cdc.gov/covid-data-tracker/#vaccinations.
\243\ The White House. Remarks by President Biden Marking the
150 Millionth COVID-19 Vaccine Shot. Accessed April 8, 2021 at:
https://www.whitehouse.gov/briefing-room/speeches-remarks/2021/04/06/remarks-by-president-biden-marking-the-150-millionth-covid-19-vaccine-shot/.
\244\ The White House. FACT SHEET: Biden Administration
Announces Historic $10 Billion Investment to Expand Access to COVID-
19 Vaccines and Build Vaccine Confidence in Hardest-Hit and Highest-
Risk Communities. March 25, 2021. Available at: https://www.whitehouse.gov/briefing-room/statements-releases/2021/03/25/fact-sheet-biden-administration-announces-historic-10-billion-investment-to-expand-access-to-covid-19-vaccines-and-build-vaccine-confidence-in-hardest-hit-and-highest-risk-communities/.
---------------------------------------------------------------------------
b. COVID-19 Vaccination Coverage Among Healthcare Personnel (HCP)
Measure
We believe it is important to incentivize and track HCP vaccination
in dialysis facilities through quality measurement in order to protect
health care workers, patients, and caregivers, and to help sustain the
ability of these facilities to continue serving their communities
throughout the PHE and beyond. We recognize the importance of COVID-19
vaccination, and have proposed to include a COVID-19 HCP vaccination
measure quality measure in various pay for reporting programs, such as
the Inpatient Psychiatric Facility Quality Reporting Program (86 FR
19501 through 19504), the Hospital Inpatient Quality Reporting Program
(86 FR 25571 through 25575), and the Skilled Nursing Facility Quality
Reporting Program (86 FR 19994 through 19998). We note that there is
not a pay for reporting program under the ESRD PPS, however, we believe
that the public reporting of vaccination data on Dialysis Facility
Compare is important and would help to inform patients of a facility's
COVID-19 vaccination rates of HCP. Currently, there is a measure for
HCP \245\ and another for patient COVID-19 vaccination \246\ rates and
such measures are currently reported to CDC's National Healthcare
Safety Network via ESRD Networks. The two measures track the
proportions of a facility's HCP and patient population, respectively,
that have been fully vaccinated against COVID-19. Facilities were able
to begin weekly COVID-19 vaccination reporting for HCP in December
2020,\247\ and were able to begin weekly COVID-19 vaccination reporting
for patients in March 2021.\248\ Currently, 89 percent of ESRD
facilities are reporting HCP vaccination rates and almost 95 percent of
ESRD facilities are reporting patient vaccination rates on these
measures. We are evaluating options for publicly reporting the data on
official CMS datasets that compare the quality of care provided in
Medicare-certified dialysis facilities nationwide. We are also
exploring the potential future inclusion of a COVID-19 vaccination
measure to the ESRD QIP. Therefore, we are seeking public comment on
adding a new measure, COVID-19 Vaccination Coverage Among HCP, to the
ESRD QIP measure set in the next rulemaking cycle. The measure would
assess the proportion of a facility's health care workforce that has
been vaccinated against COVID-19.
---------------------------------------------------------------------------
\245\ https://www.cdc.gov/nhsn/hps/weekly-covid-vac/index.html.
\246\ https://www.cdc.gov/nhsn/dialysis/pt-covid-vac/index.html.
\247\ https://www.cdc.gov/nhsn/pdfs/hps/covidvax/weekly-covid-guidance-508.pdf.
\248\ https://www.cdc.gov/nhsn/pdfs/dialysis/covidvax/getting-started-508.pdf.
---------------------------------------------------------------------------
HCP are at risk of carrying COVID-19 infection to patients,
experiencing illness or death as a result of COVID-19 themselves, and
transmitting it to their families, friends, and the general public. We
believe facilities should track the level of vaccination among their
HCP as part of their efforts to assess and reduce the risk of
transmission of COVID-19 within their facilities. HCP vaccination can
potentially reduce illness that leads to work absence and limit
disruptions to care.\249\ Data from influenza vaccination
[[Page 36370]]
demonstrates that provider uptake of the vaccine is associated with
that provider recommending vaccination to patients,\250\ and we believe
HCP COVID-19 vaccination in dialysis facilities could similarly
increase uptake among that patient population. We also believe that
publishing the HCP vaccination rates will be helpful to many patients,
including those who are at high-risk for developing serious
complications from COVID-19, as they choose facilities from which to
seek treatment. Under CMS' Meaningful Measures Framework, the COVID-19
measure would address the quality priority of ``Promoting Effective
Prevention and Treatment of Chronic Disease'' through the Meaningful
Measures Area of ``Preventive Care.''
---------------------------------------------------------------------------
\249\ Centers for Disease Control and Prevention. Overview of
Influenza Vaccination among Health Care Personnel. October 2020.
(2020) Accessed March 16, 2021 at: https://www.cdc.gov/flu/toolkit/long-term-care/why.htm.
\250\ Measure Application Committee Coordinating Committee
Meeting Presentation. March 15, 2021. (2021) Accessed March 16, 2021
at: http://www.qualityforum.org/Project_Pages/MAP_Coordinating_Committee.aspx.
---------------------------------------------------------------------------
c. COVID-19 Vaccination Coverage for Patients in End-Stage Renal
Disease (ESRD) Facilities Measure
We believe it is important to encourage patient vaccination in
dialysis facilities in order to protect health care workers, patients,
and caregivers, and to help sustain the ability of these facilities to
continue serving their communities throughout the PHE and beyond.
COVID-19 can cause outbreaks in ESRD facilities, and may
disproportionately affect ESRD patients due to the nature of the
treatment and sharing of common spaces.\251\ Many patients treated in
ESRD facilities have other underlying chronic conditions, and therefore
are highly susceptible to illness and disease.\252\ Sufficient
vaccination coverage among patients in ESRD facilities may reduce
transmission of SARS-CoV-2, thereby protecting them from COVID-19
mortality. Therefore, we are seeking public comment on adding new
measure, COVID-19 Vaccination Coverage Among Patients, to the ESRD QIP
measure set in future rulemaking. The measure would assess the
proportion of a facility's patient population that has been vaccinated
against COVID-19.
---------------------------------------------------------------------------
\251\ Verma, A., Patel, A., Tio, M., Waikar, S., ``Caring for
Dialysis Patients in a Time of COVID-19''. Kidney Medicine, Volume
2, Issue 6, 2020, Pages 787-792, ISSN 2590-0595. Available at
https://doi.org/10.1016/j.xkme.2020.07.006.
\252\ Ibid.
---------------------------------------------------------------------------
We believe facilities should track the level of vaccination among
their patients as part of their efforts to assess and reduce the risk
of transmission of COVID-19 within their facilities. We also believe
that publishing the vaccination rates will be helpful to many ESRD
patients, including those who are at high-risk for developing serious
complications from COVID-19, as they choose facilities from which to
seek treatment. Under CMS' Meaningful Measures Framework, the COVID-19
measure addresses the quality priority of ``Promoting Effective
Prevention and Treatment of Chronic Disease'' through the Meaningful
Measures Area of ``Preventive Care.''
d. Review by the Measures Application Partnership and NQF
The COVID-19 HCP vaccination measure and the COVID-19 patient
vaccination measure were included on the publicly available ``List of
Measures under Consideration for December 21, 2020'' (MUC List), a list
of measures under consideration for use in various Medicare
programs.\253\ When the Measure Applications Partnership Hospital
Workgroup convened on January 11, 2021, it reviewed measures on the MUC
List including the two COVID-19 vaccination measures. The Measure
Applications Partnership Hospital Workgroup recognized that the
proposed measures represent a promising effort to advance measurement
for an evolving national pandemic and that it would bring value to the
ESRD QIP measure set by providing transparency about an important
COVID-19 intervention to help prevent infections in HCP and
patients.\254\ The Measure Applications Partnership Hospital Workgroup
also stated that collecting information on COVID-19 vaccination
coverage among HCP and ESRD patients, and providing feedback to
facilities, will allow facilities to benchmark coverage rates and
improve coverage in their facility. The Measure Applications
Partnership Hospital Workgroup further noted that reducing rates of
COVID-19 in HCP and ESRD patients may reduce transmission among a
patient population that is highly susceptible to illness and disease,
and also reduce instances of staff shortages due to illness.\255\
---------------------------------------------------------------------------
\253\ National Quality Forum. List of Measures Under
Consideration for December 21, 2020. Accessed at: https://www.cms.gov/files/document/measures-under-consideration-list-2020-report.pdf on January 29 2021.
\254\ Measure Applications Partnership. MAP Preliminary
Recommendations 2020-2021. Accessed on January 24, 2021 at: http://www.qualityforum.org/Project_Pages/MAP_Hospital_Workgroup.aspx.
\255\ Ibid.
---------------------------------------------------------------------------
In its preliminary recommendations, the Measure Applications
Partnership Hospital Workgroup did not support these two measures for
rulemaking, subject to potential for mitigation.\256\ To mitigate its
concerns, the Measure Applications Partnership Hospital Workgroup
believed that both measures needed well-documented evidence, finalized
specifications, testing, and NQF endorsement prior to
implementation.\257\ Subsequently, the Measure Applications Partnership
Coordinating Committee met on January 25, 2021, and reviewed the COVID-
19 Vaccination Coverage Among HCP measure and the COVID-19 Vaccination
Coverage for Patients in ESRD Facilities Measure. In the 2020-2021
Measure Applications Partnership Final Recommendations, Measure
Applications Partnership offered conditional support for rulemaking
contingent on CMS bringing the measures back to Measure Applications
Partnership once the specifications are further refined.\258\ The
Measure Applications Partnership specifically stated, ``the incomplete
specifications require immediate mitigation and further development
should continue.'' \259\ The Measure Applications Partnership further
noted that the measures would add value to the ESRD QIP measure set by
providing visibility into an important intervention to limit COVID-19
infections in HCP and the ESRD patients for whom they provide
care.\260\ CMS brought both measures back to the Measure Applications
Partnership on March 15, 2021 to provide additional information and
continue discussing mitigation.
---------------------------------------------------------------------------
\256\ Ibid.
\257\ Ibid.
\258\ Measure Applications Partnership. 2020-2021 MAP Final
Recommendations. Accessed on February 3, 2021 at: http://www.qualityforum.org/Setting_Priorities/Partnership/Measure_Applications_Partnership.aspx.
\259\ Measure Applications Partnership. 2020-2021 MAP Final
Recommendations. Accessed on February 23, 2021 at: http://www.qualityforum.org/Project_Pages/MAP_Hospital_Workgroup.aspx.
\260\ Measure Applications Partnership. 2020-2021 MAP Final
Recommendations. Accessed on February 23, 2021 at: http://www.qualityforum.org/Project_Pages/MAP_Hospital_Workgroup.aspx.
---------------------------------------------------------------------------
e. Request for Public Comment
In this proposed rule, we would like to seek public comment on
potentially adding the two new COVID-19 vaccination measures discussed
above, the COVID-19 vaccination measure for HCP and the COVID-19
vaccination measure for patients, to the ESRD QIP measure set.\261\
---------------------------------------------------------------------------
\261\ Specifications for both measures available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=94650.
---------------------------------------------------------------------------
We are also interested in public comment on data collection,
[[Page 36371]]
submission, and reporting for the COVID-19 vaccination measure for HCP
and the COVID-19 vaccination measure for patients. For example, we are
considering requiring reporting for these measures on an annual basis
for the performance period for each calendar year corresponding to the
associated payment year, and the reporting period would be January 1
through December 31 annually. Based on the measures currently being
developed by the CDC that were submitted to the Measure Applications
Partnership, facilities would report the measures through the National
Healthcare Safety Network (NHSN) web-based surveillance system. We also
seek public comment from stakeholders on other ways to collect data on
COVID-19 vaccination rates at dialysis facilities for ESRD QIP purposes
and their associated costs and burdens. Given the immediacy of the PHE
for COVID-19, as well as the importance of continuing to monitor and
make publicly available COVID-19 vaccination rates as the PHE ends, we
anticipate rulemaking on this requirement in the CY 2023 rulemaking
cycle.
3. Advancing to Digital Quality Measurement and the Use of Fast
Healthcare Interoperability Resources (FHIR)
We aim to move fully to digital quality measurement in CMS quality
reporting and value-based purchasing programs by 2025. As part of this
modernization of our quality measurement enterprise, we are issuing
this request for information (RFI). The purpose of this RFI is to
gather broad public input solely for planning purposes for our
transition to digital quality measurement. Any updates to specific
program requirements related to providing data for quality measurement
and reporting provisions would be addressed through future rulemaking,
as necessary. This RFI contains four parts:
Background. This part provides information on our quality
measurement programs and our goal to move fully to digital quality
measurement by 2025. This part also provides a summary of other recent
HHS policy developments that are advancing interoperability and could
support our move towards full digital quality measurement.
Definition of Digital Quality Measures (dQMs). This part
provides a potential definition for dQMs. Specific requests for input
are included in the section.
Changes Under Consideration to Advance Digital Quality
Measurement: Actions in Four Areas to Transition to Digital Quality
Measures by 2025. This part introduces four possible steps that would
enable transformation of CMS' quality measurement enterprise to be
fully digital by 2025. Specific requests for input are included in the
section.
Solicitation of Comments. This part lists all requests for
input included in the above sections of this RFI.
a. Background
As required by law, we implemented quality measurement programs and
value-based purchasing programs across a broad range of inpatient,
outpatient, and post-acute care (PAC) settings, consistent with our
mission to improve the quality of health care for Americans through
measurement, transparency, and increasingly, value-based purchasing.
These quality programs are foundational for incentivizing value-based
care, contributing to improvements in health care, enhancing patient
outcomes, and informing consumer choice. We aim to move fully to
digital quality measurement by 2025. We acknowledge providers within
the various care and practice settings covered by our quality programs
may be at different stages of readiness, and therefore, the timeline
for achieving full digital quality measurement across our quality
reporting programs may vary.
We also continue to evolve the Medicare Promoting Interoperability
Program that advances the use of certified electronic health record
(EHR) technology, from an initial focus on electronic data capture to
enhancing information exchange and expanding quality measurement (83 FR
41634). However, reporting quality data via EHRs remains burdensome,
and our current approach to quality measurement does not readily
incorporate emerging data sources such as patient-reported outcomes
(PRO) and patient-generated health data (PGHD).\262\ There is a need to
streamline our approach to data collection, calculation, and reporting
to fully leverage clinical and patient-centered information for
measurement, improvement, and learning.
---------------------------------------------------------------------------
\262\ What are patient generated health data: https://www.healthit.gov/topic/otherhot-topics/what-are-patient-generated-health-data.
---------------------------------------------------------------------------
Additionally, advancements in technical standards and regulatory
initiatives to improve interoperability of healthcare data are creating
an opportunity to significantly improve our quality measurement
systems. In May 2020, we finalized interoperability requirements in the
CMS Interoperability and Patient Access final rule (85 FR 25510) to
support beneficiary access to data held by certain payers. At the same
time, the Office of the National Coordinator for Health Information
Technology (ONC) finalized policies in the ONC 21st Century Cures Act
final rule (85 FR 25642) to advance the interoperability of health IT
as defined in section 4003 of the Cures Act, including the ``complete
access, exchange, and use of all electronically accessible health
information.'' Closely working with ONC, we collaboratively identified
HL7 Fast Healthcare Interoperability Resources (FHIR[supreg]) Release
4.0.1 as the standard to support Application Programming Interface
(API) policies in both rules. ONC, on behalf of HHS, adopted the HL7
FHIR Release 4.0.1 for APIs and related implementation specifications
at 45 CFR 170.215. We believe the FHIR standard has the potential to be
a more efficient and modular standard to enable APIs. We also believe
this standard enables collaboration and information sharing, which is
essential for delivering high-quality care and better outcomes at a
lower cost. By aligning technology requirements for payers, health care
providers, and health IT developers, HHS can advance-an interoperable
health IT infrastructure that ensures providers and patients have
access to health data when and where it is needed.
In the ONC 21st Century Cures Act final rule ONC adopted a
``Standardized API for Patient and Population Services'' certification
criterion for health IT that requires the use of the FHIR Release 4 and
several implementation specifications. Health IT certified to this
criterion will offer single patient and multiple patient services that
can be accessed by third party applications (85 FR 25742).\263\ The ONC
21st Century Cures Act final rule also requires health IT developers
update their certified health IT to support the U.S. Core Data for
Interoperability (USCDI) standard.\264\ The scope of patient data
identified in the USCDI and the data standards that support this data
set are expected to evolve over time, starting with data specified in
Version 1 of the USCDI. In November 2020, ONC issued an interim final
rule with comment period extending the date when health IT developers
must make technology meeting updated certification criteria available
under the ONC Health IT
[[Page 36372]]
Certification Program until December 31, 2022 (85 FR 70064).\265\
---------------------------------------------------------------------------
\263\ Application Programming Interfaces (API) Resource Guide,
Version 1.0. Available at: https://www.healthit.gov/sites/default/files/page/2020-11/API-Resource-Guide_v1_0.pdf.
\264\ https://www.healthit.gov/isa/united-states-core-data-interoperability-uscdi.
\265\ Information Blocking and the ONC Health IT Certification
Program: Extension of Compliance Dates and Timeframes in Response to
the Covid-19 Public Health Emergency. https://www.govinfo.gov/content/pkg/FR-2020-11-04/pdf/2020-24376.pdf.
---------------------------------------------------------------------------
The CMS Interoperability and Patient Access final rule (85 FR
25510) and program policies build on the ONC 21st Century Cures Act
final rule (85 FR 25642). The CMS Interoperability and Patient Access
final rule and policies require certain payers (for example, Medicare
Advantage organizations, Medicaid, and CHIP fee for service programs,
Medicaid managed care plans, CHIP managed care entities, and Qualified
Health Plan [QHP] issuers on the Federally-facilitated Exchanges
[FFEs]) to implement and maintain a standards-based Patient Access API
using HL7 FHIR Release 4.0.1 to make available certain data to their
enrollees and beneficiaries (called ``patients'' in the CMS
interoperability rule). These certain data include data concerning
claims and encounters, with the intent to ensure access to their own
health care information through third-party software applications. The
rule also established new Conditions of Participation for Medicare and
Medicaid participating hospitals, psychiatric hospitals, and critical
access hospitals (CAHs), requiring them to send electronic
notifications to another healthcare facility or community provider or
practitioner when a patient is admitted, discharged, or transferred (85
FR 25603). In the CY 2021 Physician Fee Schedule (PFS) final rule (85
FR 84472), we finalized a policy to align the certified EHR technology
required for use in the Promoting Interoperability programs and the
MIPS Promoting Interoperability performance category with the updates
to health IT certification criteria finalized in the ONC 21st Century
Cures Act. Under this policy, eligible clinicians, MIPS eligible
clinicians, and eligible hospitals and CAHs participating in the
Promoting Interoperability Programs, must use technology meeting the
updated certification criteria for performance and reporting periods
beginning in 2023 (85 FR 84825).
The use of APIs can also reduce long-standing barriers to quality
measurement. Currently, health IT developers are required to implement
individual measure specifications within their health IT product. The
health IT developer must also accommodate how that product connects
with the unique variety of systems within a specific care setting.\266\
This may be further complicated by systems which integrate a wide range
of data schemas. This process is burdensome and costly, and it is
difficult to reliably obtain high quality data across systems. As
health IT developers map their health IT data to the FHIR standard and
related implementation specifications, APIs can enable these data to be
easily accessible for measurement or other use cases, such as care
coordination, clinical decision support, and supporting patient access.
---------------------------------------------------------------------------
\266\ The Office of the National Coordinator for Health
Information Technology, Strategy on Reducing Regulatory and
Administrative Burden Relating to the Use of Health IT and EHRs,
Final Report (Feb. 2020). Available at: https://www.healthit.gov/sites/default/files/page/2020-02/BurdenReport_0.pdf.
---------------------------------------------------------------------------
We believe the emerging data standardization and interoperability
enabled by APIs will support the transition to full digital quality
measurement by 2025, and are committed to exploring and seeking input
on potential solutions for the transition to digital quality
measurement as described in this RFI.
b. Definition of Digital Quality Measures
In this section we seek to refine the definition of digital quality
measures (dQMs) to further operationalize our objective of fully
transitioning to dQMs by 2025. We previously noted dQMs use ``sources
of health information that are captured and can be transmitted
electronically and via interoperable systems.'' (85 FR 84845). In this
RFI, we seek input on future elaboration that would define a dQM as a
software that processes digital data to produce a measure score or
measure scores. Data sources for dQMs may include administrative
systems, electronically submitted clinical assessment data, case
management systems, EHRs, instruments (for example, medical devices and
wearable devices), patient portals or applications (for example, for
collection of patient-generated health data), health information
exchanges (HIEs) or registries, and other sources. We also note that
dQMs are intended to improve the patient experience including quality
of care, improve the health of populations, and/or reduce costs.
We discuss one potential approach to developing dQM software in
section IV.G.3.c of this proposed rule. In this section, we are seeking
comment on the potential definition of dQMs in this RFI.
We also seek feedback on how leveraging advances in technology (for
example, FHIR APIs) to access and electronically transmit interoperable
data for dQMs could reinforce other activities to support quality
measurement and improvement (for example, the aggregation of data
across multiple data sources, rapid-cycle feedback, and alignment of
programmatic requirements).
The transition to dQMs relies on advances in data standardization
and interoperability. As providers and payers work to implement the
required advances in interoperability over the next several years, we
will continue to support reporting of eCQMs through CMS quality
reporting programs and through the Promoting Interoperability
programs.\267\ These fully digital measures continue to be important
drivers of interoperability advancement and learning. CMS is currently
re-specifying and testing these measures to use FHIR rather than the
currently adopted Quality Data Model (QDM) in anticipation of the wider
use of FHIR standards. CMS intends to apply significant components of
the output of this work, such as the re-specified measure logic and the
learning done through measure testing with FHIR APIs, to define and
build future dQMs that take advantage of the expansion of standardized,
interoperable data.
---------------------------------------------------------------------------
\267\ eCQI Resource Center, https://ecqi.healthit.gov/.
---------------------------------------------------------------------------
c. Changes Under Consideration To Advance Digital Quality Measurement:
Potential Actions in Four Areas To Transition to Digital Quality
Measures by 2025
Building on the advances in interoperability and learning from
testing of FHIR-converted eCQMs, we aim to move fully to dQMs,
originating from sources of health information that are captured and
can be transmitted electronically via interoperable systems, by 2025.
To enable this transformation, we are considering further
modernizing the quality measurement enterprise in four major ways: (1)
Leverage and advance standards for digital data and obtain all EHR data
required for quality measures via provider FHIR-based APIs; (2)
redesign our quality measures to be self-contained tools; (3) better
support data aggregation; and (4) work to align measure requirements
across our reporting programs, other federal programs and agencies, and
the private sector where appropriate.
These changes would enable us to collect and utilize more timely,
actionable, and standardized data from diverse sources and care
settings to improve the scope and quality of data
[[Page 36373]]
used in quality reporting and payment programs, reduce quality
reporting burden, and make results available to stakeholders in a
rapid-cycle fashion. Data collection and reporting efforts would become
more efficient, supported by advances in interoperability and data
standardization. Aggregation of data from multiple sources would allow
assessments of costs and outcomes to be measured across multiple care
settings for an individual patient or clinical conditions. We believe
that aggregating data for measurement can incorporate a more holistic
assessment of an individual's health and healthcare and produce the
rich set of data needed to enable patients and caregivers to make
informed decisions by combining data from multiple sources (for
example, patient reported data, EHR data, and claims data) for
measurement.
Perhaps most importantly, these steps would help us deliver on the
full promise of quality measurement and drive us toward a learning
health system that transforms healthcare quality, safety, and
coordination and effectively measures and achieves value-based care.
The shift from a static to a learning health system hinges on the
interoperability of healthcare data, and the use of standardized data.
dQMs would leverage this interoperability to deliver on the promise of
a learning health system wherein standards-based data sharing and
analysis, rapid-cycle feedback, and quality measurement and incentives
are aligned for continuous improvement in patient-centered care.
Similarly, standardized, interoperable data used for measurement can
also be used for other use cases, such as clinical decision support and
care coordination and care decision support, which impacts health care
and care quality.
We are requesting comments on four potential future actions that
would enable transformation to a fully digital quality measurement
enterprise by 2025.
(1) Leveraging and Advancing Standards for Digital Data and Obtaining
All EHR Data Required for Quality Measures via Provider FHIR-Based APIs
We are considering targeting the data required for our quality
measures that utilize EHR data to be data retrieved via FHIR-based APIs
based on standardized, interoperable data. Utilizing standardized data
for EHR-based measurement (based on FHIR and associated implementation
guides) and aligning where possible with interoperability requirements
can eliminate the data collection burden providers currently experience
with required chart-abstracted quality measures and reduce the burden
of reporting digital quality measure results. We can fully leverage
this advance to adapt eCQMs and expand to other dQMs through the
adoption of interoperable standards across other digital data sources.
We are considering methods and approaches to leverage the
interoperability data requirements for APIs set by the ONC 21st Century
Cures Act final rule for certified health technology to support
modernization of CMS quality measure reporting. As discussed
previously, these requirements will be included in certified technology
in future years (85 FR 84825), including availability of data included
in the USCDI via standards-based APIs, and CMS will require clinicians
and hospitals participating in MIPS and the Promoting Interoperability
Programs, respectively, to transition to use of certified technology
updated consistent with the 2015 Cures Edition Update (85 FR 84825).
Digital data used for measurement could expand beyond data captured
in traditional clinical settings, administrative claims data, and EHRs.
Many important data sources are not currently captured digitally, such
as survey and PGHD. We intend to work to innovate and broaden the
digital data used across the quality measurement enterprise beyond the
clinical EHR and administrative claims. Agreed upon standards for these
data, and associated implementation guides will be important for
interoperability and quality measurement. We will consider developing
clear guidelines and requirements for these digital data that align
with interoperability requirements, for example, expressing in
standards, exposing via APIs, and incentivizing technologies that
innovate data capture and interoperability.
High quality data are also essential for reliable and valid
measurement. Hence, in implementing the shift to capture all clinical
EHR data via FHIR-based APIs, we would support efforts to strengthen
and test the quality of the data obtained through FHIR-based APIs for
quality measurement. We currently conduct audits of electronic data
with functions including checks for data completeness and data
accuracy, confirmation of proper data formatting, alignment with
standards, and appropriate data cleaning. These functions would
continue and be applied to dQMs and further expanded to automate the
manual validation of the data compared to the original data source (for
example, the medical record) where possible. Analytic advancements such
as natural language processing, big data analytics, and artificial
intelligence, can support this evolution. These techniques can be
applied to validating observed patterns in data and inferences or
conclusions drawn from associations, as data are received, to ensure
high quality data are used for measurement.
We are seeking feedback on the goal of aligning data needed for
quality measurement with interoperability requirements and the
strengths and limitations of this approach. We are also seeking
feedback on the importance of and approaches to supporting inclusion of
PGHD and other currently non-standardized data. We also welcome comment
on approaches for testing data quality and validity.
(2) Redesigning Quality Measures To Be Self-Contained Tools
We are considering approaches for deploying quality measures to
take advantage of standardized data and interoperability requirements
that have expanded flexibility and functionality compared to CMS'
current eCQMs. We are considering defining and developing dQM software
as end-to-end measure calculation solutions that retrieve data from
primarily FHIR resources maintained by providers, payers, CMS, and
others; calculate measure score(s); and produce reports. In general, we
believe to optimize the use of standardized and interoperable data, the
software solution for dQMs should do the following:
Have the flexibility to support calculation of single or
multiple quality measure(s).
Perform three functions: (i) Obtain data via automated
queries from a broad set of digital data sources (initially from EHRs,
and in the future from claims, PRO, and PGHD); (ii) calculate the
measure score according to measure logic; and (iii) generate measure
score report(s).
Be compatible with any data source systems that implement
standard interoperability requirements.
Exist separately from digital data source(s) and respect
the limitations of the functionality of those data sources.
Be tested and updated independently of the data source
systems.
Operate in accordance with health information protection
requirements under applicable laws and comply with governance functions
for health information exchange.
Have the flexibility to be deployed by individual health
systems, health IT vendors, data aggregators, and health plans; and/or
run by CMS depending on the program and measure needs and
specifications.
[[Page 36374]]
Be designed to enable easy installation for supplemental
uses by medical professionals and other non-technical end-users, such
as local calculation of quality measure scores or quality improvement.
Have the flexibility to employ current and evolving
advanced analytic approaches such as natural language processing.
Be designed to support pro-competitive practices for
development, maintenance, and implementation and diffusion of quality
measurement and related quality improvement and clinical tools through
for example the use of open-source core architecture.
We seek comment on these suggested functionalities and other
additional functionalities that quality measure tools should ideally
have particularly in the context of the pending availability of
standardized and interoperable data (for example, standardized EHR data
available via FHIR-based APIs).
We are also interested whether and how this more open, agile
strategy may facilitate broader engagement in quality measure
development, the use of tools developed for measurement for local
quality improvement, and/or the application of quality tools for
related purposes such as public health or research.
(3) Building a Pathway to Data Aggregation in Support of Quality
Measurement
Using multiple sources of collected data to inform measurement
would reduce data fragmentation (or, different pieces of data regarding
a single patient stored in many different places). Additionally, we are
also considering expanding and establishing policies and processes for
data aggregation and measure calculation by third-party aggregators
that include, but are not limited to, HIEs and clinical registries.
Qualified Clinical Data Registries and Qualified Registries that report
quality measures for eligible clinicians in the Merit-based Incentive
Payment System (MIPS) program are potential examples \268\ at 42 CFR
414.1440(b)(2)(iv) and (v) and Sec. 414.1440(c)(2)(iii) and (iv) and
can also support measure reporting. We are considering establishing
similar policies for third-party aggregators to maintain the integrity
of our measure reporting process and to encourage market innovation.
---------------------------------------------------------------------------
\268\ Calendar Year (CY) 2021 Physician Fee Schedule Final Rule:
Finalized (New and Updated) Qualified Clinical Data Registry (QCDR)
and Qualified Registry Policies, https://qpp-cm-prod-content.s3.amazonaws.com/uploads/1362/QCDR%20and%20QR%20Updates%202021%20Final%20Rule%20Fact%20Sheet.pdf.
---------------------------------------------------------------------------
We seek feedback on aggregation of data from multiple sources being
used to inform measurement. We also seek feedback on the role data
aggregators can and should play in CMS quality measure reporting in
collaboration with providers, and how we can best facilitate and enable
aggregation.
(4) Potential Future Alignment of Measures Across Reporting Programs,
Federal and State Agencies, and the Private Sector
We are committed to using policy levers and working with
stakeholders to solve the issue of interoperable data exchange and to
transition to full digital quality measurement. We are considering the
future potential development and multi-staged implementation of a
common portfolio of dQMs across our regulated programs, agencies, and
private payers. This common portfolio would require alignment of: (1)
Measure concepts and specifications including narrative statements,
measure logic, and value sets, and (2) the individual data elements
used to build these measure specifications and calculate the measure
logic. Further, the required data elements would be limited to
standardized, interoperable data elements to the fullest extent
possible; hence, part of the alignment strategy will be the
consideration and advancement of data standards and implementation
guides for key data elements. We would coordinate closely with quality
measure developers, federal and state agencies, and private payers to
develop and to maintain a cohesive dQM portfolio that meets our
programmatic requirements and that fully aligns across federal and
state agencies and payers to the extent possible.
We intend for this coordination to be ongoing and allow for
continuous refinement to ensure quality measures remain aligned with
evolving healthcare practices and priorities (for example, PROs,
disparities, care coordination), and track with the transformation of
data collection, alignment with health IT module updates including
capabilities and standards adopted by ONC (for example, standards to
enable APIs). This coordination would build on the principles outlined
in HHS' National Health Quality Roadmap.\269\ It would focus on the
quality domains of safety, timeliness, efficiency, effectiveness,
equitability, and patient-centeredness. It would leverage several
existing federal and public-private efforts including our Meaningful
Measures 2.0 Framework; the Federal Electronic Health Record
Modernization (DoD/VA); the Agency for Healthcare Research and
Quality's Clinical Decision Support Initiative; the Centers for Disease
Control and Prevention's Adapting Clinical Guidelines for the Digital
Age initiative; the Core Quality Measure Collaborative, which convenes
stakeholders from America's Health Insurance Plans (AHIP), CMS, NQF,
provider organizations, private payers, and consumers and develops
consensus on quality measures for provider specialties; and the NQF-
convened Measure Applications Partnership, which recommends measures
for use in public payment and reporting programs. We would coordinate
with HL7's ongoing work to advance FHIR resources in critical areas to
support patient care and measurement such as social determinants of
health. Through this coordination, we would identify which existing
measures could be used or evolved to be used as dQMs, in recognition of
current healthcare practice and priorities.
---------------------------------------------------------------------------
\269\ Department of Health and Human Services, National Health
Quality Roadmap (May 2020). Available at: https://www.hhs.gov/sites/default/files/national-health-quality-roadmap.pdf.
---------------------------------------------------------------------------
This multi-stakeholder, joint federal and industry, made possible
and enabled by the pending advances towards true interoperability,
would yield a significantly improved quality measurement enterprise.
The success of the dQM portfolio would be enhanced by the degree to
which the measures achieve our programmatic requirements for measures
as well as the requirements of other agencies and payers.
We seek feedback on initial priority areas for the dQM portfolio
given evolving interoperability requirements (for example, measurement
areas, measure requirements, tools, and data standards). We also seek
to identify opportunities to collaborate with other federal agencies,
states, and the private sector to adopt standards and technology-driven
solutions to address our quality measurement priorities across sectors.
d. Solicitation of Comments
As noted previously, we seek input on the future development of the
following:
Definition of Digital Quality Measures: We are
seeking feedback on the following as described in section IV.G.3.c.(2):
++ Do you have feedback on the dQM definition?
++ Does this approach to defining and deploying dQMs to interface
with FHIR-based APIs seem promising? We
[[Page 36375]]
also welcome more specific comments on the attributes or functions to
support such an approach of deploying dQMs.
Changes Under Consideration to Advance Digital Quality
Measurement: Actions in Four Areas to Transition to Digital Quality
Measures by 2025
++ We are seeking feedback on the following as described in section
IV.G.3.c.(1) of this proposed rule:
--Do you agree with the goal of aligning data needed for quality
measurement with that required for interoperability? What are the
strengths and limitations of this approach?
--How important is a data standardization approach that also
supports inclusion of PGHD and other currently non-standardized data?
--What are possible approaches for testing data quality and
validity?
++ We are seeking feedback on the following as described in section
IV.G.3.c.(2) of this proposed rule:
--What functionalities, described in section IV.G.3.c.(2) of this
proposed rule or others, should quality measure tools ideally have in
the context of the pending availability of standardized and
interoperable data (for example, standardized EHR data available via
FHIR-based APIs)?
--How would this more open, agile strategy for end-to-end measure
calculation facilitate broader engagement in quality measure
development, the use of tools developed for measurement for local
quality improvement, and/or the application of quality tools for
related purposes such as public health or research?
++ We seek feedback on the following as described in section
IV.G.3.c.(3) of this proposed rule:
--Do you have feedback on policy considerations for aggregation of
data from multiple sources being used to inform measurement?
--Do you have feedback on the role data aggregators can and should
play in CMS quality measure reporting in collaboration with providers?
How can CMS best facilitate and enable aggregation?
++ We seek feedback on the following as described in section
IV.G.3.c.(4) of this proposed rule:
--What are initial priority areas for the dQM portfolio (for
example, measurement areas, measure requirements, tools)?
--We also seek to identify opportunities to collaborate with other
federal agencies, states, and the private sector to adopt standards and
technology-driven solutions to address our quality measurement
priorities and across sectors.
We plan to continue working with other agencies and stakeholders to
coordinate and to inform any potential transition to dQMs by 2025.
While we will not be responding to specific comments submitted in
response to this RFI in the CY 2022 ESRD PPS final rule, we will
actively consider all input as we develop future regulatory proposals
or future subregulatory policy guidance. Any updates to specific
program requirements related to quality measurement and reporting
provisions would be addressed through separate and future notice-and-
comment rulemaking, as necessary.
V. End-Stage Renal Disease Treatment Choices (ETC) Model
A. Background
1. Overview of the ETC Model
As described in the Specialty Care Models final rule (85 FR 61114),
beneficiaries with ESRD are among the most medically fragile and high-
cost populations served by the Medicare program. ESRD Beneficiaries
require dialysis or kidney transplantation to survive, and the majority
of ESRD Beneficiaries receiving dialysis receive hemodialysis in an
ESRD facility. However, as described in the Specialty Care Models final
rule, alternative renal replacement modalities to in-center
hemodialysis, including home dialysis and kidney transplantation, are
associated with improved clinical outcomes, better quality of life, and
lower costs than in-center hemodialysis (85 FR 61264).
Section 1115A of the Act authorizes the Innovation Center to test
innovative payment and service delivery models expected to reduce
Medicare, Medicaid, and CHIP expenditures while preserving or enhancing
the quality of care furnished to such programs' beneficiaries. The
purpose of the ETC Model is to test the effectiveness of adjusting
certain Medicare payments to ESRD facilities and Managing Clinicians to
encourage greater utilization of home dialysis and kidney
transplantation, support beneficiary modality choice, reduce Medicare
expenditures, and preserve or enhance the quality of care.
The ETC Model is a mandatory payment model, as we seek to test the
effect of payment incentives on availability and choice of treatment
modality among a diverse group of providers and suppliers. ESRD
facilities and Managing Clinicians are selected as ETC Participants
based on their location in Selected Geographic Areas--a set of 30
percent of Hospital Referral Regions (HRRs) that have been randomly
selected to be included in the ETC Model, as well as HRRs with at least
20 percent of component ZIP codes \270\ located in Maryland. CMS
excludes all U.S. Territories from the Selected Geographic Areas.
---------------------------------------------------------------------------
\270\ ZIP code \TM\ is a trademark of the United States Postal
Service.
---------------------------------------------------------------------------
Under the ETC Model, ETC Participants are subject to two payment
adjustments. The first is the Home Dialysis Payment Adjustment (HDPA),
which is an upward adjustment on certain payments made to participating
ESRD facilities under the ESRD PPS on home dialysis claims, and an
upward adjustment to the MCP paid to participating Managing Clinicians
on home dialysis-related claims. The HDPA applies to claims with claim
service dates beginning in January 1, 2021, and ending on December 31,
2023.
The second payment adjustment under the ETC Model is the
Performance Payment Adjustment (PPA). For the PPA, we assess ETC
Participants' home dialysis rate and transplant rate during a
Measurement Year (MY), which includes 12 months of performance data.
Each MY overlaps with the previous MY, if any, and the subsequent MY,
if any, for a period of 6 months. Each MY has a corresponding PPA
Period--a 6-month period which begins 6 months after the conclusion of
the MY. We adjust certain payments for ETC Participants during the PPA
Period based on the ETC Participant's home dialysis rate and transplant
rate, calculated as the sum of the transplant waitlist rate and the
living donor transplant rate, during the corresponding MY. Based on an
ETC Participant's achievement in relation to benchmarks based on the
home dialysis rate and transplant rate observed in Comparison
Geographic Areas during the Benchmark Year, and the ETC Participant's
improvement in relation to its own home dialysis rate and transplant
rate during the Benchmark Year, we make an upward or downward
adjustment to certain payments to the ETC Participant. The magnitude of
the positive and negative PPAs for ETC Participants increases over the
course of the ETC Model. These PPAs apply to claims with claim service
dates beginning July 1, 2022, and ending June 30, 2027.
2. Summary of Proposed Changes to the ETC Model
In this proposed rule, we are proposing a number of policy changes
to the ETC Model beginning for the third Measurement Year (MY3) of the
Model, which begins January 1, 2022. We are proposing changes to the
methodology
[[Page 36376]]
for attributing Pre-emptive LDT Beneficiaries to Managing Clinicians to
better reflect the care relationship between beneficiaries who receive
pre-emptive LDT transplants and the Managing Clinicians who provide
their care. We are also proposing to include nocturnal in-center
dialysis in the numerator of the home dialysis rate calculation for
ESRD facilities not owned in whole or in part by an LDO as well as
Managing Clinicians, to incentivize additional alternative renal
replacement modalities. In addition, we are proposing to exclude
beneficiaries who are diagnosed with and receiving treatment with
chemotherapy or radiation for vital solid organ cancers from the
transplant rate to align with common transplant center requirements.
We are proposing to modify the PPA achievement benchmarking
methodology to increase achievement benchmarks by 10 percent above
rates observed in Comparison Geographic Areas every two MYs, beginning
for MY3 (2022). We are proposing to stratify PPA achievement benchmarks
based on the proportion of attributed beneficiaries who are dually-
eligible for Medicare and Medicaid or receive the Low-Income Subsidy
during the MY, and to introduce the Health Equity Incentive to the PPA
improvement scoring methodology, both in an effort to encourage ETC
Participants to address disparities in renal replacement modality
choice among beneficiaries with lower socioeconomic status. We are
proposing to modify the PPA improvement benchmarking and scoring
methodology to ensure an ETC Participant can receive an improvement
score even if its home dialysis rate or transplant rate was zero during
the relevant Benchmark Year.
We are proposing to add processes and requirements for CMS to share
certain model data with ETC Participants. We are also proposing
additional programmatic waivers as necessary solely for purposes of
allowing Managing Clinicians who are ETC participants to furnish kidney
disease patient education services via telehealth under the ETC Model.
In addition, we propose to permit Managing Clinicians who are ETC
Participants to reduce or waive beneficiary coinsurance for kidney
disease patient education services, subject to certain requirements.
CMS expects that the proposed changes would continue to promote the
larger goals of increased renal replacement modality choice and are
based on many of the issues we laid out in the Specialty Care Models
final rule as issues for which CMS was considering further rulemaking,
including updating benchmarks for ETC Participants and adjusting model
parameters based on our implementation experience.
3. Impact of Proposed Changes on the ETC Model Evaluation
As we described in the Specialty Care Models final rule, an
evaluation of the ETC Model will be conducted in accordance with
section 1115A(b)(4) of the Act, which requires the Secretary to
evaluate each model tested by the Innovation Center. We noted that we
believe an independent evaluation of the Model is necessary to
understand the impacts of the Model on quality of care and Medicare
program expenditures (85 FR 61345).
We propose to update the evaluation plan presented in the Specialty
Care Models final rule to account for all the policies proposed in this
rule, if finalized. However, changes in the construction of the PPA, if
finalized, would have no impact on the evaluation approach to analyzing
the final PPA values. This is because the evaluation plan already
includes a consideration of the final PPA values, rather than an
evaluation of each step in the PPA calculation. However, we expect to
conduct subgroup analyses in the evaluation to determine the effect of
the proposed Health Equity Incentive, if finalized, in reducing health
disparities among beneficiaries with lower socioeconomic status.
As part of the detailed economic analysis included in section
IX.B.4 of this proposed rule, the transplant waitlist benchmarks were
annually inflated by approximately 3-percentage points growth. This was
a change from the Specialty Care Models final rule (85 FR 61352), where
the waitlist benchmarks were annually inflated by approximately 2-
percentage points growth observed during years 2017 through 2019 to
project rates of growth. By increasing the expected effect to a 3-
percentage point change, we improve our ability to detect such an
effect at the ETC Model's current size. In the Specialty Care Models
final rule, we stated that to detect a 2-percentage point increase in
the transplant waitlist rate, we would need 30 percent of the 306 HRRs
in order to detect an effect of this size with 80 percent power and an
alpha of 0.05. Further, we stated that a model of this size would be
large enough to detect a one and one-half percentage point change in
the home dialysis rate (85 FR 61280). We clarify that our unadjusted
power calculations show that the model requires 30 percent of the 306
HRRs to detect the one and one-half percentage point change in the home
dialysis rate with 80 percent power and an alpha of 0.05. Given the
updated expectation that the transplant waitlist rate is likely to
increase by 3-percentage points as a result of the ETC Model, the power
analysis shows the evaluation would also have sufficient sample size to
detect, as statistically significant, a 3-percentage point change in
the transplant waitlist rate with 80 percent power and an alpha of
0.05.
B. Provisions of the Proposed Rule
1. Technical Clarifications
For ESRD facilities that are ETC Participants, the ETC Model makes
certain upward and downward adjustments to the Adjusted ESRD PPS per
Treatment Base Rate for certain dialysis claims via the Home Dialysis
Payment Adjustment (HDPA) and the Performance Payment Adjustment (PPA).
The term ``Adjusted ESRD PPS per Treatment Base Rate'' is defined at 42
CFR 512.310 as the per-treatment payment amount as defined in Sec.
413.230 of this chapter, including patient-level adjustments and
facility-level adjustments, and excluding any applicable training
adjustment, add-on payment amount, outlier payment amount, TDAPA
amount, and TPNIES amount. In this proposed rule, we are clarifying the
claims subject to adjustment under the ETC Model. Specifically, as
Sec. 413.230 is specific to the calculation of payment amounts under
the ESRD PPS, we clarify that the HDPA and PPA do not apply to claims
from ESRD facilities that are not paid under ESRD PPS and are instead
paid through other Medicare payment systems.
We are also updating the name of one of the sources of data used
throughout the ETC Model. In the Specialty Care Models final rule, we
specify that one source of data for the ETC Model is CROWNWeb, a data
management system that CMS uses to collect data from ESRD facilities
(85 FR 61317). Since publication, CMS has replaced CROWNWeb with the
End Stage Renal Disease Quality Reporting System (EQRS). As such, we
will refer to CROWNWeb for data that was generated before the change to
EQRS, which CMS began using in 2020, and EQRS for data that was
generated after the change to EQRS.
2. Performance Payment Adjustment (PPA) Beneficiary Attribution for
Living Kidney Donor Transplants
In the Specialty Care Models final rule, we established that
beneficiaries are attributed to Managing Clinicians for the purposes of
calculating the home
[[Page 36377]]
dialysis rate and transplant rate (85 FR 61297). For the home dialysis
rate and the transplant waitlist and living donor kidney transplant
portions of the transplant rate, as described in 42 CFR
512.360(c)(2)(i), an ESRD Beneficiary is generally attributed to the
Managing Clinician with the earliest monthly capitation payment (MCP)
claim billed during the month. If more than one Managing Clinician
submits a claim for the MCP furnished to a single ESRD Beneficiary with
the same earliest claim service date at the claim line through date for
the month, the ESRD Beneficiary is randomly attributed to one of these
Managing Clinicians.
However, a beneficiary who receives a pre-emptive living donor
transplant (Pre-emptive LDT Beneficiary) is not on dialysis and
therefore cannot be attributed to a Managing Clinician using an MCP
claim. As a result, under Sec. 512.360(c)(2)(ii), a Pre-emptive LDT
Beneficiary is generally attributed to the Managing Clinician with whom
the Pre-emptive LDT Beneficiary had the most claims between the start
of the MY and the month of the transplant. If no Managing Clinician has
had the plurality of claims for a given Pre-emptive LDT Beneficiary
such that multiple Managing Clinicians each had the same number of
claims for that beneficiary during the MY, the Pre-emptive LDT
Beneficiary is attributed to the Managing Clinician associated with the
latest claim service date during the MY up to and including the month
of the transplant, as described in Sec. 512.360(c)(2)(ii)(A). If no
Managing Clinician had the plurality of claims for a given Pre-emptive
LDT Beneficiary such that multiple Managing Clinicians each had the
same number of services for that beneficiary during the MY, and more
than one of those Managing Clinicians had the latest claim service date
during the MY up to and including the month of the transplant, the Pre-
emptive LDT Beneficiary is randomly attributed to one of these Managing
Clinicians, as described in Sec. 512.360(c)(2)(ii)(B).
Upon further review of the beneficiary attribution methodology for
living donor kidney transplants, we realized that an unintended
consequence of the current attribution methodology is that Pre-emptive
LDT Beneficiaries may be attributed to the nephrologist who manages
their transplant, not the Managing Clinician who has seen them through
the living donor transplant process. To avoid this effect, CMS believes
it is necessary to update the attribution methodology for Pre-emptive
LDT Beneficiaries. Living donor transplants are relatively rare events
that require nephrologist support over time in order to inform
beneficiaries of their transplant options and to assist them in finding
a living donor. However, the current Pre-emptive LDT Beneficiary
attribution methodology is based on visits from the beginning of a MY.
As a result, if a Pre-emptive LDT Beneficiary has a transplant early in
a MY, the beneficiary may be attributed to a transplant nephrologist
who may have had only a single visit with the beneficiary, rather than
the Managing Clinician who oversaw the largest share of the care that
led to the beneficiary receiving the living donor transplant.
As a result, we propose to update the attribution methodology for
Pre-emptive LDT Beneficiaries to Managing Clinicians, beginning for
MY3, in new provisions at Sec. 512.360(c)(2)(iii). Rather than
attributing a Pre-emptive LDT Beneficiary to the Managing Clinician
with the plurality of claims from the start of the MY and the month of
the transplant, beginning for MY3, we propose to attribute Pre-emptive
LDT Beneficiaries to the Managing Clinician with whom the beneficiary
has had the most claims during the 365 days prior to the transplant
date. Further, we propose that if no Managing Clinician has had the
most claims for the Pre-emptive LDT Beneficiary such that multiple
Managing Clinicians each had the same number of claims for that
beneficiary in the 365 days preceding the date of the transplant, the
Pre-emptive LDT Beneficiary would be attributed to the Managing
Clinician associated with the latest claim service date at the claim
line through date during the 365 days preceding the date of the
transplant. We propose that if more than one of those Managing
Clinicians had the latest claim service date at the claim line through
date during the 365 days preceding the date of the transplant, the Pre-
emptive LDT Beneficiary would be randomly attributed to one of these
Managing Clinicians. We propose that the Pre-emptive LDT Beneficiary
would be considered eligible for attribution to a Managing Clinician
under this proposed new Sec. 512.360(c)(2)(iii) if the Pre-emptive LDT
Beneficiary has at least 1 eligible-month during the 12-month period
that includes the month of the transplant and the 11 months prior to
the transplant month. We propose that an eligible month would refer to
a month during which the Pre-emptive LDT Beneficiary not does not meet
exclusion criteria in Sec. 512.360(b). CMS is proposing changes for
Pre-emptive LDT Beneficiary attribution to Managing Clinicians in order
to identify and attribute Pre-emptive LDT Beneficiaries to the Managing
Clinician who assisted the Beneficiary through the living donor
transplant process. We seek comment on these proposed changes for Pre-
emptive LDT Beneficiary attribution to Managing Clinicians beginning
for MY3 in proposed new Sec. 512.360(c)(2)(iii).
3. PPA Home Dialysis Rate
a. Background on Home Dialysis Rate Calculation
A primary goal of the ETC Model is to support beneficiary modality
choice by encouraging ETC Participants to support beneficiaries in
selecting alternatives to in-center dialysis. Under 42 CFR 512.365(b),
CMS includes in-center self-dialysis treatment beneficiary years in the
numerator of the home dialysis rate. Specifically, the home dialysis
rate for both Managing Clinicians and ESRD facilities is calculated as
the number of dialysis treatment beneficiary years during the MY in
which attributed beneficiaries received dialysis at home, plus one half
of the total number of dialysis treatment beneficiary years during the
MY in which the attributed beneficiaries received self-dialysis in
center. As described in the Specialty Care Models final rule, we
included self-dialysis in the home dialysis rate calculation because we
believe in-center self-dialysis may provide a gradual transition from
in-center to home dialysis, and provide beneficiaries with the time
needed to get comfortable conducting dialysis by themselves, under
medical supervision (85 FR 61306).
The denominator for the home dialysis rate is the total dialysis
treatment beneficiary years for attributed ESRD beneficiaries during
the MY, as described in Sec. Sec. 512.365(b)(1)(i) and
512.365(b)(2)(i). This includes the months during which attributed
beneficiaries received maintenance dialysis at home or in an ESRD
facility.
b. Nocturnal Dialysis
Nocturnal in-center dialysis is a form of in-center dialysis
conducted overnight for extended hours while the beneficiary is asleep.
This dialysis is longer and slower than traditional in-center dialysis,
can take more than 5 hours per treatment, and can be performed 3 to 7
days a week. As this type of in-center dialysis is conducted overnight,
it allows the beneficiary more time and flexibility to have a
continuous job, as well as a social and family life.\271\
---------------------------------------------------------------------------
\271\ Wilk, Adam S., Lea, Janice P. (2019). How Extended
Hemodialysis Treatment Time Can Affect Patient Quality of Life.
Clinical Journal of the American Society of Nephrology, 23, 479-485.
doi:10.1111/hdi.12782.
---------------------------------------------------------------------------
[[Page 36378]]
Dialysis conducted at a slower rate over a longer period of time is
also associated with positive health impacts in comparison to
traditional dialysis, including improved blood pressure control, better
phosphate control, better management of anemia and bone and mineral
metabolism, improved cardiovascular disease, increases in urea
reduction ratio, and better beneficiary quality of life
measures.272 273 274 275 276
---------------------------------------------------------------------------
\272\ Burton, J. and Graham-Brown, M., 2018. Nocturnal
hemodialysis. Current Opinion in Nephrology and Hypertension, 27(6),
pp.472-477.
\273\ Kalim, S., Wald, R., Yan, A. T., Goldstein, M. B., Kiaii,
M., Xu, D., . . . Perl, J. (2018). Extended duration nocturnal
hemodialysis and changes in plasma metabolite profiles. Clinical
Journal of the American Society of Nephrology, 13(3), 436-444.
doi:10.2215/cjn.08790817.
\274\ Nesrallah, G. E., Lindsay, R. M., Cuerden, M. S., Garg, A.
X., Port, F., Austin, P. C., . . . Suri, R. S. (2012). Intensive
hemodialysis associates with improved survival compared with
conventional hemodialysis. Journal of the American Society of
Nephrology, 23(4), 696-705. doi:10.1681/asn.2011070676.
\275\ Wong, B., Collister, D., Muneer, M., Storie, D., Courtney,
M., Lloyd, A., . . . Pauly, R. P. (2017). In-center nocturnal
hemodialysis versus conventional hemodialysis: A systematic review
of the evidence. American Journal of Kidney Diseases, 70(2), 218-
234. doi:10.1053/j.ajkd.2017.01.047.
276 Wilk, Adam S., Lea, Janice P. (2019). How Extended
Hemodialysis Treatment Time Can Affect Patient Quality of Life.
Clinical Journal of the American Society of Nephrology, 23, 479-485.
doi:10.1111/hdi.12782.
\276\ Lacson E, Diaz-Buxo J. In-center nocturnal hemodialysis
performed thrice-weekly--a provider's perspective. Semin Dial. 2011
Nov-Dec;24(6):668-73. doi: 10.1111/j.1525-139X.2011.00998.x. Epub
2011 Nov 22. PMID: 22106828.
---------------------------------------------------------------------------
In addition to the clinical benefits, nocturnal in-center dialysis
also provides an alternative to traditional in-center dialysis for
those beneficiaries for whom home dialysis is not an option due to
limited financial resources, housing insecurity, lack of social
support, or personal preference. For example, a beneficiary
experiencing housing insecurity may be unable to dialyze at home due to
inability to receive and store home dialysis materials. However, that
beneficiary could receive nocturnal in-center dialysis, thereby
receiving the clinical benefits of a longer, slower dialysis process
and the flexibility associated with not having to receive traditional
in-center dialysis during the day.277 278
---------------------------------------------------------------------------
\277\ Bugeja A, Dacouris N, Thomas A, Marticorena R, McFarlane
P, Donnelly S, Goldstein M. In-center nocturnal hemodialysis:
another option in the management of chronic kidney disease. Clin J
Am Soc Nephrol. 2009 Apr;4(4):778-83. doi: 10.2215/CJN.05221008.
Epub 2009 Apr 1. PMID: 19339410; PMCID: PMC2666425.
\278\ Lacson E, Diaz-Buxo J. In-center nocturnal hemodialysis
performed thrice-weekly--a provider's perspective. Semin Dial. 2011
Nov-Dec;24(6):668-73. doi: 10.1111/j.1525-139X.2011.00998.x. Epub
2011 Nov 22. PMID: 22106828.
---------------------------------------------------------------------------
While nocturnal in-center dialysis offers some of the same clinical
and quality of life benefits as home dialysis in comparison to
traditional in-center dialysis, use of nocturnal in-center dialysis is
rare. Based on analyses described in section IX.B.4.a.(4) of this
proposed rule, less than 1 percent of beneficiaries eligible for
attribution to ETC Participants were receiving self-dialysis or
nocturnal in-center dialysis in 2019. Potential limitations to
nocturnal in-center dialysis utilization include supply factors. At
present, few ESRD facilities offer nocturnal dialysis; in 2019,
approximately 1 percent of ESRD facilities furnished nocturnal in-
center dialysis based on our analysis of claims data. ESRD facilities
may face staffing challenges to initiating a nocturnal dialysis
program. Potential limitations to nocturnal in-center dialysis also
include demand factors: beneficiaries may be unaware of nocturnal in-
center dialysis, or may be averse to sleeping at an ESRD facility or
experience difficulty sleeping while receiving dialysis.\279\
---------------------------------------------------------------------------
\279\ Ibid.
---------------------------------------------------------------------------
c. Proposed Inclusion of Nocturnal In-Center Dialysis in Home Dialysis
Rate
We propose to modify the home dialysis rate calculation, for ETC
Participants that are either ESRD facilities not owned in whole or in
part by an LDO or Managing Clinicians, to include nocturnal in-center
dialysis in the numerator beginning for MY3. As described previously in
this section of the proposed rule, we believe this modality allows
beneficiaries to continue to receive maintenance dialysis in an ESRD
facility under medical supervision, but at a time of day that is more
convenient for them, and in a manner that is associated with improved
health outcomes. In particular, we believe that including nocturnal in-
center dialysis in the home dialysis rate may improve access to
alternative renal replacement modalities for beneficiaries who are
unable to dialyze at home.
In addition to promoting access to the benefits of additional
alternative renal replacement modalities for ESRD Beneficiaries who may
not be able to dialyze at home, we believe that including nocturnal in-
center dialysis in the calculation of the home dialysis rate offers an
additional pathway to success for ETC Participants with more limited
resources. As described in the Specialty Care Models final rule, we
received comments that some ESRD facilities, particularly independent
ESRD facilities or ESRD facilities owned by small dialysis
organizations, may be unable to develop and maintain a home dialysis
program (85 FR 61322 through 61324). Operating a home dialysis program
requires specialized staff, as well as upfront investment in additional
equipment and certification. Establishing a nocturnal in-center
dialysis program does not require additional equipment or
certification, and may be more feasible for independent ESRD facilities
or ESRD facilities owned by small dialysis organizations, and by
extension, the Managing Clinicians who serve their patients.
We considered including nocturnal in-center dialysis in the
numerator of the home dialysis rate for ESRD facilities owned in whole
or in part by LDOs as well. However, we do not believe that ESRD
facilities owned in whole or in part by LDOs face the same resource
constraints in establishing a home dialysis program as independent ESRD
facilities or ESRD facilities owned by small dialysis organizations.
ESRD facilities owned in whole or in part by LDOs may be more likely to
have access to a home dialysis program, either in the ESRD facility
itself or within the network of facilities owned by the same parent
company in that facility's aggregation group. ESRD facilities owned in
whole or in part by LDOs may also have greater access to the upfront
capital necessary to establish a home dialysis program if they do not
already have, or have access to, a home dialysis program.
At present, there is not a single definition of what qualifies a
legal entity that owns ESRD facilities as an LDO. In general,
definitions of LDO focus on the number of ESRD facilities owned by the
legal entity. Other Innovation Center models have used such
definitions: The Comprehensive ESRD Care (CEC) Model defined an LDO as
a legal entity owning 200 or more ESRD facilities; the Kidney Care
Choices (KCC) Model defines an LDO as a legal entity owning 35 or more
ESRD facilities. Outside of Innovation Center models, definitions used
by academic researchers vary significantly. For example, in 2015 the
United States Renal Data System (USRDS), a national data registry
funded by the National Institutes of Health (NIH), defined an LDO as a
dialysis organization one that owns and operates 200 or more ESRD
facilities.\280\ Other academic research
[[Page 36379]]
has employed thresholds as low as owning 20 or more ESRD facilities and
as high as owning 1,000 or more ESRD facilities to consider a legal
entity an LDO.281 282 Other definitions do not focus on the
number of ESRD facilities owned, but on the relative size of dialysis
organizations in the market, or rather, the individual dialysis
organizations themselves. For example, in its March 2021 report to
Congress, the Medicare Payment Advisory Commission (MedPAC) refers to
the two largest dialysis organizations in the country as LDOs based on
their relative share of ESRD facilities and Medicare treatments.\283\
Based on our review of definitions commonly used, for the purposes of
the ETC Model we propose to define the term ``ETC Large Dialysis
Organization,'' abbreviated ``ETC LDO,'' as a legal entity that owns,
in whole or in part, 500 or more ESRD facilities. Based on the current
distribution of numbers of ESRD facilities owned by dialysis
organizations operating in the market, we believe this threshold is
appropriate, as it differentiates the largest dialysis organizations,
which at present own over 2,500 ESRD facilities, from smaller dialysis
organizations, the next largest of which owns approximately 350 ESRD
facilities. We believe the difference in size represents a meaningful
difference in access to resources necessary to establish a home
dialysis program, as well as the likelihood that an ESRD facility's
aggregation group would have at least one ESRD facility with a home
dialysis program in the aggregation group. We seek comment on our
proposal to include nocturnal in-center dialysis beneficiary years in
the numerator of the home dialysis rate calculation only for ESRD
facilities not owned in whole or in part by an ETC LDO, as well as our
proposal to define an ETC LDO as a legal entity owning 500 or more ESRD
facilities.
---------------------------------------------------------------------------
\280\ United States Renal Data System. 2015. ``2015 Researcher's
Guide to the USRDS Database.'' https://usrds.org/media/2219/2015_usrds_researchers_guide_15.pdf.
\281\ Mehrotra R, Khawar O, Duong U, Fried L, Norris K,
Nissenson A, Kalantar-Zadeh K. Ownership patterns of dialysis units
and peritoneal dialysis in the United States: utilization and
outcomes. Am J Kidney Dis. 2009 Aug;54(2):289-98. doi: 10.1053/
j.ajkd.2009.01.262. Epub 2009 Apr 8. PMID: 19359081.
\282\ Gander JC, Zhang X, Ross K, et al. Association Between
Dialysis Facility Ownership and Access to Kidney Transplantation.
JAMA. 2019;322(10):957-973. doi:10.1001/jama.2019.12803.
\283\ Medicare Payment Advisory Commission. 2021. Report to the
Congress: Medicare and the health care delivery system. Washington,
DC: MedPAC. http://www.medpac.gov/docs/default-source/reports/mar21_medpac_report_to_the_congress_sec.pdf.
---------------------------------------------------------------------------
While nocturnal in-center dialysis can potentially result in better
patient health outcomes and savings to Medicare compared to traditional
in-center dialysis, we acknowledge that its inclusion in the home
dialysis rate may reduce the incentive for ESRD facilities not owned in
whole or in part by an LDO to invest in a home dialysis infrastructure.
We therefore propose to include nocturnal in-center dialysis as one
half of the total number of dialysis treatment beneficiary years during
the MY in which the attributed beneficiaries received nocturnal in-
center dialysis in the numerator of the home dialysis rate calculation
for ESRD facilities not owned in whole or in part by an ETC LDO as well
as Managing Clinicians. We believe this policy would effectively
balance the benefits of nocturnal in-center dialysis and its ability to
help beneficiaries transition to home dialysis with the recognition
that in-center nocturnal dialysis is not home dialysis and does not
have all of the same benefits. As described in the Specialty Care
Models final rule, we included one half of the total number of dialysis
treatment beneficiary years during the MY in which the attributed
beneficiaries received self-dialysis in center in the home dialysis
rate calculation for a similar reason (85 FR 61306).
As such, we propose to amend Sec. 512.365(b) such that, beginning
for MY3, the numerator for the home dialysis rate for ESRD facilities
not owned in whole or in part by an ETC LDO and Managing Clinicians
would be the total number of dialysis treatment beneficiary years
during the MY in which attributed ESRD Beneficiaries received
maintenance dialysis at home, plus one half of the total number of
dialysis treatment beneficiary years during the MY in which attributed
ESRD Beneficiaries received maintenance dialysis via self-dialysis,
plus one half of the total number of dialysis treatment beneficiary
years during the MY in which attributed ESRD Beneficiaries received
maintenance dialysis via in-center nocturnal dialysis. We further
propose to add paragraph (C) to both Sec. Sec. 512.365(b)(1)(ii) and
512.365(b)(2)(ii) to specify that nocturnal in-center dialysis
beneficiary years included in the numerator of the home dialysis rate
calculation would be composed of those months during which attributed
ESRD Beneficiaries received nocturnal in-center dialysis, such that 1-
beneficiary year is comprised of 12-beneficiary months. The months in
which an attributed ESRD Beneficiary received nocturnal in-center
dialysis would be identified by claims with Type of Bill 072X, where
the type of facility code is 7 and the type of care code is 2, and with
the modifier UJ, which specifies that a claim with Type of Bill 072X is
for nocturnal in-center dialysis. We seek comment on these proposed
changes to Sec. 512.365(b).
4. Performance Payment Adjustment Transplant Rate
a. Status of Organ Availability
The ETC Model is designed to encourage greater rates of
transplantation. In the proposed rule published on July 18, 2019 in the
Federal Register titled, ``Medicare Program; Specialty Care Models to
Improve Quality of Care and Reduce Expenditures'' (84 FR 34478),
referred to herein as the ``Specialty Care Models proposed rule,'' CMS
proposed to include the rate of transplants, both living and deceased
donor transplants, in the numerator for the ETC Model's transplant
rate. However, in the Specialty Care Models final rule, we recognized
the limitations of supply of deceased donor organs and updated the
transplant rate to be calculated as the sum of the transplant waitlist
rate and the living donor transplant rate (85 FR 61310). We stated that
though a transplant is often the best treatment for a beneficiary with
ESRD, in light of the current shortage of deceased donor organs for
transplant, the transplant waitlist rate and living donor transplant
rate are currently more within the control of an ETC Participant (85 FR
61309).
However, in the Specialty Care Models final rule, we indicated our
intent to observe the supply of deceased donor organs available for
transplantation, with the goal of potentially modifying the transplant
rate calculation for the future (85 FR 61309). Since the Specialty Care
Models final rule was published on September 29, 2020, there have been
several initiatives pursued by the federal government that could
potentially have the effect of increasing the supply of both living
donor organs and deceased donor organs.
On September 22, 2020, the Health Resources and Services
Administration (HRSA) published a final rule in the Federal Register
titled ``Removing Financial Disincentives to Living Organ Donation''
(85 FR 59438). This rule removes financial barriers to organ donation
by expanding the scope of reimbursable expenses incurred by living
organ donors to include lost wages, and child-care and elder-care
expenses incurred by a caregiver. The rule went into effect on October
22, 2020.
[[Page 36380]]
Additionally, on December 2, 2020, CMS published in the Federal
Register a final rule titled, ``Medicare and Medicaid Programs; Organ
Procurement Organizations Conditions for Coverage: Revisions to the
Outcome Measure Requirements for Organ Procurement Organizations'' (85
FR 77898), revising Conditions for Coverage (CfCs) for Organ
Procurement Organizations (OPOs). The final rule revised the CfCs for
OPOs in order to increase donation rates and organ transplantation
rates and replaced the old outcome measures with new transparent,
reliable, and objective measures. The final rule went into effect on
March 30, 2021. The new outcome measures will be implemented for the
recertification cycle beginning in 2022 and ending in 2026. The goals
of this rule are complementary to the goals of the ETC Model, as the
revised CfCs are intended to increase the supply of organs, and the ETC
Model is designed to incentivize higher rates of transplantation.
Finally, as described in the Specialty Care Models final rule, CMS
is in the process of implementing the ETC Learning Collaborative (85 FR
61346). The ETC Learning Collaborative is a voluntary learning system
focused on increasing the availability of deceased donor kidneys for
transplantation. The ETC Learning Collaborative works with and supports
ETC Participants and other stakeholders required for successful kidney
transplantation, such as transplant centers, OPOs, and large donor
hospitals. CMS is currently in the process of jointly implementing the
ETC Learning Collaborative with HRSA.
We are pleased that these efforts have progressed since the
publication of the Specialty Care Models final rule. However, given
that these efforts are still in the implementation process, we do not
believe that it would be appropriate to update the transplant rate to
include accountability for deceased donor transplants, rather than
transplant waitlisting, at this time. We still intend to update the
transplant rate through future rulemaking to include accountability for
deceased donor transplants, but we are not proposing to do so at this
time.
Beneficiary Exclusions From the Transplant Rate
As we discussed in the Specialty Care Models final rule (85 FR
61300), CMS received comments about excluding ESRD Beneficiaries with
cancer from attribution to ETC Participants, as there was concern about
treatment appropriateness. However, at that time, CMS did not have any
evidence to suggest that this is a concern. Accordingly, we did not
exclude beneficiaries with cancer from attribution to ETC Participants
for purposes of calculating the home dialysis rate or the transplant
rate in the Specialty Care Models final rule.
Nevertheless, after we published the Specialty Care Models final
rule, we conducted further analysis, to determine if a difference
existed in either the home dialysis rate or transplant rate in
beneficiaries with cancer and beneficiaries without cancer. Using the
Medicare claims data and input from clinical specialists in the field
of nephrology, we found that the majority of ESRD Beneficiaries with
cancer, specifically ESRD Beneficiaries with cancer in vital solid
organs (heart, lung, liver, and kidney), are not considered to be
eligible candidates for transplant. Many transplant centers do not
consider these beneficiaries for transplant and require them to be
cancer-free for a specific period of time prior to assessing their
eligibility for transplant. This is true for getting on a transplant
waitlist and for receiving living donor transplants, as a beneficiary
either needs to be cancer-free or be in an initial stage of cancer
diagnosis to be considered for transplant.
In addition, we found that ESRD Beneficiaries who have a diagnosis
of solid organ cancer for which they were receiving treatment,
specifically radiation or chemotherapy, are less likely to be in the
numerator of the transplant rate--so, being placed on the transplant
waitlist or receive a living donor transplant--than ESRD Beneficiaries
without a diagnosis of vital solid organ cancer. By contrast, we did
not find any evidence to suggest that ESRD Beneficiaries with cancer
had a significant difference in the home dialysis rate compared to the
ESRD Beneficiaries without cancer.
As noted previously, under Sec. Sec. 512.310 and 512.365(c), the
transplant rate has two components: The transplant waitlist rate and
the living donor transplant rate. Upon further review and analysis,
beginning for MY3, we propose to exclude ESRD Beneficiaries and, if
applicable, Pre-emptive LDT Beneficiaries who have been diagnosed with
vital solid organ cancers (heart, lung, liver and kidney) and who are
receiving treatment, in the form of radiation or chemotherapy, for such
cancers from both components of the denominator of the transplant rate
for both ESRD facilities and Managing Clinicians for the duration of
the MY.
Furthermore, we propose to include a lookback period, a period of
time prior to the MY, to appropriately identify the ESRD Beneficiaries
and, if applicable, Pre-emptive LDT Beneficiaries with a diagnosis of
vital solid organ cancer for which they are receiving chemotherapy or
radiation therapy. Both a diagnosis code and a treatment code are
necessary to appropriately identify an ESRD Beneficiary or Pre-emptive
LDT Beneficiary with a vital solid organ cancer who is receiving
treatment with either radiation or chemotherapy. However, through our
analysis we have identified beneficiaries who have only a treatment
code available during the MY and do not have a diagnosis code during
that period. Hence, we are proposing to include a lookback period of 6-
months prior to the MY, so that the appropriate diagnosis code can be
identified for ESRD Beneficiaries and Pre-emptive LDT Beneficiaries who
have only treatment codes available in the current MY. In the
alternative, we considered a 12-month lookback period, but did not find
any significant difference in the number of ESRD Beneficiaries and Pre-
emptive LDT Beneficiaries that had a diagnosis code for a vital organ
solid cancer during a 12-month lookback period as compared to a 6-month
lookback period.
We propose to identify ESRD Beneficiaries and, if applicable, Pre-
emptive LDT Beneficiaries with a diagnosis of vital solid organ cancer
and receiving treatment with radiation or chemotherapy by using
Medicare claims. For purposes of the transplant rate calculations, an
ESRD Beneficiary or Pre-emptive LDT Beneficiary would be considered to
have a diagnosis of vital solid cancer during the MY, if the ESRD
Beneficiary has a claim with one of the following ICD-10 diagnosis
codes:
C22.0-C22.9 (malignant neoplasm of liver and intrahepatic
bile ducts),
C34.10-C34.12 (malignant neoplasm of upper lobe, bronchus
or lung),
C34.2 (malignant neoplasm of middle lobe, bronchus or
lung),
C34.30-C34.32 (malignant neoplasm of lower lobe, bronchus
or lung),
C34.80-C34.82 (malignant neoplasm of overlapping sites of
bronchus and lung),
C34.90-C34.92 (malignant neoplasm of unspecified part of
bronchus or lung),
C38.0 (malignant neoplasm of heart),
C38.8 (malignant neoplasm of overlapping sites of heart,
mediastinum and pleura),
C46.50-C46.52 (Kaposi's sarcoma of lung),
[[Page 36381]]
C64.1, C64.2, C64.9 (malignant neoplasm of kidney, except
renal pelvis),
C78.00-C78.02 (secondary malignant neoplasm of lung),
C78.7 (secondary malignant neoplasm of liver and
intrahepatic bile duct),
C79.00-C79.02 (secondary malignant neoplasm of kidney and
renal pelvis),
C7A.090 (malignant carcinoid tumor of the bronchus and
lung),
C7A.093 (malignant carcinoid tumor of the kidney), or
C7B.02 (secondary carcinoid tumors of liver).
We propose that for the purposes of the transplant rate
calculations, an ESRD Beneficiary or Pre-emptive LDT Beneficiary would
be considered to be receiving treatment for vital solid organ cancer
with either chemotherapy or radiation in the MY if the ESRD Beneficiary
or Pre-emptive LDT Beneficiary has a claim with one of the following
codes:
CPT[supreg] 96401-96402, 96405-96406, 96409, 96411, 96413,
96415-96417, 96420, 96422-26423, 96425, 96440, 96446 (chemotherapy
administration);
CPT[supreg] 96549 (unlisted chemotherapy procedure);
CPT[supreg] 77373 (stereotactic body radiation therapy);
CPT[supreg] 77401-77402, 77407, 77412 (radiation treatment
delivery);
CPT[supreg] 77423 (high energy neutron radiation treatment
delivery);
CPT[supreg] 77424-77425 (intraoperative radiation
treatment delivery);
CPT[supreg] 77520, 77522-77523, 77525 (proton treatment
delivery);
CPT[supreg] 77761-77763 (intracavitary radiation source
application);
CPT[supreg] 77770-77772, 77778, 77789, 77799 (clinical
brachytherapy radiation treatment);
CPT[supreg] 79005, 79101, 79200, 79300, 79403, 79440,
79445, 79999 (radiopharmaceutical therapy);
ICD-10-PCS DB020ZZ, DB021ZZ, DB022ZZ, DB023Z0, DB023ZZ,
DB024ZZ, DB025ZZ, DB026ZZ, DB1297Z, DB1298Z, DB1299Z, DB129BZ, DB129CZ,
DB129YZ, DB12B6Z, DB12B7Z, DB12B8Z, DB12B9Z, DB12BB1, DB12BBZ, DB12BCZ,
DB12BYZ, DB22DZZ, DB22HZZ, DB22JZZ, DBY27ZZ, DBY28ZZ, DBY2FZZ, DBY2KZZ
(radiation of lung);
ICD-10-PCS DB070ZZ, DB071ZZ, DB072ZZ, DB073Z0, DB073ZZ,
DB074ZZ, DB075ZZ, DB076ZZ, DB1797Z, DB1798Z, DB1799Z, DB179BZ, DB179CZ,
DB179YZ, DB17B6Z, DB17B7Z, DB17B8Z, DB17B9Z, DB17BB1, DB17BBZ, DB17BCZ,
DB17BYZ, DB27DZZ, DB27HZZ, DB27JZZ, DBY77ZZ, DBY78ZZ, DBY7FZZ, DBY7KZZ
(radiation of chest wall);
ICD-10-PCS DF000ZZ, DF001ZZ, DF002ZZ, DF003Z0, DF003ZZ,
DF004ZZ, DF005ZZ, DF006ZZ, DF1097Z, DF1098Z, DF1099Z, DF109BZ, DF109CZ,
DF109YZ, DF10B6Z, DF10B7Z, DF10B8Z, DF10B9Z, DF10BB1, DF10BBZ, DF10BCZ,
DF10BYZ, DF0DZZ, DF20HZZ, DF20JZZ, DFY07ZZ, DFY08ZZ, DFY0CZZ, DFY0FZZ,
DFY0KZZ (radiation of liver);
ICD-10-PCS DT000ZZ, DT001ZZ, DT002ZZ, DT003Z0, DT003ZZ,
DT004ZZ, DT005ZZ, DT006ZZ, DT1097Z, DT1098Z, DT1099Z, DT109BZ, DT109CZ,
DT109YZ, DT10B6Z, DT10B7Z, DT10B8Z, DT10B9Z, DT10BB1, DT10BBZ, DT10BCZ,
DT10BYZ, DT20DZZ, DT20HZZ, DT20JZZ, DTY07ZZ, DTY08ZZ, DTY0CZZ, DTY0FZZ
(radiation of kidney);
ICD-10-PCS DW020ZZ, DW021ZZ, DW022ZZ, DW023Z0, DW023ZZ,
DW024ZZ, DW025ZZ, DW026ZZ, DW1297Z, DW1298Z, DW1299Z, DW129BZ, DW129CZ,
DW129YZ, DW12B6Z, DW12B7Z, DW12B8Z, DW12B9Z, DW12BB1, DW12BBZ, DW12BCZ,
DW12BYZ, DW22DZZ, DW22HZZ, DW22JZZ, DWY27ZZ, DWY28ZZ, DWY2FZZ
(radiation of chest); or
ICD-10-PCS DW030ZZ, DW031ZZ, DW032ZZ, DW033Z0, DW033ZZ,
DW034ZZ, DW035ZZ, DW036ZZ, DW1397Z, DW1398Z, DW1399Z, DW139BZ, DW139CZ,
DW139YZ, DW13B6Z, DW13B7Z, DW13B8Z, DW13B9Z, DW13BB1, DW13BBZ, DW13BCZ,
DB13BYZ, DW23DZZ, DW23HZZ, DW23JZZ, DWY37ZZ, DWY38ZZ, DWY3FZZ
(radiation of abdomen);
We seek comment on the proposal to amend Sec. 512.365(c) to
exclude ESRD Beneficiaries and, if applicable, Pre-emptive LDT
Beneficiaries with a diagnosis of vital solid organ cancer and
receiving treatment with chemotherapy or radiation from the denominator
of the transplant rate as a whole, including both the transplant
waitlist rate component and the living donor transplant rate component,
for the duration of the MY for both ESRD facilities and Managing
Clinicians.
5. PPA Achievement Benchmarking
a. Background on Achievement Benchmarking
Under the ETC Model, the PPA is a positive or negative adjustment
on dialysis and dialysis-related Medicare payments, for both home
dialysis and in-center dialysis. To calculate an ETC Participant's PPA,
we assess ETC Participant achievement on the home dialysis rate and
transplant rate in relation to achievement and improvement benchmarks,
as described in 42 CFR 512.370(b) and Sec. 512.370(c), respectively.
The Model more heavily weights achievement of results, allowing
participating Managing Clinicians or ESRD facilities to earn up to 2
points in the scoring methodology, as opposed to only 1.5 points for
maximum level of improvement, as described in Sec. Sec. 512.370(b) and
512.370(c).
The achievement benchmarks are constructed based on the home
dialysis rate and transplant rate observed in Comparison Geographic
Areas during corresponding Benchmark Years. Achievement benchmarks are
percentile based, and an ETC Participant receives the achievement
points that correspond with its performance, at the aggregation group
level, on the home dialysis rate and transplant rate in relation to the
achievement benchmarks, as described in Sec. 512.370(b). Table 7
details the achievement score scale described in Sec. 512.370(b).
[[Page 36382]]
[GRAPHIC] [TIFF OMITTED] TP09JY21.006
In the Specialty Care Models proposed rule, we proposed to apply
this achievement benchmark policy only for MY1 and MY2, and stated our
intent to increase achievement benchmarks for ETC Participants above
the rates observed in Comparison Geographic Areas. We stated our belief
that increasing the achievement benchmarks for future MYs, which we
would do through subsequent rulemaking, was necessary in order to
provide sufficient incentive for ETC Participants to increase rates of
home dialysis and transplantation at a rate faster than would occur
absent the ETC Model (84 FR 34556 through 34557). In the Specialty Care
Models final rule, in response to comments, we finalized the
applicability of the achievement benchmarks for MY1-MY2 and for
subsequent MYs (85 FR 61323), but reiterated our intent to establish a
different method for establishing achievement benchmarks for future
years of the Model through subsequent rulemaking (85 FR 61320). We
stated our belief that future modifications to the achievement
benchmark methodology finalized in the Specialty Care Models final rule
would be necessary to provide sufficient incentive for ETC Participants
to raise home dialysis and transplant rates at a rate faster than would
occur absent the ETC Model (85 FR 61321). However, we clarified that
while we had stated a goal of 80 percent of an ETC Participant's
receiving home dialysis or a transplant in order to receive the maximum
upward payment adjustment by the final MYs, we were not finalizing that
goal in the Specialty Care Models final rule (85 FR 61321).
b. Addressing Socioeconomic Factors That Impact ETC Participant
Achievement
In the Specialty Care Models final rule, we acknowledged
commenters' concerns that non-clinical factors, such as socioeconomic
status, may impact a beneficiary's likelihood to receive home dialysis
or transplant. We discussed commenters' suggestions to incorporate
consideration of socioeconomic status in two elements of the ETC Model:
(1) Beneficiary attribution; and (2) risk adjustment. However, we
declined to exclude beneficiaries from attribution based on
socioeconomic status. Noting the importance of not excluding these
beneficiaries, CMS stated its intent to assess the use of various codes
for purposes of adding any additional beneficiary exclusions from
attribution to ETC Participants based on socioeconomic status,
homelessness, or other social determinants of health through future
rulemaking (85 FR 61299). We also noted that commenters' suggestions
for ways to risk adjust the home dialysis rate based on socioeconomic
status were a significant departure from the policy originally proposed
(85 FR 61315).
We continue to acknowledge the impact that non-clinical factors,
such as socioeconomic status, have on a beneficiary's likelihood to
receive home dialysis or a transplant. Based on our additional analysis
of Medicare claims data show that beneficiaries who are dual-eligible
for Medicare and Medicaid or receive the Medicare Low-Income Subsidy
(LIS) are less likely than beneficiaries who are not dual-eligible and
are not LIS recipients to dialyze at home or to receive a kidney
transplant. As such, ETC Participants who have a higher proportion of
attributed beneficiaries who are dual-eligible or LIS recipients may be
less likely to achieve high home dialysis and transplant rates than ETC
Participants who have a lower proportion of attributed beneficiaries
who are dual-eligible or LIS recipients.
c. Proposed Achievement Benchmarking and Scoring
(1) Achievement Benchmarking and Scoring for MY3 Through MY10
We propose to modify the percentile-based achievement benchmarking
methodology based on the home dialysis rate and transplant rate
observed in Comparison Geographic Areas during the Benchmark Year as
the basis for achievement benchmarks in MY3 through MY10. Rather than
using rates observed in Comparison Geographic Areas, we propose to
modify Sec. 512.370(b)(1) to use rates observed in Comparison
Geographic Areas as the base for the achievement benchmarks, and to
increase the achievement benchmarks above the Comparison Geographic
Area rates during the Benchmark Year by 10 percent every two MYs,
beginning for MY3. As such, we propose that achievement benchmarks
would be calculated by multiplying the percentile rate observed in
Comparison Geographic Areas during the Benchmark Year by 1.1 for MY3
and MY4, by 1.2 for MY5 and MY6, by 1.3 for MY7 and MY8, and by 1.4 for
MY9 and MY10.
Based on CMS analyses detailed in section IX.B.4 of this proposed
rule, this proposed methodology for increasing benchmarks by 10 percent
every two MYs would produce results in keeping with the initial impact
estimates for the ETC Model, as described in the Specialty Care Models
final rule (85 FR 61353 through 61354). In the Specialty Care Models
final rule, we estimated impacts based on projected growth rates for
the home dialysis and transplant rates based on historical observation,
projected a 1.5 percentage point growth rate (85 FR 61354). In section
IX.B.4 of this proposed rule, updated projections assume the same
projected growth rate, but note that observed rates of increase have
accelerated in more recent data. As such, we believe that this proposed
rate
[[Page 36383]]
of increase would be attainable for ETC Participants, as initial impact
estimates were based on rates of increase observed on the home dialysis
rate and transplant rate before the ETC Model began (85 FR 61353). We
also note that, unlike in the Specialty Care Models proposed rule (84
FR 34556), we are not proposing to increase achievement benchmarks such
that of 80 percent of an ETC Participant's attributed beneficiaries
would need to be receiving home dialysis or a transplant in order for
the ETC Participant to receive the maximum upward payment adjustment by
the final MYs.
Table 8 details the proposed scoring methodology for assessment of
MY3 through MY10 achievement scores.
[GRAPHIC] [TIFF OMITTED] TP09JY21.007
We considered increasing achievement benchmarks by a percentage
point amount, rather than by a percent amount, every two MYs (for
example, increasing achievement benchmarks by 10-percentage points for
MY3 and MY4, by 20-percentage points for MY5 and MY6, etc.). However,
we believe that this percentage point-based approach would be less
flexible to and accommodating of variation in the underlying
distributions of home dialysis and transplant rates than the percent-
based approach we are proposing. We also believe this percentage point-
based approach would add additional complexity, as we would likely need
to develop separate percentage point amounts by which to increase
benchmarks as the home dialysis rate and transplant rate observed in
Comparison Geographic Areas are not sufficiently similar to expect the
same percentage point growth rate for the two rates.
We also considered proposing to modify the Benchmark Year, such
that the Benchmark Year would be a fixed duration (for example, July 1,
2018 through June 30, 2019), rather than a period of time defined in
relation to the relevant MY. However, we determined that this approach
would not account for aggregate changes in the home dialysis rate and
transplant rate over time.
We believe that the proposed approach for increasing achievement
benchmarks over the course of the ETC Model balances the intent of the
model design to increase rates of home dialysis and transplantation
above what would have occurred in the absence of the Model with what is
achievable for ETC Participants, based on rates of home dialysis and
transplantation observed at the high ends of the distributions (for
additional discussion, see section IX.B.4.a.(3) of this proposed rule).
We also believe the proposed approach would provide clarity to ETC
Participants about the benchmarking methodology for the duration of the
ETC Model while maintaining flexibility in
[[Page 36384]]
that methodology to address long term trends in the home dialysis rate
and transplant rate.
We seek public comment on our proposal to modify the achievement
benchmarking methodology under Sec. 512.370(b) beginning for MY3 to
increase achievement benchmarks, and the proposal to increase
achievement benchmarks by 10 percent every two MYs above percentile-
based rates of observed in Comparison Geographic Areas.
(2) Achievement Benchmark Stratification by Dual-Eligible and Low
Income Subsidy (LIS) Status
We also propose to modify Sec. 512.370(b) to stratify achievement
benchmarks based on the proportion of beneficiary years attributed to
the ETC Participant's aggregation group for which attributed
beneficiaries were dually-eligible for Medicare and Medicaid or
received the LIS, based on rates in Comparison Geographic Areas. Under
our proposal, we would create two strata with the cutpoint set at 50
percent of attributed beneficiary years being for attributed
beneficiaries who were dual-eligible or received the LIS. As such,
there would be one stratum for ETC Participants whose aggregation
groups had 50 percent or more of their attributed beneficiary years
during the MY for beneficiaries who were dual-eligible or received the
LIS, based on rates in Comparison Geographic Areas for aggregation
groups with 50 percent or more attributed beneficiary years during the
Benchmark Year being for dual-eligible or LIS beneficiaries. There
would be a second stratum for ETC Participants whose aggregation groups
had less than 50 percent of their attributed beneficiary years during
the MY for beneficiaries who were dual-eligible or received the LIS,
based on rates in Comparison Geographic Areas for aggregation groups
with less than 50 percent attributed beneficiary years during the
Benchmark Year being for dual-eligible or LIS beneficiaries. We propose
to determine whether an attributed beneficiary was dual-eligible or
received the LIS for a given month using Medicare administrative data.
We believe this proposal would address concerns that socioeconomic
factors may impact a beneficiary's likelihood to receive alternative
renal replacement modalities, lowering the transplant rate and home
dialysis rates for ETC Participants who provide services to low income
beneficiaries. We expect that stratifying the achievement benchmarks as
proposed would increase home dialysis rate and transplant rates for
such ETC Participants.
We considered using more than two strata, in order to increase the
precision of the achievement benchmarks and the degree of similarity
between ETC Participants within a given stratum. However, increasing
the number of strata would decrease the number of observations within
each stratum, in turn decreasing statistical reliability. Additionally,
analysis of the distribution of the home dialysis rate and transplant
rate demonstrates that the underlying distribution does not lend itself
to more than two strata, as the distribution is not multi-modal. For
this reason, we are proposing only two strata.
We seek public comment on our proposal to amend Sec. 512.370(b) to
stratify achievement benchmarks based on the proportion of attributed
beneficiary years for which attributed beneficiaries were dual-eligible
or received the LIS, and on our proposal to create two strata for this
purpose.
6. PPA Improvement Benchmarking and Scoring
a. Background on Improvement Benchmarking and Scoring
Another part of the scoring methodology for the PPA is improvement
scoring. We calculate an ETC Participant's improvement score under
Sec. 512.370(c) by comparing MY performance on the home dialysis rate
and transplant rate against past ETC Participant performance. As
described in the Specialty Care Models final rule, the purpose of the
improvement score is to acknowledge efforts made in practice
transformation to improve rates of home dialysis and transplants (85 FR
61318). The percentage improvement in the ETC Participant's MY
performance on the home dialysis rate and the transplant rate relative
to the Benchmark Year rate is scored as follows:
Greater than 10 percent improvement relative to the Benchmark
Year rate: 1.5 points
Greater than 5 percent improvement relative to the Benchmark
Year rate: 1 point
Greater than 0 percent improvement relative to the Benchmark
Year rate: 0.5 points
Less than or equal to the Benchmark Year rate: 0 points
However, when the Benchmark Year rate is zero, an improvement score
for the MY cannot be calculated. This is because, when calculating
percent change, as used in improvement scoring, the Benchmark Year rate
is the denominator. As such, we cannot calculate percent improvement
for an aggregation group with a rate of zero during the Benchmark Year
because the denominator of the improvement score calculation is zero,
and division by zero is undefined. Thus, an aggregation group in this
situation will not receive an improvement score if the Benchmark Year
rate is zero, even if the aggregation group has made improvements in
the home dialysis rate and/or the transplant rate between the Benchmark
Year and MY.
b. Incentivizing Improvement for Socioeconomically Disadvantaged
Beneficiaries
As described in section V.B.5.b of this proposed rule,
beneficiaries who are dual-eligible or receive the LIS are less likely
than beneficiaries who are not dual-eligible and do not receive the LIS
to dialyze at home or receive a kidney transplant. As described
previously in this section of the proposed rule, we are proposing to
stratify achievement benchmarks by the proportion of attributed
beneficiary years for beneficiaries who are dual-eligible or LIS
recipients to avoid disadvantaging ETC Participants who provide care
for a high proportion of these beneficiaries. However, this proposed
stratification would not provide a direct financial incentive for ETC
Participants to focus on reducing disparities by improving the home
dialysis rate and transplant rate for beneficiaries who are dual-
eligible or receive the LIS. We are interested in creating that
incentive as part of the ETC Model, as these beneficiaries may require
additional support from ETC Participants to pursue home dialysis and
transplant as alternative renal replacement modalities.
c. Proposed Changes to Improvement Benchmarking and Scoring
(1) Revised Improvement Calculation
As described above, when the Benchmark Year rate for an aggregation
group is zero, the aggregation group cannot receive an improvement
score, even if the aggregation group has made improvements in the home
dialysis rate and transplant rate between the Benchmark Year and MY. To
address this issue, we propose to amend Sec. 512.370(c)(1) to change
the improvement calculation such that the aggregation group's Benchmark
Year rate cannot be zero. Specifically, for MY3 through MY10, we
propose to add one beneficiary month to the numerator of the home
dialysis rate and the transplant rate for the Benchmark Year rate for
an ETC Participant's aggregation group Benchmark Year when that rate is
zero. CMS does not propose to change
[[Page 36385]]
the denominator of the Benchmark Year rate calculations because doing
so would negate the purpose of mathematically correcting ETC
Participants' improvement scoring. CMS does not expect that adding a
beneficiary month to the numerator of the Benchmark Year rate
calculations, as proposed, would affect the improvement scoring enough
to change the number of points awarded to the ETC Participant, and has
the advantage that it would enable an improvement score to be
calculated, even when the Benchmark Year rate is zero.
(2) Health Equity Incentive
To incentivize ETC Participants to decrease disparities in the home
dialysis rate and transplant rate between beneficiaries who are dual-
eligible or LIS recipients and those who are not, we propose to add a
Health Equity Incentive to the improvement scoring methodology. We
propose to define the Health Equity Incentive at Sec. 512.310 as the
amount added to the ETC Participant's improvement score calculated as
described in Sec. 512.370(c)(1) if the ETC Participant's aggregation
group demonstrated sufficient improvement on the home dialysis rate or
transplant rate for attributed beneficiaries who are dual-eligible or
LIS recipients between the Benchmark Year and the MY. We propose that
this improvement on the home dialysis rate or transplant rate would be
based on the performance of the ETC Participant's aggregation group.
As noted previously in this section of the proposed rule,
socioeconomic factors impact a beneficiary's receipt of alternative
renal replacement modalities. Beneficiaries with limited resources may
require more assistance from ESRD facilities and Managing Clinicians to
use alternative renal replacement modalities. We believe our proposal
to add a Health Equity Incentive would benefit these beneficiaries and
improve scoring for home dialysis rate and transplant rate for ETC
Participants that serve disproportionately high numbers of
beneficiaries with lower socioeconomic status. To earn the Health
Equity Incentive, ETC Participants would have to demonstrate
sufficiently significant improvement on the home dialysis rate or
transplant rate among their attributed beneficiaries who are dual
eligible or receive the LIS between the Benchmark Year and the MY. ETC
Participants who earn the Health Equity Incentive would receive a 0.5
point increase on their improvement score, thus increasing the maximum
improvement score to 2 points. We believe the proposed Health Equity
Incentive would benefit attributed beneficiaries who are dual eligible
or receive the LIS, by encouraging ETC Participants to address
disparities in access to alternative renal replacement modalities among
these beneficiaries. We believe that providing this incentive for ETC
Participants to increase their home dialysis and transplant rate among
their dual eligible or LIS beneficiary population would ultimately
reduce this disparity in access for the beneficiaries in question.
Therefore, we believe this incentive to reduce socioeconomic
disparities in access to alternative renal replacement modalities would
be an improvement to the PPA scoring methodology.
We propose to amend Sec. 512.370(c) to add the Health Equity
Incentive to the improvement scoring methodology, beginning for MY3. We
propose that the Health Equity Incentive would be equal to 0.5 points,
which would be added to the ETC Participant's improvement score for the
home dialysis rate or for the transplant rate, calculated as described
in Sec. 512.370(c)(1), such that the maximum improvement score would
increase from 1.5 points to 2 points for ETC Participants that earn the
Health Equity Incentive. Therefore, for those ETC Participants that
earn the Home Equity Incentive, we propose that the ETC Participant's
improvement score for the home dialysis rate and for the transplant
rate would be the sum of the improvement score calculated as described
in Sec. 512.370(c)(1) and the Health Equity Incentive. The Health
Equity Incentive would allow ETC Participants to increase their
improvement score, and thereby increase their payment adjustment.
We propose to award the Health Equity Incentive to an ETC
Participant if the ETC Participant's aggregation group's home dialysis
rate and/or transplant rate among attributed beneficiaries who are
dual-eligible or LIS recipients increases by 5 or more percentage
points from the Benchmark Year to the MY. We believe that 5-percentage
points is the correct threshold for awarding the Health Equity
Incentive based on our analysis of Medicare claims. Five percentage
points is one standard deviation above the average difference between
the home dialysis rate and the transplant rate for attributed
beneficiaries who are dual-eligible or LIS recipients and those
beneficiaries who are not dual-eligible or LIS recipients, rounded to
the nearest integer. We anticipate improvement in home dialysis and
transplant rates among dual-eligible or LIS recipients between the MY
and the Benchmark Year, but we expect that attaining the proposed
threshold for earning the Health Equity Incentive would generally
require significant effort on the part of the ETC Participant.
We propose that an ESRD Beneficiary or Pre-emptive LDT Beneficiary
would be considered to be dual eligible or an LIS recipient for a given
month if at any point during the month the beneficiary was dually
eligible for Medicare and Medicaid or an LIS recipient. We propose to
determine whether an attributed beneficiary was dual-eligible or
received the LIS using Medicare administrative data.
We propose to modify Sec. 512.370(c) such that the improvement
benchmarking and scoring methodology for MY1 and MY2 would be specified
at Sec. 512.370(c)(1), and the improvement benchmarking and scoring
methodology for MY3 through MY10, described above, would be specified
at Sec. 512.370(c)(2). We seek comment on the proposal to modify Sec.
512.370(c) accordingly.
We considered using a rolling approach to setting the threshold for
earning the Health Equity Incentive, such that the threshold would be
recalculated every other MY, to reflect changes in underlying
disparities. Under this approach, we would calculate the threshold as
one standard deviation above the average difference between the home
dialysis rate and the transplant rate for attributed beneficiaries who
are dual-eligible or LIS recipients and those beneficiaries who are not
dual-eligible or LIS recipients, rounded to the nearest integer. We
would calculate this threshold either using data from the Benchmark
Year, such that ETC Participants would know the threshold for earning
the Health Equity Incentive in advance of the MY, or using data from
the MY, such that the threshold for earning the Health Equity Incentive
would accurately reflect the magnitude of the disparity observed during
the MY. However, we believe that setting a threshold for earning the
Health Equity Incentive applicable for all MYs, beginning for MY3, is
more appropriate. This approach would be in keeping with the intent of
the proposed Health Equity Incentive, which is to provide ETC
Participants a financial incentive to focus on decreasing the disparity
in the home dialysis and transplant rates between beneficiaries who are
dual-eligible or LIS recipients, and those who are not. We believe
providing ETC Participants clear information about what they need to
achieve to earn the Health Equity Incentive in advance would best
enable them to work towards the goal.
[[Page 36386]]
We propose that ETC Participants in aggregation groups that fall
below a low-volume threshold would be ineligible to earn the Health
Equity Incentive. Specifically, we propose that an ETC Participant in
an aggregation group with fewer than 11 attributed beneficiary years
comprised of months in which ESRD Beneficiaries and, if applicable,
Pre-emptive LDT Beneficiaries are dual eligible or LIS recipients
during either the Benchmark Year or the MY would be ineligible to earn
the Health Equity Incentive. We selected this particular low-volume
threshold for consistency with the low-volume threshold for the
applicability of the PPA generally, as specified at Sec. 512.385. We
believe it is necessary to apply a low volume threshold in determining
whether an ETC Participant has earned the Home Equity Incentive to
ensure statistical reliability of the home dialysis rate and transplant
rate calculations. This statistical reliability provides consistency in
the home dialysis rate and transplant rate calculations. Therefore,
similar results are produced under consistent conditions when applying
a low volume threshold to ETC Participants. We are proposing a low-
volume threshold specific to attributed beneficiaries who are dual-
eligible or receive the LIS because whether an ETC Participant has
earned the Health Equity Incentive is being assessed on this subset of
attributed beneficiaries.
We propose to amend the Modality Performance Score (MPS)
methodology to incorporate the Health Equity Incentive. To that end, we
propose to modify Sec. 512.370(d) such that the calculation of the MPS
for MY1 and MY2 is specified at Sec. 512.370(d)(1), and the
calculation of the MPS for MY3 through MY10 is specified at Sec.
512.370(d)(2). We propose that the formula for the MPS for MY3 through
MY10 would be the following:
Modality Performance Score
= 2
x (Higher of the home dialysis achievement or (home dialysis
improvement score + Health Equity Bonus [dagger]))
+ (Higher of the transplant achievement or (transplant improvement
score + Health Equity Bonus [dagger]))
[dagger] The Health Equity Incentive is applied to the home
dialysis improvement score or transplant improvement score only if
earned by the ETC Participant and provided that the ETC Participant is
not ineligible to receive the Home Equity Incentive as described in
proposed Sec. 512.370(c)(2)(iii).
We seek comment on our proposed definition for the Health Equity
Incentive at Sec. 512.310 and our proposal to amend Sec. 512.370(c)
to add the Health Equity Incentive to the improvement scoring
methodology for the home dialysis rate and the transplant rate. We also
seek comment on our proposal to set the threshold for earning the
Health Equity Incentive at 5-percentage points improvement from the
Benchmark Year to the MY.
7. PPA Reports and Data Sharing
a. Background on Beneficiary Attribution and Performance Reporting
Under the ETC Model, as described in 42 CFR 512.360, CMS attributes
ESRD Beneficiaries and, if applicable, Pre-emptive LDT Beneficiaries to
an ETC Participant for each month during a MY based on the
beneficiary's receipt of services during that month. CMS performs this
attribution for a MY retrospectively, after the end of the MY. As
described in Sec. 512.365, each ETC Participant's performance is
assessed based on the transplant rate and home dialysis rate among the
population of beneficiaries attributed to the ETC Participant. As
described in 42 CFR 512.370 and 42 CFR 512.380, these rates are used to
calculate the ETC Participant's MPS and, in turn, the ETC Participant's
PPA. The PPA is then used to adjust certain Medicare payments of the
ETC Participant during 6-month PPA periods, with the first PPA Period
taking place from July 1, 2022, through December 31, 2022. As described
in 42 CFR 512.390(a), CMS will notify each ETC Participant, in a form
and manner determined by CMS, of the ETC Participant's attributed
beneficiaries, MPS, and PPA for a PPA Period no later than one month
before the start of the applicable PPA Period.
In order to ensure ETC Participant have timely access to these ETC
Model reports, we are proposing to add a new paragraph (b) to Sec.
512.390 to establish a process for CMS to share certain beneficiary-
identifiable and aggregate data with ETC Participants pertaining to
their participation in the ETC Model. CMS believes that ETC
Participants need this data to successfully coordinate the care of
their ESRD Beneficiaries and, if applicable, Pre-emptive LDT
Beneficiaries; to succeed under the ETC Model; and to assess CMS's
calculations of the individual ETC Participant's PPA for a given PPA
Period. Specifically, CMS believes that ETC Participants must have a
clear understanding of the beneficiaries CMS has attributed to them
under the ETC Model and how each attributed beneficiary has factored
into the ETC Participant's home dialysis rate, transplant waitlist
rate, and living donor transplant rate, to better identify care
coordination and care management opportunities, and to have the
opportunity to seek targeted review of CMS's calculation of the MPS.
The purpose of the targeted review process, established under current
Sec. 512.390(b), which we would redesignate as paragraph (c), is to
determine whether an incorrect PPA has been applied during the PPA
Period. CMS additionally believes that timely access to this data is
important and proposes to require CMS to make this data available twice
a year, prior to each PPA Period in an MY.
In the following sections of this proposed rule, we describe our
proposed process for CMS to share and for ETC Participants to retrieve
certain beneficiary-identifiable attribution data and performance data,
as well as the protections that would apply to this data under a data
sharing agreement with CMS. We also describe our proposed process for
sharing certain aggregate, de-identified performance data with ETC
Participants.
b. CMS Sharing of Beneficiary-Identifiable Data
We propose to establish a process in new Sec. 512.390(b)(1) under
which CMS would share certain beneficiary-identifiable data with ETC
Participants regarding their attributed beneficiaries and performance
under the ETC Model. We are proposing that, in accordance with the
timing of the notification requirement described in Sec. 512.390(a),
CMS would be required to make the beneficiary-identifiable data
pertaining to a given PPA Period available for retrieval by ETC
Participants no later than 1 month before the start of that PPA Period.
The ETC Participant would be able to retrieve this data at any point
during the relevant PPA Period, but, in accordance with current Sec.
512.390(b)(1), which would be redesignated as paragraph (c)(1), the ETC
Participant would have 90 days from the date that CMS shares the MPS,
including the data CMS used in calculating the MPS, to request a
targeted review. We propose that CMS would notify ETC Participants of
the availability of the beneficiary-identifiable data for a relevant
PPA Period and the process for retrieving that data, through the ETC
listserv and through the ETC Model website, available at https://innovation.cms.gov/innovation-models/esrd-treatment-choices-model.
Regarding the specific beneficiary-identifiable data that CMS would
be required to share with ETC Participants,
[[Page 36387]]
we are proposing in Sec. 512.390(b)(1)(ii)(A) to include, when
available, the following data for each PPA Period: The ETC
Participant's attributed beneficiaries' names, Medicare Beneficiary
Identifiers (MBIs), dates of birth, dual-eligible status, and LIS
recipient status. We believe that the patient's name, MBI, and date of
birth constitute the minimum elements to enable an ETC Participant to
properly identify an attributed beneficiary, and to confirm the
identity of an attributed during any communications with a beneficiary
or a beneficiary's caregiver, as appropriate and allowable. In
addition, the ETC Participant needs to be aware of each attributed
beneficiary's dual-eligible status and LIS recipient status to
understand how each attributed beneficiary contributed to how CMS
calculated the ETC Participant's Health Equity Incentive, if finalized.
We propose in Sec. 512.390(b)(1)(ii)(B) that this beneficiary-
identifiable data also would include, when available, data regarding
the ETC Participant's performance under the ETC Model, including, for
each attributed beneficiary, as applicable, the number of months the
beneficiary was attributed to the ETC Participant, received home
dialysis, self-dialysis, or nocturnal in-center dialysis, or was on a
transplant waitlist; and the number of months that have passed since
the beneficiary has received a living donor transplant, as applicable.
We believe that sharing these data elements would help the ETC
Participant understand and, as appropriate, seek targeted review of
CMS's calculation of the ETC Participant's MPS, and otherwise
understand how CMS adjusted the ETC Participant's Medicare payments by
the PPA.
We recognize there are sensitivities surrounding the disclosure of
individually-identifiable (beneficiary-specific) health information,
and we note that a number of laws place constraints on the sharing of
individually identifiable health information. For example, section 1106
of the Act generally bars the disclosure of information collected under
the Act without consent unless a law (statute or regulation) permits
for the disclosure. In this instance, the HIPAA Privacy Rule provides
that legal authority and authorizes this proposed disclosure of
individually identifiable health information by us to ETC Participants.
Under the HIPAA Privacy Rule, covered entities (defined as health care
plans, health care providers that submit certain transactions
electronically, and health care clearinghouses) are barred from using
or disclosing individually identifiable health information (called
``protected health information'' or PHI) in a manner that is not
explicitly permitted or required under the HIPAA Privacy Rule, without
the individual's authorization. The Medicare FFS program, a ``health
plan'' function of the Department, is subject to the HIPAA Privacy Rule
limitations on the disclosure of PHI, without an individual's
authorization. ETC Participants are also covered entities, provided
they are health care providers as defined by 45 CFR 160.103 and they or
their agents electronically engage in one or more HIPAA standard
transactions, such as for claims, eligibility or enrollment
transactions.
The proposed disclosure of ETC Model beneficiary-identifiable data
would be permitted by the HIPAA Privacy Rule under the provisions that
permit disclosures of PHI as ``required by law.'' Under 45 CFR
164.512(a)(1), a covered entity may use or disclose PHI to the extent
that such use or disclosure is required by law and the use or
disclosure complies with and is limited to the relevant requirements of
such law.\284\ We are proposing to establish a requirement under Sec.
512.390(b)(1) for CMS to share this data with ETC Participants.
---------------------------------------------------------------------------
\284\ Under 45 CFR 164.103, ``Required by law'' means ``a
mandate contained in law that compels an entity to make a use or
disclosure of protected health information and that is enforceable
in a court of law.'' It includes, among other things, ``statutes or
regulations that require the production of information, including
statutes or regulations that require such information if payment is
sought under a government program providing public benefits.''
---------------------------------------------------------------------------
The Privacy Act of 1974 also places limits on agency data
disclosures. The Privacy Act applies when federal agencies maintain
systems of records by which information about an individual is
retrieved by use of one of the individual's personal identifiers
(names, Social Security numbers, or any other codes or identifiers that
are assigned to the individual). The Privacy Act generally prohibits
disclosure of information from a system of records to any third party
without the prior written consent of the individual to whom the records
apply, 5 U.S.C. 552a(b). ``Routine uses'' are an exception to this
general principle. A routine use is a disclosure outside of the agency
that is compatible with the purpose for which the data was collected.
Routine uses are established by means of a publication in the Federal
Register about the applicable system of records describing to whom the
disclosure will be made and the purpose for the disclosure. We believe
that the proposed data disclosures are consistent with the purposes for
which the data discussed in this rule was collected, and thus, should
not run afoul of the Privacy Act, provided we ensure that an
appropriate Privacy Act system of records ``routine use'' is in place
prior to making any disclosures. The systems of records from which CMS
would share data are the Medicare Integrated Data Repository (``IDR''),
system of records number 09-70-0571, and the Health Resources and
Services Administration (``HRSA'') Organ Procurement and
Transplantation Network (``OPTN'')/Scientific Registry of Transplant
Recipients (``SRTR'') Data System, system of records number 09-15-0055.
We believe that establishing a regulatory requirement for CMS to
share the beneficiary-identifiable data described above would be
appropriate for the ETC Model for several reasons. First, we believe
that all ETC Participants not only desire but need this data to know
which beneficiaries CMS has attributed to them (and thus is holding
them financially accountable for such beneficiaries' individual
contributions to the ETC Participant's performance measures described
in 42 CFR part 512, subpart C, with the proposed modifications
described in this proposed rule, if finalized), and for each ETC
Participant to understand the basis by which CMS computed their MPS.
Second, CMS believes that all ETC Participants, regardless of size,
would have the capability of managing and meaningfully using the shared
data. We would provide the data in a form and manner that CMS believes
is user-friendly. In addition, the ETC Participant would be able to
review the beneficiary-identifiable data along with the aggregated
data, which should help the ETC Participant understand the data CMS
would share with the ETC Participant. Finally, CMS believes that any
other approach to making beneficiary-identifiable data available,
including the alternative proposal considered by CMS and described
below, would impose additional operational burdens on CMS and
administrative burdens on both CMS and the ETC Participants without
producing any meaningful privacy or security benefit.
We considered an alternative proposal for making beneficiary-
identifiable data available to ETC Participants based on the data
sharing policies currently used in many models tested under section
1115A of the Act, which would involve ETC Participants formally
requesting the data from CMS before CMS could share the data. In
particular, ETC Participants
[[Page 36388]]
would have the opportunity to request the data for their own ``health
care operations'' and CMS would be permitted to disclose the requested
data based on the HIPAA Privacy Rule provisions that permit disclosures
of PHI for the recipient's health care operations purposes as described
in 45 CFR 164.506(c)(4) and Sec. 164.501. Under this alternative
approach, ETC Participants that request this information would have to
attest to compliance with specific HIPAA requirements in addition to,
or as part of, the data sharing agreement described in the next section
of this proposed rule.
After considering this option, we believe that having the ETC
Participant request the data from CMS would add steps in the process
that would cause administrative burden for both CMS and ETC
Participants, and operational cost and burden for CMS. We further
believe that adding these steps would not produce a meaningful privacy
or security benefit based on the specific circumstances of this ETC
Model. Both this option and the approach proposed above would require
that the ETC Participant complete and sign a data sharing agreement,
and both would allow an ETC Participant to decline receiving
beneficiary-identifiable data by declining to complete or sign a data
sharing agreement. As such, there are no meaningful privacy or security
benefits that this option would create that are not already realized by
the proposed approach to data sharing in the ETC Model. We also
anticipate that all ETC Participants would want and need, and
overwhelmingly would request, the data described previously in this
section, would be capable of handling such data, and would take the
steps necessary to obtain the data. In addition, under an alternative
approach based on the HIPAA provisions for the ETC Participant's
``health care operations,'' CMS would only be able to disclose the
beneficiary-identifiable data for a purpose listed in paragraph (1) or
(2) of the definition of ``health care operations'' in 45 CFR 164.501.
However, we also believe it is crucial that an ETC Participant has the
opportunity to understand how CMS calculated the ETC Participant's PPA
for a PPA Period, and have the information needed to request a targeted
review of CMS's MPS calculation if the ETC Participant believes CMS
made an error.
Given the policies proposed in this section and the following
sections related to data sharing, we propose to modify the title of
Sec. 512.390 from ``Notification and targeted review'' to
``Notification, data sharing, and targeted review.'' We propose this
change so that the section title will more accurately reflect the
contents of the section.
We solicit public comment on our proposal to require, under
proposed Sec. 512.390(b)(1), that CMS make available certain
beneficiary-identifiable attribution and performance data for retrieval
by ETC Participants no later than one month prior to the start of each
PPA Period, and on our considered alternative to this proposal.
(1) Conditions for Retrieving Beneficiary-Identifiable Data
Given the sensitive nature of the beneficiary-identifiable data
that CMS would be required to share under our proposal, we are
proposing certain conditions for ETC Participants to be able to
retrieve this data and certain protections that would govern use of the
data following retrieval. First, we propose that CMS would only share
the beneficiary-identifiable data on the condition that the ETC
Participant observes all relevant statutory and regulatory provisions
regarding the appropriate use of data and the confidentiality and
privacy of individually identifiable health information as would apply
to a covered entity under the Health Insurance Portability and
Accountability Act of 1996 (HIPAA) regulations and agrees to comply
with the terms of a separate data sharing agreement. Although we expect
ETC Participants are covered entities and must comply with the HIPAA
regulations directly, we are including this provision to ensure an ETC
Participant would abide by those rules with respect to the data, even
if, for example, the ETC Participant is a hybrid entity under HIPAA and
the component requesting the data has not been designated as a health
care component under 45 CFR 164.105. The HIPAA provisions that the ETC
Participant would have to observe would include, but would not be
necessarily limited to, standards regarding the use and disclosure of
PHI; administrative, physical, and technical safeguards and other
security provisions; and breach notification.
We propose that, if an ETC Participant wishes to retrieve the
beneficiary-identifiable data, the ETC Participant would be required to
first complete, sign, and submit--and thereby agree to the terms of--a
data sharing agreement with CMS, which we would call the ETC Data
Sharing Agreement. This agreement would include certain protections and
limitations on the ETC Participant's use and further disclosure of the
beneficiary-identifiable data, and would be provided in a form and
manner specified by CMS, which we discuss in more detail in later
sections of this proposed rule. This agreement also potentially would
require the ETC Participant to make certain attestations, for example,
if required under the applicable Privacy Act system of records notice.
An ETC Participant that wishes to retrieve the beneficiary-identifiable
data would be required to complete and submit a signed ETC Data Sharing
Agreement at least annually. CMS believes that it is important for the
ETC Participant to complete and submit a signed ETC Data Sharing
Agreement at least annually so that CMS has up-to-date information that
the ETC Participant wishes to retrieve the beneficiary-identifiable
data attestations (if required), and information on the designated data
custodian(s). As described in greater detail below, we propose that a
designated data custodian would be the individual(s) that an ETC
Participant would identify as responsible for ensuring compliance with
all privacy and security requirements and for notifying CMS of any
incidents relating to unauthorized disclosures of beneficiary-
identifiable data.
CMS believes it is important for the ETC Participant to first
complete and submit a signed ETC Data Sharing Agreement before it
retrieves any beneficiary-identifiable data to help protect the privacy
and security of any beneficiary-identifiable data shared by CMS with
the ETC Participant. As described previously in this section of the
proposed rule, there are important sensitivities surrounding the
sharing of this type of individually identifiable health information,
and CMS must ensure to the best of its ability that any beneficiary-
identifiable data that it shares with ETC Participants would be further
protected in an appropriate fashion.
We considered an alternative proposal under which ETC Participants
would not need to complete and submit a signed ETC Data Sharing
Agreement, but we concluded that, if we proceeded with this option, we
would not have adequate assurances that the ETC Participants would
appropriately protect the privacy and security of the beneficiary-
identifiable data that we are proposing to share with them. We also
considered an alternative proposal under which the ETC Participant
would need to complete and submit a signed ETC Data Sharing Agreement
only once for the duration of the ETC Model. However, we concluded that
this similarly would not give CMS adequate assurances that the ETC
Participant would protect the privacy and security of the beneficiary-
identifiable data from
[[Page 36389]]
CMS. We concluded that it is critical that we have up-to-date
information and designated data custodians, and that requiring the ETC
Participant to submit an ETC Data Sharing Agreement at least annually
would represent the best means of achieving this goal.
We solicit public comment on our proposal to require, in Sec.
512.390(b)(1)(iii), that the ETC Participant agree to comply with all
applicable laws and the terms of the ETC Data Sharing Agreement as a
condition of retrieving the beneficiary-identifiable data, and on our
proposal in Sec. 512.390(b)(1)(iv) that the ETC Participant would need
to submit the signed ETC Data Sharing Agreement at least annually if
the ETC Participant wishes to retrieve the beneficiary-identifiable
data.
(2) Content of ETC Data Sharing Agreement Provisions for Beneficiary-
Identifiable Data
We are proposing in new Sec. 512.390(b)(iv) that, under the ETC
Data Sharing Agreement, ETC Participants would agree to certain terms,
namely: (1) To comply with the requirements for use and disclosure of
this beneficiary-identifiable data that are imposed on covered entities
by the HIPAA regulations and the requirements of the ETC Model set
forth in 42 CFR part 512; (2) to comply with additional privacy,
security, and breach notification requirements to be specified by CMS
in the ETC Data Sharing Agreement; (3) to contractually bind each
downstream recipient of the beneficiary-identifiable data that is a
business associate of the ETC Participant or performs a similar
function for the ETC Participant, to the same terms and conditions to
which the ETC Participant is itself bound in its data sharing agreement
with CMS as a condition of the downstream recipient's receipt of the
beneficiary-identifiable data retrieved by the ETC Participant under
the ETC Model; and (4) that if the ETC Participant misuses or discloses
the beneficiary-identifiable data in a manner that violates any
applicable statutory or regulatory requirements or that is otherwise
non-compliant with the provisions of the ETC Data Sharing Agreement,
the ETC Participant would no longer be eligible to retrieve the
beneficiary-identifiable data and may be subject to additional
sanctions and penalties available under the law. CMS believes that
these terms for sharing beneficiary-identifiable data with ETC
Participants are appropriate and important, as CMS must ensure to the
best of its ability that any beneficiary-identifiable data that it
shares with ETC Participants would be further protected by the ETC
Participant, and any business associates of the ETC Participant, in an
appropriate fashion. CMS believes that these proposals would allow CMS
to accomplish that.
CMS seeks public comment on the additional privacy, security,
breach notification, and other requirements that we would include in
the ETC Data Sharing Agreement. CMS has these types of agreements in
place as part of the governing documents of other models tested under
section 1115A of the Act and in the Medicare Shared Savings Program. In
these agreements, CMS typically requires the identification of data
custodian(s) and imposes certain requirements related to
administrative, physical, and technical safeguards relating to data
storage and transmission; limitations on further use and disclosure of
the data; procedures for responding to data incidents and breaches; and
data destruction and retention. These provisions would be imposed in
addition to any restrictions required by law, such as those provided in
the HIPAA privacy, security and breach notification regulations. These
provisions would not prohibit the ETC Participant from making any
disclosure of the data otherwise required by law.
CMS is considering limiting the use of beneficiary-identifiable
data for specific purposes, either alone or in combination. For
example, in the ETC Data Sharing Agreement, CMS is considering imposing
limits on how the ETC Participant may use the beneficiary-identifiable
data without prior written authorization from CMS to specific purposes,
such as assessing CMS's calculation of the MPS for a given PPA Period,
the ETC Participant's clinical care or ``treatment'' (as that term is
defined at 45 CFR 164.501) of an attributed beneficiary, and certain
``health care operations'' (as that term is defined at 45 CFR 164.501)
of the ETC Participant. As noted previously in this section of the
proposed rule, CMS believes that ETC Participants would require this
data to be able to request a targeted review of CMS's calculation of
the MPS as it relates to a given PPA Period, as understanding and being
able to seek review of CMS's calculation of the MPS, and thus the
reason CMS adjusted the ETC Participant's Medicare payments in the
manner it did, is critical for the ETC Model. Importantly, there is no
other source of this information outside of CMS. In addition to
limiting use to reviewing how CMS calculated the ETC Participant's MPS,
CMS is also considering limiting, in the ETC Data Sharing Agreement,
use of the beneficiary-identifiable data without prior written
authorization from CMS to use for clinical treatment purposes. CMS
believes that this beneficiary-identifiable data would be important in
helping the ETC Participant determine which of its ESRD Beneficiaries
are not on the transplant waitlist or have not received a living donor
transplant, to inform how the ETC Participant engages in clinical care
of the subject ESRD Beneficiary.
In addition to the previous two uses, CMS is also considering
limiting, in the ETC Data Sharing Agreement, the ETC Participant's use
of the beneficiary-identifiable data without prior written
authorization from CMS to care management and coordination, quality
improvement activities, and provider incentive design and
implementation, to the extent these activities would constitute
``health care operations'' that fall within the first and second
paragraphs of the definition of that phrase under the HIPAA Privacy
Rule (45 CFR 164.501). As it relates to case management and
coordination and quality improvement activates, CMS believes that this
beneficiary-identifiable data would help the ETC Participant to conduct
the important task of identifying which ESRD Beneficiaries are not
currently on the transplant waitlist and thus better enable the ETC
Participant to engage those beneficiaries, as clinically appropriate,
about the process of signing up for the transplant waitlist, thereby
improving the ETC Participant's performance on the transplant waitlist
rate, and increasing the likelihood that the subject ESRD Beneficiaries
would receive a transplant. In addition, CMS believes that sharing this
data with the ETC Participant would help the ETC Participant to conduct
the important task of identifying which ESRD Beneficiaries are
receiving dialysis in-center, and to consider whether furnishing kidney
disease patient education services or otherwise making such
beneficiaries aware of the possibility of receiving home dialysis,
self-dialysis, or nocturnal in-center dialysis, as clinically
appropriate in the ESRD Beneficiary's individual situation.
We seek public comment on how an ETC Participant might need to, and
want to, use the beneficiary-identifiable data retrieved from CMS under
the ETC Model to accomplish the goals of the ETC Model in accordance
with applicable law.
CMS also seeks public comment on what further disclosures of the
beneficiary-identifiable data might be appropriate to permit or
prohibit under the ETC Data Sharing Agreement. For example, CMS is
considering
[[Page 36390]]
prohibiting, in the ETC Data Sharing Agreement, any further disclosure,
not otherwise required by law, of the beneficiary-identifiable data
described previously in this section of the proposed rule to anyone who
is not a HIPAA covered entity or business associate, as defined in 45
CFR 160.103, or to an individual practitioner in a treatment
relationship with the subject ESRD Beneficiary or Pre-emptive LDT
Beneficiary, or that practitioner's business associates. Such a
prohibition would be similar to that imposed by CMS in other models
tested under section 1115A of the Act in which CMS shares beneficiary-
identifiable data with model participants. In the alternative, CMS is
also considering including more restrictive prohibitions in the ETC
Data Sharing Agreement, which would limit further discloses to only
some, one, or none of the categories of individuals or entities
described above.
CMS is considering all of these possibilities because there exist
important legal and policy limitations on the sharing of the
beneficiary-identifiable data discussed previously in this section of
the proposed rule, and CMS must consider carefully the ways in which
and reasons for which we would provide access to this data for purposes
of the ETC Model. CMS believes that some ETC Participants may require
the assistance of business associates, such as contractors, to perform
data analytics or other functions using this beneficiary-identifiable
data to support the ETC Participant's review of CMS's MPS calculations,
care management and coordination, quality improvement activities, or
clinical treatment of attributed beneficiaries. CMS also believes that
this beneficiary-identifiable data may be helpful for any HIPAA covered
entities who are in a treatment relationship with the subject ESRD
Beneficiary or Pre-emptive LDT Beneficiary.
We seek public comment on how an ETC Participant might need to, and
want to, disclose the beneficiary-identifiable data to other
individuals and entities to accomplish the goals of the ETC Model, in
accordance with applicable law.
Under our proposal, the ETC Data Sharing Agreement would include
other provisions, including requirements regarding data security,
retention, destruction, and breach notification. For example, we are
considering including, in the ETC Data Sharing Agreement, a requirement
that the ETC Participant designate one or more data custodians who
would be responsible for ensuring compliance with the privacy, security
and breach notification requirements for the data set forth in the ETC
Data Sharing Agreement; various security requirements like those found
in other models tested under section 1115A of the Act, but no less
restrictive than those provided in the relevant Privacy Act system of
records notices; how and when beneficiary-identifiable data could be
retained by the ETC Participant or its downstream recipients of the
beneficiary-identifiable data; procedures for notifying CMS of any
breach or other incident relating to the unauthorized disclosure of
beneficiary-identifiable data; and provisions relating to destruction
of the data. These are only examples, and are not the only terms CMS
would potentially include in the ETC Data Sharing Agreement.
We solicit public comment on this proposal that CMS, by adding
Sec. 512.390(b)(1)(iv)(B), would impose certain requirements in the
ETC Data Sharing Agreement related to privacy, security, data
retention, breach notification, and data destruction.
Finally, as described above, CMS proposes, at Sec.
512.390(b)(1)(iv)(D), that the ETC Data Sharing Agreement would include
a term providing that if the ETC Participant misuses or discloses the
beneficiary-identifiable data in a manner that violates any applicable
statutory or regulatory requirements or that is otherwise non-compliant
with the provisions of the ETC Data Sharing Agreement, the ETC
Participant would no longer be eligible to retrieve beneficiary-
identifiable data under proposed Sec. 512.390(b)(1)(i) and may be
subject to additional sanctions and penalties available under law. We
also propose to make conforming amendments to 42 CFR 512.160. Section
512.160(b) outlines the remedial actions available under the RO Model
and ETC Model, and paragraph (b)(8), in particular provides that, if
CMS determines that one or more grounds for remedial action specified
in Sec. 512.160(a) has taken place, CMS may discontinue the provision
of data sharing and reports to the model participant. We propose to add
a new Sec. 512.160(a)(9) to specify that, for the ETC Model only, CMS
may take remedial action if the model participant misuses or discloses
the beneficiary-identifiable data in a manner that violates any
applicable statutory or regulatory requirements or that is otherwise
non-compliant with the provisions of the applicable data sharing
agreement. This proposed change, if finalized, would align the
regulatory provision on remedial action with the proposed remedial
action we propose to include in the ETC Data Sharing Agreement.
We solicit public comment on this proposal, to prohibit the ETC
Participant from obtaining beneficiary-identifiable data pertaining to
the ETC Model if the ETC Participant fails to comply with applicable
laws and regulations, the terms of the ETC Model, or the ETC Data
Sharing Agreement.
(3) Process for Retrieving the ETC Data Sharing Agreement and
Beneficiary-Identifiable Data
We propose that we would make the ETC Data Sharing Agreement and
beneficiary-identifiable data available in a form and manner specified
by CMS. We expect to provide a web-based platform for ETC Participants
to use to retrieve the beneficiary-identifiable data. CMS would provide
ETC Participants further information about this web-based platform
through the ETC listserv and the ETC Model website at a date to be
determined by CMS, but at least 1 month before the first PPA Period
begins on June 1, 2022. We expect that CMS would notify ETC
Participants of each opportunity to retrieve a new set of beneficiary-
identifiable data and the process for accessing the web-based platform
to receive the data through the ETC listserv and on the ETC Model
website. Under this proposal, the ETC Participant would be required to
use the form and manner specified by CMS (which we expect will be a
web-based platform) to retrieve the data. If the ETC Participant did
not use the form and manner specified by CMS or did not agree to the
ETC Data Sharing Agreement, the ETC Participant would be unable to
retrieve the beneficiary-identifiable data described previously in this
section of the proposed rule. We propose that ETC Participants would be
permitted to retrieve this data at any point during the relevant PPA
Period. We considered establishing certain periods of time within a PPA
Period during which the ETC Participant would be able to retrieve the
data, but we concluded that permitting the ETC Participant to obtain
the data at any point during the relevant PPA Period would be
relatively operationally low-burden for CMS while providing additional
flexibility to the ETC Participant.
CMS believes that it is important that the ETC Participant complete
and submit its signed ETC Data Sharing Agreement, and retrieve the
beneficiary-identifiable data, in the same form and manner (which we
expect to be a web-based platform).
In the alternative, we considered providing the beneficiary-
identifiable data to ETC Participants via paper mail rather than
through a web-based
[[Page 36391]]
platform, but we concluded that making the data available through a
web-based platform would reduce administrative burden on both CMS and
the ETC Participants. We also concluded that making this beneficiary-
identifiable data available through a web-based platform would allow
CMS to provide the data in a manner that is more secure than if CMS
were to make the data available through paper mail. By using a web-
based platform, to be further described by CMS through the ETC listserv
and the ETC Model website, CMS would help ensure that only authorized
users would be able to obtain the data, and would be able to implement
a two-factor authentication to help ensure that no one other than an
ETC Participant would have access to the data. In addition, we
concluded that it would be more efficient to provide the ETC Data
Sharing Agreement and the beneficiary-identifiable data itself through
the same form and manner (which we expect to be a web-based platform),
rather than using two different processes and that using a web-based
platform would be more efficient than paper mail. For these reasons, we
believe the best option would be for us to use only the web-based
platform both for providing the ETC Data Sharing Agreement and for
sharing data pertaining to the ETC Model.
We solicit public comment on our proposal to require the ETC
Participant to complete and submit a signed ETC Data Sharing Agreement
before the ETC Participant could retrieve the beneficiary-identifiable
data, and on our proposal that the ETC Participant would be required to
retrieve the beneficiary-identifiable data in the same form and manner
as the ETC Participant receives and submits the ETC Data Sharing
Agreement. We also solicit comment regarding our expectation that we
will use a web based platform, rather than paper mail, for these
purposes.
e. CMS Sharing of Aggregate Data
In addition to the proposed process for sharing beneficiary-
identifiable data described previously in this section, we are
proposing in Sec. 512.390(b)(2) that CMS would make available certain
aggregate data for retrieval by the ETC Participant, in a form and
manner to be specified by CMS, no later than one month before each PPA
Period. This aggregate performance data, would include, when available,
the following information for each PPA Period, de-identified in
accordance with 45 CFR 164.514(b): The ETC Participant's performance
scores on the home dialysis rate, transplant waitlist rate, living
donor transplant rate, and, if finalized, Health Equity Incentive; the
ETC Participant's aggregation group's scores on the home dialysis rate,
transplant waitlist rate, living donor transplant rate, and, if
finalized, Health Equity Incentive; information on how the ETC
Participant's and ETC Participant's aggregation group's scores relate
to the achievement benchmark and improvement benchmark (that is,
whether the ETC Participant met or exceeded the threshold for each such
benchmark); and the ETC Participant's MPS and PPA for the corresponding
PPA Period. CMS believes that sharing this aggregate, de-identified
data with the ETC Participant would be important to help the ETC
Participant better understand its performance in the ETC Model relative
to its aggregation group and to the achievement and improvement
benchmarks against which CMS is measuring the ETC Participant's
performance. Whereas the beneficiary-identifiable data described
previously in this section of the proposed rule would indicate which
ESRD Beneficiaries and, if applicable, Pre-emptive LDT Beneficiaries
the ETC Participant could devote greater resources to, CMS believes
this aggregate, de-identified data would better enable the ETC
Participant to see which performance rates the ETC Participant might
need to improve to more generally improve its performance under the ETC
Model.
We are proposing that CMS would make this data available to the ETC
Participant for retrieval in a form and manner to be specified by CMS
no less than one month prior to each PPA Period. We expect that CMS
would make this data available to the ETC Participant on the same web-
based platform on which CMS would be providing the beneficiary-
identifiable data described previously in this section. The ETC
Participant would be required to use the form and manner specified by
CMS to retrieve this aggregate data, but would not have to agree to the
ETC Data Sharing Agreement to retrieve this aggregated data, as it is
not beneficiary-identifiable. We believe that using a web-based
platform for sharing this aggregate data would be appropriate for the
same reasons it would be appropriate for sharing the beneficiary-
identifiable data. By using a web-based platform, CMS would help ensure
that only authorized users would be able to obtain the data, and would
be able to implement a two-factor authentication to help ensure that no
one other than an ETC Participant would have access to the data. In
addition, because CMS would be providing the ETC Data Sharing Agreement
and beneficiary-identifiable data on the same web-based platform, we
believe it would be convenient for the ETC Participant if CMS shared
the aggregate data on the same web-based platform.
In the alternative, we considered sending this aggregate data to
the ETC Participant via paper mail. However, CMS concluded that it
would be more convenient to the ETC Participant to retrieve this data
from a web-based platform rather than via paper mail, and that sending
this data via paper mail would represent significant administrative and
operational burdens for CMS.
We solicit public comment on our proposal to share aggregate data
generally, to share aggregated data in the same form and manner we are
proposing to use for sharing beneficiary-identifiable data. We also
solicit public comment on our expectation to use a web-based platform
for this purpose, as well as our considered alternative to share the
aggregate data via paper mail.
8. Medicare Waivers and Additional Flexibilities
a. Background on Kidney Disease Patient Education Services Waiver
Pursuant to section 1861(ggg)(1) of the Act and Sec. 410.48 of our
regulations, Medicare Part B covers outpatient, face-to-face kidney
disease patient education services provided by certain qualified
persons to beneficiaries with Stage IV chronic kidney disease. As noted
in the Specialty Care Models final rule, kidney disease patient
education services play an important role in educating patients about
their kidney disease and to help them make informed decisions on the
appropriate type of care and/or dialysis needed for them (85 FR 61337).
In addition, we noted in the Specialty Care Models final rule that
kidney disease patient education services are designed to educate and
inform beneficiaries about the effects of kidney disease, their options
for transplantation, dialysis modalities, and vascular access (85 FR
61337). Because kidney disease patient education services have been
infrequently billed, we found it necessary for purposes of testing the
ETC Model to waive select requirements of kidney disease patient
education services authorized in section 1861(ggg)(1) of the Act and in
the implementing regulation at 42 CFR 410.48. Specifically, to broaden
the availability of kidney disease patient education services under the
ETC Model, we have used our authority under section 1115A(d) of the Act
to waive certain requirements for
[[Page 36392]]
individuals and entities that furnish and bill for kidney disease
patient education services. We codified these waivers at Sec.
512.397(b). These include waivers to allow more types of beneficiaries
to have access to kidney disease patient education services, as well as
greater flexibility in how the kidney disease patient education
services are performed. For instance, CMS waived the requirement that
kidney disease patient education services are covered only for Stage IV
chronic kidney disease (CKD) patients to permit beneficiaries to
receive kidney disease patient education services if they are diagnosed
with CKD Stage V or are in the first 6 months of starting dialysis to
receive the benefit. CMS also waived the requirements in section
1861(ggg)(2)(A)(i) of the Act and Sec. 410.48(a) and (c)(2)(i) of the
applicable regulations pertaining to the definition of ``qualified
person'' such that registered dieticians/nutrition professionals,
licensed clinical social workers, or a clinic/group practice may
furnish kidney disease patient education services under the direction
of, and incident to the services of a Managing Clinician who is an ETC
Participant.
Finally, CMS waived two requirements relating to the content of
kidney disease patient education services furnished to a beneficiary.
CMS waived the requirement under Sec. 410.48(d)(1) of our regulations
that the content of kidney disease patient education services include
the management of co-morbidities, including delaying the need for
dialysis, when such services are furnished to beneficiaries with CKD
Stage V or ESRD, unless such content is relevant for the beneficiary.
In addition, CMS waived the requirement under Sec. 410.48(d)(5)(iii)
of our regulations that an outcomes assessment designed to measure
beneficiary knowledge about chronic kidney disease and its treatment be
performed during one of the kidney disease patient education services,
requiring instead that such outcomes assessment is performed within 1
month of the final kidney disease patient education services session
furnished by qualified staff.
b. Proposed Kidney Disease Patient Education Services Telehealth Waiver
and Additional Flexibilities
Many changes took place in 2020 and early 2021 due to the COVID-19
PHE. Legislation enacted to address the PHE for COVID-19 provided the
Secretary with new authorities under section 1135(b)(8) of the Act to
waive or modify Medicare telehealth payment requirements during the PHE
for COVID-19. We established several flexibilities to accommodate these
changes in the delivery of care. Through waiver authority under section
1135(b)(8) of the Act, in response to the PHE for COVID-19, we
temporarily waived the geographic and site of service originating site
restrictions in section 1834(m)(4)(C) of the Act. For example, CMS
waived the rural area requirement at section 1834(m) of the Act to
allow for telehealth services, including kidney disease patient
education services that can be furnished via telehealth, to be
furnished to beneficiaries in any geographic area, regardless of
location and in their homes, for the duration of the PHE. These waivers
are set to terminate at the end of the COVID-19 PHE.
We believe that, once the PHE ends, these waivers removing the
geographic and site of service originating site restrictions for kidney
disease patient education services furnished via telehealth would be
necessary solely for purposes of testing the ETC Model. Except under
very limited circumstances, under section 1834(m) of the Act and its
implementing regulations, the originating site where the beneficiary is
located at the time a telehealth service is furnished is limited to
certain, mostly rural, geographic locations and a site of service that
is one of certain types of health care facilities. We believe that
allowing qualified staff to furnish kidney disease patient education
services via telehealth, regardless of the beneficiary's geographic
area or the site of the beneficiary, and regardless of the site of
service of the practitioner, would increase access to kidney disease
patient education services for a few reasons. First, some beneficiaries
may not have access to reliable transportation, especially those
beneficiaries who suffered economically during the ongoing PHE, but may
have access to the technology necessary for practitioners to furnish
kidney disease patient education services. Moreover, some
beneficiaries, even those with reliable transportation, may be more
comfortable receiving kidney disease patient education services via
telehealth rather than appearing in person after over a year of social
distancing, even when it becomes safe according to Federal guidance for
such beneficiaries to enter physical spaces with other individuals.
This is especially likely to be the case for instances in which a
practitioner would furnish kidney disease patient education services in
a group session rather than an individual session. Increasing access to
kidney disease patient education services is consistent with one of the
main goals of the ETC Model, insofar as we believe that education, as
delivered through kidney disease patient education services, helps
improve beneficiary choice of dialysis modality.
In addition, we believe that removing beneficiary cost barriers for
kidney disease patient education services would be helpful. As we
demonstrate below, there is a significant relationship between
household income or poverty status and kidney disease, and removing or
mitigating cost barriers to access to kidney disease patient education
services would likely increase the number of beneficiaries who would be
willing to receive kidney disease patient education services.
We therefore propose that, starting in MY3, kidney disease patient
education services may be furnished to certain beneficiaries via
telehealth in a manner that is more flexible than that required under
existing telehealth requirements. In addition, we propose to permit the
reduction or waiver of coinsurance for the kidney disease patient
education services, starting in MY3.
(1) Kidney Disease Patient Education Services Telehealth Waiver
CMS proposes to amend Sec. 512.397 to add a waiver of certain
telehealth requirements to provide qualified staff, as we are proposing
to define for purposes of the ETC Model at Sec. 512.310, the
flexibility to furnish kidney disease patient education services via
telehealth for the reasons described above. Specifically, we propose to
waive the geographic and site of service originating site requirements
in sections 1834(m)(4)(B) and 1834(m)(4)(C) of the Act, and in our
regulations at 42 CFR 410.78(b)(3) and (4), for kidney disease patient
education services furnished via telehealth. We believe the kidney
disease patient education services telehealth waiver would allow more
Medicare beneficiaries to receive kidney disease patient education
services via telehealth by removing the originating site restrictions,
thus allowing for the beneficiary to be located anywhere, and including
at a site not specified in Sec. 410.78(b)(3) of our regulations; and
by allowing for the beneficiary to be located outside of a rural area.
CMS also proposes to waive the requirement in section 1834(m)(2)(B) of
the Act and 42 CFR 414.65(b) such that CMS would not pay an originating
site facility fee for kidney disease patient education services
furnished via telehealth to a beneficiary at a site not specified in
Sec. 410.78(b)(3) of our regulations under this proposed waiver, if
finalized.
[[Page 36393]]
However, we do not propose to waive the requirement under section
1834(m)(1) of the Act and 42 CFR 410.78(b) that telehealth services be
furnished via an ``interactive telecommunications system,'' as that
term is defined in Sec. 410.78(a)(3) to mean multimedia communications
equipment that includes, at a minimum, audio and video equipment
permitting two-way, real-time interactive communication between the
patient and distant site physician or practitioner. Accordingly, we
would continue to require that the kidney disease patient education
services furnished via telehealth be provided through an interactive
telecommunications system; audio-only telehealth services would not be
permitted.
We propose that kidney disease patient education services could be
furnished via telehealth health only by qualified staff. We used the
term ``clinical staff'' and ``qualified staff'' in the Specialty Care
Models final rule, but did not provide definitions of these terms. For
clarity, we now propose to define ``clinical staff'' and ``qualified
staff'' in 42 CFR 512.310. We propose to define ``clinical staff'' to
mean a licensed social worker or registered dietician/nutrition
professional who furnishes services for which payment may be made under
the physician fee schedule under the direction of and incident to the
services of the Managing Clinician who is an ETC Participant. We are
proposing to define the term clinical staff in this manner to describe
those clinicians who are authorized to furnish kidney disease patient
education services only pursuant to the waiver specified at Sec.
512.390(b)(1)--namely licensed social workers and registered
dieticians/nutrition professionals. The remaining clinicians currently
specified in Sec. 512.390(b)(1)--doctors, physician assistants, nurse
practitioners, and clinical nurse specialists--fall within the existing
definition of qualified person at 42 CFR 410.48(a). We therefore
propose to define ``qualified staff'' to mean both clinical staff and
any qualified person (as defined at Sec. 410.48(a) of our regulations)
who is an ETC Participant.
We seek comment on our proposal to waive the originating site
requirements for telehealth services to allow qualified staff to
furnish kidney disease patient education services via telehealth to a
beneficiary regardless of where the beneficiary is geographically
located such that kidney disease patient education services could be
furnished via telehealth regardless of the beneficiary's location,
including at a site not specified in Sec. 410.78(b)(3) of our
regulations. We further seek comment on our proposal to waive the
originating site facility fee requirements such that CMS would not pay
an originating site facility fee for kidney disease patient education
services furnished via telehealth to a beneficiary at a site not
specified in Sec. 410.78(b)(3) of our regulations.
(2) Kidney Disease Patient Education Services Beneficiary Coinsurance
Waiver
Available data and scholarly research suggest that there is a
significant relationship between socioeconomic status and prevalence of
CKD. For example, evidence suggests that CKD is more prevalent among
individuals with lower income.\285\ In addition, at least one study
suggests that as an individual's CKD severity increases (for example,
from CKD III to CKD IV), the likelihood of the CKD patient falling into
poverty increases.\286\ In light of this research, CMS believes that
cost represents a meaningful barrier for beneficiaries in accessing
kidney disease patient education services. While there does not appear
to be any research that explicitly investigates to what extent cost
barriers preclude access to kidney disease patient education services,
the identified relationship between household income or poverty status
and prevalence of CKD suggests that cost is an important factor when
considering a beneficiary's access to kidney disease patient education
services.
---------------------------------------------------------------------------
\285\ Table 1.2 in United States Renal Data System, 2020 Annual
Report, Chronic Kidney Disease: Chapter 1, CKD in the General
Population, available at https://adr.usrds.org/2020/chronic-kidney-disease/1-ckd-in-the-general-population (indicating that the
prevalence of CKD in those above the poverty line is 14.4 percent
while the prevalence of CKD in those below the poverty line is 17.4
percent. See also McClellan, W.M., et al., Poverty and Racial
Disparities in Kidney Disease: The REGARDS Study, Am. J Nephrol,
2010, Volume 32, Issue 1, pages 38-46, available at https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2914392/ (providing data
suggesting that lower household income is associated with higher
prevalence of CKD).
\286\ Morton, R.L, et al., Impact of CKD on Household Income,
Kidney International Reports, Volume 3, Issue 3, 2018, pages 610-
618, available at https://www.sciencedirect.com/science/article/pii/S2468024917304795?via%3Dihub.
---------------------------------------------------------------------------
Under section 1833 of the Act, the amounts paid by Medicare for
kidney disease patient education services are equal to 80 percent of
the applicable payment amount; beneficiaries are thus subject to a 20
percent coinsurance for kidney disease patient education services.
Kidney disease patient education services can be billed under G0420 for
an individual session, or under G0421 for a group session. The current
national unadjusted payment for G0420 under the CY2021 Physician Fee
Schedule is $114.10; for G0421, it is $27.22. As such, a beneficiary
would be required to pay $22.82 for an individual session of kidney
disease patient education services or $5.44 for kidney disease patient
education services furnished to a group, which may be higher or lower
depending on certain factors, such as the geographic location of the
beneficiary. Medicare covers up to six kidney disease patient education
services for an individual beneficiary during that beneficiary's
lifetime, meaning that a beneficiary may be required to pay $136.92 if
six individual kidney disease patient education services are clinically
appropriate for that beneficiary, or $32.64 if six group kidney disease
patient education services are clinically appropriate for that
beneficiary.
CMS believes that it is necessary, for purposes of testing the ETC
Model, to permit ETC participants the flexibility to reduce or waive
the 20 percent coinsurance requirement for kidney disease patient
education services. We believe this patient incentive, if finalized,
would increase the provision of kidney disease patient education
services to beneficiaries, given the relationship between income or
poverty and prevalence of CKD, and the relationship between kidney
disease patient education services and progression of CKD. CMS has
determined that, if this proposal were finalized, this CMS-sponsored
patient incentive would advance the ETC Model's goal of increasing
access to kidney disease patient education services, and to making
beneficiaries more aware of their choices in preparing for kidney
treatment, including the choice of receiving home dialysis, self-
dialysis, or nocturnal in-center dialysis, rather than traditional in-
center dialysis.
Accordingly, beginning January 1, 2022, we propose at Sec.
512.397(c) to permit ETC Participants to reduce or waive the
beneficiary coinsurance obligations for kidney disease patient
education services furnished to an eligible beneficiary who does not
have secondary insurance on the date the kidney disease patient
education services are furnished if certain conditions are satisfied.
We refer to this patient incentive herein as the ``kidney disease
patient education services coinsurance patient incentive.'' As more
fully explained below, we expect to make a determination that the anti-
kickback statute safe harbor for CMS-sponsored model patient incentives
(42 CFR 1001.952(ii)(2)) would be available to protect cost-sharing
support that is furnished in compliance with ETC
[[Page 36394]]
Model requirements with respect to kidney disease patient education
services. If CMS makes such a determination, the safe harbor for CMS-
sponsored model patient incentives would protect an ETC Participant, as
that term is defined at Sec. 512.310, who offers a reduction or waiver
of coinsurance for kidney disease patient education services to
beneficiaries who are eligible to receive kidney disease patient
education services, including those eligible pursuant to the waiver
described in Sec. 512.397(b)(2), and who do not have secondary
insurance on the date that the kidney disease patient education
services were furnished.
We are proposing that the kidney disease patient education services
coinsurance patient incentive would be available to the ETC Participant
for kidney disease patient education services furnished by an
individual or entity who is qualified staff. This proposal would align
with the individuals who may furnish kidney disease patient education
services under Sec. 512.397(b) of this subpart, which are we replacing
in its entirety to standardize certain terms and add clarity, as
described in greater detail below.
We are proposing to limit the kidney disease patient education
services coinsurance patient incentive to beneficiaries who do not have
secondary insurance, as secondary insurance typically provides cost-
sharing support of the type CMS is proposing in this proposed rule. We
also believe that limiting the kidney disease patient education
services coinsurance patient incentive to beneficiaries without
secondary insurance would better ensure that only beneficiaries who
need cost-sharing support would receive it, rather than permitting
cost-sharing support for all beneficiaries for whom kidney disease
patient education services are clinically appropriate.
We are also proposing that the kidney disease patient education
services coinsurance patient incentive would be available only for
kidney disease patient education services that were furnished in
compliance with the applicable provisions of Sec. 410.48 of our
regulations, which includes a requirement that a beneficiary obtain a
referral from the physician (as defined in section 1861(r)(1) of the
Act) managing the beneficiary's kidney condition in order for the
beneficiary to be eligible to receive kidney disease patient education
services. We are proposing to include this requirement because we
waived some but not all provisions of Sec. 410.48, and we believe that
the requirement that the beneficiary receive a referral from their
physician is important for ensuring that kidney disease patient
education services are furnished only to beneficiaries for whom it is
clinically appropriate.
CMS proposes that such coinsurance support would be permitted for
the kidney disease patient education services offered either in-person
or via telehealth, and that it would be permitted for both individual
sessions and group sessions. However, we are considering limiting the
kidney disease patient education services coinsurance patient incentive
to kidney disease patient education services furnished to an individual
beneficiary, rather than allowing the kidney disease patient education
services coinsurance patient incentive for kidney disease patient
education services furnished either individually or to a group. The
cost burden on beneficiaries who receive kidney disease patient
education services in a group setting is much lower than it is on
beneficiaries who receive kidney disease patient education services
individually. However, we are concerned that any cost barrier to kidney
disease patient education services, even if low, represents a
meaningful barrier to some beneficiaries who would otherwise elect to
receive such services. We solicit comments on this issue.
An ETC Participant that offers coinsurance support for kidney
disease patient education services would be required to maintain
records of certain information. Specifically, an ETC Participant that
offers the kidney disease patient education services coinsurance
patient incentive would be required to maintain records of the
following: The identity of the qualified staff who furnished the kidney
disease patient education services for which the coinsurance was
reduced or waived; the date the kidney disease patient education
services coinsurance patient incentive was provided; the identity of
the beneficiary to whom the kidney disease patient education services
coinsurance patient incentive was provided; evidence that the
beneficiary who received the kidney disease patient education services
coinsurance patient incentive was eligible to receive the kidney
disease patient education services and did not have secondary
insurance; and the amount of the kidney disease patient education
services coinsurance patient incentive reduced or waived by the ETC
Participant. We propose to require an ETC Participant that offers this
kidney disease patient education services coinsurance patient incentive
to maintain and provide the government with access to these records in
accordance with 42 CFR 512.135(b) and (c) of this part.
We further propose in proposed 42 CFR 512.160(b)(6)(ii) that, for
the ETC Model only, CMS could suspend or terminate the ability of an
ETC Participant to offer the kidney disease patient education services
coinsurance patient incentive if CMS determined that any grounds for
remedial action exist pursuant to Sec. 512.160(a).
In lieu of a waiver of certain fraud and abuse provisions in
sections 1128A and 1128B of the Act, CMS may determine that the anti-
kickback statute safe harbor CMS-sponsored model patient incentives (42
CFR 1001.952(ii)(2)) is available to protect the reduction or waiver of
kidney disease patient education services coinsurance permitted under
the ETC Model final rule, if issued. Specifically, we expect to
determine that the CMS-sponsored model safe harbor will be available to
protect the reduction or waiver of coinsurance that satisfies the
requirements of such safe harbor and the provisions of proposed Sec.
512.397(c)(1). We propose that, if we make this determination, we would
specify in regulation text at Sec. 512.397(c)(4) that the safe harbor
is available.
We are also considering prohibiting on an ESRD facility or other
entity from providing qualified staff or the ETC Participant with
financial support to enable such qualified staff or ETC Participant to
provide the kidney disease patient education services coinsurance
patient incentive. CMS is concerned that permitting such financial
support may encourage unlawful or abusive arrangements designed to
induce or reward referrals for Federal health care program business. We
solicit comments on whether this prohibition is a necessary to
safeguard against fraud and abuse or if other laws effectively provide
sufficient protection.
We also considered waiving Medicare payment requirements such that
CMS would pay the full amount of the kidney disease patient education
services furnished to a beneficiary who does not have secondary
insurance, rather than just 80 percent of the amount. Under section
1115A(d)(1) of the Act, the Secretary may waive such requirements of
titles XI and XVIII and of sections 1902(a)(1), 1902(a)(13),
1903(m)(2)(A)(iii) of the Act, and certain provisions of section 1934
of the Act as may be necessary solely for purposes of carrying out
section 1115A of the Act respect to testing models described in section
1115A(b) of the Act. This is the authority under which we would waive
[[Page 36395]]
such Medicare payment requirements. Under such a policy, Medicare would
pay 100 percent of the payment amount for kidney disease patient
education services furnished by Managing Clinicians who are ETC
Participants to beneficiaries who do not have secondary insurance, and
such beneficiaries would have no cost-sharing obligation for that
benefit. However, we determined that this policy would likely represent
too large an impact to the ETC Model's savings estimates, and thus
would potentially jeopardize our ability to continue to test the ETC
Model, if such a policy were finalized.
Given the policies proposed in this section related to programmatic
waivers and additional flexibilities available under the ETC Model, we
propose to modify the title of Sec. 512.397 from ``ETC Model Medicare
program waivers'' to ``ETC Model Medicare program waivers and
additional flexibilities.'' We propose this change so that the section
title would more accurately reflect the contents of the section if our
proposed kidney disease patient education services coinsurance patient
incentive is finalized.
We solicit public comments on our proposal to allow qualified
staff, as we propose to define the term under Sec. 512.310, to offer
coinsurance support for kidney disease patient education services to
beneficiaries who are eligible for such services, including those
eligible under Sec. 512.397(b)(2), and who do not have secondary
insurance on the date the kidney disease patient education services are
furnished. We also solicit comment on our proposal to require the ETC
Participant to maintain and provide the government with access to
records regarding the use of the kidney disease patient education
services coinsurance patient incentive.
(3) Revising Language Providing Other ETC Model Medicare Program
Waivers
We propose to revise Sec. 512.397(b)(1) through (4) in their
entirety to accomplish a few goals. First, we propose to make
conforming changes throughout Sec. 512.397(b) to the manner in which
CMS discusses kidney disease patient education services. Currently,
Sec. 512.397(b) includes references to ``KDE services,'' ``the KDE
benefit,'' ``KDE sessions,'' and, simply, ``KDE.'' CMS would change all
of these references to ``kidney disease patient education services''
for clarity and to conform with the term used elsewhere in our
regulations. In addition, we propose to make conforming changes through
Sec. 512.397(b) to the manner in which CMS discusses the individuals
who are permitted to furnish kidney disease patient education services
under the ETC model programmatic waivers. Specifically, as discussed
previously, CMS is proposing to add definitions for ``clinical staff''
and ``qualified staff'' in this proposed rule, and CMS believes
clarifying how CMS discusses these individuals in Sec. 512.397(b) will
enhance clarity. Finally, CMS is proposing to remove the ``clinic/group
practice'' from the list of individuals or entities that are permitted
to furnished kidney disease patient education services under the ETC
Model programmatic waivers, and to remove the waiver of 42 CFR
410.48(c)(2)(i) from Sec. 512.397(b)(1) of this part. CMS believes
that its inclusion of clinic/group practices previously was in error; a
clinic/group practice is not able to furnish or bill for kidney disease
patient education services under existing law and CMS did not intend
for the waiver described in Sec. 512.397(b) to permit anyone other
than a clinican to furnish kidney disease patient education services.
Because the waiver of the requirements under 42 CFR 410.48(c)(2)(i) was
implemented only to broaden the ``qualified person'' that could furnish
kidney disease patient education services pursuant to Sec.
512.397(b)(1) to include a clinic/group practice, we are proposing to
remove references to 42 CFR 410.48(c)(2)(i) in Sec. 512.397(b)(1) of
this part.
We solicit public comments on these proposed changes to Sec.
512.397(b) to make conforming and clarifying changes to the manner in
which CMS discusses kidney disease patient education services and the
individuals who are permitted to furnish kidney disease patient
education services under the ETC Model waivers described in Sec.
512.397(b), and to our proposed removal of ``clinic/group practice''
from the list of individuals or entities who may, under the ETC Model
waivers described in Sec. 512.397(b), furnish kidney disease patient
education services.
C. Requests for Information (RFIs) on Topics Relevant to the ETC Model
This section includes several requests for information (RFIs). In
responding to the RFIs, the public is encouraged to provide complete,
but concise responses. These RFIs are issued solely for information and
planning purposes; RFIs do not constitute a Request for Proposal (RFP),
application, proposal abstract, or quotation. The RFIs do not commit
the U.S. Government to contract for any supplies or services or make a
grant award. Further, CMS is not seeking proposals through these RFIs
and will not accept unsolicited proposals. Respondents are advised that
the U.S. Government will not pay for any information or administrative
costs incurred in response to this RFI; all costs associated with
responding to these RFIs will be solely at the respondent's expense.
Failing to respond to either RFI will not preclude participation in any
future procurement, if conducted.
Please note that CMS will not respond to questions about the policy
issues raised in these RFIs. CMS may or may not choose to contact
individual respondents. Such communications would only serve to further
clarify written responses. Contractor support personnel may be used to
review RFI responses. Responses to these RFIs are not offers and cannot
be accepted by the U.S. Government to form a binding contract or issue
a grant. Information obtained because of this RFI may be used by the
U.S. Government for program planning on a non-attribution basis.
Respondents should not include any information that might be considered
proprietary or confidential. All submissions become U.S. Government
property and will not be returned. CMS may publicly post the comments
received, or a summary thereof.
1. Peritoneal Dialysis Catheter Placement
The most common modality of home dialysis is peritoneal dialysis
(PD). In order to perform PD, a beneficiary needs placement of a PD
catheter. A PD catheter is a flexible plastic tube that enables
dialysate to enter the abdomen for blood filtration purposes. The
catheter is generally installed via outpatient surgery, as it is an
invasive procedure.
However, CMS has heard concerns from numerous stakeholders about
their ability to effectively get PD catheters installed in
beneficiaries who may be otherwise interested in home dialysis. These
stakeholders reported a variety of issues related to PD catheter
placement, including the lack of availability of vascular surgeons to
perform PD catheter placements, lack of appropriate operating room
time, and a lack of training on PD catheter placement for vascular
surgeons.\287\ As many stakeholders have pointed out, the lack of
timely PD catheter placement is a key barrier preventing many
beneficiaries from being able to use PD as a dialysis modality.
---------------------------------------------------------------------------
\287\ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2924406/#B38.
---------------------------------------------------------------------------
Based on these issues, we seek feedback about how CMS can test and
[[Page 36396]]
use Medicare payment policy, under the ETC model, to promote placement
of PD catheters. Specifically, we are seeking feedback on the following
questions:
What are the key barriers to increased placement of PD
catheters?
How can CMS promote placement of PD catheters in a more
timely manner?
Should the Innovation Center use its authority to test
alternative payment structures to address the barriers to PD catheter
placement as a part of the ETC Model? If so, why and how?
2. Beneficiary Experience Measure
The ETC Model uses two ESRD facility quality measures; Standardized
Mortality Ratio (SMR) (NQF #0369) and Standardized Hospitalization
Ratio (NQF #1463). Both measures are currently calculated and displayed
on Dialysis Facility Compare, a public reporting tool maintained by
CMS. Because data collection and measure reporting are ongoing through
claims, there is no additional burden to ETC Participants.
In the Specialty Care Models proposed rule, we considered including
the In-Center Hemodialysis (ICH) Consumer Assessment of Healthcare
Providers and Systems Survey (CAHPS)[supreg] survey to monitor
beneficiary perceptions of changes in quality of care as a result of
the ETC Model (84 FR 34565). However, the ICH CAHPS survey includes
only beneficiaries who receive in-center dialysis, and specifically
excludes the two beneficiary populations that the ETC Model focuses on:
Beneficiaries who dialyze at home and beneficiaries who receive
transplants.
We are considering the inclusion of a measure to capture the
beneficiary experience of home dialysis care. The measure could be
either an existing measure or one that CMS would develop. The measure
could assess any aspect of the patient experience. The domains could
include, but are not limited to, patient satisfaction, patient
activation, and quality of life. If a new measure is developed, CMS
would like to make it useful to other CMS kidney disease programs.
We seek comments on any aspect of a patient experience measure.
Questions to consider include:
What domains of a patient experience of care with home
dialysis would be the most useful to assess and why?
Would you prefer the measure to be newly developed or an
update to an existing measure? If an update, which existing measure
should be updated?
How would a patient experience measure be best used to
further the purpose of the ETC Model?
How should CMS use a patient experience measure to assess
the quality of care of beneficiaries?
How should CMS use a patient experience measure to
incentivize improved quality of care in the ETC Model and/or for other
CMS programs?
While we will not be responding to specific comments submitted in
response to this Request for Information, CMS intends to use this input
to inform our future quality measure efforts.
CMS is considering publishing the quality outcomes for the ETC
Model. While we seek comments on any aspect of reporting quality data,
we specifically want input on the following:
What is the frequency with which CMS should disseminate
the results?
What should be the unit of analysis for the reported data?
VI. Requests for Information
This section addresses several requests for information (RFIs).
Upon reviewing the RFIs, respondents are encouraged to provide
complete, but concise responses. These RFIs are issued solely for
information and planning purposes; RFIs do not constitute a Request for
Proposal (RFP), application, proposal abstract, or quotation. The RFIs
do not commit the United States (U.S.) Government to contract for any
supplies or services or make a grant award. Further, CMS is not seeking
proposals through these RFIs and will not accept unsolicited proposals.
Responders are advised that the U.S. Government will not pay for any
information or administrative costs incurred in response to this RFI;
all costs associated with responding to these RFIs will be solely at
the interested party's expense. Failing to respond to either RFI will
not preclude participation in any future procurement, if conducted.
Please note that CMS will not respond to questions about the policy
issues raised in these RFIs. CMS may or may not choose to contact
individual responders. Such communications would only serve to further
clarify written responses. Contractor support personnel may be used to
review RFI responses. Responses to these RFIs are not offers and cannot
be accepted by the U.S. Government to form a binding contract or issue
a grant. Information obtained because of this RFI may be used by the
U.S. Government for program planning on a non-attribution basis.
Respondents should not include any information that might be considered
proprietary or confidential. All submissions become U.S. Government
property and will not be returned. CMS may publically post the comments
received, or a summary thereof.
A. Informing Payment Reform Under the ESRD PPS
Over the last several years, CMS, in conjunction with its
contractor, has been conducting research, including holding three
technical expert panels (TEPs), to explore possible improvements to the
ESRD payment model. Additionally, in the CY 2020 ESRD PPS proposed rule
(84 FR 38398 through 38400), CMS invited further comment on a number of
topics, including expanding the outlier policy to include composite
rate drugs, laboratory tests and supplies; reporting the length of each
dialysis session directly on the ESRD claim; patient characteristics
which contribute significantly to the cost of dialysis care; and
improving the quality of facility-level data as reflected in the
Medicare cost report. Stakeholders have asked CMS to explore a refined
case-mix adjustment model for the ESRD PPS, stating that the existing
case mix adjustors may not correlate well with the current cost of
dialysis treatment.
Under section 632(b) of ATRA, as amended by section 217(a) of PAMA
and section 204 of the ABLE Act, oral-only drugs cannot be incorporated
into the ESRD PPS bundled payment until January 1, 2025. In order to
provide payment for oral-only renal dialysis service drugs and
biologicals under the ESRD PPS beginning January 1, 2025, as provided
in 42 CFR 413.174(f)(6), we will need to propose refinements to the
payment system through notice-and comment rulemaking. A refinement
involves revising the patient and facility-level adjustments by
changing the adjustment payment amounts based on updated regression
analysis using more recent ESRD claims and cost report data. When
refinements occur, due to the nature of regression analysis, all
patient-level and facility-level adjustments are affected which can
impact budget neutrality requirements and impact ESRD facilities
differently than if adopted incrementally. Payment system changes can
also require extensive efforts by CMS and health care providers to
implement. Consequently, we believe CMS and ESRD facilities would best
be served if these major payment methodology changes occur as a unified
approach for CY 2025.
In order to obtain additional feedback from as wide of an audience
as possible, we are soliciting comments from the
[[Page 36397]]
public through this proposed rule. We are seeking comments from all
perspectives, including differing beneficiary populations of ESRD
facilities and ESRD facilities located in remote locations and their
infrastructure issues. Obtaining a variety of perspectives enables CMS
to ultimately work toward an improved payment methodology for the ESRD
PPS that is both patient-data focused and accounts for the changing
landscape in providing renal dialysis services to Medicare
beneficiaries.
We encourage the public, and all stakeholders to provide comments
and recommend approaches that will assist CMS in making refinements to
the ESRD PPS through rulemaking in the future. We are soliciting
comments this year so that we have time to consider them for potential
proposals in the CY 2023 ESRD PPS proposed rule for a CY 2025
implementation.
B. Technical Expert Panels (TEPs)
CMS' contractor held three TEPs to discuss refinements to the ESRD
PPS. The TEPs included panelists representing dialysis providers,
independent researchers, patient advocates, and representatives from
professional associations and industry groups. The first TEP held in
2018 explored the components of the existing ESRD PPS, and identified
limitations of the current model. The TEP discussed topics such as
current measures of ESRD PPS costs, costs associated with length of
dialysis treatment, variations in cost associated with complex
patients, facility level drivers of cost, and additional patient
attributes necessary for developing a revised ESRD payment model. One
of the main goals of the TEP was to identify items and services
potentially appropriate for either itemized data collection on claims
or improved reporting on the cost reports. The second TEP held in 2019
elaborated on the previous TEP's themes and focused on alternative
approaches to measuring the cost of a dialysis session to better
reflect treatment-level variation in cost. Topics included measurement
of costs for determining case-mix adjustments, wage index, low volume
payment adjustments and rural adjustments, TDAPA, outlier
determinations, TPNIES, and home dialysis. The third TEP held in 2020
focused on aspects of the ESRD PPS for which refinements or
enhancements were being considered. The topics discussed included adult
and pediatric case-mix adjustments, low volume payment adjustments, the
acute kidney injury payment system, and cost report revisions.
During each TEP, the data contractor presented to the panelists,
and the panelists presented to all the TEP participants, innovative
methodological approaches that addressed stakeholder concerns about the
current payment model and presented alternative approaches with the
goal of soliciting specific input for developing a more refined case-
mix adjusted payment system. Panelists discussed potential approaches
while weighing the ESRD facility burden those approaches may require.
Alternative approaches were presented to solicit feedback from
panelists about feasibility and acceptability of the options. The TEPs
did not provide formal recommendations, but discussion items and
suggestions were captured in three subsequent reports. The materials
from the TEPs and summary reports can be found at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/ESRDpayment/Educational_Resources.
The following sections of this RFI provide information and solicit
feedback specifically on the following topics: Low-volume payment
adjustment (LVPA), calculations for case-mix adjustment, the
calculation for the outlier payment adjustment, the current pediatric
dialysis payment model, recommendations for ESRD PPS and hospital cost
report modifications, recommendations for modifying the pediatric cost
report, and home dialysis for Medicare beneficiaries with acute kidney
injury. While TEP discussions are noted in each section, CMS encourages
the public to reference the TEP reports on CMS' website, noted above,
for more details.
C. Calculation of the Low-Volume Payment Adjustment (LVPA)
1. Background on the LVPA
Section 1881(b)(14)(D)(iii) of the Act provides that the ESRD PPS
``shall include a payment adjustment that reflects the extent to which
costs incurred by low-volume facilities (as defined by the Secretary)
in furnishing renal dialysis services exceed the costs incurred by
other facilities in furnishing such services, and for payment for renal
dialysis services furnished on or after January 1, 2011, and before
January 1, 2014, such payment adjustment shall not be less than 10
percent.''
In the CY 2011 ESRD PPS final rule (75 FR 49118 through 49125), we
finalized the methodology used to target the appropriate population of
ESRD facilities that were low-volume and to determine the treatment
threshold for those facilities identified. After consideration of
public comments, we established an 18.9 percent adjustment for
facilities that furnish less than 4,000 treatments annually with the
intention of encouraging small facilities to continue providing access
to care.
In the CY 2016 ESRD PPS proposed rule (80 FR 37819), we analyzed
ESRD facilities that met the definition of low-volume under Sec.
413.232(b) as part of the updated regression analysis and found that
the facilities still had higher costs compared to other facilities. A
regression analysis of CYs 2012 and 2013 low-volume facility claims and
cost report data indicated a multiplier of 1.239 percent; therefore, we
proposed an updated LVPA adjustment factor of 23.9 percent in the CY
2016 ESRD PPS proposed rule (80 FR 37819) and finalized this policy in
the CY 2016 ESRD PPS final rule (80 FR 69001). In CY 2019, 332
facilities received the LVPA and using the most recent available data
for CY 2020, the number of facilities receiving the LVPA was 344 as of
April 2021.
2. Current LVPA Methodology
Under Sec. 413.232(b), a low-volume facility is an ESRD facility
that, based on the submitted documentation: (1) Furnished less than
4,000 treatments in each of the 3 cost reporting years (based on as-
filed or final settled 12-consecutive month costs reports, whichever is
most recent) preceding the payment year; and (2) has not opened,
closed, or received a new provider number due to a change in ownership
in the three cost reporting years (based on as-filed or final settled
12-consecutive month cost reports, whichever is most recent) preceding
the payment year.
In addition, under Sec. 413.232(c), for purposes of determining
the number of treatments furnished by the ESRD facility, the number of
treatments considered furnished by the ESRD facility equals the
aggregate number of treatments furnished by the ESRD facility and the
number of treatments furnished by other ESRD facilities that are both
under common ownership with, and 5 road miles or less from, the ESRD
facility in question. In order to receive the LVPA, an ESRD facility
must submit a written attestation statement to its Medicare
Administrative Contractor (MAC) confirming that it meets all of the
requirements specified in Sec. 413.232 and qualifies as a low-volume
ESRD facility. For purposes of determining eligibility for the LVPA,
``treatments'' mean total hemodialysis equivalent treatments (Medicare
and non-Medicare). For peritoneal dialysis patients, one week of
peritoneal dialysis is considered
[[Page 36398]]
equivalent to two hemodialysis treatments (80 FR 68994). Section
413.232(e) imposes a yearly November 1 deadline for attestation
submissions, with a few exceptions where the deadline is December 31.
The November 1 timeframe provides 60 days for a MAC to verify that an
ESRD facility meets the LVPA eligibility criteria (76 FR 70236). The
ESRD facility would then receive the LVPA payment for all the Medicare-
eligible treatments in the payment year. Once a facility is determined
to be eligible for the LVPA, a 23.9 percent increase is applied to the
ESRD PPS base rate for all treatments furnished by the facility (80 FR
69001).
In the CY 2021 ESRD PPS final rule (85 FR 71443), we finalized a
policy to allow ESRD facilities flexibility for LVPA eligibility due to
the COVID-19 PHE. Under Sec. 413.232(g)(4), for purposes of
determining ESRD facilities' eligibility for payment years 2021, 2022,
and 2023, we will only consider total dialysis treatments for any 6
months of their cost-reporting period ending in 2020. ESRD facilities
will attest that their total dialysis treatments for those 6 months of
their cost reporting period ending in 2020 are less than 2,000. The
attestation must further include that although the total number of
treatments furnished in the entire year otherwise exceeded the LVPA
threshold, the excess treatments furnished were due to temporary
patient shifting resulting from the COVID-19 PHE. MACs will annualize
the total dialysis treatments for the total treatments reported in
those 6 months by multiplying by 2.
3. Current Issues and Stakeholder Concerns
ESRD facilities, the Medicare Payment Advisory Commission (MedPAC),
and the Government Accountability Office \288\ have recommended that we
make refinements to the LVPA to better target ESRD facilities that are
critical to beneficiary access to dialysis care in remote or isolated
areas.\289\ These groups have also have expressed concern that the
strict treatment count introduces a ``cliff-effect'' that may
incentivize facilities to restrict their patient caseload to remain
below the 4,000 treatments per year for the LVPA threshold.\290\
---------------------------------------------------------------------------
\288\ http://www.medpac.gov/docs/default-source/reports/jun20_ch7_reporttocongress_sec.pdf?sfvrsn=0.
\289\ https://www.cms.gov/files/document/end-stage-renal-disease-prospective-payment-system-technical-expert-panel-summary-report-april-2021.pdf.
\290\ https://www.cms.gov/files/document/end-stage-renal-disease-prospective-payment-system-technical-expert-panel-summary-report-april-2021.pdf.
---------------------------------------------------------------------------
In addition, we have heard from stakeholders that the eligibility
criteria for the LVPA are very explicit and leave little room for
flexibility in certain circumstances (85 FR 71442). Finally, some view
the attestation process as burdensome to facilities and believe it may
discourage participation by small facilities with limited resources
that would otherwise qualify for the LVPA.\291\ Given these concerns,
we have been asked to consider alternative approaches to the LVPA that
would reduce burden, remove negative incentives that may cause gaming,
and better target facilities that are critical for beneficiary access.
---------------------------------------------------------------------------
\291\ https://www.cms.gov/files/document/end-stage-renal-disease-prospective-payment-system-technical-expert-panel-summary-report-april-2021.pdf.
---------------------------------------------------------------------------
4. Suggestions for Calculating the LVPA
a. Census Tract
During the 2020 ESRD PPS TEP, panelists discussed alternatives to
the current LVPA. One methodology discussed utilized census tracts to
identify geographic areas with low demand, which suggested increased
beneficiary access by incentivizing dialysis organizations to continue
operating facilities in otherwise non-viable locations.\292\ As
discussed during the TEP, an advantage to this approach would be a
shift in the focus from identifying low volume facilities to
identifying geographical areas, specifically census tracts, with low
demand for dialysis.
---------------------------------------------------------------------------
\292\ https://www.cms.gov/files/document/end-stage-renal-disease-prospective-payment-system-technical-expert-panel-summary-report-april-2021.pdf.
---------------------------------------------------------------------------
This census tract methodology often results in a single facility
being the only dialysis provider for a number of miles. The process
would involve dividing the U.S. into geographic areas based on a
reasonable assessment of ESRD beneficiaries' ability or willingness to
travel. Latent demand is then calculated by counting the number of ESRD
beneficiaries near each facility. ``Near'' is defined by driving time
to facilities. Latent demand is calculated by multiplying the number of
beneficiaries near an ESRD facility by average number of treatments for
ESRD beneficiaries. The LVPA threshold is then applied by determining
the threshold of adjusted latent demand. That is, those facilities,
which fall below the threshold are LVPA eligible. The panelists noted
that this methodology appears administratively simple and could
eliminate the burden associated with the LVPA attestation process for
facilities and MACs.
b. Low-Volume and Isolated (LVI) Adjustment
In its June 2020 report to Congress, MedPAC recommended that the
Secretary replace the LVPA and rural adjustment under the ESRD PPS with
a single payment adjustment, a low-volume and isolated (LVI)
adjustment, in an effort to better protect isolated, low-volume ESRD
facilities that are critical to ensure beneficiary access.\293\ A
determination that a facility is low volume and isolated would be based
on that facility's distance from the nearest facility and its total
treatment volume. MedPAC stated that the facilities that would receive
the adjustment would be more appropriately targeted. This methodology
would be accomplished via a single facility-level regression approach
instead of the current two-regression approach utilized by CMS. As an
example of how the LVI adjustment would more directly target isolated,
low-volume dialysis facilities, the TEP compared the current LVPA and
suggested LVI methodologies using 2017 data. In this example, 575
facilities would have been eligible for the LVI verses 1,734 facilities
under the current LVPA and rural adjustment methodology.
---------------------------------------------------------------------------
\293\ http://www.medpac.gov/docs/default-source/reports/jun20_ch7_reporttocongress_sec.pdf?sfvrsn=0.
---------------------------------------------------------------------------
5. Request for Information on Calculating the LVPA
CMS is considering alternative approaches to the LVPA that directly
address stakeholder concerns, and is issuing a request for information
to seek feedback on the approaches suggested above, other alternate
approaches, and support of the current LVPA methodology. We are
soliciting information that will better inform potential future
modifications to the methodology. In addition to any other input the
public wants to provide regarding the LVPA under the ESRD PPS, we are
requesting responses to the following questions.
Should a distinction other than census tract information
be considered?
What criteria should be used to determine the threshold(s)
of adjusted latent demand (in treatment counts) which determine LVPA
eligibility (for example, a threshold of high average cost per-
treatment)?
What are the concerns for facilities that would lose the
LVPA under the LVI methodology?
What are the concerns about the potential for gaming
within the LVI methodology?
[[Page 36399]]
To the extent that the LVI methodology captures more
isolated (and most often rural) facilities, should a separate rural
adjustment be maintained?
D. Calculation of the Case-Mix Adjustments
1. Background on the Case-Mix Adjustments
Section 1881(b)(14)(D)(i) of the Act mandates that the single
payment system under the ESRD PPS implemented by the Secretary ``shall
include a payment adjustment based on case mix that may take into
account patient weight, body mass index, comorbidities, length of time
on dialysis, age, race, ethnicity, and other appropriate factors.'' The
ESRD PPS includes facility-level and patient-level adjustments to the
base rate associated with resource utilization and the cost of
providing dialysis treatment. The goal of case-mix adjustment is to
ensure that payment for a dialysis treatment reflects expected resource
use. Payment adjustments protect access to care for the most costly
beneficiaries by mitigating financial disincentives to providing that
care. The ESRD PPS is a case-mix adjusted, bundled payment model
intended to reflect total treatment costs, which consist of formerly
separately billable costs and composite rate costs (75 FR 49032). As
required by section 1881(b)(14) of the Act, formerly separately
billable services were included in the ESRD PPS bundled payment,
effective January 1, 2011. Refinements to the current case-mix
adjusters were implemented in the CY 2016 ESRD PPS final rule,
effective January 1, 2016, and are currently in use.
2. Current Case-Mix Methodology
The current model uses two equations, including a patient-level
equation for formerly separately billable costs and a facility-level
equation for composite rate costs (75 FR 49083 through 49127). Formerly
separately billable services are itemized on the ESRD Facility claim,
(Type of Bill: 72x) and include injectable drugs and their oral
equivalents plus certain laboratory tests and supplies. Composite rate
services, which are captured on the cost report, constitute
approximately 90 percent of a treatment's cost and include capital,
labor, and administrative costs plus certain drugs, laboratory tests,
and supplies (75 FR 49036; 84 FR 38396). Final case-mix adjusters for
adults are the weighted average of estimated coefficients from these
two equations (that is, patient level and facility level equations).
Weights are the fraction of costs that are composite rate versus
formerly separately billable. The regression equations and weighted
averages are calculated using 2012 through 2013 claims and cost report
data. Case-mix factors in the current model include age categories,
body surface area (BSA), low body mass index (BMI) indicator, onset
status, and comorbidities (that is, pericarditis, gastrointestinal
tract bleeding, hereditary hemolytic or sickle cell anemia, and
myelodysplastic syndrome) (80 FR 68989 through 68992). Facility
adjusters include wage index, low volume status, and rural status (80
FR 68972 and 69001).
3. Current Issues and Stakeholder Concerns
Over the last several years, stakeholders have asked CMS to explore
a refined case-mix adjustment model for the ESRD PPS, arguing that the
existing case-mix adjustors may not correlate well with the current
cost of dialysis treatment. They stated that:
The current adult case-mix adjustors were calculated using
old data (that is, 2012-2013 claims and cost report data);
current adjustors may not align with resource-intensive
patient-level services such as isolation rooms, behavioral issues, or
neurocognitive issues;
apportioned composite rate costs (such as labor and
capital related costs), from the cost reports, used in the case-mix
adjustment are currently only observable at the facility level and do
not include patient or treatment level variations; and
composite rate items are not individually collected on the
claim, resulting in the payment not differentiating between the cost of
hemodialysis verses peritoneal dialysis, which are affected by
different labor and equipment costs.
Other stakeholders raised similar concerns during the TEP meetings.
Additionally, panel members questioned the magnitude/significance of
age, BMI, and BSA coefficients; the validity of taking weighted average
of estimates across the two equations when the joint distribution of
composite rate and formerly separately billable costs is not accounted
for in the case-mix; and logistical challenges in obtaining the
accurate diagnosis and comorbidity data that it is not routinely
reported in the 72x claims.
In a comment letter to the Acting CMS Administrator on July 29,
2016,\294\ MedPAC noted the current ESRD PPS does not have patient-
level variation of composite rate (resource) costs and suggested CMS
move to a ``one-equation model'' (that is, a patient-data focused
model). MedPAC specifically stated that CMS should develop payment
adjustment factors using a single-equation methodology that accounts
for variation in the cost of providing the full PPS payment bundle. CMS
is not currently able to implement this recommendation for the ESRD PPS
because we do not have data on the charges associated with the
components of dialysis treatment costs that vary across patients in the
use of the formerly composite rate services.
---------------------------------------------------------------------------
\294\ http://medpac.gov/docs/default-source/comment-letters/medpac-comment-on-cmss-/proposed-rule-on-the-esrd-prospective-payment-/system-and-the-dmepos-competiti.pdf?sfvrsn=0.
---------------------------------------------------------------------------
4. Suggestions for Allocating Composite Rate Costs
CMS has been carefully studying MedPAC's suggestion to base the
ESRD PPS on a ``one-equation model'' (that is, a patient-data focused
model). CMS has over the years publicly discussed potential changes
with our stakeholders who support a patient-data focused model. For
instance, during the 2018 and 2019 TEP meetings discussions included
using time on machine to address allocation of composite rate costs,
case mix, and patient level adjustments. Time on machine would not be
used to directly adjust payment; rather, it would be used to apportion
composite rate costs (such as labor and capital-related costs) that are
currently only observable at the facility level to the patient or
treatment level for use in the case-mix adjustment. Data on the time on
machine receiving dialysis would allow for a proportionately higher
amount of composite rate costs to be allocated to patients with longer
dialysis treatment times. During the December 2019 TEP, a panelist
indicated that this option would reduce burden since dialysis treatment
time (that is, time on machine) is automatically generated by the
dialysis machine and easily entered into the patient's medical record.
Under this option, a single aggregate number would be reported on each
claim. That number corresponds to the total number of minutes the
beneficiary spent on dialysis during that claim period. A panelist
noted that reporting a single number would minimize provider burden.
Panelists reached consensus that the reporting of actual time on
[[Page 36400]]
machine offered the best solution for capturing patient-level
differences in the cost of dialysis sessions and would be superior to
the current case-mix adjusters.
We included discussions about expanding the data elements, moving
to a patient-data focused model, and the use of time on machine to
determine patient level variation in dialysis treatment costs in the CY
2019 ESRD PPS final rule (83 FR 56963 through 56970) as well as the CY
2020 ESRD PPS proposed rule (84 FR 38396 through 38400) A comment
letter from a large dialysis organization in response to the CY 2019
ESRD PPS proposed rule stated that costs in the remaining category--
wages, salaries, and benefits--account for nearly 40 percent of the
market basket weight. Additionally, the large dialysis organization
noted that these costs represent the majority of expenses associated
with dialysis treatment and will vary by patient because they are
dependent on dialysis treatment times. The large dialysis organization
stated that time on machine was a good proxy for costs in dialysis.
Based on information gathered from our stakeholders and panelists
from the first two TEP meetings and comments received based on RFIs in
the CY 2020 ESRD PPS proposed rule, CMS took steps towards developing a
patient-data focused model. Based on stakeholder input, CMS chose to
utilize time on machine to determine patient level variation in
dialysis treatment costs. In order to collect this information from
ESRD facilities, CMS petitioned the National Uniform Billing Committee
(NUBC) for a new value code for time on machine. This value code allows
CMS to add time on machine to the ESRD claim. In April 2020, NUBC
approved the request. CMS included a requirement to collect time on
machine data effective January 1, 2021 in two technical direction
letters and two Medicare Learning Network articles. CMS later rescinded
the time on machine requirement,\295\ but we are discussing this
potential requirement in this RFI as a possible future refinement of
the ESRD PPS to address allocation of composite rate costs, case mix,
and patient level adjustments.
---------------------------------------------------------------------------
\295\ https://www.cms.gov/files/document/mm11871.pdf.
---------------------------------------------------------------------------
During the 2020 TEP, the data contractor for CMS presented and the
panelists discussed potential refinement to concerns regarding the
current case-mix adjustment. One of the refinements discussed was
collecting time on machine data on the 72x claim using a value code.
Specifically, the suggested method includes the costs per beneficiary-
facility-month which are the sum of formerly separately billable costs,
directly calculated from claims (quantities) and from Part B prices,
and composite rate costs for each beneficiary-facility-month,
calculated by allocating annual facility costs (less formerly
separately billable costs) to the beneficiary-facility-month level
using time on machine (duration of all treatments). For some modalities
and settings, time on machine is not available and must be imputed.
Finally, a regression is run of beneficiary-facility-month costs on
case-mix adjusters and facility characteristics. Following a
presentation by the data contractor, the panelists agreed that this
method would identify a magnitude of factors that best reflect
variation in this measure of total cost per treatment. This method
would select a set of case-mix adjusters that account for a significant
portion of the variance of total costs, subject to intuitive clinical
relationship to dialysis treatment costs, reasonable number of risk
adjusters, easy to diagnose, identify, or report, and not gameable.
Panelists at the TEPs and stakeholder comments received in response
to the CY 2019 ESRD PPS proposed rule believe this one-equation model
is more intuitive than current ESRD PPS case-mix adjusters.\296\ The
suggested case-mix adjusters discussed during the December 2019 and
2020 TEPS are derived relative to variation in total cost of case and
that the change in reporting burden is small and would change claims in
two ways, including reporting total machine reported treatment minutes
and reporting codes for new comorbidities. Finally, stakeholders
believe that a magnitude of case-mix adjusters appears to be
significantly attenuated relative to the existing ESRD PPS adjusters.
As discussed in the TEP Report for the December 2020 TEP,\297\ a budget
neutral implementation of such a system would result in a 5-10 percent
increase in the base rate. Options discussed by the panelists included
the one-equation model and keeping the current ESRD PPS case-mix
adjustments. CMS is seeking feedback from the public on these options
and any additional approaches not yet considered.
---------------------------------------------------------------------------
\296\ https://www.cms.gov/files/document/end-stage-renal-disease-prospective-payment-system-technical-expert-panel-summary-report-april-2021.pdf.
\297\ https://www.cms.gov/files/document/end-stage-renal-disease-prospective-payment-system-technical-expert-panel-summary-report-april-2021.pdf.
---------------------------------------------------------------------------
5. Request for Information on Calculation of the Case-Mix Adjustments
CMS welcomes the opportunity to inform the public and solicit
stakeholder feedback on potential changes to the modeling used to
develop the case-mix payment adjustments under the ESRD PPS, in order
to inform future model refinements. CMS is considering alternative
approaches to calculating the case-mix adjustment that directly address
stakeholder concerns, and more appropriately reflects resource use and
costs, and is issuing this RFI both to seek feedback on the suggested
approach discussed previously, and to solicit information that will
better inform future modifications to this methodology. In particular,
we are soliciting comments on the methodology to collect data to
reflect patient-level differences in composite rate costs, including
the use of a value code to collect time on machine on the claim. In
addition to any other input the public wants to provide regarding the
calculation of the case-mix adjustment, we are requesting responses to
the following questions.
Which of the five composite rate cost components (that is,
age, BSA, BMI, onset of dialysis, comorbidities) are most likely to
vary with treatment duration?
Should new information for these cost components be
collected on cost reports, for use in better inferring the composite
rate costs associated with treatment duration?
What are the advantages and disadvantages of obtaining
treatment duration information from blood urea nitrogen time on
dialysis through the End Stage Renal Disease Quality Reporting System
(EQRS) (our new system that has replaced the Consolidated Renal
Operations in a Web-enabled Network (CROWNWeb)), versus collecting
treatment duration through new fields on claims?
What challenges would be encountered in reporting
treatment duration on claims, using one of the options discussed?
Are there alternative proxies for resource utilization
that can be reported at the patient/treatment level?
E. Calculation of the Outlier Payment Adjustment
1. Background on the Outlier Payment Adjustment
Section 1881(b)(14)(D)(ii) of the Act requires that the ESRD PPS
include a
[[Page 36401]]
payment adjustment for high-cost outliers due to unusual variations in
the type or amount of medically necessary care, including variations in
the amount of ESAs necessary for anemia management. As discussed in
section II.B.1.c of this proposed rule, we recognize that the
utilization of ESAs and other outlier services have continued to
decline under the ESRD PPS, and that we have lowered the MAP amount and
FDL amounts every year under the ESRD PPS. As discussed in the CY 2021
ESRD PPS final rule (85 FR 71439), we acknowledge that, even with
annually adjusting the MAP and FDL to reflect the most recent
utilization and costs of ESRD PPS eligible outlier services, total
outlier payments have not yet reached the 1 percent target.
2. Current Outlier Payment Adjustment Methodology
The current outlier policy was implemented in the CY 2011 ESRD PPS
final rule (75 FR 49134 through 49145) and codified at Sec. 413.237.
Under Sec. 413.237, an ESRD facility will receive an outlier payment
if its actual or imputed Medicare Allowable Payment (MAP) amount per
treatment for ESRD outlier services exceeds a threshold. The MAP amount
represents the average incurred amount per treatment for services that
were or would have been considered separately billable services prior
to January 1, 2011. The threshold is equal to the ESRD facility's
predicted ESRD outlier services MAP amount per treatment (which is
case-mix adjusted) plus the FDL amount, set each year by CMS.\298\ The
predicted outlier service MAP amount is the outlier MAP amount
published by CMS adjusted for the case mix in the payment year; that
is, it is calculated by multiplying the separately billable case mix
multipliers by the outlier MAP amount. The outlier MAP and FDL amounts
are estimated using the most recent, complete data set available, which
are data from 2 years prior to the payment year in question.
---------------------------------------------------------------------------
\298\ The FDL amount is the amount by which an ESRD facility's
per-treatment Medicare allowable payment amount for furnishing ESRD
outlier services to an adult/pediatric beneficiary must exceed the
adult/pediatric predicted ESRD outlier services Medicare allowable
payment amount to be eligible for an outlier payment.
---------------------------------------------------------------------------
The predicted outlier MAPamounts and FDLs create thresholds where,
if the outlier MAP amount per treatment on the claim is above the
threshold, there will be a per-treatment outlier payment equal to 80
percent of the amount exceeding the threshold. The loss-sharing
percentage was set at 80 percent in the CY 2011 ESRD PPS final rule (75
FR 49144) to make it consistent with the loss-sharing percentages in
other Medicare payment systems.
In the CY 2011 ESRD PPS final rule and codified in Sec.
413.220(b)(4), using 2007 data, we established the outlier percentage,
which is used to reduce the per treatment base rate to account for the
proportion of the estimated total payments under the ESRD PPS that are
outlier payments, at 1.0 percent of total payments (75 FR 49142 through
49143).
The policy provides that the following ESRD outlier items and
services are included in the ESRD PPS bundled payment: (1) Renal
dialysis drugs and biological products that were or would have been,
prior to January 1, 2011, separately billable under Medicare Part B;
(2) Renal dialysis laboratory tests that were or would have been, prior
to January 1, 2011, separately billable under Medicare Part B; (3)
Renal dialysis medical/surgical supplies, including syringes, used to
administer renal dialysis drugs and biological products that were or
would have been, prior to January 1, 2011, separately billable under
Medicare Part B; (4) Renal dialysis drugs and biological products that
were or would have been, prior to January 1, 2011, covered under
Medicare Part D, including renal dialysis oral-only drugs effective
January 1, 2025; and (5) Renal dialysis equipment and supplies that
receive the transitional add-on payment adjustment as specified in
Sec. 413.236 after the payment period has ended. Beginning January 1,
2021, calcimimetics became outlier services (85 FR 71405).
In the CY 2011 ESRD PPS final rule (75 FR 49064 through 49065), CMS
explained that it estimates an ESRD facility's costs based on most
recent available data. Since the rulemaking is done in the year prior
to the effective date, the most complete available data would be from
the year before. This means that for CY 2022 (as discussed in section
II.B.1.c of this proposed rule), CMS is proposing to recalibrate the
outlier MAP and FDL amounts for each calendar year using data from 2
years prior, which is the most recent and complete claims data. This
methodology assumes consistent utilization over time, that is, it
assumes that 2020 utilization rates for ESRD PPS outlier items and
services are the same as those for 2018. However, the use of ESRD PPS
outlier items and services has in fact declined each year since the
implementation of the ESRD PPS.
For example, the CY 2020 FDL amount ($48.33 for adult patients) was
calculated and added to the predicted MAP to determine the outlier
thresholds using 2018 data. However, ESRD PPS outlier spending
continued to fall from 2018 to 2020. Consequently, outlier payments for
CY 2020 claims comprised only 0.6 percent of total ESRD PPS payments,
demonstrating that the use of 2018 data results in thresholds too high
to achieve the targeted 1.0 percent outlier payment. Outlier payments
for the adult population have constituted less than 1.0 percent of
total ESRD PPS payments since such payments began in 2011.\299\
---------------------------------------------------------------------------
\299\ Outlier percentages for the pediatric population have high
variability from year to year, but have consistently met or exceeded
the 1.0 percent target. The methodological modifications in this RFI
do not apply to the pediatric population.
---------------------------------------------------------------------------
3. Current Issue and Stakeholder Concerns
As the outlier payments have consistently landed below the targeted
1.0 percent of total ESRD PPS payment threshold, stakeholders have
noted that the methodology currently used to calculate the outlier
results in underpayment to the providers, as money was removed from the
base rate to balance the outlier payment (85 FR 71409, 71438 through
71439; 84 FR 60705 through 60706; 83 FR 56969). Therefore, they have
urged us to adopt an alternative modeling approach, one that accounts
for declining trends in outlier-eligible items and services spending
over time. MedPAC echoed these concerns in a comment letter in response
to the CY 2021 ESRD PPS proposed rule, where it also suggested that the
introduction of calcimimetics as outlier-eligible items could
perpetuate the pattern of underpayment. MedPAC stated that if
calcimimetic use decreases between 2019 (when the products were paid
under the ESRD PPS using the TDAPA) and 2021 (when the products will be
paid as part of the ESRD PPS base rate), the outlier threshold will be
set too high, and outlier payments will be lower than the 1 percent of
total 2021 payments.
4. Suggestions for Outlier Payment Adjustment
During the second and third annual TEP meetings convened by the CMS
contractor in 2019 and 2020, panelists discussed concerns regarding the
current outlier adjustment policy and alternative methodologies to
achieve the 1 percent outlier target. Some TEP panelists and
stakeholders have strongly advocated that we establish a new outlier
threshold using alternative modeling approaches that account for trends
in separately billable spending over time. Overall, panelists expressed
support for any change to outlier calculations that result in total
outlier payments closer to the target.
[[Page 36402]]
Panelists noted that the underlying basis of an alternative
methodology could be to re-examine the assumption of constant
utilization over time. Unlike the current outlier methodology that
predicts FDL amounts using a single year of claims data, this approach
allows for the modeling of the MAP amounts as they change over a longer
period of time. CMS has received a number of suggested techniques that
could be employed to reach the 1.0 percent target more predictably.
One of these suggestions is a calculation of ``after the fact''
FDLs that would achieve the 1.0 percent outlier target for each year
included in the FDL calculation. This has been referred to as the
retrospective FDL, which would be lower than the FDLs published in the
final rule for each corresponding year. This calculation would be used
for future outlier calculations. For more information, please refer to
the TEP reports here: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/ESRDpayment/Educational_Resources.
Data presented during the TEP meeting showed that using the three
most recent years to simulate FDLs and outlier payments for 2020
resulted in an FDL amount for adults of $33.83 and a MAP amount of
$37.41, respectively. By contrast, the 2020 FDLs and MAPs published in
the CY 2020 ESRD PPS final rule (84 FR 60649) were $48.33 and $35.78,
respectively. The simulated outlier percentage for 2020 using the
alternative methodology was 0.8 percent. The actual outlier payment
percentage made for 2020 claims was 0.6 percent. Therefore, the
alternative methodology results in an outlier percentage that is closer
to the 1.0 percent target in the adult population.
6. Request for Information
CMS is considering potential revisions to the calculation of the
outlier threshold to address stakeholder concerns, and is issuing a
request for information both to seek feedback on the approach suggested
above, and to solicit information that will better inform future
modifications to the methodology. In addition to any other input the
public wants to provide for calculating the outlier payment adjustment,
we are requesting responses to the following questions.
An alternative approach could be to estimate the
retrospective FDL trend by using historical utilization data. The
example above was constructed by using 2016-2018 data. There is
flexibility in the time used to estimate this trend. The data must
contain at least 2 years' worth of claims data and may begin as early
2011. Additionally, it must end with the most recent year with complete
data (typically 2 years before the year in which the FDL will take
effect).\300\
---------------------------------------------------------------------------
\300\ The example uses CY 2020 to judge the performance of the
alternative methodology. The most recent year with complete data
when the 2020 FDL was determined was 2018.
---------------------------------------------------------------------------
++ How many years of data should be included in calculation of this
trend to best capture changes in treatment patterns?
The simulation of the FDL can be improved by better
anticipating changes in utilization of ESRD outlier services. What are
the factors that affect the use of ESRD outlier services over time, and
to what extent should CMS try to forecast the effect of these factors?
ESRD beneficiaries can now choose to enroll in Medicare
Advantage.
++ Please describe any anticipated effects of this enrollment
change on the use of ESRD outlier services in the ESRD PPS.
Adoption of the suggested methodology may account for
systematic changes in the use of high-cost outlier items. However,
inherently unpredictable changes may still push the outlier payment off
the 1.0 percent target.
++ Please comment on the acceptability of the below payment
adjustment methods.
++ Payment reconciliation--in the form of an add-on payment
adjustment or a payment reduction--might be necessary to bring payments
in line with the 1 percent target.
++ An add-on payment adjustment would be distributed after
sufficient data reveal the magnitude of the deviation (1 year after the
end of the payment year). The distribution of these monies could be
done via a lump sum or via a per-treatment payment add-on effective for
1 year. This add-on payment adjustment would be paid irrespective of
the outlier claim status in that year.
++ A payment reduction could take the form of a reduction in the
base rate, also to be applied 1 year after the end of the payment year.
F. Calculation of the Pediatric Dialysis Payment Adjustment
1. Background on the Pediatric Dialysis Payment Adjustment
Section 1881(b)(14)(D)(iv)(I) of the Act provides that the ESRD PPS
may include such other payment adjustments as the Secretary determines
appropriate, such as a payment adjustment for pediatric providers of
services and renal dialysis facilities. Below we discuss the current
ESRD PPS with regard to ESRD facilities that furnish renal dialysis
services to pediatric patients, and request information on specific
approaches as well as other topics related to developing a pediatric
payment adjustment under the ESRD PPS.
Prior to implementation of the ESRD PPS, payment for dialysis
treatments was made through a composite rate per treatment that was
based on cost report data and did not account for differences among
patients with ESRD (48 FR 21254). The initial payment rates were
established at $127 per treatment for independent facilities and $131
for hospital-based facilities, which reflect the costs incurred by
dialysis facilities furnishing outpatient maintenance dialysis,
including some routinely provided drugs, laboratory tests, and
supplies, whether furnished by hospital-based and independent
facilities in a facility or at home.
In addition, we provided a process under which facilities with
costs per treatment in excess of their composite rates could seek
exceptions to those rates under specified circumstances in Sec. Sec.
413.182 and 413.184. For example, when a substantial proportion of the
facility's outpatient maintenance dialysis treatments involve
atypically intense dialysis services, special dialysis procedures, or
supplies necessary to meet special medical needs of the facility's
patients could qualify for an exception rate. Under Sec. 413.182, CMS
could approve exceptions if the facility demonstrates, by convincing
objective evidence, that its total per treatment costs are reasonable
and allowable under the relevant cost reimbursement principles of part
413 and that its per treatment costs in excess of its payment rate are
directly attributable to its patient mix. As a result of these
provisions, many pediatric facilities secured an exception rate and
were paid the exception rate until the transition to the ESRD PPS ended
in CY 2014.
Section 1881(b)(12) of the Act, added by section 623(d) of the
Medicare Prescription Drug, Improvement, and Modernization Act of 2003
(MMA) required the Secretary to implement a basic case-mix adjustment
to an ESRD facility's composite payment rate reflecting a limited
number of patient characteristics. On August 5, 2004 and November 15,
2004, we published a proposed rule and final rule with comment period
(69 FR 47487 through 47730 and 69 FR 66235 through 66915),
respectively, implementing the provisions affecting the composite
payment system. The development and
[[Page 36403]]
application of the basic case-mix adjustments, using regression-based
adjustment factors for the patient variables of age, BSA and BMI are
explained in each of those rules (69 FR 47529 through 47531 and 69 FR
66323 through 66324, respectively). The product of the specific
adjusters for each patient, multiplied by the otherwise applicable
composite payment rate, yielded the basic case-mix adjustment as
required by statute. The basic case-mix adjusted composite payment
system was effective April 1, 2005 and continued until the ESRD PPS was
implemented on January 1, 2011.
As we explained in the CY 2005 ESRD PPS final rule with comment
period (69 FR 66326 through 66327), we attempted to develop case-mix
adjusters for outpatient patients with ESRD under age 18. However, we
found that for the approximately 600 Medicare pediatric patients for
whom claims were available from 2000 through 2002, the results were
highly variable and statistically unstable, and therefore,
inappropriate for the development of case-mix adjusters in accordance
with the same methodology otherwise applicable to adult Medicare
patients with ESRD.
For this reason, we described an alternative methodology we used to
develop a 62 percent pediatric increase (that is, an adjustment factor
of 1.62) applied to the composite payment rate per treatment for any
facility furnishing outpatient dialysis services to pediatric patients.
That factor was based on the average amount of the atypical services
exceptions granted for 20 ESRD facilities, each of which sought and
received an exception for the atypical costs incurred for the treatment
of outpatient pediatric patients, compared to the average unadjusted
composite payment rate (that is, the payment without regard to
exception amounts) for these same 20 facilities. We explained that
application of the pediatric adjustment factor of 1.62 in lieu of an
explicit pediatric case-mix adjustment was temporary, and would be
eliminated once an appropriate methodology, preferably one applicable
to both pediatric and adult Medicare patients, could be developed.
In the CY 2011 ESRD PPS proposed rule (74 FR 49986 through 49987),
we proposed a pediatric payment methodology with comorbidity adjusters.
However, in the CY 2011 ESRD PPS final rule (75 FR 49130 through
49134), in response to public comments, we explained that instead of
using the regression-based composite rate multiplier of 1.199, we
established the pediatric payment adjusters using the overall
difference in average payments per treatment between pediatric and
adult dialysis patients for composite rate services in CY 2007 based on
the 872 pediatric dialysis patients reflected in the data. That is, the
average CY 2007 MAP for composite rate services for pediatric dialysis
patients was $216.46, compared to $156.12 for adult patients. We used
CY 2007 data consistent with our determination that 2007 represented
the year with the lowest per patient utilization of dialysis services
in accordance with section 1881(b)(14)(A)(ii) of the Act. We developed
payment adjusters using the variables of age (that is, <13 and 13-17)
and modality (peritoneal dialysis or hemodialysis).
In the CY 2016 ESRD PPS final rule (80 FR 68968), we refined the
ESRD PPS in accordance with section 632(c) of ATRA, which required CMS
to conduct an analysis and make appropriate revisions to the case mix
payment adjustments. We analyzed the case-mix payment adjustments under
the ESRD PPS and revised the payment adjusters using CYs 2012 and 2013
ESRD claims and cost report data. For pediatric dialysis, we used the
same methodology that was used for the CY 2011 ESRD PPS final rule,
except for the use of more recent data years (2012 through 2013) and in
the method of obtaining payment data. Specifically, we used the
projected MAP based on 2013 claims to calculate the ratio of pediatric
total MAP per session to adult total MAP per session. The resulting
adjustment factors reflected an 8.21 percent increase to account for
the overall difference in average payments per treatment for pediatric
patients. The pediatric adjusters that were finalized for CY 2016 and
are currently in effect are:
<13 peritoneal dialysis = 1.063
<13 hemodialysis = 1.306
13-17 peritoneal dialysis = 1.102
13-17 hemodialysis = 1.327
2. Current Issues and Stakeholder Concerns
Since 2015, we have continued to hear from organizations associated
with pediatric dialysis about the undervaluation of pediatric ESRD
care, which requires significantly different staffing and supply needs
from those required to deliver ESRD care to adults. These organizations
support CMS efforts to explore ways to improve collecting pediatric-
specific data to better characterize the necessary resources and
associated costs of delivering pediatric ESRD care. Commenters have
also suggested that we reinstate the exceptions process that would
provide individual hospitals and ESRD facilities with their own payment
rate based on their costs. We note that this approach would require a
statutory change because section 1881(b)(14)(A)(i) of the Act requires
the Secretary to implement a payment system under which a single
payment is made to all ESRD facilities.
Stakeholders have informed us that costs unique to pediatric
dialysis are not adequately captured in current cost reports or claims,
and therefore are not accounted for in the pediatric adjustments. In
addition, they have explained that pediatric dialysis often requires
developmental and behavioral specialists, pediatric dieticians, and
social workers, and that pediatric comorbidities require unique
specialized care. Further, pediatric nephrologists have told CMS that
pediatric patients disproportionately receive treatment in hospital-
based facilities, but the hospital cost report (CMS Form 2552-10) does
not distinguish pediatric and adult dialysis cost.
One organization suggested that we expand the pediatric age groups
and create either pediatric modifiers or a pediatric add-on payment by
age group. Alternatively, the organization suggested that we create a
pediatric-specific ESRD bundle that would allow for full accounting of
costs for pediatric staffing and specialized equipment, and the
economic implications of pediatric medical comorbidities that are not
addressed in the current PPS. In order to engage dialysis stakeholders
in advance of rulemaking, CMS' data contractor conducted TEP
discussions for the past three years on various dialysis payment
approaches and issues. For the 2020 TEP, one of the discussion topics
was pediatric dialysis. Based on discussions and meetings with
stakeholders and TEP panelists, the contractor performed several
analyses on pediatric dialysis to inform the TEP discussion. The
analyses confirmed many of the challenges reflected in stakeholder
comments regarding pediatric dialysis.
For example, a small number of facilities provide 95 percent of
pediatric dialysis treatments (approximately 100) and those pediatric
facilities are hospitals, mostly children's hospitals. Pediatric
treatments are split between home peritoneal dialysis (mostly for
children younger than 13) and in-center hemodialysis (for older
children 13-17). One analysis, using cost report data, found that the
median registered nurse/licensed practical nurse hours per-treatment is
higher in pediatric facilities and pediatric comorbidities require more
(specialized) staffing. Dialysis for
[[Page 36404]]
pediatric patients is furnished in hospitals, primarily children's
hospitals or in large dialysis organization facilities. For more
information, please refer to the TEP reports.
The contractor performed analyses using the expanded age groupings
suggested by the commenters and found that finer stratification of the
age groups reveals differences in cost per treatment. The contractor
found that the median cost per treatment for the pediatric population
using the same methodology used in the 2016 refinement but using more
recent data (2018 and 2019) resulted in significant differences in cost
among the pediatric age categories. The contractor also found that the
median cost per treatment for the pediatric population using the
national average treatment duration, the relationship between total
cost per-treatment and age is consistent with stakeholder comments.
3. Suggestions for the Pediatric Dialysis Payment Adjustment
During the December 2020 TEP, three approaches were discussed among
the panelists that could potentially lead to a more accurate estimate
of pediatric dialysis costs under a revised payment model: (1) The
addition of pediatric-specific case-mix adjustment multipliers; (2) the
creation of a separate payment bundle for pediatric ESRD treatment
costs; and (3) revisions to current data collection practices.
To illustrate how the refined model would incorporate the pediatric
population, the contractor applied the model using each of the two
current age groupings, resulting in an increased effect of age on
costs, with multipliers of 1.61 and 1.74 for age <13 years and age 13
to 17 years, respectively, compared to the reference adult population.
Please refer to the TEP report \301\ for more specific information on
the analyses and discussion.
---------------------------------------------------------------------------
\301\ https://www.cms.gov/files/document/end-stage-renal-disease-prospective-payment-system-technical-expert-panel-summary-report-april-2021.pdf.
---------------------------------------------------------------------------
Stakeholders suggest that the variables affecting pediatric
dialysis costs are sufficiently different from those associated with
adult dialysis costs, and that a separate payment system may be
warranted. Although the creation of a pediatric bundle or separate
pediatric ESRD PPS may improve cost estimates for the pediatric
population, if there were a statutory change to authorize this separate
payment system, the time required for implementation would be
substantial due to the subsequent need for new, pre-implementation data
collection, which providers may find burdensome.
The TEP panelists also discussed several modifications to the cost
reports that they believe would better capture resources utilized in
the pediatric dialysis setting. These include adding lines itemizing
pediatric specific labor categories and pediatric specific supplies,
clarifying cost report instructions as they pertain to pediatric
dialysis, and better aligning the freestanding facility cost report
with the hospital cost report. Although these changes have the
advantage of being highly feasible to implement, stakeholders have
noted that uptake may take additional time, as pediatric facility
accounting and billing staff are not generally familiar with Medicare
cost reports. Furthermore, stakeholders have noted that changes to the
freestanding facility cost report would be of limited value, since
pediatric dialysis primarily takes place in hospital-based facilities.
Panelists generally favored the addition of pediatric case-mix
adjustment multipliers. One panelist noted that prior to the current
case-mix adjustment; the multiplier applied to pediatric facilities was
based on actual costs incurred during treatment that were more accurate
than the costs being reported currently. The case-mix adjustment
multipliers presented during the TEP were similar to the multipliers
from the prior payment method, which the panelist found encouraging.
However, there was shared concern among TEP panelists that there
will continue to be underpayment for pediatric dialysis patients. One
panelist noted that time on dialysis may not accurately reflect all
costs, and may be especially misleading for those under 2 years of age.
For this patient population, expenditures on some fixed costs (for
example, dialysate) will decrease, but staffing costs would be
considerably higher, as they require one-on-one nursing and child life
specialists and are more difficult to initiate on dialysis. Therefore,
panelists expressed the concern that the multipliers based on duration
of treatment would not accurately reflect costs. Another panelist noted
that certain state laws with personnel requirements for pediatric
dialysis could also increase costs.
Panelists supported moving forward with the cost report and case-
mix multiplier modifications due to the burden of implementing a new
bundle. One panelist noted that a time and motion study attempted by
their dialysis organization failed, as there was a high degree of
variation among facilities. However, another panelist described their
facility's success in securing additional funding for their pediatric
dialysis unit as a result of a time and motion study.
Panelists affirmed that accounting and billing departments at
children's hospitals are not well equipped to accurately complete
Medicare cost reports and suggest that this may be due both to their
general lack of familiarity with Medicare (one panelist noted that only
30 percent of pediatric patients are Medicare beneficiaries) and the
cost report's current structure.
One panelist cautioned that because most pediatric dialysis is
delivered in the hospital setting, if the revised hospital cost report
does not include the modifications recommended for the dialysis
facility's cost report, pediatric expertise for dieticians, social
workers, child life specialists, and behavioral specialists may remain
overlooked. Despite this, panelists expressed the desire to move
forward with the suggested cost report modifications to improve
pediatric payment, which is presented later on in the preamble in
section VI.H of this proposed rule.
4. Request for Information for Pediatric Dialysis Payment
CMS is soliciting feedback from the public on pediatric dialysis
payment. In addition to any other input the public wants to provide for
the pediatric dialysis payment adjustment, we are requesting responses
to the following questions.
Does the magnitude of total costs and pediatric
multipliers reflect ESRD facilities' actual incurred costs? If not,
what specific costs are not being reported on claims and/or cost
reports?
Is there sufficient variation in composite rate costs
among pediatric patients to justify use of a proxy to distribute
facility-level composite rate costs to individual treatments?
If duration of treatment is not a valid proxy for
composite rate costs per treatment, what are alternative proxies to
consider?
What, if any, are the specific concerns about
incorporating pediatric patients into the estimation of multipliers for
both the adult and pediatric populations?
What are the issues facing pediatric billing and
accounting staff with regard to completion of claims and cost reports?
How can these problems be remedied?
Are there additional costs factors for pediatric patients
that are not adequately captured on the 72X claim?
[[Page 36405]]
G. Modifying the ESRD PPS and Hospital Cost Reports
1. Special Audit Adjustment Summary
a. Background
Throughout the years, we have received comments about updating the
Medicare Renal Cost Reports (CMS-Form-265-11). Data from the Medicare
Renal Cost Reports is received by the Hospital Cost Report Information
System (HCRIS). Stakeholders have asserted that the cost reports need
more granularity to align resource use with payment. In addition,
section 217(e) of PAMA mandated an audit of Medicare cost reports
beginning during 2012 for a representative sample of providers of
services and renal dialysis facilities furnishing renal dialysis
services. The following discusses CMS's audit process and findings.
Organizations that consist of multiple ESRD facilities or business
entities may have Home Offices that furnish central management and
administrative services (for example, centralized accounting,
purchasing, personnel services, and management) to other organizations
within the chain. To the extent that the Home Office furnishes services
related to patient care to a provider, the reasonable costs of such
services are included in the ESRD facility's cost report and are
reimbursable as part of the ESRD facility's costs. The CMS' Office of
the Actuary (OACT) selected a sample of 1,479 freestanding ESRD
facilities from five Home Offices of large dialysis organizations for
the cost audit. A contractor performed cost audits of these ESRD
facilities in September of 2015. All audits were completed by September
of 2018.
Upon completion of the audits, adjustments for unallowable costs
were made by CMS's Office of Financial Management to the ESRD cost
reports and reflected in the HCRIS data. As of March 2020, 1,395 of the
1,479 ESRD facilities had complete HCRIS data (that is, containing both
pre-and post-audit information). A summary of the audit adjustments
include Home Office costs, drugs, and treatments, which are discussed
in this section.
b. Home Office Cost
Of the ESRD facilities sampled, 1,278 of 1,479 received an
allocation of Home Office costs from the five Home Offices selected for
review. Any adjustments of unallowable Home Office costs would flow
down and be reflected in the ESRD facilities' cost reports.
c. Adjustments
Using the HCRIS data, of the 1,395 ESRD freestanding facilities
analyzed, a total of $147.5 million of unallowable costs were removed
from the total costs reported on Worksheet A. Noteworthy adjustment
areas included $136.5 million of the unallowable costs initially
reported in the administrative and general cost center on Worksheet A,
with $75 million of this $136.5 million pertaining to related-party
adjustments recorded on Worksheet A-3. Of the $75 million, $72 million
were for Home Office costs, including disallowed related party costs
associated with Home Office and management fee adjustments. Some of the
major adjustments noted at the Home Office level reviews included the
following: Unsupported documentation; related-party management fees;
lobbying expense; taxes for items not related to patient care;
executive compensation in excess of reasonable guidelines, and related
party laboratory costs, which were reduced to cost. Other certain non-
allowable items included: Advertising, legal fees interest expense and
financing fees, corporate travel/lodging/relocation, various consulting
fees, business development expenses; insurance settlement payments;
insurance expenses (malpractice, etc.).
d. Drugs
In general, there were minimal adjustments to drugs cost and these
were made to both drug expense and drug rebates (<1.0 percent in
aggregate). The top five ESRD dialysis organizations were examined
based on total reimbursable cost and average cost per treatment for
adult hemodialysis (the most common treatment type). No material
adjustment was made to total number of treatments. However, there was a
significant decrease in the average cost per treatment because of
material adjustments made to the total allowable costs. The number of
Epoetin Units furnished during the Cost Reporting Period (reported on
Worksheet S-1, Line 14) was reduced by approximately 13 percent in
aggregate. However, the majority of these adjustments related to two
specific facilities, with one of the facilities having the total amount
reported reduced to zero. The number of Aranesp Units furnished during
the cost reporting period (reported on Worksheet S-1, Line 15) was
reduced by approximately 18 percent in aggregate. However, the majority
of these adjustments related to two specific facilities, both of which
were reduced to zero.
e. Treatments
The total number of treatments not billed to Medicare and furnished
directly (Worksheet S-1, Line 1) decreased by an average of 2.6
percent. However, the total number of treatments not billed to Medicare
and Furnished under Arrangement (Worksheet S-1, Line 2) had no change.
The average cost per treatment among the various types of treatments
and categories appears to have decreased by an average of 1.75 percent.
However, some of the adult average costs per treatment related to home
program continuous ambulatory peritoneal dialysis increased after the
audit by an average of 1.5 percent.
Based on this audit, our cost report data was corrected.
2. Suggestions for Modifying the ESRD PPS and Hospital Cost Reports
a. Independent Dialysis Facility Cost Report
During the 2020 ESRD PPS TEP, the data contractor engaged the
panelists in a discussion regarding potential revisions to the
Independent Dialysis Facility Cost Report (CMS Form 265-11). (See
https://www.cms.gov/Research-Statistics-Data-and-Systems/Downloadable-Public-Use-Files/Cost-Reports/Renal-Facility-265-2011-form.) These
potential revisions, which would support the efforts to develop a
refined case-mix model for the ESRD PPS, are described in this section.
CMS seeks input from the public on the feasibility of implementing
these suggestions in freestanding ESRD facilities. These potential
reporting changes would require facilities to allocate composite rate
costs across settings and modalities. Taken together, the resulting
cost report data would enable the determination of variation in costs
across patient types (by risk groups and dialysis modalities).
In the CY 2020 ESRD PPS proposed rule (84 FR 38396 through 38400)
CMS sought input on identifying components of composite rate costs,
including specific facility-level costs that, in combination with
treatment-level data, could be used to understand variation in dialysis
treatment costs across patients. While composite rate costs constitute
nearly 90 percent of total treatment costs, they are not itemized on
claims, leaving facility cost reports as the only source of information
on these costs. Commenters' suggestions included adding detail and
stratifying the reporting detail of selected composite rate costs by
setting and modality and providing additional data to determine
variation in treatment costs across patient risk groups and treatment
modalities.
[[Page 36406]]
The facility-level cost components of interest include capital
costs related to dialysis machines and other equipment used in dialysis
treatment, labor costs, and supply costs. Based on the input received
and further analysis conducted by the data contractor, several specific
changes to the cost reports were suggested. These include changes in
the reporting of composite rate components: (1) Capital costs for
dialysis machines and related equipment, (2) direct patient labor
costs, (3) administrative and managerial costs, and (4) differentiation
of separately billable from composite rate laboratory and supply costs.
The suggested changes would also require reporting of these costs by
modality. While the ``step down'' worksheet (Worksheet B-1) in the
current cost report separates capital and labor costs by modality, this
separation is based on proportionally allocating costs according to a
specified statistical basis (for example, treatment counts), rather
than the reporting of actual capital and labor resources associated
with each modality. The data contractor and panelists agreed that
changing the specifications in the instructions to the cost report to
indicate that the allocations be made on the basis of actual resource
use, would allow for a better estimation of component costs per
treatment and analysis of how these costs vary among patient groups and
across modalities.
b. Costs for Capital-Related Assets That Are Dialysis Machines
Based on stakeholder feedback, CMS would like to understand
difficulties ESRD facilities have in reporting capital costs,
particularly as they relate to dialysis machines. Both TEP panelists
and dialysis associations have suggested that modifications to
reporting of the capital costs of dialysis machines focus on two goals.
The first goal is to improve the fidelity and comparability of dialysis
machine capital cost reporting across individual facilities. They
suggested that this would be achieved with more specific instructions
for completing the cost report. The second goal is to ensure CMS's
ability to distinguish between dialysis machine capital costs among
various modalities and dialysis settings in a way that preserves
fidelity and comparability among facilities. This could be achieved
with revisions to the cost report itself. As suggested by panelists and
some stakeholders, to achieve these ends, revisions to the cost report
related to dialysis machine capital costs might include:
Improve the instructions related to the reporting of
dialysis machine capital costs.
++ For purchased equipment: Specify purchase price, depreciation,
maintenance, repair, insurance, replacement.
++ For rented equipment: Specify rental rates, maintenance, repair,
insurance, rent escalators.
List and stratify the costs of capital equipment used in
dialysis treatment by setting and modality.
++ Differentiate between rented and purchased equipment.
++ Differentiate among machines used in-facility and in the home
setting.
++ Differentiate machine costs in the home setting by modality for
home hemodialysis and home peritoneal dialysis.
++ Include water treatment machines and indicate location of use:
Home versus in-facility.
Location in Form 265-11
++ Expand Worksheet A, Line 6.
++ Revise instructions for Worksheet A-1, adding specificity
corresponding to item definitions discussed earlier in the preamble.
c. Direct Patient Labor Allocation
Currently, the cost report does not stratify full-time equivalent
(FTE) hours for direct patient care staff by dialysis modality. It also
does not include several job classifications that are commonly found in
present-day ESRD facilities.
At present, the statistical basis for allocating direct patient
care costs is hours of service (as seen in Worksheet B-1, Column 5).
Using this metric and allocating resource (or labor) use proportionally
by labor hour (independent of labor type) can result in miscalculation
of labor costs by modality. For example, if labor for the provision of
home dialysis is on average more expensive than labor for in-facility
hemodialysis, then a strict by-hour cost allocation will result in a
calculation of home dialysis labor costs that is less costly per-hour
than in practice. Suggestions have included that by substituting FTE
for hours for each appropriate direct patient care labor category, and
using labor categories that more accurately reflect current staffing
patterns in ESRD facilities, any potential misrepresentations of
relative labor costs across modalities can be remedied.
To this end, CMS has received a suggestion to consider the use of
Bureau of Labor Statistics (BLS) occupational categories for outpatient
care centers to remedy this situation, as it would provide up-to-date
job classifications that the comment believes would better correspond
to staffing patterns in ESRD facilities than the currently used
Inpatient Prospective Payment System job categories. Selecting BLS
occupational categories for outpatient care centers could be added or
substituted in Lines 23-31 on Worksheet S-1 of CMS Form 265-11 to
reflect current staffing patterns, and columns could be added to
separately report home dialysis FTE and in-facility dialysis FTE for
each relevant occupational category. Additional labor categories might
include registered nurses with varying credentials, dieticians,
pharmacists, and nurse practitioners and other intermediate-level
providers, as appropriate.
d. Managerial and Administrative Labor Allocation
The data contractor and TEP panelists discussed Medicare cost
report's non-direct patient care positions, specifically the current
managerial and labor allocation. They made recommendations for
differentiating high-cost management from lower-cost administrative and
clerical functions, which included a set of potential revisions to
bring management and administrative labor categories up to date using
occupational categories that reflect current usage in dialysis
facilities.
As with the direct patient labor allocation above, suggestions
include the use of BLS occupational categories for outpatient care
centers that correspond to the roles employed in contemporary dialysis
facilities. Suggested additions to these job categories might include
business and financial operations personnel, office and administrative
workers, facility support workers, and programmers and analysts. With
more accurate data, it may be possible to determine how management and
administrative costs are differentially allocated across facilities (by
region and treatment-type specialization). These suggested changes to
managerial and administrative job categories would be made to Worksheet
S-1, Lines 31-34.
e. Supplies and Laboratory Services
While composite rate and separately billable drug costs are
differentiated on the cost report, supplies and laboratory tests are
not differentiated. Supplies comprise approximately 10 percent of
composite rate costs. To bring uniformity to the reporting of drugs,
laboratory tests, and supplies, we have received suggestions that
supplies and laboratory tests be similarly stratified. These costs are
currently reported on Worksheet B/B-1. Specifically,
[[Page 36407]]
stakeholders have suggested the following changes: (1) Add separate
columns differentiating composite rate from separately billable
supplies (Worksheet B/B-1, Column 7-8); (2) add separate columns
differentiating composite rate from separately billable laboratory
services (Worksheet B/B-1, Column 9-10).
3. Request for Information on Independent Facility Cost Report
CMS invites comments on the suggested changes to the Independent
Facility Cost Report (CMS Form 265-11), as described earlier in this
section of the proposed rule. In addition to any other input the public
wants to provide on modifying the Independent Facility Cost Report, we
are requesting responses to the following questions.
What challenges, including operational difficulties, do
ESRD facilities currently face in reporting capital costs:
++ In general.
++ Due to inadequate instructions:
--Which instructions should be revised for clarity?
--Of those above, which are most problematic?
++ In responding, please indicate whether you are representing the
views of a
--Large dialysis organization.
--Regional organization.
--Independent and/or rural facility or another entity.
++ What level of expertise do personnel typically filling out cost
reports have:
--With cost accounting principles and practices?
--With health care cost accounting principles and practices?
--With operational details of how capital equipment is used in
their ESRD facility?
++ Are accounting record-keeping systems currently used by ESRD
facilities adequate to the task of responding to current and
contemplated (in this RFI) cost reporting requirements?
What challenges, including operational difficulties, would
ESRD facilities face:
++ In reporting dialysis-related machine costs by modality and
location?
++ In determining the facility level distribution of direct patient
labor FTE across modalities for each type of direct patient labor?
++ In reporting separate costs for composite rate supplies and
separately billable supplies?
++ In reporting separate costs for composite rate laboratory
services and separately billable laboratory services?
What categories of direct patient care labor, such as
registered nurses (North American Classification System (NAICS) 29-
1141) and dieticians (NAICS 29-1031), are routinely employed by your
dialysis facility and which can be documented in cost reports? Please
provide the specific Bureau of Labor Statistics NAICS code associated
with each labor category for outpatient care centers found at this
website: https://www.bls.gov/oes/current/naics4_621400.htm.
Please detail the specific categories of administrative
and management personnel currently employed by your ESRD facility and
which can be reported on CMS Form 265-11. Please provide the specific
Bureau of Labor Statistics NAICS code associated with each labor
category for management (https://www.bls.gov/oes/current/naics4_541600.htm#11-0000) and administrative (https://www.bls.gov/oes/2018/may/naics3_561000.htm). Please indicate if relevant labor
categories are not represented here and how these categories can be
documented and reported on CMS Form 265-11.
Stakeholders have commented on other categorical costs
that are not reported on the cost report. These include missed
treatments and use of isolation rooms.
++ Specifically, please comment on adding reporting of (1) missed
treatments, and (2) maintenance of isolation rooms.
++ Where on CMS Form 265-11 should these items be inserted (if at
all)?
What challenges would hospital-based facilities face were
the hospital-based cost report to be revised to harmonize with the
changes suggested for the independent facility cost report? How can the
two cost reporting forms be brought into congruence as related to:
Dialysis related equipment, direct patient care, administrative labor,
drugs, laboratory services, and supplies?
Costing accuracy is difficult to achieve for home
dialysis. The suggested revisions described above strive to
differentiate costs among the different modalities. Are there other
means for facilities to report more accurate cost data for home
dialysis modalities? Specifically, how can staff time dedicated to home
dialysis treatment be better reported?
What other changes might be made to the cost report to
better differentiate costs across modalities and patient risk groups?
H. Modifying the Pediatric Cost Report
1. Background
Pediatric composite rate costs are not differentiated from adult
costs on hospital cost reports, while some pediatric-specific costs are
itemized on the existing free-standing cost report. Using CY 2019 cost
report data, CMS' data contractor computed total and component specific
cost per treatment for hemodialysis-equivalent treatments, stratified
by modality, and obtained the ratio of pediatric to adult cost per
treatment for each dialysis facility that reported both adult and
pediatric treatments. The results indicate that there is variation in
costs across composite rate cost components for pediatric and adult
treatments. Overall the cost ratio of pediatric to adult treatment
costs is 1.58,\302\ indicating that pediatric treatments are more
expensive to administer than adult treatments. For one cost component
in particular, supplies, the ratio is 7.30,\303\ indicating much higher
costs for pediatric dialysis supplies than for adult supplies. Further
analysis, however, revealed that a substantial portion of facilities
does not differentiate between adult and pediatric costs in their cost
report accounting. Overall, we found that 13 percent of facilities that
treat both pediatric and adult dialysis patients do not differentiate
costs between the two age groups.
---------------------------------------------------------------------------
\302\ The fraction would be 158/100, that is $1.58 is spent
overall on pediatric dialysis treatments for every $1.00 spent for
adult patients.
\303\ $7.30 is spent, overall, on supplies for a pediatric
dialysis treatment for every $1.00 spent on supplies for an adult
treatment.
---------------------------------------------------------------------------
2. Suggestions for the Pediatric Cost Report
In response, CMS is considering that two types of changes be made
to the hospital and free-standing ESRD facility cost report that would
facilitate the separate reporting of adult and pediatric treatment
costs: (1) Changes that differentiate pediatric from adult composite
rate component costs, and (2) changes that allow for further
differentiation of component costs by modality and age group within the
pediatric population. The potential revisions for which stakeholder
input is being sought include the addition of select direct patient
care labor categories, which correspond to the type of labor typically
employed by pediatric dialysis facilities, and the differentiation of
pediatric supplies and equipment.
Specifically, CMS is considering adding the following staff
categories to CMS Form 265-11, Worksheet S-1, Lines 21-31 (Renal
Dialysis Facility--Number of Employees (Full Time Equivalents)):
Pediatric dialysis nurses and nurse practitioners, pediatric social
workers, pediatric dieticians, child life specialists, teachers, and
pediatric
[[Page 36408]]
dialysis unit coordinator. We have also received recommendations that
additional columns be added to this section of the cost report to
differentiate pediatric home dialysis and in-facility dialysis.
With regard to pediatric supplies and equipment, stakeholders have
suggested that there be clear differentiation of supplies used in
dialysis treatment of pediatric patients, which vary in type and size,
from those used with adult dialysis patients. Stakeholders have further
indicated that there is added cost involved with the stocking of the
range of sizes and types of supplies needed for this population.
Categories of supplies for which there is a significantly increased
cost for the pediatric population include: Dialyzers, catheter kits,
fistula needles, saline flushes, monitors for vitals, blood pressure
cuffs and items used to occupy children during their treatment.
Pediatric nephrologists have noted that these suggested revisions
would have the greatest impact on the hospital cost report, which
currently does not differentiate pediatric from adult dialysis
patients. Approximately two-thirds of pediatric dialysis treatments
take place in the hospital or medical center setting.
3. Request for Information on the Pediatric Cost Report
CMS invites comments on the potential changes to cost reports,
described previously in this section of the proposed rule, as these
changes (if proposed and finalized in the future) would apply to ESRD
facilities treating pediatric dialysis patients. In addition to any
other input the public wants to provide regarding the cost reports, we
are requesting responses to the following questions.
What degree of specificity is needed in the reporting of
pediatric dialysis costs?
Are there dialysis supply costs associated with the
treatment of pediatric patients that cannot be reported currently on
the cost reports? If so, please specify.
For ESRD facilities that administer dialysis to both adult
and pediatric patients:
++ To what extent can ESRD facilities differentiate dialysis supply
costs for adult versus pediatric patients?
--Are there specific high-cost supplies unique to the treatment of
pediatric patients that could be used to isolate additional costs
related to pediatric dialysis?
--When differentiating pediatric dialysis supply costs on the cost
reports, would providers prefer that the cost reports include
additional specific items for pediatric supplies or a separate section
for supply costs associated with pediatric dialysis?
++ To what extent can providers differentiate dialysis labor costs
for adult versus pediatric patients?
Are there potential revisions that could be made to the
cost report, other than those described above, that would help identify
costs unique to the pediatric population (for example, revisions to
items and services being reported; format revisions to help facilitate
reporting on pediatric costs)?
What obstacles do providers face in reporting pediatric
specific costs of dialysis treatment? How can these obstacles be
overcome?
Pediatric dialysis patients comprise a small number of
patients in ESRD facilities other than children's hospitals or medical
centers. How can pediatric dialysis costs be reported in non-
specialized ESRD facilities that predominantly serve adult patients
without undue burden on the provider?
I. Modifying Site of Services Provided to Medicare Beneficiaries With
Acute Kidney Injury (AKI)
1. Background on Medicare Payment for AKI
On June 29, 2015, the TPEA was enacted. In the TPEA, Congress
amended the Act to include coverage and provide for payment for
dialysis furnished by an ESRD facility to an individual with AKI.
Specifically, section 808(a) of the TPEA amended section 1861(s)(2)(F)
of the Act to provide coverage for renal dialysis services furnished on
or after January 1, 2017, by a renal dialysis facility or a provider of
services paid under section 1881(b)(14) of the Act to individuals with
AKI at the ESRD PPS base rate, as adjusted by any applicable geographic
adjustment applied under section 1881(b)(14)(D)(iv)(II) of the Act and
may be adjusted by the Secretary on a budget neutral basis for payments
under section 1834(r) of the Act by any other adjustment factor under
section 1881(b)(14)(D) of the Act. In CY 2017 ESRD PPS final rule (81
FR 77870 through 77872), we finalized the AKI dialysis payment rate.
2. Current Issues and Stakeholder Concerns
Over the years, we have received several comments, including
concerns from ESRD facilities; national renal groups, nephrologists and
patient organizations; patients and care partners; manufacturers;
health care systems; and nurses regarding the site of renal dialysis
services for Medicare beneficiaries with AKI. A patient advocacy
organization supported the proposal in the CY 2017 ESRD PPS proposed
rule to adjust the AKI payment rate by only the geographic and wage
indices, and stated that some patients with AKI can safely dialyze at
home and have their urine and blood tests performed for the assessment
of kidney function in a location closer to home. The organization
recommended that home training be paid separately, without dollars
removed from the base rate. In the CY 2017 ESRD PPS final rule, we
finalized several coverage and payment policies in order to implement
subsection (r) of section 1834 of the Act and the amendments to section
1881(s)(2)(F) of the Act, including the payment rate for AKI dialysis
(81 FR 77866 through 77872). We interpreted section 1834(r)(1) of the
Act to mean the amount of payment for AKI dialysis services is the base
rate for renal dialysis services determined for such year under the
ESRD base rate as set forth in Sec. 413.220, updated by the ESRD
bundled market basket percentage increase factor minus a productivity
adjustment as set forth in Sec. 413.196(d)(1), adjusted for wages as
set forth in Sec. 413.231, and adjusted by any other amounts deemed
appropriate by the Secretary under Sec. 413.373. We codified this
policy in Sec. 413.372 and finalized a CY 2021 payment rate for renal
dialysis services furnished by ESRD facilities to individuals with AKI
as $253.13 (85 FR 71399).
In the CY 2017 ESRD PPS final rule, we stated that we do not expect
that AKI beneficiaries will dialyze at home (81 FR 77871). We affirmed
in the CY 2017 ESRD PPS final rule that payment will only be made for
in-center peritoneal dialysis or hemodialysis treatments for AKI
beneficiaries. CMS also stated in the CY 2017 ESRD PPS final rule that
we would monitor this policy to determine if changes are necessary in
the future, understanding that there may be a subset of patients for
whom AKI dialysis at home is an appropriate treatment. Currently, CMS
continues to believe that this population requires close medical
supervision by qualified staff during their dialysis treatment.
Due to the COVID-19 PHE and an increase in the number of
hospitalized patients with AKI receiving peritoneal dialysis,
stakeholders have raised concerns about patients with AKI having to
both travel to, and be present in, an ESRD facility post
hospitalization. CMS received comments that patients with AKI require
more vigilant monitoring, particularly in infection prevention, blood
pressure
[[Page 36409]]
management, more frequent laboratory testing, additional medication
administration and increased educational needs. Commenters stated that
patients with AKI are distinct from regular patients with ESRD in that
they need specific critical treatment. CMS continued to receive
comments in response to the CY 2021 ESRD PPS proposed rule regarding
this concern, including the recommendation that CMS allow patients with
AKI to be dialyzed at home. Specifically, the commenters requested that
CMS allow patients with AKI to pursue peritoneal dialysis in the home
if the patient and nephrologist agree it is safe to do so and the home
setting is the patient's choice. We also received comments from
organizations requesting that CMS remove barriers that make it
difficult for patients who want to select home dialysis. They
specifically requested that, for the duration of the COVID-19 PHE, CMS
waive the requirement that health care providers are paid for providing
care to patients with AKI only when they receive in-center
hemodialysis.
The 2020 TEP included a session on AKI and the current Medicare
payment system. The panelists discussed cost and utilization of AKI
related dialysis services since the policy change in 2017, including
the incorporation of payment for dialysis treatment for patients with
AKI into the ESRD PPS, assessment of the accuracy of the reported data
and the effectiveness of the current AKI payment parameters for
accurately capturing the costs of this population.
Panelists agreed that some patients with AKI could benefit from
different treatment regimens. In particular, they noted that more
frequent, gentler dialysis would be a viable option for some patients,
possibly preventing hypotension. During the COVID-19 PHE, many patients
received acute peritoneal dialysis treatments in the hospital upon
developing AKI, and panelists expressed support for allowing patients
with AKI to continue receiving acute peritoneal dialysis once they are
discharged from the hospital. One panelist noted that their hospital
tries to get patients with AKI accustomed to a more standard treatment
regimen such as three treatments per week before discharging them to an
ESRD facility. Another panelist expressed support for the
implementation of transitional care units, noting they would help
patients new to dialysis adjust to dialysis and the lifestyle changes
that accompany it. Panelists also advocated for allowing patients with
AKI to be treated at home, especially in light of the COVID-19 PHE.
Members of the TEP commented on the similar treatment frequencies
observed for patients with AKI and ESRD, stating that the payment
system is currently constructed to facilitate the observed treatment
patterns for patients with AKI. Panelists stressed that the payment
system should continue to be flexible in terms of number of treatments
for patients with AKI so that those who need more frequent treatments
are not impeded from receiving them.
Panelists expressed support for the CMS guidance temporarily
allowing dialysis facilities to send dialysis facility staff to furnish
72x dialysis to their patients in nursing homes, from both a cost and
patient health perspective. (See https://www.cms.gov/files/document/covid-19-emergency-declaration-waivers.pdf.) Panelists noted that it
was more efficient to send ESRD facility staff to the skilled nursing
facilities rather than the costly routine and ambulance-required
transportation and physical isolation expenses incurred during the
public health emergency. Panelists stated that the full spectrum of
care provided in the SNF setting is invaluable, particularly for the
patients with multiple comorbidities.
Panelists commented on the costs per treatment observed for
patients with AKI, expressing that the higher observed costs compared
to ESRD treatments aligns with their expectations. Members of the panel
noted that patients with AKI receive more laboratory tests to monitor
for recovery, but typically are not prescribed calcimimetics or ESAs.
Some panelists also noted that due to the very small population size of
Medicare beneficiaries with AKI, reporting AKI costs and statistics on
cost reports at a granular level introduces an outsized reporting
burden on the part of the providers.
Overall, panelists expressed that the current AKI payment structure
is effective and benefits both patients and facilities. One panelist
pointed out that the AKI policy change, which we implemented in the CY
2017 ESRD PPS final rule (81 FR 77866 through 77872), helps hospitals,
as they can send patients with AKI requiring dialysis to ESRD
facilities and consequently free up capacity at the hospital.
4. Request for Information on Modifying the Site of Services Provided
to Medicare Beneficiaries With AKI
CMS is soliciting feedback from the public on the differences in
care for patients with AKI versus patients with ESRD and whether it has
bearing on the ability of patients with AKI to perform home dialysis
safely. We request any additional comments regarding potentially
modifying site of renal dialysis services and payment for AKI in the
home setting.
VII. Collection of Information Requirements
A. Legislative Requirement for Solicitation of Comments
Under the Paperwork Reduction Act of 1995, we are required to
provide 60-day notice in the Federal Register and solicit public
comment before a collection of information requirement is submitted to
the Office of Management and Budget (OMB) for review and approval. In
order to fairly evaluate whether an information collection requirement
should be approved by OMB, the Paperwork Reduction Act of 1995 (44
U.S.C. 3506(c)(2)(A)) requires that we solicit comment on the following
issues:
The need for the information collection and its usefulness
in carrying out the proper functions of our agency.
The accuracy of our estimate of the information collection
burden.
The quality, utility, and clarity of the information to be
collected.
Recommendations to minimize the information collection
burden on the affected public, including automated collection
techniques.
We are soliciting public comment on each of these issues for the
following sections of this document that contain information collection
requirements (ICRs):
B. Requirements in Regulation Text
In sections V through V.B of this proposed rule, we are proposing
changes to the regulatory text for the ETC Model. However, the changes
that are being proposed do not impose any new information collection
requirements.
C. Additional Information Collection Requirements
This proposed rule does not impose any new information collection
requirements in the regulation text, as specified above. However, there
are changes in some currently approved information collections. The
following is a discussion of these information collections.
1. ESRD QIP--Wage Estimates (OMB control numbers 0938-1289 and 0938-
1340)
To derive wages estimates, we used data from the U.S. Bureau of
Labor Statistics' May 2020 National Occupational Employment and Wage
[[Page 36410]]
Estimates. In the CY 2016 ESRD PPS final rule (80 FR 69069), we stated
that it was reasonable to assume that Medical Records and Health
Information Technicians, who are responsible for organizing and
managing health information data, are the individuals tasked with
submitting measure data to CROWNWeb (now EQRS) and NHSN, as well as
compiling and submitting patient records for purpose of the data
validation studies, rather than a Registered Nurse, whose duties are
centered on providing and coordinating care for patients. We stated
that the median hourly wage of a Medical Records and Health Information
Technician is $21.20 per hour.\304\ We also stated that fringe benefit
and overhead are calculated at 100 percent. Therefore, using these
assumptions, we estimated an hourly labor cost of $42.40 as the basis
of the wage estimates for all collections of information calculations
in the ESRD QIP. We adjusted these employee hourly wage estimates by a
factor of 100 percent to reflect current HHS department-wide guidance
on estimating the cost of fringe benefits and overhead. We stated that
these are necessarily rough adjustments, both because fringe benefits
and overhead costs vary significantly from employer to employer and
because methods of estimating these costs vary widely from study to
study. Nonetheless, we stated that there is no practical alternative
and we believe that these are reasonable estimation methods.
---------------------------------------------------------------------------
\304\ https://www.bls.gov/oes/current/oes292098.htm. Accessed on
June 7, 2021.
---------------------------------------------------------------------------
We used this updated wage estimate, along with updated facility and
patient counts to re-estimate the total information collection burden
in the ESRD QIP for PY 2024 that we discussed in the CY 2021 ESRD QIP
final rule (85 FR 71473 through 71474) and to estimate the total
information collection burden in the ESRD QIP for PY 2025. We provide
the re-estimated information collection burden associated with the PY
2024 ESRD QIP and the newly estimated information collection burden
associated with the PY 2025 ESRD QIP in section VII.C.3 of this
proposed rule.
2. Estimated Burden Associated With the Data Validation Requirements
for PY 2024 and PY 2025 (OMB Control Numbers 0938-1289 and 0938-1340)
In the CY 2020 ESRD PPS final rule, we finalized a policy to adopt
the CROWNWeb data validation methodology that we previously adopted for
the PY 2016 ESRD QIP as the methodology we would use to validate
CROWNWeb data for all payment years, beginning with PY 2021 (83 FR
57001 through 57002). Although, as noted in section IV.B.2 of this
proposed rule, we are now using EQRS to report data that was previously
reported in CROWNWeb, the data validation methodology remains the same.
Under this methodology, 300 facilities are selected each year to submit
10 records to CMS, and we reimburse these facilities for the costs
associated with copying and mailing the requested records. The burden
associated with these validation requirements is the time and effort
necessary to submit the requested records to a CMS contractor. In this
proposed rule, we are updating these estimates using a newly available
wage estimate of a Medical Records and Health Information Technician.
In the CY 2020 ESRD PPS final rule, we estimated that it would take
each facility approximately 2.5 hours to comply with this requirement.
If 300 facilities are asked to submit records, we estimated that the
total combined annual burden for these facilities would be 750 hours
(300 facilities x 2.5 hours). Since we anticipate that Medical Records
and Health Information Technicians or similar administrative staff
would submit these data, we estimate that the aggregate cost of the
EQRS data validation each year would be approximately $31,800 (750
hours x $42.40), or an annual total of approximately $106.00 ($31,800/
300 facilities) per facility in the sample. The burden cost increase
associated with these requirements will be revised in information
collection request (OMB control number 0938-1289).
In the CY 2021 ESRD PPS final rule, we finalized our policy to
reduce the number of records that a facility selected to participate in
the NHSN data validation must submit to a CMS contractor, beginning
with PY 2023 (85 FR 71471 through 71472). Under this finalized policy,
a facility is required to submit records for 20 patients across any two
quarters of the year, instead of 20 records for each of the first two
quarters of the year. The burden associated with this policy is the
time and effort necessary to submit the requested records to a CMS
contractor. Applying our policy to reduce the number of records
required from each facility participating in the NHSN validation, we
estimated that it would take each facility approximately 5 hours to
comply with this requirement. If 300 facilities are asked to submit
records each year, we estimated that the total combined annual burden
hours for these facilities per year would be 1,500 hours (300
facilities x 5 hours). Since we anticipate that Medical Records and
Health Information Technicians or similar staff would submit these
data, using the newly available wage estimate of a Medical Records and
Health Information Technician, we estimate that the aggregate cost of
the NHSN data validation each year would be approximately $63,600
(1,500 hours x $42.40), or a total of approximately $212 ($63,600/300
facilities) per facility in the sample. While the burden hours estimate
will not change, the burden cost updates associated with these
requirements will be revised in the information collection request (OMB
control number 0938-1340).
3. EQRS Reporting Requirements for PY 2024 and PY 2025 (OMB Control
Number 0938-1289)
To determine the burden associated with the EQRS reporting
requirements (previously known as the CROWNWeb reporting requirements),
we look at the total number of patients nationally, the number of data
elements per patient-year that the facility would be required to submit
to EQRS for each measure, the amount of time required for data entry,
the estimated wage plus benefits applicable to the individuals within
facilities who are most likely to be entering data into EQRS, and the
number of facilities submitting data to EQRS. In the CY 2021 ESRD PPS
final rule, we estimated that the burden associated with CROWNWeb (now
EQRS) reporting requirements for the PY 2024 ESRD QIP was approximately
$208 million (85 FR 71400).
As discussed in section IV.C and section IV.D of this proposed
rule, we are proposing measure suppressions that would apply for PY
2022 and updates to the scoring methodology and payment reductions for
the PY 2022 ESRD QIP. We also announce an extension of EQRS reporting
requirements for facilities due to systems issues. However, we believe
that none of the policies proposed in this proposed rule would affect
our estimates of the annual burden associated with the Program's
information collection requirements, as facilities are still expected
to continue to collect measure data during this time period. We are not
proposing any changes that would affect the burden associated with EQRS
reporting requirements for PY 2024 or PY 2025. However, we have re-
calculated the burden estimate for PY 2024 using updated estimates of
the total number of dialysis facilities, the total number of
[[Page 36411]]
patients nationally, and wages for Medical Records and Health
Information Technicians or similar staff as well as a refined estimate
of the number of hours needed to complete data entry for EQRS
reporting. Consistent with our approach in the CY 2021 ESRD PPS final
rule (85 FR 71474), in this proposed rule we estimated that the amount
of time required to submit measure data to EQRS was 2.5 minutes per
element and did not use a rounded estimate of the time needed to
complete data entry for EQRS reporting. There are 229 data elements for
532,931 patients across 7,610 facilities. At 2.5 minutes per element,
this yields approximately 668.21 hours per facility. Therefore, the PY
2024 burden is 5,085,050 hours (668.21 hours x 7,610 facilities). Using
the wage estimate of a Medical Records and Health Information
Technician, we estimate that the PY 2024 total burden cost is
approximately $215 million (5,085,050 hours x $42.40). There is no net
incremental burden change from PY 2024 to PY 2025 because we are not
changing the reporting requirements for PY 2025.
VIII. Response to Comments
Because of the large number of public comments we normally receive
on Federal Register documents, we are not able to acknowledge or
respond to them individually. We will consider all comments we receive
by the date and time specified in the ``DATES'' section of this
preamble, and, when we proceed with a subsequent document, we will
respond to the comments in the preamble to that document.
IX. Economic Analyses
A. Regulatory Impact Analysis
1. Introduction
We have examined the impacts of this rule as required by Executive
Order 12866 on Regulatory Planning and Review (September 30, 1993),
Executive Order 13563 on Improving Regulation and Regulatory Review
(January 18, 2011), the Regulatory Flexibility Act (RFA) (September 19,
1980; Pub. L. 96-354), section 1102(b) of the Social Security Act,
section 202 of the Unfunded Mandates Reform Act of 1995 (March 22,
1995; Pub. L. 104-4), Executive Order 13132 on Federalism (August 4,
1999), and the Congressional Review Act (5 U.S.C. 801(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.
A regulatory impact analysis (RIA) must be prepared for major rules
with economically significant effects ($100 million or more in any 1
year). We estimate that this rulemaking 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 to the best of our ability presents the
costs and benefits of the rulemaking. We solicit comments on the
regulatory impact analysis provided.
2. Statement of Need
a. ESRD PPS
This rule proposes a number of routine updates to the ESRD PPS for
CY 2022. The proposed routine updates include the CY 2022 wage index
values, the wage index budget-neutrality adjustment factor, and outlier
payment threshold amounts. Failure to publish this proposed rule would
result in ESRD facilities not receiving appropriate payments in CY 2022
for renal dialysis services furnished to ESRD beneficiaries.
b. AKI
This rule also proposes routine updates to the payment for renal
dialysis services furnished by ESRD facilities to individuals with AKI.
Failure to publish this proposed rule would result in ESRD facilities
not receiving appropriate payments in CY 2022 for renal dialysis
services furnished to patients with AKI in accordance with section
1834(r) of the Act.
c. ESRD QIP
This proposed rule proposes to implement requirements for the ESRD
QIP, including a proposal to adopt a measure suppression policy and to
suppress several ESRD QIP measures under that proposed measure
suppression policy, proposals regarding the scoring methodology and
payment reductions for the PY 2022 ESRD QIP, a proposed update to the
SHR measure, and a proposed update to the PY 2024 performance
standards. This proposed rule also includes a request for public
comment on closing the gap in health equity, as well as a request for
public comment on potential actions and priority areas that would
enable the continued transformation of our quality measurement
enterprise toward greater digital capture of data and use of the FHIR
standard.
d. ETC Model
Beneficiaries with ESRD are among the most medically fragile and
high-cost populations served by the Medicare program. One of CMS' goals
in designing the ETC Model is to test ways to incentivize home dialysis
and kidney transplants, to enhance beneficiary choice of modality for
renal replacement therapy, and improve quality of care and quality of
life while reducing Medicare program expenditures. The substantially
higher expenditures, mortality, and hospitalization rates for dialysis
patients in the U.S. compared to those for individuals with ESRD in
other countries indicate a population with poor clinical outcomes and
potentially avoidable expenditures. This proposed rule would refine the
methodology for setting and updating achievement and improvement
benchmarks for participating ESRD facilities and Managing Clinicians
serving the ESRD population over the remaining years of the ETC Model,
among other proposed changes. Notwithstanding the proposed changes, we
continue to anticipate improvement in quality of care for beneficiaries
and reduced expenditures under the ETC Model inasmuch as the Model is
designed to create incentives for beneficiaries, along with their
families and caregivers, to choose the optimal kidney replacement
modality.
As noted in section IV.B of the Specialty Care Models final rule
(85 FR 61264), Medicare payment rules and a deficit in beneficiary
education result in a bias toward in-center hemodialysis, which is
often not preferred by patients or physicians relative to home dialysis
or kidney transplantation. We provided evidence from the published
literature
[[Page 36412]]
to support the projection that higher rates of home dialysis and kidney
transplants would likely reduce Medicare expenditures, and, not only
enhance beneficiary choice, independence, and quality of life, but also
preserve or enhance the quality of care for ESRD beneficiaries.
As described in detail in section V of this proposed rule, we
believe it is necessary to propose certain changes to the ETC Model.
Under the proposed changes to the ETC Model, ETC Participants would
continue to receive adjusted payments but beginning for MY3, certain
aspects of the ETC Model that determine those payment adjustments would
change. The proposed change to the achievement benchmarking methodology
is necessary to the ETC Model as this change maintains the ETC Model's
expectation of savings. The proposed changes to the transplant rate,
the achievement benchmarking methodology, and the improvement
benchmarking and scoring methodology are necessary to increase accuracy
and fairness of performance assessment. The proposed changes to the
home dialysis rate, data sharing, and kidney disease patient education
services waivers are necessary to support ETC Participants operating in
the ETC Model.
3. Overall Impact
a. ESRD PPS
We estimate that the proposed revisions to the ESRD PPS would
result in an increase of approximately $140 million in payments to ESRD
facilities in CY 2022, which includes the amount associated with
updates to the outlier thresholds, and updates to the wage index.
b. AKI
We estimate that the proposed updates to the AKI payment rate would
result in an increase of approximately $1 million in payments to ESRD
facilities in CY 2022.
c. ESRD QIP
For PY 2024 and PY 2025, we have re-estimated the costs associated
with the information collection requirements under the ESRD QIP with
updated estimates of the total number of dialysis facilities, the total
number of patients nationally, wages for Medical Records and Health
Information Technicians or similar staff, and a refined estimate of the
number of hours needed to complete data entry for EQRS reporting. We
have made no changes to our methodology for calculating the annual
burden associated with the information collection requirements for the
EQRS validation study (previously known as the CROWNWeb validation
study), the NHSN validation study, and EQRS reporting. As discussed in
section IV.C and section IV.D of this proposed rule, we are proposing
measure suppressions that would apply for PY 2022 and updates to the
scoring methodology and payment reductions for the PY 2022 ESRD QIP. We
also announce an extension of EQRS reporting requirements for
facilities due to systems issues. However, we believe that none of the
policies proposed in this proposed rule would affect our estimates of
the annual burden associated with the Program's information collection
requirements, as facilities are still expected to continue to collect
measure data during this time period.
We also updated the payment reduction scale using more recent data
for the measures in the ESRD QIP measure set. We estimate approximately
$215 million in information collection burden, which includes the cost
of complying with this rule, and an additional $17 million in estimated
payment reductions across all facilities for PY 2024.
For PY 2025, we estimate that the proposed revisions to the ESRD
QIP would result in $215 million in information collection burden, and
$17 million in estimated payment reductions across all facilities, for
an impact of $232 million as a result of the policies we have
previously finalized and the policies we have proposed in this proposed
rule.
d. ETC Model
We estimate that the proposed changes to the ETC Model would
increase the Model's projected direct savings from payment adjustments
alone by $7 million over the duration of the Model. We estimate that
the Model would generate $38 million in direct savings related to
payment adjustments over 6.5 years with the proposed changes, and would
generate $31 million in savings in the absence of the proposed changes.
4. Regulatory Review Cost Estimation
If regulations impose administrative costs on private entities,
such as the time needed to read and interpret this proposed rule 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 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 welcome any comments on the approach in estimating the
number of entities, which will review 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 $110.74 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 6.25 hours
for the staff to review half of this proposed rule. For each entity
that reviews the rule, the estimated cost is $692.13 (6.25 hours x
$110.74). Therefore, we estimate that the total cost of reviewing this
regulation is $ 78,903 ($692.13 x 114).
B. Detailed Economic Analysis
1. CY 2021 End-Stage Renal Disease Prospective Payment System
a. Effects on ESRD Facilities
To understand the impact of the changes affecting payments to
different categories of ESRD facilities, it is necessary to compare
estimated payments in CY 2021 to estimated payments in CY 2022. To
estimate the impact among various types of ESRD facilities, it is
imperative that the estimates of payments in CY 2021 and CY 2022
contain similar inputs. Therefore, we simulated payments only for those
ESRD facilities for which we are able to calculate both current
payments and new payments.
For this proposed rule, we used CY 2020 data from the Part A and
Part B Common Working Files as of February 12, 2021, as a basis for
Medicare dialysis treatments and payments under the ESRD PPS. We
updated the 2020 claims to 2021 and 2022 using various updates. The
updates to the ESRD PPS base rate are described in section II.B.1.d of
this proposed rule. Table 9 shows the impact of the estimated CY 2022
ESRD PPS
[[Page 36413]]
payments compared to estimated payments to ESRD facilities in CY 2021.
[GRAPHIC] [TIFF OMITTED] TP09JY21.008
[[Page 36414]]
BILLING CODE 4120-01-C
Column A of the impact table indicates the number of ESRD
facilities for each impact category and column B indicates the number
of dialysis treatments (in millions). The overall effect of the
proposed changes to the outlier payment policy described in section
II.B.1.c of this proposed rule is shown in column C. For CY 2022, the
impact on all ESRD facilities as a result of the proposed changes to
the outlier payment policy would be a 0.2 percent increase in estimated
payments. All ESRD facilities are anticipated to experience a positive
effect in their estimated CY 2022 payments as a result of the proposed
outlier policy changes.
Column D shows the effect of the annual update to the wage index,
as described in section II.B.1.b of this proposed rule. That is, this
column reflects the update from the CY 2021 ESRD PPS wage index using
2018 OMB delineations as finalized in the CY 2021 ESRD PPS final rule,
with a basis of the FY 2022 pre-floor, pre-reclassified IPPS hospital
wage index data in a budget neutral manner. The total impact of this
change is 0.0 percent; however, there are distributional effects of the
change among different categories of ESRD facilities. The categories of
types of facilities in the impact table show changes in estimated
payments ranging from a 0.7 percent decrease to a 0.5 percent increase
due to the annual update to the ESRD PPS wage index.
Column E shows the effect of the proposed CY 2022 ESRD PPS payment
rate update as described in section II.B.1.a of this proposed rule. The
proposed ESRD PPS payment rate update is 1.0 percent, which reflects
the proposed ESRDB market basket percentage increase factor for CY 2022
of 1.6 percent and the proposed productivity adjustment of 0.6 percent.
Column F reflects the overall impact, that is, the effects of the
proposed outlier policy changes, the proposed updated wage index, and
the payment rate update. We expect that overall ESRD facilities would
experience a 1.2 percent increase in estimated payments in CY 2022. The
categories of types of facilities in the impact table show impacts
ranging from a 0.4 percent increase to a 1.6 percent increase in their
CY 2022 estimated payments.
b. Effects on Other Providers
Under the ESRD PPS, Medicare pays ESRD facilities a single bundled
payment for renal dialysis services, which may have been separately
paid to other providers (for example, laboratories, durable medical
equipment suppliers, and pharmacies) by Medicare prior to the
implementation of the ESRD PPS. Therefore, in CY 2022, we estimate that
the proposed ESRD PPS would have zero impact on these other providers.
c. Effects on the Medicare Program
We estimate that Medicare spending (total Medicare program
payments) for ESRD facilities in CY 2022 would be approximately $8.9
billion. This estimate takes into account a projected decrease in fee-
for-service Medicare dialysis beneficiary enrollment of 5.9 percent in
CY 2022.
d. Effects on Medicare Beneficiaries
Under the ESRD PPS, beneficiaries are responsible for paying 20
percent of the ESRD PPS payment amount. As a result of the projected
1.2 percent overall increase in the proposed CY 2022 ESRD PPS payment
amounts, we estimate that there would be an increase in beneficiary co-
insurance payments of 1.2 percent in CY 2022, which translates to
approximately $30 million.
e. Alternatives Considered
CY 2022 Impacts: 2019 Versus 2020 Claims Data
Each year CMS uses the latest available ESRD claims to update the
outlier threshold, budget neutrality factor, and payment rates. Due to
the COVID-19 PHE, we compared the impact of using CY 2019 claims
against CY 2020 claims to determine if there was any substantial
difference in the results that would justify potentially deviating from
our longstanding policy to use the latest available data. Analysis
suggested that ESRD utilization did not change substantially during the
pandemic, likely due to the patients' vulnerability and need for these
services. Consequently, we proposed to use the CY 2020 data because it
does not negatively impact ESRD facilities and keeps with our
longstanding policy to make updates using the latest available ESRD
claims data.
2. Proposed Payment for Renal Dialysis Services Furnished to
Individuals With AKI
a. Effects on ESRD Facilities
To understand the impact of the changes affecting payments to
different categories of ESRD facilities for renal dialysis services
furnished to individuals with AKI, it is necessary to compare estimated
payments in CY 2021 to estimated payments in CY 2022. To estimate the
impact among various types of ESRD facilities for renal dialysis
services furnished to individuals with AKI, it is imperative that the
estimates of payments in CY 2021 and CY 2022 contain similar inputs.
Therefore, we simulated payments only for those ESRD facilities for
which we are able to calculate both current payments and new payments.
For this proposed rule, we used CY 2020 data from the Part A and
Part B Common Working Files as of February 12, 2021, as a basis for
Medicare for renal dialysis services furnished to individuals with AKI.
We updated the 2020 claims to 2021 and 2022 using various updates. The
proposed updates to the AKI payment amount are described in section
III.B of this proposed rule. Table 10 shows the impact of the estimated
CY 2022 payments for renal dialysis services furnished to individuals
with AKI compared to estimated payments for renal dialysis services
furnished to individuals with AKI in CY 2021.
BILLING CODE 4120-01-P
[[Page 36415]]
[GRAPHIC] [TIFF OMITTED] TP09JY21.010
[[Page 36416]]
[GRAPHIC] [TIFF OMITTED] TP09JY21.011
BILLING CODE 4120-01-C
Column A of the impact table indicates the number of ESRD
facilities for each impact category and column B indicates the number
of AKI dialysis treatments (in thousands). Column C shows the effect of
the proposed CY 2022 wage indices. Column D shows the effect of the
proposed CY 2022 ESRD PPS payment rate update. The proposed ESRD PPS
payment rate update is 1.0 percent, which reflects the proposed ESRDB
market basket percentage increase factor for CY 2022 of 1.6 percent and
the proposed productivity adjustment of 0.6 percent.
Column E reflects the overall impact, that is, the effects of the
updated wage index and the payment rate update. We expect that overall
ESRD facilities would experience a 1.0 percent increase in estimated
payments in CY 2022. The categories of types of facilities in the
impact table show impacts ranging from an increase of 0.0 percent to
1.6 percent in their CY 2022 estimated payments.
b. Effects on Other Providers
Under section 1834(r) of the Act, as added by section 808(b) of
TPEA, we propose to update the payment rate for renal dialysis services
furnished by ESRD facilities to beneficiaries with AKI. The only two
Medicare providers and suppliers authorized to provide these outpatient
renal dialysis services are hospital outpatient departments and ESRD
facilities. The patient and his or her physician make the decision
about where the renal dialysis services are furnished. Therefore, this
proposal will have zero impact on other Medicare providers.
c. Effects on the Medicare Program
We estimate approximately $52 million would be paid to ESRD
facilities in CY 2022 as a result of patients with AKI receiving renal
dialysis services in the ESRD facility at the lower ESRD PPS base rate
versus receiving those services only in the hospital outpatient setting
and paid under the outpatient prospective payment system, where
services were required to be administered prior to the TPEA.
d. Effects on Medicare Beneficiaries
Currently, beneficiaries have a 20 percent co-insurance obligation
when they receive AKI dialysis in the hospital outpatient setting. When
these services are furnished in an ESRD facility, the patients would
continue to be responsible for a 20 percent coinsurance. Because the
AKI dialysis payment rate paid to ESRD facilities is lower than the
outpatient hospital PPS's payment amount, we would expect beneficiaries
to pay less co-insurance when AKI dialysis is furnished by ESRD
facilities.
e. Alternatives Considered
As we discussed in the CY 2017 ESRD PPS proposed rule (81 FR
42870), we considered adjusting the AKI payment rate by including the
ESRD PPS case-mix adjustments, and other adjustments at section
1881(b)(14)(D) of the Act, as well as not paying separately for AKI
specific drugs and laboratory tests. We ultimately determined that
treatment for AKI is substantially different from treatment for ESRD
and the case-mix adjustments applied to ESRD patients may not be
applicable to AKI patients and as such, including those policies and
adjustment would be inappropriate. We continue to monitor utilization
and trends of items and services furnished to individuals with AKI for
purposes of refining the payment rate in the future. This monitoring
would assist us in developing knowledgeable, data-driven proposals.
3. ESRD QIP
a. Effects of the PY 2022 ESRD QIP on ESRD Facilities
The ESRD QIP is intended to prevent reductions in the quality of
ESRD dialysis facility services provided to beneficiaries. Although the
general methodology that we use to determine a facility's TPS is
described in our regulations at 42 CFR 413.178(e), we are proposing to
codify special scoring policies for PY 2022 at 42 CFR 413.178(h). Under
these proposed regulations, we would calculate measure rates for all
measures but would not calculate achievement and improvement points for
any measures. We would also not calculate or award a TPS for any
facility. Finally, we would not reduce payment to any facility for PY
2022.
If these policies are finalized as proposed, we believe there will
be no effects of the PY 2022 ESRD QIP on ESRD Facilities, as no
facilities will receive a TPS or payment reductions for PY 2022.
[[Page 36417]]
b. Effects of the PY 2024 ESRD QIP on ESRD Facilities
Any reductions in the ESRD PPS payments as a result of a facility's
performance under the PY 2024 ESRD QIP will apply to the ESRD PPS
payments made to the facility for services furnished in CY 2024, as
codified in our regulations at 42 CFR 413.177.
For the PY 2024 ESRD QIP, we estimate that, of the 7,610 dialysis
facilities (including those not receiving a TPS) enrolled in Medicare,
approximately 24.4 percent or 1,799 of the facilities that have
sufficient data to calculate a TPS would receive a payment reduction
for PY 2024. We are presenting an estimate for the PY 2024 ESRD QIP to
update the estimated impact that was provided in the CY 2021 ESRD PPS
final rule (85 FR 71481 through 71483). If our proposals are finalized
as proposed, the total estimated payment reductions for all the 1,799
facilities expected to receive a payment reduction in PY 2024 would
decrease from $18,247,083.76 to approximately $17,154,657.12.
Facilities that do not receive a TPS do not receive a payment
reduction.
Table 11 shows the overall estimated distribution of payment
reductions resulting from the PY 2024 ESRD QIP.
[GRAPHIC] [TIFF OMITTED] TP09JY21.012
To estimate whether a facility would receive a payment reduction
for PY 2024, we scored each facility on achievement and improvement on
several clinical measures we have previously finalized and for which
there were available data from EQRS and Medicare claims. Payment
reduction estimates are calculated using the most recent data available
(specified in Table 12) in accordance with the policies proposed in
this proposed rule. Measures used for the simulation are shown in Table
12.
[GRAPHIC] [TIFF OMITTED] TP09JY21.013
For all measures except the SHR clinical measure, the Standardized
Readmission Ratio (SRR) clinical measure, and the STrR reporting
measure, measures with less than 11 patients for a facility were not
included in that facility's TPS. For the SHR clinical measure and the
SRR clinical measure, facilities were required to have at least 5
patient-years at risk and 11 index discharges, respectively, in order
to be included in the facility's TPS. For the STrR reporting measure,
facilities were required to have at least 10 patient-years at risk in
order to be included in the facility's TPS. Each facility's TPS was
compared to an estimated mTPS and an estimated payment reduction table
that were consistent with the proposals outlined in sections IV.E and
IV.F of this proposed rule. Facility reporting measure scores were
estimated using available data from CY 2019. Facilities
[[Page 36418]]
were required to have at least one measure in at least two domains to
receive a TPS.
To estimate the total payment reductions in PY 2024 for each
facility resulting from this final rule, we multiplied the total
Medicare payments to the facility during the 1-year period between
January 2019 and December 2019 by the facility's estimated payment
reduction percentage expected under the ESRD QIP, yielding a total
payment reduction amount for each facility.
Table 13 shows the estimated impact of the finalized ESRD QIP
payment reductions to all ESRD facilities for PY 2024. The table also
details the distribution of ESRD facilities by size (both among
facilities considered to be small entities and by number of treatments
per facility), geography (both rural and urban and by region), and
facility type (hospital based and freestanding facilities). Given that
the performance period used for these calculations differs from the
performance period we are using for the PY 2024 ESRD QIP, the actual
impact of the PY 2024 ESRD QIP may vary significantly from the values
provided here.
[GRAPHIC] [TIFF OMITTED] TP09JY21.014
c. Effects of the PY 2025 ESRD QIP on ESRD Facilities
For the PY 2025 ESRD QIP, we estimate that, of the 7,610 dialysis
facilities (including those not receiving a TPS) enrolled in Medicare,
approximately 24.4 percent or 1,799 of the facilities that have
sufficient data to calculate a TPS would receive a payment reduction
for PY 2025. The total payment reductions for all the 1,799 facilities
expected to receive a
[[Page 36419]]
payment reduction is approximately $17,154,657.121. Facilities that do
not receive a TPS do not receive a payment reduction.
Table 14 shows the overall estimated distribution of payment
reductions resulting from the PY 2025 ESRD QIP.
[GRAPHIC] [TIFF OMITTED] TP09JY21.015
To estimate whether a facility would receive a payment reduction in
PY 2025, we scored each facility on achievement and improvement on
several clinical measures we have previously finalized and for which
there were available data from EQRS and Medicare claims. Payment
reduction estimates were calculated using the most recent data
available (specified in Table 14) in accordance with the policies
finalized in this proposed rule. Measures used for the simulation are
shown in Table 15.
[GRAPHIC] [TIFF OMITTED] TP09JY21.016
For all measures except the SHR clinical measure, the SRR clinical
measure, and the STrR reporting measure, measures with less than 11
patients for a facility were not included in that facility's TPS. For
SHR and SRR, facilities were required to have at least 5 patient-years
at risk and 11 index discharges, respectively, in order to be included
in the facility's TPS. For the STrR reporting measure, facilities were
required to have at least 10 patient-years at risk in order to be
included in the facility's TPS. Each facility's TPS was compared to an
estimated mTPS and an estimated payment reduction table that
incorporates the policies outlined in section IV.E and IV.F of this
proposed rule. Facility reporting measure scores were estimated using
available data from CY 2019. Facilities were required to have at least
one measure in at least two domains to receive a TPS.
To estimate the total payment reductions in PY 2025 for each
facility resulting from this proposed rule, we multiplied the total
Medicare payments to the facility during the 1-year period between
January 2019 and December 2019 by the facility's estimated payment
reduction percentage expected under the ESRD QIP, yielding a total
payment reduction amount for each facility.
Table 16 shows the estimated impact of the finalized ESRD QIP
payment reductions to all ESRD facilities for PY 2025. The table
details the distribution of ESRD facilities by size (both among
facilities considered to be small entities and by number of treatments
per facility), geography (both rural and urban and by region), and
facility type (hospital based and freestanding facilities). Given that
the performance period used for these calculations differs from the
performance period we are proposing to use for the PY 2025
[[Page 36420]]
ESRD QIP, the actual impact of the PY 2025 ESRD QIP may vary
significantly from the values provided here.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TP09JY21.017
d. Effects on Other Providers
The ESRD QIP is applicable to dialysis facilities. We are aware
that several of our measures impact other providers. For example, with
the introduction of the SRR clinical measure in PY 2017 and the SHR
clinical measure in PY 2020, we anticipate that hospitals may
experience financial savings as dialysis facilities work to reduce the
number of unplanned readmissions and hospitalizations. We are exploring
various methods to assess the impact these measures have on hospitals
and other facilities, such as through the impacts of the Hospital
Readmissions Reduction Program and the Hospital-Acquired Condition
Reduction Program, and we intend to continue examining the interactions
between our quality programs to the greatest extent feasible.
e. Effects on the Medicare Program
For PY 2025, we estimate that the ESRD QIP would contribute
approximately $17,154,657.12 in Medicare savings. For comparison, Table
17 shows the payment reductions that we estimate will be applied by the
ESRD QIP from PY 2018 through PY 2025. This includes our PY 2022
scoring and payment proposals as described in section IV.D of this
proposed rule.
[[Page 36421]]
[GRAPHIC] [TIFF OMITTED] TP09JY21.018
BILLING CODE 4120-01-C
f. Effects on Medicare Beneficiaries
The ESRD QIP is applicable to dialysis facilities. Since the
Program's inception, there is evidence on improved performance on ESRD
QIP measures. As we stated in the CY 2018 ESRD PPS final rule, one
objective measure we can examine to demonstrate the improved quality of
care over time is the improvement of performance standards (82 FR
50795). As the ESRD QIP has refined its measure set and as facilities
have gained experience with the measures included in the Program,
performance standards have generally continued to rise. We view this as
evidence that facility performance (and therefore the quality of care
provided to Medicare beneficiaries) is objectively improving. We are in
the process of monitoring and evaluating trends in the quality and cost
of care for patients under the ESRD QIP, incorporating both existing
measures and new measures as they are implemented in the Program. We
will provide additional information about the impact of the ESRD QIP on
beneficiaries as we learn more. However, in future years we are
interested in examining these impacts through the analysis of available
data from our existing measures.
g. Alternatives Considered
In section IV.D. of this proposed rule, we are proposing a special
rule to modify the scoring methodology such that no facility would
receive a payment reduction for PY 2022. Under this special rule for PY
2022, we would calculate measure rates for all measures for that
payment year, but would not use those measure rates to generate an
achievement or improvement score, domain scores, or a TPS. We
considered retaining our current scoring policy for PY 2022. However,
we concluded that this was not feasible because of the EQRS system
issues described in section IV.B.2, and additionally, due to the impact
of the COVID-19 PHE on some of the PY 2022 ESRD QIP measures, as
described more fully in section IV.C. of this proposed rule. This
approach would help to ensure that a facility would not be penalized
due to extraordinary circumstances beyond the facility's control.
4. ETC Model
(1) Overview
Under the ESRD PPS under Medicare Part B, a single per-treatment
payment is made to an ESRD facility for all of the renal dialysis
services defined in section 1881(b)(14)(B) of the Act and furnished to
individuals for the treatment of ESRD in the ESRD facility or in a
patient's home. Under the Physician Fee Schedule, medical management of
an ESRD beneficiary receiving dialysis by a physician or other
practitioner is paid through the MCP. The ETC Model is a mandatory
payment model designed to test payment adjustments to certain dialysis
and dialysis-related payments, as discussed in the Specialty Care
Models final rule (85 FR 6114), for ESRD facilities and for Managing
Clinicians for claims with dates of service from January 1, 2021 to
June 30, 2027. The requirements for the ETC Model are set forth in 42
CFR part 512, subpart C. The changes proposed in this proposed rule
(discussed in detail in section V.B of this proposed rule) would impact
model payment adjustments for PPA Period 3, starting in July 1, 2023.
Under the current ETC Model, there are two payment adjustments
designed to increase rates of home dialysis and kidney transplantation
through financial incentives. The HDPA is an upward payment adjustment
on certain home dialysis claims for ESRD facilities, as described in
Sec. Sec. 512.340 and 512.350, and to certain home dialysis-related
claims for Managing Clinicians, as described in Sec. Sec. 512.345 and
512.350, during the initial 3 years of the ETC Model.
The PPA is an upward or downward payment adjustment on certain
dialysis and dialysis-related claims submitted by ETC Participants, as
described in Sec. Sec. 512.375(a) and 512.380 for ESRD facilities and
Sec. Sec. 512.375(b) and 512.380 for Managing Clinicians, which will
apply to claims with claim service dates beginning on July 1, 2022 and
increase in magnitude over the duration of the ETC Model. We will
assess each ETC Participant's home dialysis rate, as described in Sec.
512.365(b), and transplant rate, as described in Sec. 512.365(c), for
each MY. The ETC Participant's transplant rate will be aggregated, as
described in Sec. 512.365(e), and the ETC Participant's home dialysis
rate will be aggregated, as described in Sec. 512.365(e). The ETC
Participant will receive a Modality Performance Score (MPS) based on
the weighted sum of the higher of the ETC Participant's achievement
score or improvement score for the home dialysis rate and the higher of
the ETC Participant's achievement score or improvement score for the
transplant rate, as described in Sec. 512.370(d).
For MY1 and MY2 (January 1, 2021 through July 6, 2022), the
achievement scores will be calculated in relation to a set of
benchmarks based on the historical rates of home dialysis and inclusion
on the transplant waitlist among ESRD facilities and Managing
Clinicians located in Comparison Geographic Areas. The improvement
scores will be calculated in relation to a set of benchmarks based on
the ETC Participant's own historical performance. The ETC Participant's
MPS for a MY will determine the magnitude of its PPA during the
corresponding 6-month PPA Period, which will begin 6 months after the
end of the MY. An ETC Participant's MPS will be updated on a rolling
basis every 6 months.
As mentioned in section IV.C.2.b(1) of the Specialty Care Models
final rule (85 FR 61351), the intention was to increase these
benchmarks over time through subsequent notice and comment
[[Page 36422]]
rulemaking. In this proposed rule, the changes listed with bullets are
being proposed for MY3 (beginning January 1, 2022) through the final MY
of ETC Model (MY10). More detail on these changes is provided in
section V.B of this proposed rule. The proposed changes that are most
likely to affect the impact estimate for the ETC Model are:
Include nocturnal in-center dialysis in the home dialysis
rate calculation for Managing Clinicians and ESRD facilities not owned
in whole or in part by an ETC LDO.
Exclude beneficiaries with a diagnosis of and who are
receiving chemotherapy or radiation for vital solid organ cancer from
the transplant rate calculation.
Modify the PPA achievement benchmarking methodology:
++ Stratify the home dialysis and transplant rate benchmark by the
proportion of beneficiaries who are dual-eligible for Medicare and
Medicaid, or, receive the Low-Income Subsidy (LIS), resulting in two
strata.
++ Increase the home dialysis and transplant rate benchmarks by 10
percent for each MY couplet (that is, 1.10 for MY3 and MY4, 1.20 for
MY5 and MY6, 1.30 for MY7 and MY8, and 1.40 for MY9 and MY10).
Modify the PPA improvement benchmarking methodology:
++ Health Equity Incentive: Participants can earn 0.5 improvement
points in addition to their improvement score for a significant
increase in the rate of dual eligible or LIS recipient beneficiaries.
++ Modify improvement calculation to ensure that the Benchmark Year
rate cannot be zero, such that improvement is calculable for all
participants.
The ETC Model is not a total cost of care model. ETC Participants
will still bill FFS Medicare, and items and services not subject to the
ETC Model's payment adjustments will continue to be paid as they would
in the absence of the Model.
(2) Data and Methods
A stochastic simulation was created to estimate the financial
impacts of the proposed changes to the ETC Model relative to baseline
expenditures, where baseline expenditures were defined as data from CYs
2018 and 2019 without the proposed changes applied. The simulation
relied upon statistical assumptions derived from retrospectively
constructed ESRD facilities' and Managing Clinicians' Medicare dialysis
claims, transplant claims, and transplant waitlist data reported during
2018 and 2019, the most recent years with complete data available. Both
datasets and the risk-adjustment methodologies for the ETC Model were
developed by the CMS Office of the Actuary (OACT).
The ESRD facilities and Managing Clinicians datasets were
restricted to the following eligibility criteria. Beneficiaries must be
residing in the United States, 18 years of age or older, and enrolled
in Medicare Part B. Beneficiaries enrolled in Medicare Advantage or
other cost or Medicare managed care plans, who have elected hospice,
are receiving dialysis for acute kidney injury (AKI) only, with a
diagnosis of dementia, who are receiving dialysis in a nursing
facility, or reside in a skilled nursing facility were excluded. In
addition, beneficiaries who have a diagnosis of and are receiving
treatment with chemotherapy or radiation for a vital solid organ cancer
were excluded from the transplant rate calculations. Diagnosis of a
vital solid organ cancer was defined as a beneficiary that had a claim
with any of 39 ICD-10-CM codes ranging from C22.0 through C79.02.
Treatment of a vital solid organ cancer was defined as a beneficiary
with a claim with any of 2,087 radiation administration ICD-10-PCS
codes, 19 chemotherapy administration CPT codes, or 41 radiation
administration CPT codes. Last, the HRR was matched to the claim
service facility zip code or the rendering physician zip code for ESRD
facility and Managing Clinician, respectively.
For the modeling exercise used to estimate changes in payment to
providers and suppliers and the resulting savings to Medicare, OACT
maintained the previous method to identify ESRD facilities with common
ownership, the low-volume exclusion threshold, and the aggregation
assumptions as CMS has not proposed changes to these model policies. To
clarify OACT's methodology, the ESRD facilities' data were aggregated
to the CMS Certification Number (CCN) level for beneficiaries on
dialysis identified by outpatient claims with Type of Bill 072X to
capture all dialysis services furnished at or through ESRD facilities.
Beneficiaries receiving home dialysis services were defined as
condition codes 74 and 76 (Sec. 512.340). Condition code 75 was
removed from the home dialysis definition because that billing code is
no longer in use. Condition code 80 was removed because we want to
exclude beneficiaries who received home dialysis furnished in a SNF or
nursing facility. Beneficiaries receiving in-center dialysis services
were defined using condition code 71. Two new variables were created:
In-center self-dialysis, condition code 72 (Sec. 512.365) and in-
center nocturnal dialysis, based on any of the claims' lines 1-5 HCPCS
codes equal to the ``UJ'' modifier. Self-care in training and ESRD
self-care retraining, condition codes 73 and 87, respectively, were
only included in the denominator for the home dialysis rate
calculation. For consistency with the exclusion in Sec. 512.385(a),
after grouping within each HRR, aggregated ESRD facilities with less
than 132 total attributed beneficiary months during a given MY were
excluded. When constructing benchmarks, for consistency with the
methodology for aggregating performance for purposes of the PPA
calculation, we aggregated all ESRD facilities owned in whole or in
part by the same dialysis organization located in the same HRR.
The Managing Clinicians' performance data were aggregated to the
Tax Identification Number (TIN) level (for group practices) and the
individual National Provider Identifier (NPI) level (for solo
practitioners). For purposes of calculating the home dialysis rate,
beneficiaries on home dialysis were identified using outpatient claims
with CPT[supreg] codes 90965 and 90966 (Sec. 512.345). Beneficiaries
receiving in-center dialysis were identified by outpatient claims with
CPT[supreg] codes 90957, 90958, 90959, 90960, 90961, and 90962 (Sec.
512.360). Last, following the low-volume threshold described in Sec.
512.385(b), after grouping within each HRR, Managing Clinicians with
less than 132 total attributed beneficiary months during a given MY
were excluded.
The Scientific Registry of Transplant Recipients (SRTR) transplant
waitlist data were obtained from the Center for Clinical Standards and
Quality (CCSQ). To construct the transplant waitlist rate, the
numerator was based on per-patient counts and included every addition
to the waitlist for a patient in any past year. The waitlist counts for
the numerator included waitlists for kidney transplants, alone or with
another organ, active and inactive records, multi-organ listings, and
patients that have subsequently been removed from the waitlist. The
denominator was a unique count of prevalent dialysis patients as of the
end of the year. Only patients on dialysis as of December 31st for the
selected year were included. Facility attribution was based on the
facility the patient was admitted to on the last day of the year.
For MY1 and MY2, the home dialysis score and transplant score for
the PPA were calculated using the following methodology for the ESRD
facilities and Managing Clinicians. ETC Participant
[[Page 36423]]
behavior for each year was simulated by adjusting the ETC Participant's
baseline home dialysis (or transplant) rate for a simulated statistical
fluctuation and then summing with the assumed increase in home dialysis
(or transplant) rate multiplied by a randomly generated improvement
scalar. The achievement and improvement scores were assigned by
comparing the ETC Participant's simulated home dialysis (or transplant)
rate for the MY to the percentile distribution of home dialysis (or
transplant) rates in the prior year. Last, the MPS was calculated using
the weighted sum of the higher of the achievement or improvement score
for the home dialysis rate and the transplant waitlist rate. The home
dialysis rate constituted two-thirds of the MPS, and the transplant
rate one-third of the MPS.
For MY3 through MY10, the home dialysis rate calculation accounts
for modifications proposed in this proposed rule. For Managing
Clinicians, the proposed revisions include changing the numerator for
the home dialysis rate from the home dialysis beneficiary months to the
home dialysis beneficiary months + 0.5(in-center self-dialysis
beneficiary months) + 0.5*(nocturnal in-center dialysis beneficiary
months), such that 1-beneficiary year is comprised of 12-beneficiary
months. The proposed revision for the numerator of the home dialysis
rate for ESRD facilities varied if the facility was owned in whole or
in part by an ETC LDO, as identified by ownership information for the
associated CCN. If the CCN had facilities owned by an ETC LDO, then the
proposed numerator for the home dialysis rate was the home dialysis
beneficiary months + 0.5*(in-center self-dialysis beneficiary months);
therefore, not including nocturnal in-center dialysis months from the
numerator. Otherwise, if the CCN did not have facilities owned by an
ETC LDO, then the numerator was the same as described above for
Managing Clinicians, such that the numerator for the home dialysis rate
was home dialysis beneficiary months + 0.5*(in-center self-dialysis
beneficiary months) + 0.5*(nocturnal in-center dialysis beneficiary
months).
The number of beneficiaries on in-center self-dialysis who met the
eligibility criteria for the ETC Model was very small, ranging from 102
to 277 over the period 2012-2019 and decreasing 89.9 percent to 22
beneficiaries in 2020 (based on preliminary 2020 data at CMS). With
such a small sample size, the growth rate vacillated significantly. In
addition, the in-center nocturnal dialysis UJ modifier code did not
become effective until January 1, 2017; therefore, there were
insufficient data to generate growth rate assumptions. The in-center
nocturnal dialysis beneficiary growth rate decreased by 91.3 percent in
2020. As a solution to these data limitations, to simulate the impact
of incorporating in-center self-dialysis and in-center nocturnal
dialysis for the purpose of the savings to Medicare estimate, the
simulation assumed any given ESRD facility or Managing Clinician would
have a one percent chance of receiving an increased achievement score
due to this policy proposal.
The overall process for generating achievement and improvement
scoring followed modeling from section VI.C.2 of the Specialty Care
Models final rule (85 FR 61352), with the exception of the following
changes.
Beginning for MY3 and beyond, the achievement benchmarking
methodology had two proposed modifications. First, the home dialysis
rate and transplant waitlist rate benchmarks were increased by a total
of 10 percent relative to ESRD facilities and Managing Clinicians not
selected for participation, every two MYs. To clarify, no changes to
the achievement benchmarking methodology were made to MYs 1 and 2. The
latter MY couplets' achievement benchmarking included the following
preset benchmark updates:
MYs 3 and 4: Comparison Geographic Area percentiles*1.10,
MYs 5 and 6: Comparison Geographic Area percentiles*1.20,
MYs 7 and 8: Comparison Geographic Area percentiles*1.30,
and
MYs 9 and 10: Comparison Geographic Area percentiles*1.40.
The percentiles represented the 30th, 50th, 75th, and 90th
percentile of the home dialysis rate and transplant rate for ESRD
facilities and Managing Clinicians not selected for participation. The
preset benchmark updates method provides greater certainty to ETC
Participants than the rolling updates in section IV.C.2.b(3) of the
Specialty Care Models final rule (85 FR 61353), which would have
involved updating benchmarks based on emerging trends over the most
recent experience periods for which data were available.
Second, in this proposed rule, we proposed to incorporate two
proxies for socioeconomic status, dual eligibility status or receipt of
the Low Income Subsidy (LIS), as part of the achievement benchmarking
starting for MY3 and beyond. Dual eligibility status was defined as a
Medicare beneficiary with any of the following full-time dual type
codes: 02=Eligible is entitled to Medicare Qualified Medicare
Beneficiary (QMB) and Medicaid coverage including prescription drugs,
04=Eligible is entitled to Medicare Specified Low-Income Medicare
Beneficiary (SLMB) and Medicaid coverage including prescription drugs,
or 08=Eligible is entitled to Medicare Other dual eligible with
Medicaid coverage including prescription drugs. Separately, a yes/no
indicator was created for any beneficiary that was either deemed or
determined by the Social Security Administration (SSA) to be receiving
the LIS. The home dialysis rate and transplant waitlist rate
achievement benchmarks were then stratified by the proportion of
attributed beneficiaries who are dual-eligible or receive the LIS. Two
strata were created with a cutpoint of approximately 50 percent for
participants with any dual-eligible or LIS recipient beneficiaries and
those who do not have beneficiaries meeting the socioeconomic status
proxies.
Third, a Health Equity Incentive was proposed for improvement
scoring starting in MY3. For the purpose of the estimates in this
Regulatory Impact Analysis, we incorporated a random variable to
simulate each ETC Participant's baseline variation and behavioral
improvement for each MY. If the participant's simulated improvement
behavior in MY3 through MY10 was greater than 5 percent, then the
participant received a 0.5 point increase on their improvement score,
allowing for a maximum of 2.0 total points.
For all MYs, the transplant waitlist benchmarks were annually
inflated by approximately 3-percentage points growth. This was a
modification from section VI.C.2 of the Specialty Care Models final
rule (85 FR 61352), where the waitlist benchmarks were annually
inflated by approximately 2-percentage points growth observed during
years 2017 through 2019 in the CCSQ data, to project rates of growth.
The additional 1 percentage point growth in this proposed rule was
included to account for uncertainty from the COVID-19 PHE disruption
and section 17006 of the 21st Century Cures Act (Cures Act) (Pub. L.
114-255), which amended the Act to increase enrollment options for
individuals with ESRD into Medicare Advantage. To clarify, applying the
3-percentage point annual growth from the median transplant waitlist
rate across HRR condensed facilities grew from 8 percent in 2017 to 11
percent in 2018 to 14 percent in 2019 (that is, not a growth rate of
1.03 percent per year).
To assess the impact of the COVID-19 PHE on the kidney transplant
[[Page 36424]]
waitlist, we analyzed data from the United Network for Organ Sharing
(UNOS).\305\. The UNOS data suggest that the number of new patients
added to the kidney transplant waitlist steadily decreased between the
weeks of March 15, 2020 through May 10, 2020, when between 16 to 81
percent of patients listed on the weekly kidney transplant waitlist
became inactive due to COVID-19 precautions. During July through
December 2020, the number of new patients added to the kidney
transplant waitlist increased to near pre-pandemic levels with an
average of less than 3 percent of patients listed as inactive due to
COVID-19. Anomalous dips in the number of new patients added to the
kidney transplant waitlist were observed during the weeks of November
22, 2020 and December 27, 2020, which correspond with federal holidays
in addition to a period that Americans were asked to social distance to
slow the spread of COVID-19. Continuing into the first quarter of 2021,
new additions to the kidney transplant waitlist remained at
approximately pre-pandemic rates. Therefore, we assume that the number
of new patients added to the waitlist will not decrease as a result of
the pandemic and the linear 2-percentage point growth rate for the
transplant waitlist calculated using years 2017 through 2019 CCSQ data
remains a reasonable assumption for baseline growth going forward. In
the proposed rule, we also included a 1 percent increase to the
standard error to account for a new variation assumption to address how
year-over-year changes could fluctuate at the ESRD facility or Managing
Clinician level, which was potentially exacerbated by the exclusion
criteria (that is, residents of a nursing facility, receiving dialysis
in a skilled nursing facility, dialysis for AKI only) applied to the
updated model data source used for estimates in this proposed rule.
---------------------------------------------------------------------------
\305\ UNOS. 2021. COVID-19 and Solid Organ Transplants.
Transplant and Waitlist Data Visualizations. https://unos.org/covid/
.
---------------------------------------------------------------------------
No changes were proposed to the payment structure for the HDPA
calculation described in the final rule (Sec. 512.350). As such, the
HDPA was calculated using the home dialysis and home dialysis-related
payments adjusted by decreasing amounts (3, 2, and 1 percent) during
each of the first 3 years of the Model.
The kidney disease patient education services utilization and cost
data were identified by codes G0420 and G0421, to capture face-to-face
individual and group training sessions for chronic kidney disease
beneficiaries on treatment modalities. The home dialysis training costs
for incident beneficiaries on home dialysis for Continuous Ambulatory
Peritoneal Dialysis (CAPD) or Continuous Cycler-Assisted Peritoneal
Dialysis (CCPD) were defined using CPT[supreg] codes 90989 and 90993
for complete and incomplete training sessions, respectively.
Data from CY 2019 were used to project baseline expenditures (that
is, expenditures before the proposed changes were applied) and the
traditional FFS payment system billing patterns were assumed to
continue under current law.
(3) Medicare Estimate--Primary Specification, Assume Proposed Benchmark
Updates
BILLING CODE 4120-01-P
[[Page 36425]]
[GRAPHIC] [TIFF OMITTED] TP09JY21.019
[[Page 36426]]
[GRAPHIC] [TIFF OMITTED] TP09JY21.020
BILLING CODE 4120-01-C
Table 18 summarizes the estimated impact of the ETC Model when
assuming preset benchmark updates where the achievement benchmarks for
each year are set using the average of the home dialysis rates for year
t-1 and year t-2 for the HRRs randomly selected for participation in
the ETC Model. We estimate the Medicare program will save a net total
of $53 million from the PPA and HDPA between January 1, 2021 and June
30, 2027 less $15 million in increased training and education
expenditures. Therefore, the net impact to Medicare spending is
estimated to be $38 million in savings. In Table 18 and Table 19,
negative spending reflects a reduction in Medicare spending, while
positive spending reflects an increase. The results for both tables
were generated from an average of 400 simulations under the assumption
that benchmarks are rolled forward with a 1.5-year lag.
Table 19 is provided to isolate the total impact of the changes
proposed in this proposed rule for years 2023 going forward by
calculating the difference from our final estimates in Table 18 less
totals from our current baseline estimates that used the same years of
data, but without the model changes applied. To clarify, the baseline
estimates are not the estimates reported in Table 19 of the Specialty
Care Models final rule (85 FR 61354); the final rule used data from CYs
2016 and 2017 and this proposed rule used the most recent data
available, from CYs 2018 and 2019. There was no impact reported in
years 2021 and 2022 since the proposed payment adjustments were not
effective until MY3. In addition, the proposed changes did not apply to
the HDPA or the Kidney Disease Patient Education Services Costs and HD
Training Costs. As expected, Table 19 shows that the proposed changes
had a very small effect on Medicare savings; only $7 million in savings
for the net impact to Medicare spending over the 4.5-year period can be
attributed to the changes proposed in this rule.
As was the case in the Specialty Care Models final rule (85 FR
61353), the projections do not include the Part B premium revenue
offset because the payment adjustments under the ETC Model will not
affect beneficiary cost-sharing. Any potential effects on Medicare
Advantage capitation payments were also excluded from the projections.
This approach is consistent with how CMS has previously conveyed the
primary FFS effects anticipated for an uncertain model without also
assessing the potential impact on Medicare Advantage rates.
Returning to Table 18, as anticipated, the expected Medicare
program savings were driven by the net effect of the Facility PPA; a
reduction in Medicare spending of $74 million over the period from July
1, 2022 through June 30, 2027. In comparison, the net effect of the
Clinician PPA was only $9 million in Medicare savings. This estimate
was based on an empirical study of historical home dialysis utilization
and transplant waitlist rates for Medicare FFS beneficiaries that CMS
virtually attributed to ESRD facilities and to Managing Clinicians
based on the plurality of associated spending at the beneficiary level.
We analyzed the base variation in those facility/practice level
measures and simulated the effect of the payment policy assuming
providers and suppliers respond by marginally increasing their share of
patients utilizing home dialysis. Random variables were used to vary
the effectiveness that individual providers and suppliers might show in
such progression over time and to simulate the level of year-to-year
variation already noted in the base multi-year data that was analyzed.
The uncertainty in the projection was illustrated in sections
VII.C.2.b.(3)(a) and VII.C.2.b.(3)(b) of the Specialty Care Models
final rule (85 FR 61354), respectively, through alternate scenarios
assuming that the benchmarks against which ETC Participants are
measured were to not be updated. In those sensitivity analyses, we
analyzed a modified version of the model that included a fixed
benchmark for the home dialysis and transplant waitlist rates as well
as a separate sensitivity analysis that assumed a rolling benchmark for
the home dialysis rate and a fixed benchmark for the transplant
waitlist rate.
For this proposed rule, we are modeling a preset benchmark growth
rate as proposed in this rule but continue to incorporate sensitivity
to a range of potential behavioral changes for the home dialysis rate
and transplant waitlist rate for ETC facilities and Managing Clinicians
assumed to participate in the model. Kidney disease patient education
services on treatment modalities and home dialysis (HD) training for
incident dialysis beneficiaries are relatively small outlays
[[Page 36427]]
and were projected to represent only relatively modest increases in
Medicare spending each year.
The key assumptions underlying the impact estimate are that each
consolidated ESRD facility or Managing Clinician's share of total
maintenance dialysis provided in the home setting was assumed to grow
by up to an assumed maximum growth averaging 3-percentage points per
year. Factors underlying this assumption about the home dialysis growth
rate include: Known limitations that may prevent patients from being
able to dialyze at home, such as certain common disease types that make
peritoneal dialysis impractical (for example, obesity); current
equipment and staffing constraints; and the likelihood that a patient
new to maintenance dialysis starts dialysis at home compared to the
likelihood that a current dialysis patient who dialyzes in center
switches to dialysis at home. In any given trial of the simulation, the
maximum growth rate was chosen from a uniform distribution of 0 to 5-
percentage points per year. Preliminary data from CMS show that the
growth rate for home dialysis was 3.9 percent in CY 2020 for
beneficiaries meeting the eligibility criteria for the ETC Model. This
growth rate is within range to what was observed prior to the
establishment of the Advancing American Kidney Health initiative in
2019 and it also shows that the COVID-19 PHE did not cause the home
dialysis growth assumption to become invalid. The 3-percentage point
per year average max growth rate will, in effect, move the average
market peritoneal dialysis rate (about 10 percent) to the highest
market baseline peritoneal dialysis rate (for example, Bend, Oregon HRR
at about 25 percent), which we believe is a reasonable upper bound on
growth over the duration of the ETC Model for the purposes of this
actuarial model.
Consolidated ESRD facilities at the HRR level or Managing
Clinicians were assumed to achieve anywhere from zero to 100 percent of
such maximum growth in any given year. Thus, the average projected
growth for the share of maintenance dialysis provided in the home was
1.5-percentage points per year (expressed as the percentage of total
dialysis). In contrast, we do not include an official assumption that
the overall number of kidney transplants will increase and provide
justification for this assumption in sections VI.C.2.b.(4) and
VI.C.2.b.(5) of the Specialty Care Models final rule (85 FR 61355).
However, as part of the sensitivity analysis for the savings
calculations for the model, we laid out a different savings scenario if
the ETC Learning Collaborative described in VI.C.2.b.(6) of the
Specialty Care Models final rule (85 FR 61355) were to be successful in
decreasing the discard rate of deceased donor kidneys and increasing
the utilization rate of deceased donor kidneys that have been
retrieved.
(a) Sensitivity Analysis: Medicare Savings Estimate--Results for the
10th and 90th Percentiles
Using the primary specification for the Medicare estimate with
preset benchmark updates for home dialysis and transplant waitlist
rates, we compare the results for the top 10th and 90th percentiles of
the 400 individual simulations to the average of all simulation results
reported in Table 18. Since the impact on Medicare spending for the ETC
Model using the present benchmark updates is estimated to be in savings
rather than losses, the top 10th and 90th percentiles represent the
most optimistic and conservative projections, respectively. The overall
net PPA and HDPA for the top 10th and 90th percentiles using the
present benchmark updates method are $117 million in savings and $3
million in losses (encompassing the mean estimate of $53 million in
savings in Table 18). The overall uncertainty of the impact of the
model is further illustrated in Table 18, the change from baseline,
where the mean $7 million dollars in savings reported for the Overall
PPA Net & HDPA has $83 million in savings and $75 million in losses,
for the top 10th and 90th percentiles, respectively.
(4) Effects on the Home Dialysis Rate
This proposed rule proposes to modify the home dialysis rate
equation by adding 0.5 multiplied by the sum of the self-dialysis
beneficiary months and the in-center nocturnal dialysis beneficiary
months to the numerator such that 1-beneficiary year is comprised of
12-beneficiary months. The proposed modification was different for ESRD
facilities with an aggregation group that had facilities owned by an
ETC LDO, for which the nocturnal dialysis months were not included in
the numerator.
Less than 1 percent of beneficiaries eligible for attribution into
the ETC Model were receiving either self-dialysis or nocturnal in-
center dialysis in CY 2019. In addition, in CY 2020, the annual growth
rate decreased by 89.9 and 91.3 percent for beneficiaries receiving
self-dialysis or nocturnal dialysis, respectively. The sharp decline in
these dialysis modalities is potentially in response to the COVID-19
pandemic. The low historical take-up for self-dialysis and shortage of
historical years for nocturnal dialysis (that is, a nocturnal dialysis
claims line instruction became effective in 2017) result in these
proposed modifications having an insignificant impact on the savings to
Medicare.
Two of the changes proposed in this proposed rule have the
potential to generate higher PPA scores for a limited subset of
providers and therefore a small negative impact on estimated savings
for the model. First, we proposed two strata for the achievement and
improvement benchmarking based on a 50 percent cutpoint for the
proportion of attributed beneficiaries with dual eligibility status or
receipt of the LIS. This proposed modification would allow participants
to be compared to participants who serve ESRD patients with a similar
socioeconomic status, essentially making the comparison groups fairer
and potentially increasing the cost to Medicare. Second, the proposed
Health Equity Incentive rewarded participants with 0.5 points to their
improvement score who demonstrated a sufficiently significant
improvement on the home dialysis rate among their attributed
beneficiaries who are dual eligible or receive the LIS.
Furthermore, we modeled the home dialysis rate achievement and
improvement benchmarks by incrementally increasing every two
measurement periods the benchmarks by 10 percent relative to ESRD
facilities and Managing Clinicians not selected for participation.
Applying the preset benchmarks update method balanced out the negative
impact to Medicare savings generated from stratification and the Health
Equity Incentive, essentially preserving the overall savings level
reported in the Specialty Care Models final rule.
(5) Effects on Kidney Transplantation
Kidney transplantation is considered the optimal treatment for most
ESRD beneficiaries. The PPA includes a one-third weight on the ESRD
facilities' or Managing Clinician's transplant waitlist rate, with the
ultimate goal of increasing the rate of kidney transplantation.
However, the changes proposed in this proposed rule do not impact our
decision in the previous final rule to not include an assumption that
the overall number of kidney transplants will increase. The number of
ESRD patients on the kidney transplant waitlist has for many years far
exceeded the annual number of transplants performed. Transplantation
rates have not increased to meet such demand because of the limited
supply of deceased donor
[[Page 36428]]
kidneys. The U.S. Renal Data System \306\ reported 22,393 kidney
transplants in 2018 compared to a kidney transplant waiting list \307\
of over 98,000. Refer to section VI.C.2.b(4) in the Specialty Care
Models final rule (85 FR 61355) for a detailed justification for our
assumption that the overall number of kidney transplants will not
increase in response to ESRD facilities and Managing Clinicians
participating in the ETC Model.
---------------------------------------------------------------------------
\306\ United States Renal Data System. 2020. ``ADR Reference
Table E6 Renal Transplants by Donor Type.'' https://adr.usrds.org/2020/reference-tables.
\307\ Organ Procurement and Transplantation Network. 2021.
``Current US Waiting List, Overall by Organ.'' https://optn.transplant.hrsa.gov/data/view-data-reports/national-data/#.
---------------------------------------------------------------------------
(6) Effects of the Transplant Waitlist Rate
This proposed rule includes the transplant waitlist rate described
in the Specialty Care Models final rule (Sec. 512.365) with the
following proposed modifications. First, we are proposing to exclude
Medicare beneficiaries with a diagnosis of and treatment with
chemotherapy or radiation for vital solid organ cancers. In our
analysis of beneficiaries' eligible for the ETC Model, we found that
less than 1 percent of the beneficiaries had claims for any vital solid
organ cancers. Therefore, the effect of this proposed exclusion
criterion is to make the beneficiaries included in the calculation of
the transplant rate an improved representation of beneficiaries who are
able to join the transplant waitlist and/or receive pre-emptive living
donor kidney transplantation. But, due to the very low number of ETC
Model potential beneficiaries with these types of cancer, the exclusion
criterion is unlikely to have any significant impact on the transplant
waitlist rate.
Two of the changes proposed in this proposed rule have the
potential to generate higher scores for a limited subset of health care
providers and therefore a small negative impact on estimated savings
for the model. First, we proposed two strata for the achievement and
improvement benchmarking based on a 50 percent cutpoint for the
proportion of attributed beneficiaries with dual eligibility status or
receipt of the LIS. This proposed modification allowed participants to
be compared to participants who serve ESRD patients with a similar
socioeconomic status, essentially making the comparison groups fairer
and potentially increasing the cost to Medicare. Second, the proposed
Health Equity Incentive rewarded participants with 0.5 points to their
improvement score who demonstrated a sufficiently significant
improvement on the transplant rate among their attributed beneficiaries
who are dual eligible or receive the LIS.
Furthermore, we proposed to modify the transplant waitlist rate
achievement and improvement benchmarks by incrementally increasing the
benchmarks every two measurement periods by 10 percent relative to ESRD
facilities and Managing Clinicians not selected for participation.
Applying the preset benchmarks update method balanced out the negative
impact to Medicare savings generated from the proposed stratification
and the Health Equity Incentive, roughly preserving the overall savings
level estimated at baseline for the model parameters previously
finalized before the changes offered in this proposed rule.
(7) Effects on Kidney Disease Patient Education Services and HD
Training Add-Ons
The changes in this proposed rule do not impact the findings
reported for the effects of the ETC Model on the Kidney Disease Patient
education services and HD training add-ons described in section
VI.C.2.b(6) in the Specialty Care Models final rule (85 FR 61355).
b. Effects on Medicare Beneficiaries
The changes in this proposed rule could incentivize ESRD facilities
and Managing Clinicians serving dual eligible or LIS recipient Medicare
beneficiaries to potentially improve access to care for those
beneficiaries. The changes could also marginally improve take-up of the
in-center nocturnal dialysis treatment modality compared to how the
model was finalized previously since these dialysis methods were not
directly incentivized (that is, accounted for in the home dialysis rate
and in-center self dialysis rate numerator) in the Specialty Care
Models final rule.
As previously noted in section VI.C.3.B of the Specialty Care
Models final rule (85 FR 61357), we continue to anticipate that the ETC
Model would have a negligible impact on the cost to beneficiaries
receiving dialysis. Under current policy, Medicare FFS beneficiaries
are generally responsible for 20 percent of the allowed charge for
services furnished by providers and suppliers. This policy will remain
the same under the ETC Model. However, we will waive certain
requirements of title XVIII of the Act as necessary to test the PPA and
HDPA under the ETC Model and to hold beneficiaries harmless from any
effect of these payment adjustments on cost sharing. In addition, the
Medicare beneficiary's quality of life has the potential to improve if
the beneficiary elects to have home dialysis as opposed to in-center
dialysis. Studies have found that home dialysis patients experienced
improved quality of life as a result of their ability to continue
regular work schedules or life plans; as well as better overall,
physical, and psychological health in comparison to other dialysis
options.
c. Alternatives Considered
Throughout this proposed rule, we have identified our policies and
alternatives that we have considered, and provided information as to
the likely effects of these alternatives and the rationale for each of
our policies.
This proposed rule addresses a model specific to ESRD. It provides
descriptions of the requirements that we would waive, identifies the
performance metrics and payment adjustments proposed to be tested, and
presents rationales for our proposals, and where relevant, alternatives
that we considered. We carefully considered the alternatives to this
proposed rule, including the degree that benchmark targets should be
prospectively updated to provide greater transparency to ETC
Participants while preserving the expectation for model net savings for
the program. For context related to alternatives previously considered
when establishing the ETC Model we refer readers to the Specialty Cares
Model final rule (85 FR 61114) for more information on policy-related
stakeholder comments, our responses to those comments, and statements
of final policy preceding the limited modifications proposed here.
C. Accounting Statement
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 20, we have prepared an accounting statement showing
the classification of the transfers and costs associated with the
various provisions of this proposed rule.
[[Page 36429]]
[GRAPHIC] [TIFF OMITTED] TP09JY21.021
In accordance with the provisions of Executive Order 12866, this
proposed rule was reviewed by the Office of Management and Budget.
D. Regulatory Flexibility Act Analysis (RFA)
The Regulatory Flexibility Act (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. Approximately 11
percent of ESRD dialysis facilities are considered small entities
according to the Small Business Administration's (SBA) size standards,
which classifies small businesses as those dialysis facilities having
total revenues of less than $41.5 million in any 1 year. Individuals
and states are not included in the definitions of a small entity. For
more information on SBA's size standards, see the Small Business
Administration's website at http://www.sba.gov/content/small-business-size-standards (Kidney Dialysis Centers are listed as 621492 with a
size standard of $41.5 million).
When viewed as individual entities, as opposed to being a part of
an LDO, there are approximately 643 (~12 percent of total number of
ESRD facilities) ESRD facilities that provide fewer than 4,000
treatments per year. With a low volume payment adjustment, each
facility generates revenue from dialysis treatments of ~$1.26 million
per year per facility. This is shown in the Table 21.
[[Page 36430]]
[GRAPHIC] [TIFF OMITTED] TP09JY21.022
We do not believe ESRD facilities are operated by small government
entities such as counties or towns with populations of 50,000 or less,
and therefore, they are not enumerated or included in this estimated
RFA analysis. Individuals and states are not included in the definition
of a small entity.
For purposes of the RFA, we estimate that approximately 11 percent
of ESRD facilities are small entities as that term is used in the RFA
(which includes small businesses, nonprofit organizations, and small
governmental jurisdictions). This amount is based on the number of ESRD
facilities shown in the ownership category in Table 9. Using the
definitions in this ownership category, we consider 515 facilities that
are independent and 378 facilities that are shown as hospital-based to
be small entities. The ESRD facilities that are owned and operated by
Large Dialysis Organizations (LDOs) and regional chains would have
total revenues of more than $41.5 million in any year when the total
revenues for all locations are combined for each business (individual
LDO or regional chain), and are not, therefore, included as small
entities.
For the ESRD PPS updates proposed in this rule, a hospital-based
ESRD facility (as defined by type of ownership, not by type of dialysis
facility) is estimated to receive a 1.3 percent increase in payments
for CY 2022. An independent facility (as defined by ownership type) is
estimated to receive a 1.1 percent increase in payments for CY 2022.
For AKI dialysis, we are unable to estimate whether patients would
go to ESRD facilities, however, we have estimated there is a potential
for $52 million in payment for AKI dialysis treatments that could
potentially be furnished in ESRD facilities.
For ETC Model, this proposed rule includes as ETC Participants
Managing Clinicians and ESRD facilities required to participate in the
Model pursuant to Sec. 512.325(a). We assume for the purposes of the
regulatory impact analysis that the great majority of Managing
Clinicians are small entities and that the greater majority of ESRD
facilities are not small entities. Throughout the proposed rule we
describe how the adjustments to certain payments for dialysis services
and dialysis-related services furnished to ESRD beneficiaries may
affect Managing Clinicians and ESRD facilities participating in the ETC
Model. The great majority of Managing Clinicians are small entities by
meeting the SBA definition of a small business (having minimum revenues
of less than $8 million to $41.5 million in any 1 year, varying by type
of provider and highest for hospitals) with a minimum threshold for
small business size of $41.5 million (https://www.sba.gov/document/support--table-size-standards http://www.sba.gov/content/small-businesssize-standards). The great majority of ESRD facilities are not
small entities, as they are owned, partially or entirely by entities
that do not meet the SBA definition of small entities.
The HDPA in the ETC Model is a positive adjustment on payments for
specified home dialysis and home dialysis-related services. The PPA in
the ETC Model, which includes both positive and negative adjustments on
payments for dialysis services and dialysis-related services, excludes
aggregation groups with fewer than 132 attributed beneficiary-months
during the relevant year.
The aggregation methodology groups ESRD facilities owned in whole
or in part by the same dialysis organization within a Selected
Geographic Area and Managing Clinicians billing under the same TIN
within a Selected Geographic Area. This aggregation policy increases
the number of beneficiary months, and thus statistical reliability, of
the ETC Participant's home dialysis and transplant rate for ESRD
facilities that are owned in whole or in part by the same dialysis
organization and for Managing Clinicians that share a TIN with other
Managing Clinicians.
Taken together, the low volume threshold exclusions and aggregation
policies previously described, coupled with the fact that the ETC Model
would affect Medicare payment only for select services furnished to
Medicare FFS beneficiaries; we have determined that the provisions of
the proposed rule would not have a significant impact on spending for a
substantial number of small entities (defined as greater than 5 percent
impact).
Therefore, the Secretary has determined that this proposed rule
would not have a significant economic impact on a substantial number of
small entities. 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. We solicit comment on the RFA analysis
provided.
In addition, section 1102(b) of the Act requires us to prepare a
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
[[Page 36431]]
of the RFA. For purposes of section 1102(b) of the Act, we define a
small rural hospital as a hospital that is located outside of a
metropolitan statistical area and has fewer than 100 beds. We do not
believe this proposed rule would have a significant impact on
operations of a substantial number of small rural hospitals because
most dialysis facilities are freestanding. While there are 122 rural
hospital-based dialysis facilities, we do not know how many of them are
based at hospitals with fewer than 100 beds. However, overall, the 122
rural hospital-based dialysis facilities would experience an estimated
1.0 percent increase in payments.
Therefore, the Secretary has determined that this proposed rule
would not have a significant impact on the operations of a substantial
number of small rural hospitals.
E. Unfunded Mandates Reform Act Analysis (UMRA)
Section 202 of the Unfunded Mandates Reform Act 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 2021, that
threshold is approximately $158 million. This proposed rule does not
mandate any requirements for state, local, or tribal governments in the
aggregate, or by the private sector. Moreover, HHS interprets UMRA as
applying only to unfunded mandates. We do not interpret Medicare
payment rules as being unfunded mandates, but simply as conditions for
the receipt of payments from the federal government for providing
services that meet federal standards. This interpretation applies
whether the facilities or providers are private, state, local, or
tribal.
F. 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 the threshold
criteria of Executive Order 13132, Federalism, and have determined that
it would not have substantial direct effects on the rights, roles, and
responsibilities of states, local or Tribal governments.
G. Congressional Review Act
These proposed rules are subject to the Congressional Review Act
provisions of the Small Business Regulatory Enforcement Fairness Act of
1996 (5 U.S.C. 801 et seq.) and has been transmitted to the Congress
and the Comptroller General for review.
X. Files Available to the Public via the Internet
The Addenda for the annual ESRD PPS proposed and final rulemakings
will no longer appear in the Federal Register. Instead, the Addenda
will be available only through the internet and is posted on the CMS
website at http://www.cms.gov/ESRDPayment/PAY/list.asp. In addition to
the Addenda, limited data set files are available for purchase at
http://www.cms.gov/Research-Statistics-Data-and-Systems/Files-for-Order/LimitedDataSets/EndStageRenalDiseaseSystemFile.html. Readers who
experience any problems accessing the Addenda or LDS files, should
contact [email protected].
Chiquita Brooks-LaSure, Administrator of the Centers for Medicare &
Medicaid Services, approved this document on June 16, 2021.
List of Subjects
42 CFR Part 413
Diseases, Health facilities, Medicare, Puerto Rico, Reporting and
recordkeeping requirements.
42 CFR Part 512
Administrative practice and procedure, Health facilities, Medicare,
Reporting and recordkeeping requirements.
For the reasons set forth in the preamble, the Centers for Medicare
& Medicaid Services proposes to amend 42 CFR chapter IV as follows:
PART 413--PRINCIPLES OF REASONABLE COST REIMBURSEMENT; PAYMENT FOR
END-STAGE RENAL DISEASE SERVICES; PROSPECTIVELY DETERMINED PAYMENT
RATES FOR SKILLED NURSING FACILITIES; PAYMENT FOR ACUTE KIDNEY
INJURY DIALYSIS
0
1. The authority citation for part 413 continues to read as follows:
Authority: 42 U.S.C. 1302, 1395d(d), 1395f(b), 1395g, 1395l(a),
(i), and (n), 1395x(v), 1395hh, 1395rr, 1395tt, and 1395ww.
0
2. Section 413.177 is amended by revising paragraph (a) introductory
text to read as follows:
Sec. 413.177 Quality incentive program payment.
(a) With respect to renal dialysis services as defined under Sec.
413.171, except for those renal dialysis services furnished during
payment year 2022, in the case of an ESRD facility that does not earn
enough points under the program described at Sec. 413.178 to meet or
exceed the minimum total performance score (as defined at Sec.
413.178(a)(8)) established by CMS for a payment year (as defined at
Sec. 413.178(a)(10)), payments otherwise made to the facility under
Sec. 413.230 for renal dialysis services during the payment year, will
be reduced by up to 2 percent as follows:
0
3. Section 413.178 is amended by adding paragraph (h) to read as
follows:
Sec. 413.178 ESRD quality incentive program.
* * * * *
(h) Special rule for payment year 2022. (1) CMS will calculate a
measure rate for all measures specified by CMS under paragraph (c) of
this section for the PY 2022 ESRD QIP but will not score facility
performance on any of those measures or calculate a TPS for any
facility under paragraph (e) of this section.
(2) CMS will not establish a mTPS for PY 2022.
PART 512--RADIATION ONCOLOGY MODEL AND END STAGE RENAL DISEASE
TREATMENT CHOICES MODEL
0
4. The authority citation for part 512 continues to read as follows:
Authority: 42 U.S.C. 1302, 1315(a), and 1395hh.
0
5. Section 512.160 is amended by adding paragraph (a)(9), and by
revising paragraph (b)(6) as follows:
Sec. 512.160 Remedial action.
(a) * * *
(9) For the ETC Model only, has misused or disclosed the
beneficiary-identifiable data in a manner that violates any applicable
statutory or regulatory requirements or that is otherwise non-compliant
with the provisions of the applicable data sharing agreement.
(b) * * *
(6) In the ETC Model only:
(i) Terminate the ETC Participant from the ETC Model.
(ii) Suspend or terminate the ability of the ETC Participant,
pursuant to Sec. 512.397(c), to reduce or waive the
[[Page 36432]]
coinsurance for kidney disease patient education services.
0
6. Section 512.310 is amended by adding the definitions of ``Clinical
staff'', ``Health Equity Incentive'', ``Kidney disease patient
education services coinsurance patient incentive'', and ``Qualified
staff'' in alphabetical order to read as follows:
Sec. 512.310 Definitions.
* * * * *
Clinical staff means a licensed social worker or registered
dietician/nutrition professional who furnishes services for which
payment may be made under the physician fee schedule under the
direction of and incident to the services of the Managing Clinician who
is an ETC Participant.
* * * * *
ETC Large Dialysis Organization (ETC LDO) means a legal entity that
owns, in whole or in part, 500 or more ESRD facilities.
* * * * *
Health Equity Incentive means the amount added to the ETC
Participant's improvement score, calculated as described in Sec.
512.370(c)(1) of this chapter, if the ETC Participant's aggregation
group demonstrated sufficient improvement on the home dialysis rate or
transplant rate for attributed beneficiaries who are dual eligible or
Medicare Low Income Subsidy (LIS) recipients between the Benchmark Year
and the MY.
* * * * *
Qualified staff means both clinical staff and any qualified person
(as defined at Sec. 410.48(a)) who is an ETC Participant.
* * * * *
0
7. Section 512.360 is amended by revising paragraph (c)(2)(ii)
introductory text and adding paragraph (c)(2)(iii) to read as follows:
Sec. 512.360 Beneficiary population and attribution.
* * * * *
(c) * * *
(2) * * *
(ii) For MY1 and MY2, a Pre-emptive LDT Beneficiary who is not
excluded based on the criteria in paragraph (b) of this section is
attributed to the Managing Clinician with whom the beneficiary has had
the most claims between the start of the MY and the month in which the
beneficiary received the transplant for all months between the start of
the MY and the month of the transplant.
* * * * *
(iii) For MY3 through MY10, a Pre-emptive LDT Beneficiary who is
not excluded based on the criteria in paragraph (b) of this section is
attributed to the Managing Clinician who submitted the most claims for
services furnished to the beneficiary in the 365 days preceding the
date in which the beneficiary received the transplant.
(A) If no Managing Clinician has had the most claims for a given
Pre-emptive LDT Beneficiary such that multiple Managing Clinicians each
had the same number of claims for that beneficiary in the 365 days
preceding the date of the transplant, the Pre-emptive LDT Beneficiary
is attributed to the Managing Clinician associated with the latest
claim service date at the claim line through date during the 365 days
preceding the date of the transplant.
(B) If no Managing Clinician had the most claims for a given Pre-
emptive LDT Beneficiary such that multiple Managing Clinicians each had
the same number of claims for that beneficiary in the 365 days
preceding the date of the transplant, and more than one of those
Managing Clinicians had the latest claim service date at the claim line
through date during the 365 days preceding the date of the transplant,
the Pre-emptive LDT Beneficiary is randomly attributed to one of these
Managing Clinicians.
(C) The Pre-emptive LDT Beneficiary is considered eligible for
attribution under this paragraph (c)(2)(iii) if the Pre-emptive LDT
Beneficiary has at least 1-eligible month during the 12-month period
that includes the month of the transplant and the 11 months prior to
the month of the transplant. An eligible month refers to a month during
which the Pre-emptive LDT Beneficiary not does not meet exclusion
criteria in paragraph (b) of this section.
0
8. Section 512.365 is amended by--
0
a. Revising paragraphs (b)(1)(ii) and (b)(2)(ii), and
0
b. Revising paragraphs (c)(1)(i)(A), (c)(1)(ii)(A), (c)(2)(i)(A), and
(c)(2)(ii)(A)(1) and (2).
The revisions read as follows:
Sec. 512.365 Performance assessment.
* * * * *
(b) * * *
(1) * * *
(ii) For MY1 and MY2, the numerator is the total number of home
dialysis treatment beneficiary years plus one half the total number of
self dialysis treatment beneficiary years for attributed ESRD
Beneficiaries during the MY. For MY3 through MY10, the numerator for
ESRD facilities owned in whole or in part by an ETC LDO is the total
number of home dialysis treatment beneficiary years plus one half the
total number of self dialysis treatment beneficiary years for
attributed ESRD Beneficiaries during the MY. For MY3 through MY10, the
numerator for ESRD facilities not owned in whole or in part by an ETC
LDO is the total number of home dialysis treatment beneficiary years,
plus one half the total number of self dialysis treatment beneficiary
years, plus one half the total number of nocturnal in center dialysis
beneficiary years for attributed ESRD Beneficiaries during the MY.
(A) Home dialysis treatment beneficiary years included in the
numerator are composed of those months during which attributed ESRD
Beneficiaries received maintenance dialysis at home, such that 1-
beneficiary year is comprised of 12-beneficiary months. Months in which
an attributed ESRD Beneficiary received maintenance dialysis at home
are identified by claims with Type of Bill 072X and condition codes 74
or 76.
(B) Self dialysis treatment beneficiary years included in the
numerator are composed of those months during which attributed ESRD
Beneficiaries received self dialysis in center, such that 1-beneficiary
year is comprised of 12-beneficiary months. Months in which an
attributed ESRD Beneficiary received self dialysis are identified by
claims with Type of Bill 072X and condition code 72.
(C) Nocturnal in center dialysis beneficiary years included in the
numerator are composed of those months during which attributed ESRD
Beneficiaries received nocturnal in center dialysis, such that 1-
beneficiary year is comprised of 12-beneficiary months. Months in which
an attributed ESRD Beneficiary received nocturnal in center dialysis
are identified by claims with Type of Bill 072X and modifier UJ.
* * * * *
(2) * * *
(ii) For MY1 and MY2, the numerator is the total number of home
dialysis treatment beneficiary years for attributed ESRD Beneficiaries
during the MY plus one half the total number of self dialysis treatment
beneficiary years. For MY3 through MY10, the numerator is the total
number of home dialysis treatment beneficiary years, plus one half the
total number of self dialysis treatment beneficiary years, plus one
half the total number of nocturnal in center dialysis beneficiary years
for attributed ESRD Beneficiaries during the MY.
(A) Home dialysis treatment beneficiary years included in the
numerator are composed of those months during which attributed ESRD
Beneficiaries received maintenance
[[Page 36433]]
dialysis at home, such that 1-beneficiary year is comprised of 12-
beneficiary months. Months in which an attributed ESRD Beneficiary
received maintenance dialysis at home are identified by claims with CPT
codes 90965 or 90966.
(B) Self-dialysis treatment beneficiary years included in the
numerator are composed of those months during which attributed ESRD
Beneficiaries received self dialysis in center, such that 1-beneficiary
year is comprised of 12-beneficiary months. Months in which an
attributed ESRD Beneficiary received self dialysis are identified by
claims with Type of Bill 072X and condition code 72.
(C) Nocturnal in center dialysis beneficiary years included in the
numerator are composed of those months during which attributed ESRD
Beneficiaries received nocturnal in center dialysis, such that 1-
beneficiary year is comprised of 12-beneficiary months. Months in which
an attributed ESRD Beneficiary received nocturnal in center dialysis
are identified by claims with Type of Bill 072X and modifier UJ.
* * * * *
(c) * * *
(1) * * *
(i) * * *
(A) The denominator is the total dialysis treatment beneficiary
years for attributed ESRD Beneficiaries during the MY. Dialysis
treatment beneficiary years included in the denominator are composed of
those months during which an attributed ESRD beneficiary received
maintenance dialysis at home or in an ESRD facility, such that 1-
beneficiary year is comprised of 12-beneficiary months. For MY1 and
MY2, months during which an attributed ESRD Beneficiary received
maintenance dialysis are identified by claims with Type of Bill 072X,
excluding claims for beneficiaries who were 75 years of age or older at
any point during the month. For MY3 through MY10, months during which
an attributed ESRD Beneficiary received maintenance dialysis are
identified by claims with Type of Bill 072X, excluding claims for
beneficiaries who were 75 years of age or older at any point during the
month, or had a vital solid organ cancer diagnosis and were receiving
treatment with chemotherapy or radiation for vital solid organ cancer
during the MY.
(1) An attributed ESRD Beneficiary had a diagnosis of vital solid
organ cancer in an MY if the beneficiary had any of the following
diagnosis codes on any claim during the MY or the 6 months prior to the
start of the MY: C22.0-C22.9, C34.10-C34.12, C34.2, C34.30-C34.32,
C34.80-C34.82, C34.90-C34.92, C38.0, C38.8, C46.50-C46.52, C64.1,
C64.2, C64.2, C78.00-C78.02, C78.7, C79.00-C79.02, C7A.090, C7A.093, or
C7B.02.
(2) Months in which an attributed ESRD Beneficiary received
treatment with chemotherapy or radiation for vital solid organ cancer
are months during which the beneficiary had a claim with any of the
following procedure codes:
(i) CPT[supreg] 96401-96402, 96405-96406, 96409, 96411, 96413,
96415-96417, 96420, 96422-26423, 96425, 96440, 96446, 96549, 77373,
77401-77402, 77407, 77412, 77423, 77424-77425, 77520, 77522-77523,
77525, 77761-77763, 77770-77772, 77778, 77789, 77799, 79005, 79101,
79200, 79300, 79403, 79440, 79445, 79999.
(ii) ICD-10-PCS[supreg] DB020ZZ, DB021ZZ, DB022ZZ, DB023Z0,
DB023ZZ, DB024ZZ, DB025ZZ, DB026ZZ, DB1297Z, DB1298Z, DB1299Z, DB129BZ,
DB129CZ, DB129YZ, DB12B6Z, DB12B7Z, DB12B8Z, DB12B9Z, DB12BB1, DB12BBZ,
DB12BCZ, DB12BYZ, DB22DZZ, DB22HZZ, DB22JZZ, DBY27ZZ, DBY28ZZ, DBY2FZZ,
DBY2KZZ, DB070ZZ, DB071ZZ, DB072ZZ, DB073Z0, DB073ZZ, DB074ZZ, DB075ZZ,
DB076ZZ, DB1797Z, DB1798Z, DB1799Z, DB179BZ, DB179CZ, DB179YZ, DB17B6Z,
DB17B7Z, DB17B8Z, DB17B9Z, DB17BB1, DB17BBZ, DB17BCZ, DB17BYZ, DB27DZZ,
DB27HZZ, DB27JZZ, DBY77ZZ, DBY78ZZ, DBY7FZZ, DBY7KZZ, DF000ZZ, DF001ZZ,
DF002ZZ, DF003Z0, DF003ZZ, DF004ZZ, DF005ZZ, DF006ZZ, DF1097Z, DF1098Z,
DF1099Z, DF109BZ, DF109CZ, DF109YZ, DF10B6Z, DF10B7Z, DF10B8Z, DF10B9Z,
DF10BB1, DF10BBZ, DF10BCZ, DF10BYZ, DF0DZZ, DF20HZZ, DF20JZZ, DFY07ZZ,
DFY08ZZ, DFY0CZZ, DFY0FZZ, DFY0KZZ, DT000ZZ, DT001ZZ, DT002ZZ, DT003Z0,
DT003ZZ, DT004ZZ, DT005ZZ, DT006ZZ, DT1097Z, DT1098Z, DT1099Z, DT109BZ,
DT109CZ, DT109YZ, DT10B6Z, DT10B7Z, DT10B8Z, DT10B9Z, DT10BB1, DT10BBZ,
DT10BCZ, DT10BYZ, DT20DZZ, DT20HZZ, DT20JZZ, DTY07ZZ, DTY08ZZ, DTY0CZZ,
DTY0FZZ, DW020ZZ, DW021ZZ, DW022ZZ, DW023Z0, DW023ZZ, DW024ZZ, DW025ZZ,
DW026ZZ, DW1297Z, DW1298Z, DW1299Z, DW129BZ, DW129CZ, DW129YZ, DW12B6Z,
DW12B7Z, DW12B8Z, DW12B9Z, DW12BB1, DW12BBZ, DW12BCZ, DW12BYZ, DW22DZZ,
DW22HZZ, DW22JZZ, DWY27ZZ, DWY28ZZ, DWY2FZZ, DW030ZZ, DW031ZZ, DW032ZZ,
DW033Z0, DW033ZZ, DW034ZZ, DW035ZZ, DW036ZZ, DW1397Z, DW1398Z, DW1399Z,
DW139BZ, DW139CZ, DW139YZ, DW13B6Z, DW13B7Z, DW13B8Z, DW13B9Z, DW13BB1,
DW13BBZ, DW13BCZ, DB13BYZ, DW23DZZ, DW23HZZ, DW23JZZ, DWY37ZZ, DWY38ZZ,
DWY3FZZ, DW050ZZ, DW051ZZ, DW052ZZ, DW053Z0, DW053ZZ, DW054ZZ, DW055ZZ,
DW056ZZ, DWY57ZZ, DWY58ZZ, DWY5FZZ, DWY5GDZ, DWY5GFZ, DWY5GGZ, DWY5GHZ,
DWY5GYZ.
* * * * *
(ii) * * *
(A) The denominator is the total dialysis treatment beneficiary
years for attributed ESRD Beneficiaries during the MY. Dialysis
treatment beneficiary years included in the denominator are composed of
those months during which an attributed ESRD Beneficiary received
maintenance dialysis at home or in an ESRD facility, such that 1-
beneficiary year is comprised of 12-beneficiary months. For MY1 and
MY2, months during which an attributed ESRD Beneficiary received
maintenance dialysis are identified by claims with Type of Bill 072X,
excluding claims for beneficiaries who were 75 years of age or older at
any point during the month. For MY3 through MY10, months during which
an attributed ESRD Beneficiary received maintenance dialysis are
identified by claims with Type of Bill 072X, excluding claims for
beneficiaries who were 75 years of age or older at any point during the
month, or had a vital solid organ cancer diagnosis and were receiving
treatment with chemotherapy or radiation for vital solid organ cancer
during the MY. Months in which an attributed ESRD Beneficiary had a
diagnosis of vital solid organ cancer are identified as described in
paragraph (c)(1)(i)(A)(1) of this section. Months in which an
attributed ESRD Beneficiary received treatment with chemotherapy or
radiation for vital solid organ cancer are identified as described in
paragraph (c)(1)(i)(A)(2) of this section.
* * * * *
(2) * * *
(i) * * *
(A) The denominator is the total dialysis treatment beneficiary
years for attributed ESRD Beneficiaries during the MY. Dialysis
treatment beneficiary years included in the denominator are composed of
those months during which an attributed ESRD Beneficiary received
maintenance dialysis at home or in an ESRD facility, such that 1-
beneficiary year is comprised of 12-beneficiary months. For MY1 and
MY2, months during which an attributed
[[Page 36434]]
ESRD Beneficiary received maintenance dialysis are identified by claims
with CPT codes 90957, 90958, 90959, 90960, 90961, 90962, 90965, or
90966, excluding claims for beneficiaries who were 75 years of age or
older at any point during the month. For MY3 through MY10, months
during which an attributed ESRD Beneficiary received maintenance
dialysis are identified by claims with CPT codes 90957, 90958, 90959,
90960, 90961, 90962, 90965, or 90966, excluding claims for
beneficiaries who were 75 years of age or older at any point during the
month, or had a vital solid organ cancer diagnosis and were receiving
treatment with chemotherapy or radiation for vital solid organ cancer
during the MY. Months in which an attributed ESRD Beneficiary had a
diagnosis of vital solid organ cancer are identified as described in
paragraph (c)(1)(i)(A)(1) of this section. Months in which an
attributed ESRD Beneficiary received treatment with chemotherapy or
radiation for vital solid organ cancer are identified as described in
paragraph (c)(1)(i)(A)(2) of this section.
* * * * *
(ii) * * *
(A) * * *
(1) Dialysis treatment beneficiary years included in the
denominator are composed of those months during which an attributed
ESRD Beneficiary received maintenance dialysis at home or in an ESRD
facility, such that 1-beneficiary year is comprised of 12-beneficiary
months. For MY1 and MY2, months during which an attributed ESRD
Beneficiary received maintenance dialysis are identified by claims with
CPT codes 90957, 90958, 90959, 90960, 90961, 90962, 90965, or 90966,
excluding claims for beneficiaries who were 75 years of age or older at
any point during the month. For MY3 through MY10, months during which
an attributed ESRD Beneficiary received maintenance dialysis are
identified by claims with CPT codes 90957, 90958, 90959, 90960, 90961,
90962, 90965, or 90966, excluding claims for beneficiaries who were 75
years of age or older at any point during the month, or had a vital
solid organ cancer diagnosis and were receiving treatment with
chemotherapy or radiation for vital solid organ cancer during the MY.
Months in which an attributed ESRD Beneficiary had a vital solid organ
cancer diagnosis are identified as described in paragraph
(c)(1)(i)(A)(1) of this section. Months in which an attributed ESRD
Beneficiary received treatment with chemotherapy or radiation for vital
solid organ cancer are identified as described in paragraph
(c)(1)(i)(A)(2) of this section.
(2) MY1 and MY2, Pre-emptive LDT beneficiary years included in the
denominator are composed of those months during which a Pre-emptive LDT
Beneficiary is attributed to a Managing Clinician, from the beginning
of the MY up to and including the month of the living donor transplant.
For MY3 through MY10, Pre-emptive LDT beneficiary years included in the
denominator are composed of those months during which a Pre-emptive LDT
Beneficiary is attributed to a Managing Clinician, from the beginning
of the MY up to and including the month of the living donor transplant,
excluding beneficiaries who had a vital solid organ cancer diagnosis
and were receiving treatment with chemotherapy or radiation for vital
solid organ cancer during the MY. Months in which an attributed ESRD
Beneficiary had a vital solid organ cancer diagnosis are identified as
described in paragraph (c)(1)(i)(A)(1) of this section. Months in which
an attributed ESRD Beneficiary received treatment with chemotherapy or
radiation for vital solid organ cancer are identified as described in
paragraph (c)(1)(i)(A)(2) of this section. Pre-emptive LDT
Beneficiaries are identified using information about living donor
transplants from the SRTR Database and Medicare claims data.
* * * * *
0
9. Section 512.370 is amended by revising paragraphs (b), (c), and (d)
to read as follows:
Sec. 512.370 Benchmarking and scoring.
* * * * *
(b) Achievement scoring. CMS assesses ETC Participant performance
at the aggregation group level on the home dialysis rate and transplant
rate against achievement benchmarks constructed based on the home
dialysis rate and transplant rate among aggregation groups of ESRD
facilities and Managing Clinicians located in Comparison Geographic
Areas during the Benchmark Year. Achievement benchmarks are calculated
as described in paragraph (b)(1) of this section and, for MY3 through
MY10, are stratified as described in paragraph (b)(2) of this section.
(1) Achievement benchmarks. CMS uses the following scoring
methodology to assess an ETC Participant's achievement score.
Table 1 to Sec. 512.370(b)(1)--ETC Model Schedule of PPA Achievment Benchmarks by Measurement Year
----------------------------------------------------------------------------------------------------------------
MY1 and MY2 MY3 and MY4 MY5 and MY6 MY7 and MY8 MY9 and MY10 Points
----------------------------------------------------------------------------------------------------------------
90th+ Percentile of benchmark 1.1 * (90th+ 1.2 * (90th+ 1.3 * (90th+ 1.4 * (90th+ 2
rates for Comparison Percentile of Percentile of Percentile of Percentile of
Geographic Areas during the benchmark rates benchmark rates benchmark rates benchmark rates
Benchmark Year. for Comparison for Comparison for Comparison for Comparison
Geographic Areas Geographic Geographic Geographic
during the Areas during Areas during Areas during
Benchmark Year). the Benchmark the Benchmark the Benchmark
Year). Year). Year).
75th+ Percentile of benchmark 1.1 * (75th+ 1.2 * (75th+ 1.3 * (75th+ 1.4 * (75th+ 1.5
rates for Comparison Percentile of Percentile of Percentile of Percentile of
Geographic Areas during the benchmark rates benchmark rates benchmark rates benchmark rates
Benchmark Year. for Comparison for Comparison for Comparison for Comparison
Geographic Areas Geographic Geographic Geographic
during the Areas during Areas during Areas during
Benchmark Year). the Benchmark the Benchmark the Benchmark
Year). Year). Year).
50th+ Percentile of benchmark 1.1 * (50th+ 1.2 * (50th+ 1.3 * (50th+ 1.4 * (50th+ 1
rates for Comparison Percentile of Percentile of Percentile of Percentile of
Geographic Areas during the benchmark rates benchmark rates benchmark rates benchmark rates
Benchmark Year. for Comparison for Comparison for Comparison for Comparison
Geographic Areas Geographic Geographic Geographic
during the Areas during Areas during Areas during
Benchmark Year). the Benchmark the Benchmark the Benchmark
Year). Year). Year).
30th+ Percentile of benchmark 1.1 * (30th+ 1.2 * (30th+ 1.3 * (30th+ 1.4 * (30th+ 0.5
rates for Comparison Percentile of Percentile of Percentile of Percentile of
Geographic Areas during the benchmark rates benchmark rates benchmark rates benchmark rates
Benchmark Year. for Comparison for Comparison for Comparison for Comparison
Geographic Areas Geographic Geographic Geographic
during the Areas during Areas during Areas during
Benchmark Year). the Benchmark the Benchmark the Benchmark
Year). Year). Year).
[[Page 36435]]
<30th Percentile of benchmark 1.1 * (<30th 1.2 * (<30th 1.3 * (<30th 1.4 * (<30th 0
rates for Comparison Percentile of Percentile of Percentile of Percentile of
Geographic Areas during the benchmark rates benchmark rates benchmark rates benchmark rates
Benchmark Year. for Comparison for Comparison for Comparison for Comparison
Geographic Areas Geographic Geographic Geographic
during the Areas during Areas during Areas during
Benchmark Year). the Benchmark the Benchmark the Benchmark
Year). Year). Year).
----------------------------------------------------------------------------------------------------------------
(2) Stratifying achievement benchmarks. For MY3 through MY10, CMS
stratifies achievement benchmarks based on the proportion of
beneficiary years attributed to the aggregation group for which
attributed beneficiaries are dual eligible or LIS recipients during the
MY. An ESRD Beneficiary or Pre-emptive LDT Beneficiary is considered to
be dual eligible or an LIS recipient for a given month if at any point
during the month the beneficiary was dual eligible or an LIS recipient
based on Medicare administrative data. CMS stratifies the achievement
benchmarks into the following two strata:
(i) Stratum 1: 50 percent or more of attributed beneficiary years
during the MY are for beneficiaries who are dual eligible or LIS
recipients.
(ii) Stratum 2: Less than 50 percent of attributed beneficiary
years during the MY are for beneficiaries who are dual eligible or LIS
recipients.
(c) Improvement scoring. CMS assesses ETC Participant improvement
on the home dialysis rate and transplant rate against benchmarks
constructed based on the ETC Participant's aggregation group's
historical performance on the home dialysis rate and transplant rate
during the Benchmark Year to calculate the ETC Participant's
improvement score, as specified in paragraph (c)(1) of this section.
For MY3 through MY10, CMS assesses ETC Participant improvement on the
home dialysis rate and transplant rate for ESRD Beneficiaries and, if
applicable, Pre-emptive LDT Beneficiaries, who are dual eligible or LIS
recipients to determine whether to add the Health Equity Incentive to
the ETC Participant's improvement score, as specified in paragraph
(c)(2) of this section.
(1) Improvement score calculation. CMS uses the following scoring
methodology to assess an ETC Participant's improvement score.
(i) Greater than 10 percent improvement relative to the Benchmark
Year rate: 1.5 points
(ii) Greater than 5 percent improvement relative to the Benchmark
Year rate: 1 point
(iii) Greater than 0 percent improvement relative to the Benchmark
Year rate: 0.5 points
(iv) Less than or equal to the Benchmark Year rate: 0 points
(v) For MY3 through MY10, when calculating improvement benchmarks
constructed based on the ETC Participant's aggregation group's
historical performance on the home dialysis rate and transplant rate
during the Benchmark Year, CMS adds one beneficiary month to the
numerator of the home dialysis rate and adds one beneficiary month to
the numerator of the transplant rate, such that the Benchmark Year
rates cannot be equal to zero.
(2) Health Equity Incentive. CMS calculates the ETC Participant's
aggregation group's home dialysis rate and transplant rate as specified
in Sec. Sec. 512.365(b) and 512.365(c), respectively, using only
attributed beneficiary years comprised of months during the MY in which
ESRD Beneficiaries and, if applicable, Pre-emptive LDT Beneficiaries,
are dual eligible or LIS recipients. CMS also calculates the threshold
for earning the Health Equity Incentive based on the ETC Participant's
aggregation group's historical performance on the home dialysis rate
and transplant rate during the Benchmark Year, using only attributed
beneficiary years comprised of months during the Benchmark Year in
which ESRD Beneficiaries and, if applicable, Pre-emptive LDT
Beneficiaries, are dual eligible or LIS recipients. An ESRD Beneficiary
or Pre-emptive LDT Beneficiary is considered to be dual eligible or an
LIS recipient for a given month if at any point during the month the
beneficiary was dual eligible or an LIS recipient. CMS determines
whether a beneficiary was dual eligible or an LIS recipient based on
Medicare administrative data.
(i) The ETC Participant earns the Health Equity Incentive for the
home dialysis rate improvement score if the home dialysis rate for the
MY, calculated as specified in paragraph (c)(2) of this section, is at
least 5-percentage points higher than the home dialysis rate for the
Benchmark Year, calculated as specified in paragraph (c)(2) of this
section. If the ETC Participant earns the Health Equity Incentive for
the home dialysis rate improvement score, CMS adds 0.5 points to the
ETC Participant's home dialysis rate improvement score, calculated as
specified in paragraph (c)(1) of this section, unless the ETC
Participant is ineligible to receive the Home Equity Incentive as
specified in paragraph (c)(2)(iii) of this section.
(ii) The ETC Participant earns the Health Equity Incentive for the
transplant rate improvement score if the home dialysis rate for the MY,
calculated as specified in paragraph (c)(2) of this section, is at
least 5-percentage points higher than the transplant rate for the
Benchmark Year, calculated as specified in paragraph (c)(2) of this
section. If the ETC Participant earns the Health Equity Incentive for
the transplant rate improvement score, CMS adds 0.5 points to the ETC
Participant's transplant rate improvement score, calculated as
specified in paragraph (c)(1) of this section, unless the ETC
Participant is ineligible to receive the Home Equity Incentive as
specified in paragraph (c)(2)(iii) of this section.
(iii) An ETC Participant in an aggregation group with fewer than
11-attributed beneficiary years comprised of months in which ESRD
Beneficiaries and, if applicable, Pre-emptive LDT Beneficiaries, are
dual eligible or LIS recipients, during either the Benchmark Year or
the MY is ineligible to earn the Health Equity Incentive.
(d) Modality Performance Score. (1) For MY1 and MY2, CMS calculates
the ETC Participant's MPS as the higher of ETC Participant's
achievement score or improvement score for the home dialysis rate,
together with the higher of the ETC Participant's achievement score or
improvement score for the transplant rate, weighted such that the ETC
Participant's score for the home dialysis rate constitutes \2/3\ of the
MPS and the ETC Participant's score for the transplant rate constitutes
\1/3\ of the MPS.
CMS uses the following formula to calculate the ETC Participant's
MPS for MY1 and MY2:
Modality Performance Score
[[Page 36436]]
= 2 x (Higher of the home dialysis achievement or improvement score)
+ (Higher of the transplant achievement or improvement score)
(2) For MY3 through MY10, CMS calculates the ETC Participant's MPS
as the higher of the ETC Participant's achievement score for the home
dialysis rate or the sum of the ETC Participant's improvement score for
the home dialysis rate calculated as specified in paragraph (c)(1) of
this section and, if applicable, the Health Equity Incentive,
calculated as described in paragraph (c)(2)(i) of this section,
together with the higher of the ETC Participant's achievement score for
the transplant rate or the sum of the ETC Participant's improvement
score for the transplant rate calculated as specified in paragraph
(c)(1) of this section and, if applicable, the Heath Equity Incentive,
calculated as described in paragraph (c)(2)(ii) of this section,
weighted such that the ETC Participant's score for the home dialysis
rate constitutes \2/3\ of the MPS and the ETC Participant's score for
the transplant rate constitutes \1/3\ of the MPS.
CMS uses the following formula to calculate the ETC Participant's
MPS for MY3 through MY10:
Modality Performance Score
= 2
x (Higher of the home dialysis achievement or (home dialysis
improvement score + Health Equity Bonus [dagger]))
+ (Higher of the transplant achievement or (transplant improvement
score
+ Health Equity Bonus [dagger]))
[dagger] The Health Equity Incentive is applied to the home dialysis
improvement score or transplant improvement score only if earned by the
ETC Participant.
0
10. Section 512.390 is amended by revising the section heading,
redesignating paragraph (b) as (c) and adding new paragraph (b) to read
as follows:
Sec. 512.390 Notification, data sharing, and targeted review.
* * * * *
(b) Data sharing with ETC Participants. CMS shares certain
beneficiary-identifiable data as described in paragraph (b)(1) of this
section and certain aggregate data as described in paragraph (b)(2) of
this section with ETC Participants regarding their attributed
beneficiaries and performance under the ETC Model.
(1) Beneficiary-identifiable data. CMS shares beneficiary-
identifiable data with ETC Participants as follows:
(i) CMS will make available certain beneficiary-identifiable data
for retrieval by ETC Participants no later than one month before the
start of each PPA Period, in a form and manner specified by CMS. ETC
Participants may retrieve this data at any point during the relevant
PPA Period.
(ii) This beneficiary-identifiable data includes, when available,
the following information for each PPA Period:
(A) The ETC Participant's attributed beneficiaries' names, Medicare
Beneficiary Identifiers, dates of birth, dual eligible status, and LIS
recipient status.
(B) Data regarding the ETC Participant's performance under the ETC
Model, including, for each attributed beneficiary, as applicable: The
number of months the beneficiary was attributed to the ETC Participant,
home dialysis months, self-dialysis months, nocturnal in-center
dialysis months, transplant waitlist months, and months following a
living donor transplant.
(iii) CMS shares this beneficiary-identifiable data on the
condition that the ETC Participants observe all relevant statutory and
regulatory provisions regarding the appropriate use of data and the
confidentiality and privacy of individually identifiable health
information as would apply to a covered entity under the Health
Insurance Portability and Accountability Act of 1996 (HIPAA)
regulations, and comply with the terms of the data sharing agreement
described in paragraph (b)(1)(iv) of this section.
(iv) Data sharing agreement. If an ETC Participant wishes to
retrieve the beneficiary-identifiable data specified in paragraph
(b)(1)(ii) of this section, the ETC Participant must complete and
submit, on at least an annual basis, a signed data sharing agreement,
to be provided in a form and manner specified by CMS, under which the
ETC Participant agrees:
(A) To comply with the requirements for use and disclosure of this
beneficiary-identifiable data that are imposed on covered entities by
the HIPAA regulations and the requirements of the ETC Model set forth
in this part.
(B) To comply with additional privacy, security, breach
notification, and data retention requirements specified by CMS in the
data sharing agreement.
(C) To contractually bind each downstream recipient of the
beneficiary-identifable data that is a business associate of the ETC
Participant or performs a similar function for the ETC Participant, to
the same terms and conditions to which the ETC Participant is itself
bound in its data sharing agreement with CMS as a condition of the
downstream recipient's receipt of the beneficiary-identifiable data
retrieved by the ETC Participant under the ETC Model.
(D) That if the ETC Participant misuses or discloses the
beneficiary-identifiable data in a manner that violates any applicable
statutory or regulatory requirements or that is otherwise non-compliant
with the provisions of the data sharing agreement, the ETC Participant
will no longer be eligible to retrieve beneficiary-identifiable data
under paragraph (b)(1)(i) of this section and may be subject to
additional sanctions and penalties available under the law.
(2) Aggregate data. CMS shares aggregate performance data with ETC
Participants as follows:
(i) CMS will make available certain aggregate data for retrieval by
the ETC Participant, in a form and manner to be specified by CMS, no
later than one month before each PPA Period.
(ii) This aggregate data includes, when available, the following
information for each PPA Period, de-identified in accordance with 45
CFR 164.514(b):
(A) The ETC Participant's performance scores on the home dialysis
rate, transplant waitlist rate, living donor transplant rate, and the
Health Equity Incentive.
(B) The ETC Participant's aggregation group's scores on the home
dialysis rate, transplant waitlist rate, and living donor transplant
rate, and the Health Equity Incentive.
(C) Information on how the ETC Participant's and ETC Participant's
aggregation group's scores relate to the achievement benchmark and
improvement benchmark.
(D) The ETC Participant's MPS and PPA for the corresponding PPA
Period.
* * * * *
0
11. Section 512.397 is amended by revising the section heading and
paragraph (b) and adding paragraph (c) to read as follows:
Sec. 512.397 ETC Model Medicare program waivers and additional
flexibilities.
* * * * *
(b) CMS waives the following requirements of title XVIII of the Act
solely for purposes of testing the ETC Model:
(1) CMS waives the requirement under section 1861(ggg)(2)(A)(i) of
the Act and Sec. 410.48(a) of this chapter that only doctors,
physician assistants, nurse practitioners, and clinical nurse
specialists can furnish kidney disease patient education services to
allow kidney disease patient education
[[Page 36437]]
services to be provided by clinical staff (as defined at Sec. 512.310)
under the direction of and incident to the services of the Managing
Clinician who is an ETC Participant. The kidney disease patient
education services may be furnished only by qualified staff (as defined
at Sec. 512.310).
(2) CMS waives the requirement that kidney disease patient
education services are covered only for Stage IV chronic kidney disease
(CKD) patients under section 1861(ggg)(1)(A) of the Act and Sec.
410.48(b)(1) of this chapter to permit beneficiaries diagnosed with CKD
Stage V or within the first 6 months of starting dialysis to receive
kidney disease patient education services.
(3) CMS waives the requirement that the content of kidney disease
patient education services include the management of co-morbidities,
including for the purpose of delaying the need for dialysis, under
Sec. 410.48(d)(1) of this chapter when such services are furnished to
beneficiaries with CKD Stage V or ESRD, unless such content is relevant
for the beneficiary.
(4) CMS waives the requirement that an outcomes assessment designed
to measure beneficiary knowledge about CKD and its treatment be
performed as part of a kidney disease patient education service under
Sec. 410.48(d)(5)(iii) of this chapter, provided that such outcomes
assessment is performed by qualified staff within one month of the
final kidney disease patient education service.
(5) Beginning January 1, 2022, CMS waives the geographic and site
of service originating site requirements in sections 1834(m)(4)(B) and
1834(m)(4)(C) of the Act and Sec. 410.78(b)(3) and (4) of this chapter
for purposes of kidney disease patient education services furnished by
qualified staff via telehealth in accordance with this section,
regardless of the location of the beneficiary or qualified staff.
Beginning January 1, 2022, CMS also waives the requirement in section
1834(m)(2)(B) of the Act and Sec. 414.65(b) of this chapter that CMS
pay a facility fee to the originating site with respect to telehealth
services furnished to a beneficiary in accordance with this section at
an originating site that is not one of the locations specified in Sec.
410.78(b)(3).
(c)(1) Beginning January 1, 2022, an ETC Participant may reduce or
waive the 20 percent coinsurance requirement under section 1833 of the
Act if all of the following conditions are satisfied:
(i) The individual or entity that furnished the kidney disease
patient education services is qualified staff.
(ii) The kidney disease patient education services were furnished
to a beneficiary described in Sec. 410.48(b) or Sec. 512.397(b)(2)
who did not have secondary insurance on the date the services were
furnished.
(iii) The kidney disease patient education services were furnished
in compliance with the applicable provisions of Sec. 410.48 and Sec.
512.397(b).
(2) The ETC Participant must maintain and provide the government
with access to records of the following information in accordance with
Sec. 512.135(b) and (c) of this part:
(i) The identity of the qualified staff who furnished the kidney
disease patient education services for which the coinsurance was
reduced or waived and the date such services were furnished.
(ii) The identity of the beneficiary who received the kidney
disease patient education services for which the coinsurance was
reduced or waived.
(iii) Evidence that the beneficiary who received the kidney disease
patient education services coinsurance waiver was eligible to receive
the kidney disease patient education services under the ETC Model and
did not have secondary insurance.
(iv) The amount of the kidney disease patient education coinsurance
reduction or waiver provided by the ETC Participant.
(3) The Federal anti-kickback statute safe harbor for CMS-sponsored
model patient incentives (42 CFR 1001.952(ii)(2)) is available to
protect the kidney disease patient education coinsurance waivers that
satisfy the requirements of such safe harbor and paragraph (c)(1) of
this section.
Xavier Becerra,
Secretary, Department of Health and Human Services.
[FR Doc. 2021-14250 Filed 7-1-21; 4:15 pm]
BILLING CODE 4120-01-P