Rule2026-10890
Medicare Program; Alternative Payment Model Updates and the Increasing Organ Transplant Access (IOTA) Model
Primary source
Metadata and text below are from the Federal Register, a public-domain U.S. government work. Always verify the official published version before relying on it for any legal matter.
Published
June 1, 2026
Effective
July 1, 2026
Issuing agencies
Health and Human Services DepartmentCenters for Medicare & Medicaid Services
Abstract
This final rule will update and revise the Increasing Organ Transplant Access (IOTA) Model for Performance Year (PY) 2. This final rule also includes a technical correction to the regulatory text.
Full Text
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[Federal Register Volume 91, Number 104 (Monday, June 1, 2026)]
[Rules and Regulations]
[Pages 32788-32873]
From the Federal Register Online via the Government Publishing Office [<a href="http://www.gpo.gov">www.gpo.gov</a>]
[FR Doc No: 2026-10890]
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Vol. 91
Monday,
No. 104
June 1, 2026
Part IV
Department of Health and Human Services
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Centers for Medicare & Medicaid Services
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42 CFR Part 512
Medicare Program; Alternative Payment Model Updates and the Increasing
Organ Transplant Access (IOTA) Model; Final Rule
Federal Register / Vol. 91, No. 104 / Monday, June 1, 2026 / Rules
and Regulations
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DEPARTMENT OF HEALTH AND HUMAN SERVICES
Centers for Medicare & Medicaid Services
42 CFR Part 512
[CMS-5544-F]
RIN 0938-AV65
Medicare Program; Alternative Payment Model Updates and the
Increasing Organ Transplant Access (IOTA) Model
AGENCY: Centers for Medicare & Medicaid Services (CMS), Department of
Health and Human Services (HHS).
ACTION: Final rule.
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SUMMARY: This final rule will update and revise the Increasing Organ
Transplant Access (IOTA) Model for Performance Year (PY) 2. This final
rule also includes a technical correction to the regulatory text.
DATES: These regulations are effective on July 1, 2026.
FOR FURTHER INFORMATION CONTACT:
<a href="/cdn-cgi/l/email-protection#6b282626221f190a05181b070a051f2b08061845030318450c041d"><span class="__cf_email__" data-cfemail="4b080606023f392a25383b272a253f0b28263865232338652c243d">[email protected]</span></a>, for questions related to the Increasing
Organ Transplant Access Model.
Thomas Duvall, (410) 786-8887, for questions related to the
Increasing Organ Transplant Access Model.
Christina McCormick, (410) 786-4012, for questions related to the
Increasing Organ Transplant Access Model.
SUPPLEMENTARY INFORMATION:
I. Background and Executive Summary
A. Model Overview and Background
The Increasing Organ Transplant Access (IOTA) Model is a 6-year
mandatory alternative payment model tested by the CMS Innovation Center
under section 1115A of the Social Security Act (the Act) that began on
July 1, 2025, and will end on June 30, 2031. The model appeared in the
December 4, 2024 Federal Register (89 FR 96280) titled ``Medicare
Program; Alternative Payment Model Updates and the Increasing Organ
Transplant Access (IOTA) Model'' (hereinafter referred to as the 2024
Final Rule), and this final rule will update IOTA Model provisions in
response to improvement opportunities that arose during implementation
of the 2024 Final Rule and to better align the model with new
administration priorities. The IOTA Model is aimed at kidney transplant
hospitals with the goal of increasing the number of kidney transplants,
improving quality, and improving patient experience during the
transplant process.
B. Executive Summary
1. Purpose
In the December 11, 2025 Federal Register (90 FR 57598), we
published the proposed rule titled ``Medicare Program; Alternative
Payment Model Updates and the Increasing Organ Transplant Access
(IOTA)'' (hereafter referred to as the 2025 Proposed Rule). In response
to the 2025 Proposed Rule, we received 114 timely pieces of
correspondence from a variety of commenters, including providers,
health plans, health care companies, professional associations,
technology companies, dialysis facilities, and individuals.
This final rule will make changes to the Increasing Organ
Transplant Access (IOTA) Model for Performance Year (PY) 2, which will
begin on July 1, 2026, and future PYs.
We are finalizing some, but not all, of the provisions discussed in
the proposed rule (hereinafter referred to as the 2025 Proposed Rule),
and we intend to address certain other provisions discussed in the 2025
Proposed Rule in future rulemaking. This final rule also makes a
technical correction to the regulation text for methodology and
criteria for identifying and de-attributing attributed patients from an
IOTA participant by redesignating Sec. 512.414(b)(3)(A) through (D) as
Sec. 512.414(b)(3)(i) through (iv). We also note that some of the
public comments were outside of the scope of the 2025 Proposed Rule.
These out-of-scope public comments are not addressed in this final
rule. We have summarized the public comments that are within the scope
of the 2025 Proposed Rule and have included our responses to those
public comments. However, we note that in this final rule we are not
addressing most comments received with respect to the provisions of the
2025 Proposed Rule that we are not finalizing at this time. Rather, we
will address them at a later time, in a subsequent rulemaking document,
as appropriate. We are clarifying and emphasizing our intent that if
any provision of this final rule is held to be invalid or unenforceable
by its terms, or as applied to any person or circumstance, or stayed
pending further action, it shall be severable from other parts of this
final rule, and from rules and regulations currently in effect, and not
affect the remainder thereof or the application of the provision to
other persons not similarly situated or to other, dissimilar
circumstances. Through this final rule, we adopt provisions that are
intended to and will operate independently of each other, even if each
serves the same general purpose or policy goal. Where a provision is
necessarily dependent on another, the context generally makes that
clear.
2. Summary of the Major Provisions
The following is a summary of the major provisions in this final
rule. A general summary of the changes in this final rule is presented
in section II.B of the preamble of this final rule.
a. IOTA Participants
In the 2024 Final Rule, CMS finalized that a kidney transplant
hospital is eligible to be selected as an IOTA participant if it meets
both of the following criteria: (1) The kidney transplant hospital
annually performed 11 or more kidney transplants for patients aged 18
years or older, regardless of payer, each of the baseline years; and
(2) the kidney transplant hospital annually performed more than 50
percent of its kidney transplants on patients 18 years of age or older
each of the baseline years. However, per sections 1835(d) and
1862(a)(3) of the Act as codified in 42 CFR 411.6, Medicare does not
pay for services furnished by a Federal provider of services or other
Federal agency, nor does Medicare pay for services that are paid for
directly or indirectly by a federal government entity, with only
limited exceptions. Therefore, we are finalizing our proposed
modification to the eligible kidney transplant hospital criteria to
exclude Department of Veteran's Affairs (VA) medical facilities and
Military medical treatment facilities (MTFs) from the IOTA Model for
PYs 2 through 6, as described in section II.B.1.b. of this final rule.
In the 2024 Final Rule, CMS established a low volume threshold
requiring kidney transplant hospitals to have performed 11 or more
kidney transplants for patients aged 18 years or older annually in each
of the 3 baseline years in order to be eligible for selection into the
IOTA Model, designed to protect beneficiary confidentiality and align
with minimum CMS data display standards while ensuring statistical
significance. However, in response to some IOTA participants expressing
concern about their ability to participate in the model and our
experience in operating the model, we believe it is necessary to
reevaluate the low volume threshold requiring a kidney transplant
hospital to have performed at least 11 kidney transplants annually in
each of the 3 baseline years in order to be
[[Page 32789]]
eligible for selection into the IOTA Model. As such, as described in
section II.B.1.b. of this final rule, we are finalizing our proposal to
raise the low volume threshold from a minimum of 11 kidney transplants
performed annually during each of the baseline years to a minimum of 15
kidney transplants performed annually during each of the baseline
years.
b. Performance Assessment
In the 2024 Final Rule, we finalized a policy to assess IOTA
participant performance each PY in the quality domain on post-
transplant outcomes using the composite graft survival rate. While the
model performance period has begun, we indicated that for certain
policies, such as the inclusion of a risk-adjustment methodology when
calculating the composite graft survival rate to account for the
complexities of donors and recipients, and their associated risks, we
would go through rulemaking in the future to promulgate new or updated
policies that will be finalized after the model start date. In the 2025
Proposed Rule, CMS proposed to include a risk-adjustment methodology in
the composite graft survival rate calculation. Specifically, we
proposed that CMS would risk-adjust the composite graft survival rate
to account for a minimum set of transplant recipient and donor
characteristics. As described in section II.B.2.b.(2).(a). of this
final rule, we are finalizing updates to the composite graft survival
rate metric that will include the following modifications:
<bullet> Adding a modified risk-adjustment framework based on the
Scientific Registry of Transplant Recipients' (SRTR's) risk adjustment
methodology for the 1-year graft survival metric.
<bullet> Excluding multi-organ transplants from the composite graft
survival rate exclusion and inclusion criteria, in recognition of their
more complicated results for kidney transplant recipients.
<bullet> Updating the allocation of points awarded for performance
on the composite graft survival rate.
A detailed description of each finalized policy change and the
corresponding scoring criteria can be found in section II.B.2.b. of
this final rule.
c. Payment
As finalized in the 2024 Final Rule, each IOTA participant's final
performance score will determine whether: (1) CMS will pay an upside
risk payment to the IOTA participant; (2) the IOTA participant will
fall into a neutral zone where no performance-based incentive payment
will be paid to or owed by the IOTA participant; or (3) the IOTA
participant will owe a downside risk payment to CMS. For a final
performance score greater than 60, CMS will apply the formula for the
upside risk payment, which will be equal to the IOTA participant's
final performance score minus 60, then divided by 40, then multiplied
by $15,000, then multiplied by the number of kidney transplants
furnished by the IOTA participant to attributed patients with Medicare
fee-for-service (FFS) as their primary or secondary payer during the
PY.
In the 2024 Final Rule (89 FR 96383), CMS proposed and finalized
two-sided performance-based payments for ``Medicare kidney
transplants,'' defined at Sec. 512.402 as kidney transplants furnished
to attributed patients whose primary or secondary insurance is Medicare
FFS, as identified in Medicare FFS claims with MS-DRGs 008, 019, 650,
651 and 652.\1\ In the 2025 Proposed Rule, we considered including
beneficiaries with Medicare Advantage (MA) as well in the definition of
Medicare kidney transplants in order to include MA beneficiaries in the
calculations for the upside risk payment and downside risk payment.
Based on the comments received, and as described in section II.B.3.b.
of this final rule, we are finalizing the inclusion of MA beneficiaries
in the calculation of the upside risk payment and downside risk
payment. We had considered lowering the maximum upside payment for a
kidney transplant performed from $15,000 to $10,000 alongside this
provision but are not finalizing this provision due to comments from
stakeholders.
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\1\ See Table 12 in the 2024 Final Rule (89 FR 96381) for a full
description of MS-DRGs 008, 019, 650, 651 and 652.
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Currently, IOTA Model regulations stipulate that IOTA participants
must remit the downside risk payment to CMS in a single payment at
least 60 days after the date on which the demand letter is issued. As
described in section II.B.3.c.(2). of this final rule, CMS is
finalizing a modification to the policy previously finalized in the
2024 Final Rule such that IOTA participants must remit the downside
risk payment to CMS in a single payment within 60 days after the date
on which the demand letter is issued. As finalized in section
II.B.3.c.(2). of this final rule, if full payment is not received by
CMS within 60 days after demand is made, the remaining amount owed will
be considered a delinquent debt.
Finally, in the 2024 Final Rule, CMS established an Extreme and
Uncontrollable Circumstance (EUC) payment policy recognizing that
events may occur outside the purview and control of the IOTA
participant that may affect their performance in the model. Under the
current provision in the IOTA Model, CMS applies determinations made by
the Quality Payment Program (QPP) with respect to whether an EUC has
occurred, and the areas impacted during the PY. The current regulations
provide that, in the event of an extreme and uncontrollable
circumstance, as determined by the QPP, CMS may reduce the downside
risk payment, if applicable, prior to recoupment. CMS determines the
amount of the reduction by multiplying the downside risk payment by
both the percentage of total months during the PY affected by the EUC
and the percentage of attributed patients who reside in an area
affected by the EUC. CMS also acknowledges the limited nature of the
current EUC provision to account for broader impacts that an EUC might
have on an IOTA participant's ability to perform in the model if
allocation systems were disrupted due to an emergency or if there were
disaster conditions that could disproportionately affect post-
transplant outcomes, which only potentially reduces downside payments
without accounting for changes in model inputs or reporting periods
that may affect an IOTA participant's performance score.
In the 2025 Proposed Rule (90 FR 57612) CMS proposed to update the
EUC policy so that at its sole discretion, CMS may apply flexibilities
if the IOTA participant is located in an emergency area during an
emergency period, as those terms are defined in section 1135(g) of the
Act, for which the Secretary has issued a waiver under section 1135 of
the Act and if the IOTA participant is located in a county, parish, or
tribal government designated in a major disaster declaration under the
Stafford Act. Additionally, we proposed that CMS has the sole
discretion to determine the time period during which payment and
reporting flexibilities are provided to the IOTA participant. Finally,
we proposed that CMS may, at its sole discretion, adjust the direction
and the magnitude of the upside or downside risk payments, if
applicable, prior to recoupment or payment for the IOTA participant if
the IOTA participant is participating in the IOTA Model when CMS has
declared such an emergency period. Due to commenter feedback, we are
finalizing this proposal with modification. We are not finalizing our
proposal to apply EUC flexibilities during an emergency period as
defined
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in section 1135(g) of the Act, but to instead continue to use EUC as
defined by the Quality Payment Program. We are finalizing our proposals
to extend payment and reporting flexibilities to IOTA participants
impacted by EUC and to adjust the upside risk payment or downside risk
payment amount for the IOTA participant if the IOTA participant is
participating in the IOTA Model when such an emergency period has been
declared.
d. Other Requirements
In the 2024 Final Rule, CMS finalized several other model
requirements for IOTA participants, including transparency
requirements, public reporting requirements, and a health equity plan
requirement which is optional for the IOTA Model performance period. In
the 2024 Final Rule, CMS signaled that there were several policies that
would be updated through future rulemaking. In addition, there were
several policy considerations raised subsequent to the publication of
the 2024 Proposed Rule, including from IOTA participants, which CMS
would have liked to incorporate into the IOTA Model, but was unable to
add to the 2024 Final Rule. Therefore, the 2025 Proposed rule proposed
updates to other requirements in the IOTA Model.
(1) Transparency
In the 2024 Final Rule CMS finalized our policy that IOTA
participants must publicly post their patient selection waitlist
criteria on a website by the end of PY 1. CMS also stated its intent to
use future rulemaking to determine the cadence of updating this website
and patient selection criteria. In the 2025 Proposed Rule (90 FR
57613), CMS proposed updates to these requirements. As such, this final
rule updates requirement that include the following modifications:
<bullet> For all subsequent PYs after PY1, the IOTA participant
must review its publicly posted patient selection waitlist criteria and
ensure that the information on its website is up to date by the end of
each relevant PY.
<bullet> IOTA participants performing living donor transplants must
publicly post their living donor selection criteria for evaluating
potential living donors for kidney transplant waitlist patients by the
end of PY 2. IOTA participants must ensure this information is up to
date by the end of each subsequent PY.
Each of the finalized provisions is discussed in detail in section
II.B.4.a.(1). of this final rule.
CMS also finalized its policy in the 2024 Final Rule to identify
each IOTA participant for each PY and to post performance across the
achievement domain, efficiency domain, and quality domain for each IOTA
participant on the IOTA Model website annually, as they become
available. As discussed in section II.B.4.a.(2). of this final rule, we
finalized a requirement to publish IOTA participant waitlist selection
criteria and the living donor selection criteria, as described in
section II.B.4.a.(1). of this final rule, on the IOTA Model website by
the end of the second quarter of each subsequent PY.
In the 2024 Final Rule, CMS finalized a requirement that IOTA
participants must review organ offer acceptance criteria with their
IOTA waitlist patients who are Medicare beneficiaries at least once
every 6 months that the Medicare beneficiary is on their waitlist.
Since the publication of the 2024 Final Rule, IOTA participants have
requested that CMS provide clarification on what acceptance criteria
information should be reviewed. Therefore, as described in section
II.B.4.(a).(4). of this final rule, we aim to clarify that review of
acceptance criteria pertains to individual patient transplant organ
offer acceptance criteria and not organ offer filters or kidney
transplant hospital level acceptance criteria. For purposes of the
model, we are defining ``transplant organ offer acceptance criteria''
as individualized patient acceptance parameters that kidney waitlist
patients, as defined at Sec. 512.402, may elect regarding the
categories of organ offers they are prepared to accept for
transplantation.
Lastly, in the 2025 Proposed Rule (90 FR 57618 through 57621), CMS
proposed the adoption of the following provisions for IOTA participants
to notify its IOTA waitlist patients who are Medicare beneficiaries
when their waitlist status has changed (that is, from active to
inactive) only if it is not redundant with other HHS guidance: The IOTA
participant would be required to: (1) inform IOTA waitlist patients who
are Medicare beneficiaries any time their status on its waitlist is
changed that will impact their ability to receive an organ offer; (2)
include the reason, and information about how IOTA waitlist patients
who are Medicare beneficiaries could become active again; and, (3)
notify the dialysis facility (as defined at 42 CFR 494.10) and managing
clinician (as defined at 42 CFR 512.310) or nephrologist if applicable.
IOTA participants would be required to notify these IOTA waitlist
patients who are Medicare beneficiaries of status changes within 10
days when they become ineligible for organ offers (if not redundant
with existing HHS guidance). CMS is finalizing this provision without
modification, as discussed in detail in section II.B.4.a.(5). of this
final rule.
(2) Health Equity Plans
In the 2024 Final Rule, CMS finalized that an IOTA participant may
voluntarily submit a health equity plan (HEP) to CMS. CMS finalized
voluntary health equity plan submissions aiming to address reducing
health disparities for attributed patients. However, CMS is removing
the voluntary HEP provisions in compliance with Executive Order 14151
Ending Radical and Wasteful Government DEI Programs and Preferencing
(90 FR 8339) issued January 20, 2025 and because, although voluntary,
they still require participant time and resources and CMS believes
those resources are better directed to the model's core objectives and
mandatory requirements.
e. Beneficiary Protections
CMS finalized in the 2024 Final Rule that IOTA participants must
provide notice to each attributed patient of its participation in the
IOTA Model. In the 2025 Proposed Rule (90 FR 57621 through 57622), CMS
proposed the following updates:
<bullet> Limit these notification requirements to Medicare
beneficiaries only.
<bullet> Allow IOTA participants to distribute this notification in
a paper notification at the first in-office or outpatient visit, or to
distribute the notification in an electronic format in cases where the
attributed patient has affirmatively opted out of receiving paper
communications and has chosen to receive communication through
electronic methods.
As described in section II.B.5. of this final rule, we have
finalized these proposals with the modification that IOTA participants
may distribute the notification in an electronic format in cases where
the attributed patient has affirmatively opted out of receiving paper
communications or has chosen to receive communication through
electronic methods.
f. Monitoring
In the 2024 Final Rule, we finalized a comprehensive list of
monitoring activities to ensure compliance and promote the safety of
attributed patients and the integrity of the IOTA Model. However, we
inadvertently omitted monitoring of the review of acceptance criteria
provision as described in Sec. 512.442. Therefore, in this final rule
we are finalizing with modification that CMS may monitor the following
transparency provisions as described in section II.B.6 of this final
rule:
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<bullet> Informing eligible IOTA waitlist patients who are Medicare
beneficiaries, as defined in section II.B.4.a.(3). of this final rule,
of the number of times an organ is declined on the Medicare
beneficiary's behalf in accordance with finalized Sec. 512.442(b);
<bullet> Reviewing selection criteria with IOTA waitlist patients
who are Medicare beneficiaries at least once every 6 months that the
Medicare beneficiary is on their waitlist as specified in Sec.
512.442(c); and
<bullet> Notifying IOTA waitlist patients who are Medicare
beneficiaries when their waitlist status has changed from active to
inactive in accordance with finalized Sec. 512.442(d).
g. Termination
In the 2024 Final Rule, we finalized a comprehensive list of
reasons for which CMS may immediately or with advance notice terminate
an IOTA participant from the IOTA Model. As mentioned in section
II.B.7. of this final rule, the 2024 Final Rule inadvertently omitted
the Department of Health and Human Services (HHS) and the Organ
Procurement and Transplantation Network (OPTN) as sources of vital
information regarding potential events by IOTA participants identified
as presenting a risk to patient safety, public health, and related
concerns that may lead CMS to terminate IOTA participants. Therefore,
in this final rule we are finalizing our policy, with minor technical
corrections as described in section II.B.7 of this final rule, that CMS
may terminate an IOTA participant from the IOTA Model if HHS or the
OPTN has determined that an IOTA participant has violated the OPTN's
policies, OPTN's Management and Membership policies, or HHS regulations
(42 CFR part 121) upon a review conducted in accordance with 42 CFR
121.10.
3. Summary of Costs and Benefits
The IOTA Model aims to incentivize transplant hospitals to overcome
system-level barriers to kidney transplantation. The chronic shortfall
in kidney transplants results in poorer outcomes for patients and
increases the burden on Medicare in terms of payments for dialysis and
dialysis-based enrollment in the program. In section V. of this final
rule, we set forth a detailed analysis of the impacts that the proposed
changes will have on the IOTA participants and beneficiaries. We
estimate that as a result of the finalized changes to the IOTA Model,
net Federal savings will increase by $60 million.
II. Changes to the Increasing Organ Transplant Access (IOTA) Model
A. Background
1. Purpose
The Increasing Organ Transplant Access (IOTA) Model is a 6-year
mandatory alternative payment model tested by the CMS Innovation Center
that began on July 1, 2025, and will end on June 30, 2031. The IOTA
Model is testing whether performance-based incentives paid to or owed
by participating kidney transplant hospitals can increase access to
kidney transplants for kidney transplant waitlist patients, while
preserving or enhancing quality of care and reducing Medicare
expenditures. CMS selected 103 kidney transplant hospitals to
participate in the IOTA Model for the first performance year and will
be measuring and assessing the participating kidney transplant
hospitals' performance during each performance year (PY) across three
performance domains: achievement, efficiency, and quality.
The IOTA Model was established through notice and comment
rulemaking, finalized in the Medicare Program; Alternative Payment
Model Updates and the Increasing Organ Transplant Access (IOTA) Model
Final Rule (2024 Final Rule), CMS-5535-F, published December 4, 2024.
In the 2024 Final Rule, CMS signaled that there were several policies
that could be addressed through future rulemaking, including: the
addition of a risk-adjustment methodology in the calculation of the
composite graft survival rate, the addition of transplants furnished to
Medicare Advantage beneficiaries to the definition of Medicare kidney
transplants, and the addition of a monthly transparency requirement for
IOTA participants to inform IOTA waitlist patients who are Medicare
beneficiaries about declined organ offers and the reasons for
declination. In addition, there were a number of policy considerations
raised subsequent to the publication of the Medicare Program;
Alternative Payment Model Updates and the Increasing Organ Transplant
Access (IOTA) Model Proposed Rule (2024 Proposed Rule), including from
IOTA participants, which CMS would like to incorporate into the IOTA
Model, but were unable to add to the 2024 Final Rule. Therefore, the
Medicare Program; Alternative Payment Model Updates and the Increasing
Organ Transplant Access (IOTA) Model (hereinafter referred to as the
2025 Proposed Rule), published December 11, 2025, proposed updates to
the IOTA Model. The policies finalized in this final rule reflect our
commitment to ensuring that the IOTA Model's incentive structure
enhances the care delivery capabilities and efficiency of kidney
transplant hospitals selected for participation, with the goal of
improving quality of care while reducing program spending.
2. Statutory Authority and Background
Section 1115A of the Act authorizes the Center for Medicare and
Medicaid Innovation (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. We have
designed and tested both voluntary Innovation Center models--governed
by participation agreements, cooperative agreements, and model-specific
addenda to existing contracts with CMS--and mandatory Innovation Center
models that are governed by regulations. Each voluntary and mandatory
model features its own specific payment methodology, quality metrics,
and certain other applicable policies, but each model also features
numerous provisions of a similar or identical nature, including
provisions regarding cooperation in model evaluation; monitoring and
compliance; and beneficiary protections.
Under the authority of section 1115A of the Act, through notice-
and-comment rulemaking, the Innovation Center established the IOTA
Model in the 2024 Final Rule that appeared in December 4, 2024, Federal
Register (89 FR 96280). The intent of the IOTA Model is to reduce
Medicare expenditures and improve performance in kidney transplantation
by creating performance-based incentive payments for participating
kidney transplant hospitals tied to access and quality of care for ESRD
patients on the hospitals' waitlists.
Participation in the IOTA Model is mandatory for approximately 50
percent of all eligible kidney transplant hospitals in the United
States, which were selected by a stratified random sampling of donation
service areas (``DSAs''). Mandatory participation in the IOTA Model was
determined to be necessary to minimize the potential for selection bias
and to ensure a representative sample size nationally, thereby
guaranteeing that there would be adequate data to evaluate the model
test. Eligible kidney transplant hospitals for PY 1 included those
that: (1) performed at least 11 kidney transplants for patients 18
years of age or older
[[Page 32792]]
annually regardless of payer type during the 3-year period ending 12
months before the model's start date; and (2) furnished more than 50
percent of the hospital's annual kidney transplants to patients 18
years of age or older during that same period. As this is a mandatory
model, the selected kidney transplant hospitals are required to
participate.
CMS measures and assesses IOTA participant performance during each
PY across three performance domains: achievement, efficiency, and
quality. The achievement domain assesses each IOTA participant on the
number of kidney transplants performed during a PY, relative to a
participant-specific transplant target. The efficiency domain assesses
the performance of IOTA participants on the organ offer acceptance rate
ratio relative to national ranking. The quality domain is focused on
improving the quality of care and measures IOTA participants
performance on the composite graft survival rate relative to national
ranking to assess post-transplant outcomes. Each IOTA participant's
performance score across these three domains determines its final
performance score and corresponding amount for the performance-based
incentive payment that CMS will pay to or the payment that will be owed
by the IOTA participant. The upside risk payment will be a lump sum
payment paid by CMS after the end of a PY to an IOTA participant with a
final performance score of 60 or greater. Conversely, beginning in PY
2, the downside risk payment will be a lump sum payment paid to CMS by
any IOTA participant with a final performance score of 40 or lower.
There is no downside risk payment for PY 1 of the IOTA Model.
B. Provisions of the Proposed Regulation
1. IOTA Participants
a. Background
In the 2024 Final Rule (89 FR 96304), we defined ``IOTA
participant'' as a kidney transplant hospital, as defined at Sec.
512.402, that is required to participate in the IOTA Model pursuant to
Sec. 512.412. In addition, we noted that the definition of ``model
participant'' contained in 42 CFR 512.110, would include an IOTA
participant. We also proposed and finalized at Sec. 512.402 the
definition of ``transplant hospital,'' ``kidney transplant hospital,''
and ``kidney transplant.'' We stated that kidney transplant hospitals
are the focus of the IOTA Model because they are the entities that
furnish kidney transplants to ESRD patients on the waiting list and
ultimately decide to accept donor recipients as transplant candidates
(89 FR 96303). Kidney transplant hospitals play a key role in managing
transplant waitlists and patient, family, and caregiver readiness. They
are also responsible for the coordination and planning of kidney
transplantation with the organ procurement organizations (OPO) and
donor facilities, staffing and preparation for kidney transplantation,
and oversight of post-transplant patient care, and they are largely
responsible for managing the living donation process. The IOTA Model is
intended to promote improvement activities across selected kidney
transplant hospitals that reduce access barriers, thereby increasing
the number of transplants, quality of care, and cost-effective
treatment. The IOTA Model aims to improve quality of care for ESRD
patients on the waiting list pre-transplant, during transplant, and
during post-transplant care.
b. Mandatory Participation
In the 2024 Final Rule (89 FR 96308), we finalized that
participation in the IOTA Model would be mandatory. We proposed and
finalized that all kidney transplant hospitals that meet the
eligibility requirements at Sec. 512.412(a), and that are selected
through the participation selection process at Sec. 512.412(b) and (c)
would be required to participate in the IOTA Model. Lastly, we also
finalized our provisions for participant eligibility criteria for
kidney transplant hospitals at Sec. 512.412(a) for all eligible kidney
transplant hospitals selected for participation in the model.
As stated in the 2024 Final Rule (89 FR 96308), we proposed kidney
transplant hospital participant eligibility criteria that would
increase the likelihood that: (1) individual kidney transplant
hospitals selected as IOTA participants represent a diverse array of
capabilities across the performance domains; and (2) the results of the
model test would be statistically valid, reliable, and generalizable to
kidney transplant hospitals nationwide should the model test be
successful and considered for expansion under section 1115A(c) of the
Act.
We proposed and finalized our participant eligibility criteria for
kidney transplant hospitals at Sec. 512.412(a) in the 2024 Final Rule
(89 FR 96311). Specifically, that eligible kidney transplant hospitals
are those that: (1) performed 11 or more transplants for patients aged
18 years or older annually, regardless of payer type, each of the
baseline years; and (2) furnished more than 50 percent of its kidney
transplants annually to patients over the age of 18 during each of the
baseline years. We also finalized the definition of ``non-pediatric
facility'' and ``baseline years'' at Sec. 512.402.
In the 2024 Final Rule, we finalized at Sec. 512.412(a)(1) a low
volume threshold requiring a kidney transplant hospital to have
performed 11 or more kidney transplants for patients aged 18 years or
older annually in each of the 3 baseline years in order to be eligible
for selection into the IOTA Model.
In our initial proposal in the 2024 Proposed Rule, we stated that
we alternatively considered using a higher threshold, such as 30 adult
kidney transplants or 50 adult kidney transplants during each of the 3
baseline years (89 FR 43541). However, we found that many kidney
transplant hospitals consistently perform between 11 and 50 transplants
per year. We received several comments expressing concern with the
proposed low-volume kidney transplant threshold for IOTA participants.
As described in the 2024 Final Rule at 89 FR 96309, a commenter noted
that there may be some unforeseen or unintended consequences of
advantaging programs classified as ``low volume,'' where the volume is
close to the dividing line, and vice versa. Additional commenters
shared concerns that the low volume threshold of 11 kidney transplants
performed will disadvantage kidney transplant hospitals that furnish a
smaller number of kidney transplants, as these transplant programs do
not meet the requirements for Center of Excellence (COE) programs and
have limited contracts with payers, and the low volume threshold does
not ensure statistical significance. Several commenters recommended
that CMS should increase the low volume threshold, setting the number
of kidney transplants at a value such as 25, 50, or 100, to ensure
statistical significance and avoid burden on kidney transplant
hospitals that furnish a smaller number of kidney transplants. Finally,
a commenter suggested CMS should only use the number of Medicare kidney
transplants to determine eligibility, rather than 11 kidney transplants
across all payers. Additionally, as described at 89 FR 96308 a
commenter expressed concerns about the impact of the IOTA Model on
small kidney transplant hospitals if participation was made mandatory.
The commenter suggested that a low volume threshold of 100 kidney
transplants, regardless of payer type, would be more appropriate. This,
the commenter believed, would ensure small kidney transplant hospitals
were excluded and protect access to kidney transplants in less
populated areas.
[[Page 32793]]
In the 2024 Final Rule, we stated that the low volume threshold was
designed to protect the confidentiality of Medicare and Medicaid
beneficiaries and that this low volume threshold aligns with the
minimum standards for CMS data display, preventing the release of
information that could identify individual beneficiaries while ensuring
statistical significance (89 FR 96309). Additionally, we stated that we
excluded these low-volume kidney transplant hospitals that may lack the
capacity to comply with the model's policies.
Since publication of the 2024 Final Rule, some IOTA participants
close to the current low volume threshold have expressed concern about
their ability to participate in the model and we stated we believed it
is necessary to reevaluate the low volume threshold requiring a kidney
transplant hospital to have performed 11 or more kidney transplants for
patients aged 18 years or older, regardless of payer, annually in each
of the 3 baseline years in order to be eligible for selection into the
IOTA Model (90 FR 57603). We also received multiple comments from the
2024 Proposed Rule urging us to increase the low volume threshold. As
such, in the 2025 Proposed Rule, we proposed at Sec. 512.412(a)(1) to
raise this low volume threshold from a minimum of 11 kidney transplants
performed annually during each of the baseline years to a minimum of 15
kidney transplants performed annually during each of the baseline
years. We also proposed this provision in response to our experience in
operating the model. IOTA participants who are above the current
minimum low volume threshold of 11 kidney transplants performed
annually, but below the updated proposed low volume threshold of a
minimum of 15 kidney transplants performed annually are still quite
small and have indicated structural difficulties in achieving the goals
of the model and complying with the requirements of the model. This
updated low volume threshold is designed to balance accommodating the
needs of smaller kidney transplant hospitals to ensure that their
transplant programs can remain viable and continue to serve their
communities, while also trying to ensure a sufficient volume of kidney
transplant hospitals to be able to test the model.
We alternatively considered higher low volume thresholds, such as
20 kidney transplants or 25 kidney transplants performed for patients
aged 18 years or older annually, regardless of payer, during each of
the baseline years, but think that a low volume threshold of 15 kidney
transplants or more performed to patients aged 18 years or older
annually best balances excluding the smallest kidney transplant
hospitals, while still being able to ensure that the model has
sufficient power to be able to test the model (90 FR 57603). We stated
in the 2025 Proposed Rule that the updated low volume threshold would
only result in the removal of one IOTA participant as of the model
start date, while higher low volume thresholds would result in
additional IOTA participants being removed, which could diminish the
ability to evaluate the model.
We sought comment on our proposal to adjust the low volume
threshold at Sec. 512.412(a)(1) to require that to be eligible for
model participation, a kidney transplant hospital must have performed a
minimum of 15 kidney transplants to patients aged 18 years or older
annually, regardless of payer, each of the baseline years, rather than
a minimum of 11 kidney transplants. We also sought public comment on
the alternatives considered.
Additionally, we stated in the 2025 Proposed Rule that since the
publication of the 2024 Final Rule, CMS completed IOTA participant
selection and notified IOTA participants of their selection to
participate in the IOTA Model (90 FR 57603). Upon completion of
selecting IOTA participants for inclusion in the model, we realized
that an unintended consequence of the current participant eligibility
criteria at Sec. 512.412(a) is that Department of Veterans Affairs
(VA) medical facilities or military medical hospitals, also known as
military medical treatment facilities (MTFs) could be selected to
participate even though Medicare does not provide reimbursement for VA
medical facilities or MTFs. A total of 103 kidney transplant hospitals
were selected to participate in the model, including four VA medical
facilities and one MTF.
As discussed in the 2025 Proposed Rule, per 42 CFR 411.6(a),
Medicare does not pay for services rendered by Federal providers of
services or other Federal agencies (90 FR 57603). Additionally,
Medicare does not provide payment for services that receive direct or
indirect funding from a governmental entity (see 42 CFR 411.8). As
such, we proposed to update the participant eligibility criteria at
Sec. 512.412(a). Specifically, we proposed at Sec. 512.412(a)(3) to
exclude kidney transplant hospitals that are a MTF or VA medical
facility from being eligible to participate in the IOTA Model. We
proposed at Sec. 512.402 to define a ``VA medical facility'' as
defined at 38 CFR 17.1505 to mean a VA hospital, a VA community-based
outpatient clinic, or a VA health care center, any of which must have
at least one full-time primary care physician, but not a Vet Center or
Readjustment Counseling Service Center (90 FR 57603). Additionally, we
proposed at Sec. 512.402 to define a ``military medical treatment
facility (MTF)'' as it is currently defined at 10 U.S.C. 1073c(j)(3) to
mean: (1) any fixed facility of the Department of Defense that is
outside of a deployed environment and used primarily for health care;
and (2) any other location used for purposes of providing healthcare
services as designated by the Secretary of Defense.
Given that Medicare does not provide coverage for services
furnished by a federal provider, federal agency, or any other
government entity, whether the services are paid for directly or
indirectly by a government source, we stated that we believed that VA
medical facilities and MTFs should not be eligible to participate in
the IOTA Model (90 FR 57603). Additionally, we stated that we did not
believe that our proposal to exclude kidney transplant hospitals that
are also a VA medical hospital or MTF from being eligible to
participate in the IOTA Model would negatively affect the remaining
IOTA participants, impact the IOTA Model, or affect CMS's ability to
evaluate the model. Moreover, we stated that the model's evaluation
would benefit from an analysis that only focuses on Medicare-
participating kidney transplant hospitals. Since the fundamental
purpose of the IOTA Model is to test interventions specifically within
the Medicare system to improve quality of care and reduce Medicare
expenditures, we stated that including non-Medicare participating
facilities like VA medical facilities and MTFs would introduce
confounding variables that could obscure the model's true
effectiveness. Additionally, we stated that VA medical facilities and
MTFs operate under entirely different payment structures, regulatory
frameworks, and patient populations compared to Medicare-participating
hospitals, making direct performance comparisons inappropriate and
potentially misleading.
By excluding these facilities, we stated that the model evaluation
can focus on kidney transplant hospitals that all operate under similar
Medicare reimbursement conditions, face comparable regulatory
requirements, and serve similar patient populations, thereby providing
more accurate data on whether the model's performance-based payment
incentives actually drive improvements in transplant outcomes and cost
efficiency within the Medicare
[[Page 32794]]
system (90 FR 57604). We stated that this approach would also eliminate
the analytical complexity of trying to account for the vastly different
operational contexts between Medicare-participating kidney transplant
hospitals and federal facilities, ultimately yielding more actionable
insights for potential broader implementation of the IOTA Model across
the Medicare program.
We sought comment on our proposal at proposed Sec. 512.412(a)(3)
to exclude kidney transplant hospitals that are a MTF or VA medical
facility as eligible to participate in the model. We also sought
comments on our proposed definitions of MTF and VA medical facility at
proposed Sec. 512.402.
Lastly, to account for our proposed kidney transplant hospital
participant eligibility criteria modifications at proposed Sec.
512.412(a)(1) and (3), we proposed updating the language at Sec.
512.412(a) (90 FR 57604). Specifically, we proposed replacing ``meets
both'' with ``meets all'' to specify that a kidney transplant hospital
is eligible to be selected as an IOTA participant, in accordance with
the methodology described in proposed Sec. 512.412(b)(3), if the
kidney transplant hospital meets all of the eligibility criteria at
Sec. 512.412(a).
We sought comment on our proposal at proposed Sec. 512.412(a) to
update existing language to account for our proposals at proposed Sec.
512.412(a)(1) and (3).
The following is a summary of the comments we received on the
provisions proposed and the alternatives considered set out in this
section and our responses.
Comment: Several commenters expressed support for the proposal to
raise the low volume threshold to a minimum of 15 kidney transplants
performed annually during each of the baseline years for patients aged
18 years or older, regardless of payer, instead of the current low
volume threshold of 11. Additionally, several commenters agreed with
CMS that the proposed update would balance the need to have statistical
validity with consideration for the IOTA participants. Another
commenter stated that the proposed change would strengthen model
integrity and that it is supported across professional societies.
Response: We thank the commenters for their support. We agree that
raising the low volume threshold from a minimum of 11 kidney
transplants performed annually during each of the baseline years to a
minimum of 15 kidney transplants performed annually during each of the
baseline years will strengthen model integrity. We stated in the 2025
Proposed Rule that the proposed change would better take into
consideration the needs of smaller kidney transplant hospitals and
would ensure that their transplant programs can remain viable and
continue to serve their communities (90 FR 57603). For these reasons,
we are finalizing our proposal without modification.
Comment: Several commenters expressed support for the proposal at
Sec. 512.412(a)(1) to raise the low-volume threshold to a minimum of
15 kidney transplants performed annually during each of the baseline
years for patients aged 18 years or older, regardless of payer, instead
of the current threshold of 11. However, commenters requested
additional information regarding the proposed change. In particular, a
commenter recommended that CMS provide a clearer explanation of the
rationale for increasing the threshold and disclose the number and
characteristics of kidney transplant hospitals that would be affected.
The commenter also suggested that CMS monitor the impact of
implementing the revised threshold.
Response: We thank the commenters for their support, feedback, and
suggestions. We stated in the 2025 Proposed Rule that our rationale for
raising the low volume threshold was a result of IOTA participant
feedback concerning the structural difficulties in meeting model goals,
commenters responding to the 2024 Proposed Rule urging CMS to increase
the low volume threshold, and our experience in operating the model (90
FR 57603). Additionally, we note that we intend to publicly post an
updated list of IOTA participants on the IOTA Model website.
Comment: A couple of commenters asked CMS to provide additional
information or analysis proving that the proposal to adjust the low
volume threshold from 11 to 15 kidney transplants would improve
statistical validity or model performance. Another commenter asked CMS
to provide additional data concerning how the change would impact
health care access in less populous regions.
Response: We thank the commenters for their comments. As described
in the 2024 Final Rule, the model's design ensures sufficient
participation of kidney transplant hospitals, which is necessary to
obtain a diverse, representative sample for a statistically robust test
of the model (89 FR 96307). We do so in accordance with section
1115A(b)(4) of the Act. As stated in the 2024 Proposed Rule, we
continue to believe the proposed, updated low volume threshold aligns
with the minimum standards for CMS data display, preventing the release
of information that could identify individual beneficiaries while
ensuring statistical significance (89 FR 96309). Additionally, as
described in the 2025 Proposed Rule and this final rule, the proposed
updated low volume threshold would only result in the removal of one
IOTA participant as of the model start date (90 FR 57603). We intend to
monitor the model for any unintended consequences.
Comment: A couple of commenters expressed concern that increasing
the low-volume threshold to 15 kidney transplants performed annually
during each of the baseline years for patients aged 18 years or older,
regardless of payer, could discourage innovation or create access
barriers for low-volume kidney transplant hospitals, particularly those
serving rural and underserved populations. These commenters recommended
alternative approaches, including adopting a tiered eligibility
framework based on transplant volume, as well as incorporating risk-
adjustment, performance benchmarks, phased participation, or enhanced
technical assistance to support broader participation and benefit for
lower-volume transplant hospitals.
Response: We thank the commenters who expressed concerns around the
impact of raising the low volume threshold to 15 kidney transplants.
However, we disagree with the commenters. We recognize that our
proposal to raise the low volume threshold to 15 kidney transplants
performed annually during each of the baseline years would exclude
smaller kidney transplant hospitals. However, as stated previously in
the 2025 Proposed Rule and discussed in the preamble of this final
rule, our proposal to raise the low volume threshold would only result
in the removal of one IOTA participant as of the model start date (90
FR 57603). However, as stated in comment responses noted previously in
this section, we are finalizing our proposal to adjust the low volume
threshold at Sec. 512.412(a)(1) to require that to be eligible for
model participation, a kidney transplant hospital must have performed a
minimum of 15 kidney transplants to patients aged 18 years or older
annually, regardless of payer, each of the baseline years. We note that
the model includes features such as risk-adjustment and performance
measurement approaches designed to account for differences in patient
complexity and care environments. In addition, we intend to monitor the
effects of the low volume threshold on participation and access to
[[Page 32795]]
care, including impacts on low volume kidney transplant hospitals and
the populations they serve. While we are not adopting the alternative
approaches suggested by commenters at this time, we will continue to
evaluate the need for potential refinements, including additional
supports or adjustments, through future notice and comment rulemaking
as appropriate.
Comment: A couple of commenters recommended that CMS further
increase the low volume threshold, suggesting levels such as 30, 50, or
100 kidney transplants, to avoid burdening kidney transplant hospitals
that furnish a smaller number of kidney transplants. A commenter stated
that a higher low volume threshold would help ensure that participating
kidney transplant hospitals are able to offset the infrastructure costs
associated with model participation. Another commenter recommended
pairing a higher low volume threshold with an exclusion for kidney
transplant hospitals serving rural and underserved populations.
Response: We thank the commenters who suggested using an even
higher low volume threshold beyond 15 adult kidney transplants;
however, we disagree with the commenters. As described in the 2025
Proposed Rule, adopting a higher threshold would result in additional
IOTA participants being removed from the model, which could diminish
CMS's ability to evaluate the model (90 FR 57603). IOTA participants
may have to make upfront investments to accommodate the model's
requirements, but we believe that the proposed low volume threshold of
15 adult kidney transplants performed for each kidney transplant
hospital in each of the baseline years will mitigate demands placed on
smaller kidney transplant hospitals. In response to the commenter who
suggested that CMS raise the low volume threshold higher and exclude
kidney transplant hospitals serving rural and underserved populations,
as described in the 2024 Proposed Rule, we stated that we did not
believe mandatory participation in the IOTA Model would increase
disparities for underserved populations such as dual-eligibles or low-
income subsidy beneficiaries, nor for rural transplant hospitals (89 FR
96306). Additionally, as stated in the 2024 Proposed Rule, we continue
to believe that IOTA participants are representative of eligible kidney
transplant hospitals from across the nation in terms of geography and
the volume of adult kidney transplants (89 FR 43542).
Comment: Several commenters expressed support for the proposed
exclusion of kidney transplant hospitals that are a MTF or VA medical
facility given that the change would ensure that removing these kidney
transplant hospitals would make it easier to compare performance for
the purposes of evaluation. Several commenters noted that the model's
payment and quality incentives may have different effects on VA medical
facilities and MTFs.
Response: We thank the commenters for their support and thoughts
regarding the advantages of the proposed change. We agree with the
commenters. Accordingly, we are finalizing the proposal at Sec.
512.412(a)(3) to exclude kidney transplant hospitals that are a MTF or
VA medical facility as eligible to participate in the model.
Comment: A commenter stated that they did not support the proposed
exclusion of these facilities, but did not provide further suggestions
or justification.
Response: We thank the commenter for their feedback.
Comment: A commenter supported CMS's proposed definitions for MTF
and VA medical facility, but did not provide a rationale for their
support.
Response: We thank the commenter for their support of the proposed
definitions.
Comment: Several commenters stated that they supported the proposed
modification replacing ``meets both'' with ``meets all'', but did not
provide further suggestions or justification.
Response: We thank the commenters for their support of the proposed
update to existing language to account for our proposed kidney
transplant hospital participant eligibility criteria. We are finalizing
the proposal at Sec. 512.412(a) to update existing language to account
for our proposed kidney transplant hospital participant eligibility
criteria at proposed Sec. 512.412(a)(1) and (3).
After consideration of the public comments we received, for the
reasons set forth in this rule, we are finalizing our proposed
provisions for participant eligibility criteria for kidney transplant
hospitals at Sec. 512.412(a) without modification. Additionally, we
are finalizing as proposed the definitions of Military medical
treatment facility (MTF) and VA medical facility without modification.
2. Performance Assessment
a. Method and Scoring Overview
In the 2024 Final Rule (89 FR 96326), we finalized provisions to
assess IOTA participants in the achievement domain, efficiency domain
and quality domain and performance scoring approach at Sec.
512.422(a). We also finalized at Sec. 512.402 the definition of
``final performance score'' as the aggregate sum of scores earned by
the IOTA participant across all three domains for a designated PY.
b. Quality Domain
(1) Background
In the 2024 Final Rule (89 FR 96358), we finalized at Sec. 512.402
the definition of ``quality domain'' as the performance assessment
category in which CMS assesses the IOTA participant's performance using
a performance measure focused on improving the quality of transplant
care as described in Sec. 512.428. We also finalized general
provisions for the quality domain at Sec. 512.424(a).
We stated at 89 FR 96358, that our goal for the quality domain
within the IOTA Model is to achieve acceptable post-transplant outcomes
while incentivizing increased kidney transplant volume.\2\ We continue
to believe that transplant hospital accountability for patient-
centricity and clinical outcomes continues post-transplantation. While
transplant outcomes have historically received the most attention,
often at the exclusion of other factors, we sought to encourage a
better balance in the system to offer the benefits of transplant to
more patients.
---------------------------------------------------------------------------
\2\ We note that we did not include a definition or criteria for
what constitutes ``acceptable'' post-transplant outcomes and we
sought comment on how to define an acceptable level (for example, 1
standard deviation of the national risk-adjusted rate or some other
way), as stated in section II.B.2.b.(2). of this final rule.
---------------------------------------------------------------------------
(2) Post Transplant Outcomes
In the 2024 Final Rule (89 FR 96361), we finalized at Sec.
512.428(b)(1) a provision to assess IOTA participant performance each
PY on post-transplant outcomes using the composite graft survival rate.
We also proposed and finalized at Sec. 512.402 the definition of
composite graft survival rate (89 FR 96361).
(a) Calculation of Metric
In the 2024 Final Rule (89 FR 96364), we proposed and finalized
provisions for calculating the composite graft survival rate at Sec.
512.428(b)(1).
In our initial proposal in the 2024 Proposed Rule (89 FR 43563), we
stated that we had considered incorporating a risk-adjustment
methodology into our proposed composite graft survival equation, such
as the one used by Scientific Registry of Transplant Recipients (SRTR)
for 1-year post-
[[Page 32796]]
transplant outcomes conditional on 90-day survival or constructing our
own. We also stated at 89 FR 43563 that we were interested in comments
on whether risk-adjustments were necessary, and which ones, such as
transplant recipient and donor characteristics, would be significant
and clinically appropriate in the context of our proposed approach. We
received over 15 comments expressing concern that the lack of risk-
adjustment in the composite graft survival rate metric could have
adverse consequences and would increase administrative burden. As
described at 89 FR 96362, many commenters expressed concern that the
unadjusted composite graft survival rate does not account for the
clinical risk factors of the transplant recipient or the donor;
therefore, it may inadvertently lead to disparities in transplant
access by incentivizing IOTA participants to select healthier patients
for transplantation. Several commenters believe that the proposed
measure misaligned with the model's goal of increasing kidney
transplants in a more complex population without risk-adjusting for
allograft and recipient factors. Without proper risk-adjustment, these
commenters suggested the proposed measure could cause IOTA participants
to be more risk averse with the types of organs they accept or
disincentivize IOTA participants from transplanting candidates who have
a higher likelihood of graft failure, such as older candidates or those
with more comorbid conditions. Some commenters suggested specific
transplant recipient and donor characteristics that CMS should risk-
adjust for when calculating the proposed composite graft survival rate.
In the 2024 Final Rule (89 FR 96363), we stated that in light of
commenters suggestions, we considered finalizing a risk-adjustment
methodology that adjusted for donor age, recipient age, and recipient
diabetes. However, we decided to finalize the provisions as proposed as
we did not believe that adjusting for these three variables alone was
appropriate. Organ availability affects kidney transplantation, leading
transplant teams to expand the criteria for accepting organ donors.\3\
In these circumstances, we believe that analysis of the impact of the
donor's characteristics on graft survival becomes mandatory before
incorporating a risk-adjustment methodology. Additionally, given that
the IOTA Model is 6 years, and the measure is rolling, meaning that it
measures the rolling total number of functioning grafts relative to the
total number of adult kidney transplants performed for all 6 years, as
described in the 2024 Final Rule at 89 FR 96324, we wanted to continue
discussions to ensure that this measure eventually includes a robust
and appropriate risk-adjustment methodology. Furthermore, we continue
to believe that the lack of risk-adjustment for PY 1 would be minimal
in terms of impacting IOTA participants scores and note that IOTA
participants do not owe a downside risk payment in PY 1, as described
in Sec. 512.430(b)(3)(i). We also note that in the 2024 Final Rule at
89 FR 96364, we stated that while we were finalizing our provision for
calculating the composite graft survival rate as proposed, we would be
stratifying the data from the composite graft survival rate measure to
inform a risk-adjustment methodology for this measure and might
consider future notice and comment rulemaking on this topic.
---------------------------------------------------------------------------
\3\ Olawade, D.B., Marinze, S., Qureshi, N., Weerasinghe, K., &
Teke, J. (2024). Transforming organ donation and transplantation:
Strategies for increasing donor participation and system efficiency.
European Journal of Internal Medicine. <a href="https://doi.org/10.1016/j.ejim.2024.11.010">https://doi.org/10.1016/j.ejim.2024.11.010</a>.
---------------------------------------------------------------------------
As stated in the 2025 Proposed Rule at 90 FR 57605, since
publication of the 2024 Final Rule, many IOTA participants have urged
CMS to include a risk-adjustment methodology in the composite graft
survival rate calculation. As such, in the 2025 Proposed Rule, we
proposed at Sec. 512.428(b)(2) to include a risk-adjustment
methodology in the composite graft survival rate calculation.
Specifically, we proposed at Sec. 512.428(b)(2)(i)(A) and (B) that CMS
would, in accordance with Sec. 512.428(b)(1) through (3), risk-adjust
the composite graft survival rate to account for multiple transplant
recipient and donor characteristics, that includes at minimum the
following:
<bullet> Transplant recipient characteristics:
++ Age.
++ Sex.
++ Kidney function (eGFR/creatinine).
++ Diabetes status.
++ Hypertension with or without cardiovascular disease.
++ Human leukocyte antigen (HLA) mismatch.
++ Plasma renin activity (PRA) levels.\4\
---------------------------------------------------------------------------
\4\ Subsequent to the publication of the 2025 Proposed Rule, we
have found that the wrong term was inadvertently used; we clarify
that actually the term that should have been used was Panel Reactive
Antibody (PRA) levels.
---------------------------------------------------------------------------
<bullet> Donor characteristics:
++ Age.
++ Sex.
++ Kidney function (eGFR/creatinine).
++ Diabetes status.
++ Hypertension history with or without cardiovascular disease.
++ Cardiovascular disease.
++ Human leukocyte antigen (HLA) mismatch.
++ Plasma renin activity (PRA) levels.\5\
---------------------------------------------------------------------------
\5\ Subsequent to the publication of the 2025 Proposed Rule, we
have found that the wrong term was inadvertently used; we clarify
that actually the term that should have been used was Panel Reactive
Antibody (PRA) levels.
---------------------------------------------------------------------------
++Cause of death.
++Donation after cardiac death.
In the 2025 Proposed Rule, we stated our belief that the proposed
transplant recipient and donor characteristics represent well-
established, non-modifiable predictors that significantly influence
graft survival independent of care quality (90 FR 57605). For example,
advanced transplant recipient age increases mortality and
cardiovascular complications, while sex-based differences in immune
response and medication metabolism create distinct risk profiles
requiring fair assessment.\6\ \7\ Diabetes, hypertension, and
cardiovascular disease represent major outcome determinants present at
transplantation that are largely beyond transplant hospitals' short-
term control.\8\ \9\ \10\ Donor age correlates with reduced nephron
mass and shorter graft lifespan, while cause of death and donation type
significantly affect both immediate function and long-term survival,
creating substantial organ quality variation across centers.\11\
[[Page 32797]]
Higher HLA mismatch increases rejection likelihood independent of
clinical management quality, while elevated PRA levels indicate pre-
existing sensitization creating immunological barriers that require
intensive immunosuppression--both characteristics determined by factors
largely beyond a kidney transplant hospital's control.\12\ \13\ Given
the scarcity of donor organs and the IOTA Model's imperative to
maximize transplant opportunities, risk-adjusted allocation strategies
support accepting suboptimal immunological compatibility when
clinically appropriate.\14\
---------------------------------------------------------------------------
\6\ Schwager, Y., Littbarski, S.A., Nolte, A., Kaltenborn, A.,
Emmanouilidis, N., Kleine-D[ouml]pke, D., Klempnauer, J., & Schrem,
H. (2019). Prediction of Three-Year Mortality After Deceased Donor
Kidney Transplantation in Adults with Pre-Transplant Donor and
Recipient Variables. Annals of Transplantation, 24, 273-290. <a href="https://doi.org/10.12659/aot.913217">https://doi.org/10.12659/aot.913217</a>.
\7\ So, S., Au, E.H., Lim, W.H., Lee, V.W., & Wong, G. (2020).
Factors influencing Long-Term patient and allograft outcomes in
elderly kidney transplant recipients. Kidney International Reports,
6(3), 727-736. <a href="https://doi.org/10.1016/j.ekir.2020.11.035">https://doi.org/10.1016/j.ekir.2020.11.035</a>.
\8\ Schwager, Y., Littbarski, S.A., Nolte, A., Kaltenborn, A.,
Emmanouilidis, N., Kleine-D[ouml]pke, D., Klempnauer, J., & Schrem,
H. (2019). Prediction of Three-Year Mortality After Deceased Donor
Kidney Transplantation in Adults with Pre-Transplant Donor and
Recipient Variables. Annals of Transplantation, 24, 273-290. <a href="https://doi.org/10.12659/aot.913217">https://doi.org/10.12659/aot.913217</a>.
\9\ So, S., Au, E.H., Lim, W.H., Lee, V.W., & Wong, G. (2020).
Factors influencing Long-Term patient and allograft outcomes in
elderly kidney transplant recipients. Kidney International Reports,
6(3), 727-736. <a href="https://doi.org/10.1016/j.ekir.2020.11.035">https://doi.org/10.1016/j.ekir.2020.11.035</a>.
\10\ Nishio, A.G., Patel, A., Mehta, S., Yadav, A., Doshi, M.,
Urbanski, M.A., Concepcion, B.P., Singh, N., Sanders, M.L., Basu,
A., Harding, J.L., Rossi, A., Adebiyi, O.O., Samaniego-Picota, M.,
Woodside, K.J., & Parsons, R.F. (2024). Expanding the access to
kidney transplantation: Strategies for kidney transplant programs.
Clinical Transplantation, 38(5). <a href="https://doi.org/10.1111/ctr.15315">https://doi.org/10.1111/ctr.15315</a>.
\11\ Watson, C.J.E., Johnson, R.J., Birch, R., Collett, D., &
Bradley, J.A. (2012). A Simplified Donor Risk Index for Predicting
Outcome After Deceased Donor Kidney Transplantation.
Transplantation, 93(3), 314-318. <a href="https://doi.org/10.1097/tp.0b013e31823f14d4">https://doi.org/10.1097/tp.0b013e31823f14d4</a>.
\12\ Ibid.
\13\ Schwager, Y., Littbarski, S.A., Nolte, A., Kaltenborn, A.,
Emmanouilidis, N., Kleine-D[ouml]pke, D., Klempnauer, J., & Schrem,
H. (2019). Prediction of Three-Year Mortality After Deceased Donor
Kidney Transplantation in Adults with Pre-Transplant Donor and
Recipient Variables. Annals of Transplantation, 24, 273-290. <a href="https://doi.org/10.12659/aot.913217">https://doi.org/10.12659/aot.913217</a>.
\14\ Riley S, Zhang Q, Tse WY, Connor A, Wei Y. Using
information available at the time of donor offer to predict kidney
transplant survival Outcomes: A Systematic Review of Prediction
Models. Transplant International. 2022;35. https://doi:10.3389/
ti.2022.10397.
---------------------------------------------------------------------------
In the 2025 Proposed Rule, we proposed at Sec.
512.428(b)(2)(ii)(A) that CMS would analyze the transplant recipient
and donor characteristics as specified at proposed Sec.
512.428(b)(2)(i)(A) and (B) (90 FR 57605). We also proposed at Sec.
512.428(b)(2)(ii)(B) that CMS would then apply a risk score to each
individual IOTA transplant patient, as defined at Sec. 512.402, based
on the analysis of the transplant recipient and donor characteristics
at proposed Sec. 512.428(b)(2)(ii)(A). Lastly, we proposed at Sec.
512.428(b)(2)(ii)(C)(1) and (2) that CMS would use the calculated
composite graft survival rate risk scores identified at proposed Sec.
512.428(b)(2)(ii)(B) to--
<bullet> Normalize the composite graft survival rate outcome to
control for differences in kidney transplant patient risk; and
<bullet> Adjust the composite graft survival rate, based on the
normalized composite graft survival rate outcome.
In the 2025 Proposed Rule, we stated our belief that this
systematic approach to risk-adjusting kidney transplantation ensures
standardized care delivery while accommodating individual kidney
transplant patient needs and optimizing long-term outcomes through
evidence-based protocols, and continuous quality improvement
initiatives (90 FR 57606). Risk-adjustment accounts for factors that
are associated with the outcome, vary across providers, and are
unrelated to quality of care, so that measure scores reflect true
differences in quality of care.\15\ Accounting for case-mix differences
is important because it recognizes that some IOTA participants care for
older or sicker kidney transplant patients who have lower graft
survival rates. Through the proposed risk-adjustment modeling, we
believed an appropriate outcome rate is set for IOTA participants who
care for kidney transplant patients with certain risk factors,
decreasing the incentive to select younger, healthier patients for
transplantation.
---------------------------------------------------------------------------
\15\ So, S., Au, E.H., Lim, W.H., Lee, V.W., & Wong, G. (2020).
Factors influencing Long-Term patient and allograft outcomes in
elderly kidney transplant recipients. Kidney International Reports,
6(3), 727-736. <a href="https://doi.org/10.1016/j.ekir.2020.11.035">https://doi.org/10.1016/j.ekir.2020.11.035</a>.
---------------------------------------------------------------------------
We sought comments on our proposed composite graft survival rate
risk-adjustment methodology at proposed Sec. 512.428(b)(2). We also
sought comment on what transplant recipient and donor characteristics,
infectious disease status or other medically complex factors,
transplant recipient comorbidity burden, and immunological risk factors
would be significant and clinically appropriate to include in the
proposed risk-adjustment methodology for the composite graft survival
rate metric.
As stated in the 2025 Proposed Rule (90 FR 57606), we considered
all recommendations made by public commenters in the 2024 Final Rule.
For example, a commenter believed that CMS should risk-adjust for at
least a small number of factors that would allow for a simple model
that is understandable by including the biggest drivers for variation
in outcomes and thereby disincentivize the creation of additional
hurdles for more complex transplant recipients (89 FR 96361). The same
commenter believed that a risk-adjustment model that includes age, ESRD
vintage, and diabetes mellitus (y/n) would leverage currently available
data and remain easily measurable and understood. We strongly
considered this recommendation and chose to propose a similar approach
with different factors to account for more scenarios and to reduce the
chance of disincentivizing transplantation.
Multiple commenters in the 2024 Final Rule and some IOTA
participants advocated for the adoption of the SRTR risk-adjustment
methodology, which is presently utilized by both the OPTN and CMS in
existing programs (90 FR 57606). The SRTR risk-adjustment framework
incorporates comprehensive adjustments for both transplant recipient
and donor characteristics, undergoes annual updates to maintain
currency, and is subject to validation and testing protocols. During
each transplant program-specific report (PSR) cycle, the SRTR conducts
a comprehensive refit of the graft survival prediction model,
systematically evaluating numerous potential predictor variables to
optimize the model's predictive accuracy and clinical relevance. The
SRTR calculates the kidney donor risk index (KDRI) in accordance with
the methodology established by Rao et al.\16\ As such, we also
considered, but did not propose, using SRTR's 1-year post-transplant
outcomes risk-adjustment methodology for adult (18+) kidney graft
survival with deceased and living donors, which includes a defined list
of transplant recipient and donor characteristics included in the
calculation that are updated periodically.\17\ There is empirical
support for sophisticated risk-adjustment methodologies like SRTR's,
while acknowledging the need for ongoing refinement as unmeasured risk
factors are identified and measurement precision improves.\18\ \19\
However, we believed this would require increased sophistication and
attention from IOTA participants to interpret the additional
information required and also require additional communications and
education resources at transplant hospitals, potentially at Organ
Procurement Organizations (OPO), and national levels.\20\
---------------------------------------------------------------------------
\16\ Rao, P.S., Schaubel, D.E., Guidinger, M.K., Andreoni, K.A.,
Wolfe, R.A., Merion, R.M., Port, F.K., & Sung, R. S. (2009). A
Comprehensive Risk Quantification Score for Deceased Donor Kidneys:
The Kidney Donor Risk Index. Transplantation, 88(2), 231-236.
<a href="https://doi.org/10.1097/TP.0b013e3181ac620b">https://doi.org/10.1097/TP.0b013e3181ac620b</a>.
\17\ Technical methods for the Program-Specific reports. (n.d.-
b). <a href="https://www.srtr.org/transplant-professionals/program-specific-report/technical-methods-for-the-program-specific-reports/">https://www.srtr.org/transplant-professionals/program-specific-report/technical-methods-for-the-program-specific-reports/</a>.
\18\ Axelrod, D.A., Schwantes, I.R., Harris, A.H., Hohmann,
S.F., Snyder, J.J., Balakrishnan, R., Lentine, K.L., Kasiske, B.L.,
& Schnitzler, M.A. (2022). The need for integrated clinical and
administrative data models for risk-adjustment in assessment of the
cost transplant care. Clinical Transplantation, 36 (12), e14817.
<a href="https://doi.org/10.1111/ctr.14817">https://doi.org/10.1111/ctr.14817</a>.
\19\ Israni, A.K., Hirose, R., Segev, D.L., Hart, A.,
Schaffhausen, C.R., Axelrod, D.A., Kasiske, B.L., & Snyder, J.J.
(2022). Toward continuous improvement of Scientific Registry of
Transplant Recipients performance reporting: Advances following 2012
consensus conference and future consensus building for 2022
consensus conference. Clinical Transplantation, 36 (8), e14716.
<a href="https://doi.org/10.1111/ctr.14716">https://doi.org/10.1111/ctr.14716</a>.
\20\ Technical methods for the Program-Specific reports. (n.d.-
b). <a href="https://www.srtr.org/about-the-data/technical-methods-for-the-program-specific-reports/">https://www.srtr.org/about-the-data/technical-methods-for-the-program-specific-reports/</a>.
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[[Page 32798]]
Additionally, SRTR implements more frequent model rebuilds in
addition to refitting the models every 6 months (90 FR 57606). The
purpose of rebuilding each cycle is to ensure that new transplant
recipient and donor characteristics are incorporated into the risk-
adjustment methodology. Therefore, for the purposes of risk-adjusting
the composite graft survival rate, we considered, but did not propose,
using only SRTR's post-transplant outcomes adult kidney model strata
and most recently available set of coefficients. Alternatively, we also
considered but did not propose utilizing a more limited set of
characteristics than those employed by SRTR for simplification
purposes.
A primary criticism of the SRTR risk-adjustment framework concerns
the potential for encouraging risk aversion (90 FR
57607).<SUP>21 22 23 24 25 26</SUP> Kidney transplant hospitals may
prioritize statistical performance over kidney transplant waitlist
patient access to care, potentially limiting transplant opportunities
for kidney transplant waitlist patients who would benefit despite
higher risk profiles.\27\ There have been persistent questions about
``whether the OPTN data are adequate for risk-adjustments used in SRTR
program-specific reporting.'' \28\ While the current methodology
provides adequate risk-adjustment for available data, the collection of
additional risk factors such as local comorbidity indexes, community
risk factors, cardiovascular risk factors, and anatomical abnormalities
or vascular injury in donor kidneys could further enhance the accuracy
and fairness of IOTA Model evaluations. \29\ Given that the objective
of the IOTA Model is to increase kidney transplant volume, we did not
propose using SRTR's risk-adjustment methodology or using only SRTR's
post-transplant outcomes adult kidney model strata and most recently
available set of coefficients due to concerns that it creates stronger
incentives for risk aversion compared to alternative approaches.
Additionally, given that the composite graft survival rate is a rolling
measure, we also had operational concerns in the use of SRTRs risk-
adjustment methodology in future PYs.
---------------------------------------------------------------------------
\21\ Schenk, A. D., Logan, A. J., Sneddon, J. M., Faulkner, D.,
Han, J. L., Brock, G. N., & Washburn, W. K. (2022). Textbook Outcome
as a Quality Metric in Living and Deceased Donor Kidney
Transplantation. Journal of the American College of Surgeons,
235(4), 624-642. <a href="https://doi.org/10.1097/xcs.000000000000030">https://doi.org/10.1097/xcs.000000000000030</a> 1.
\22\ Kasiske, B. L., Salkowski, N., Wey, A., Israni, A. K., &
Snyder, J. J. (2018). Scientific Registry of Transplant Recipients
program-specific reports: where we have been and where we are going.
Current Opinion in Organ Transplantation, 24(1), 58-63. <a href="https://doi.org/10.1097/mot.0000000000000597">https://doi.org/10.1097/mot.0000000000000597</a>.
\23\ Jay, C., & Schold, J. D. (2017). Measuring Transplant
Center Performance: the Goals Are Not Controversial but the Methods
and Consequences Can Be. Current Transplantation Reports, 4(1), 52-
58. <a href="https://doi.org/10.1007/s40472-017-0138-9">https://doi.org/10.1007/s40472-017-0138-9</a>.
\24\ Snyder, J. J., Salkowski, N., Wey, A., Israni, A. K.,
Schold, J. D., Segev, D. L., & Kasiske, B. L. (2016). Effects of
High[hyphen]Risk Kidneys on Scientific Registry of Transplant
Recipients Program Quality Reports. American Journal of
Transplantation, 16(9), 2646-2653. <a href="https://doi.org/10.1111/ajt.13783">https://doi.org/10.1111/ajt.13783</a>.
\25\ Bowring, M. G., Massie, A. B., Craig-Schapiro, R., Segev,
D. L., & Nicholas, L. H. (2018). Kidney offer acceptance at programs
undergoing a Systems Improvement Agreement. American Journal of
Transplantation, 18(9), 2182-2188. <a href="https://doi.org/10.1111/ajt.14907">https://doi.org/10.1111/ajt.14907</a>.
\26\ Abecassis, M. M., Burke, R., Klintmalm, G. B., Matas, A.
J., Merion, R. M., Millman, D., Olthoff, K., & Roberts, J. P.
(2009). American Society of Transplant Surgeons Transplant Center
Outcomes Requirements-A Threat to Innovation. American Journal of
Transplantation, 9(6), 1279-1286. <a href="https://doi.org/10.1111/j.1600-6143.2009.02606.x">https://doi.org/10.1111/j.1600-6143.2009.02606.x</a>.
\27\ Kasiske, B. L., Salkowski, N., Wey, A., Israni, A. K., &
Snyder, J. J. (2018). Scientific Registry of Transplant Recipients
program-specific reports: where we have been and where we are going.
Current Opinion in Organ Transplantation, 24(1), 58-63. <a href="https://doi.org/10.1097/mot.0000000000000597">https://doi.org/10.1097/mot.0000000000000597</a>.
\28\ Schenk, A. D., Logan, A. J., Sneddon, J. M., Faulkner, D.,
Han, J. L., Brock, G. N., & Washburn, W. K. (2022). Textbook Outcome
as a Quality Metric in Living and Deceased Donor Kidney
Transplantation. Journal of the American College of Surgeons,
235(4), 624-642. <a href="https://doi.org/10.1097/xcs.0000000000000301">https://doi.org/10.1097/xcs.0000000000000301</a>.
\29\ Snyder, J. J., Salkowski, N., Wey, A., Israni, A. K.,
Schold, J. D., Segev, D. L., & Kasiske, B. L. (2016). Effects of
High[hyphen]Risk Kidneys on Scientific Registry of Transplant
Recipients Program Quality Reports. American Journal of
Transplantation, 16(9), 2646-2653. <a href="https://doi.org/10.1111/ajt.13783">https://doi.org/10.1111/ajt.13783</a>.
---------------------------------------------------------------------------
We also considered but did not propose a risk-adjustment
methodology that utilizes a Cox regression model,\30\ which accounts
for time-to-event data and can handle censored observations, making it
a strong potential option for risk-adjustment in transplant outcome
studies (90 FR 57607). In this methodology, censored observations \31\
would include transplant recipients still alive at the end of the
follow-up period, transplant recipients lost to follow-up before
experiencing death or graft failure, and transplant recipients who
withdrew from the study before the event occurred including two donor
and five recipient variables.\32\ Cox regression models have been cited
for strong performance with extreme categories, discriminative power,
and interpretable results.<SUP>33 34 35</SUP> This methodology also
exhibits several inherent limitations, including restrictive
assumptions concerning proportional hazards and linear effects of
variables, inadequate handling of outliers within continuous variables
and variable interactions, and constraints regarding the limited number
of variables that can be incorporated into the modeling
framework.<SUP>36 37</SUP> While we recognized the importance of
incorporating a time-to-event model in the risk-adjustment methodology
to account for the length of graft survival, we chose not to propose a
Cox regression model because it shows only moderate prediction accuracy
overall and needs more validation.
---------------------------------------------------------------------------
\30\ Cox regression, formally designated as Cox proportional
hazards regression, constitutes a statistical methodology employed
to examine the relationship between the time to event occurrence and
one or more predictor variables. This analytical approach represents
a robust statistical tool for investigating survival data,
particularly when addressing time-to-event outcomes where the event
of interest may encompass mortality, disease onset, or other
clinically relevant occurrences.
\31\ In the context of risk-adjustment, a censored observation
refers to incomplete information about the true timing or occurrence
of an outcome of interest, where only certain boundaries are known
rather than the exact value. This phenomenon is particularly
prevalent in healthcare risk-adjustment models when tracking patient
outcomes such as readmissions, complications, or mortality events.
Properly accounting for censored observations through survival
analysis methods is crucial in risk-adjustment because ignoring
censoring can lead to biased risk estimates, inaccurate patient
stratification, and flawed predictive models that may unfairly
penalize or reward healthcare providers based on incomplete outcome
data.
\32\ Senanayake, S., Kularatna, S., Healy, H., Graves, N.,
Baboolal, K., Sypek, M. P., & Barnett, A. (2021). Development and
validation of a risk index to predict kidney graft survival: the
kidney transplant risk index. BMC Medical Research Methodology,
21(1). <a href="https://doi.org/10.1186/s12874-021-01319-5">https://doi.org/10.1186/s12874-021-01319-5</a>.
\33\ Ibid.
\34\ Abd ElHafeez, S., D'Arrigo, G., Leonardis, D., Fusaro, M.,
Tripepi, G., & Roumeliotis, S. (2021). Methods to Analyze Time-to-
Event Data: The Cox Regression Analysis. Oxidative Medicine and
Cellular Longevity, 2021(1), 1-6. <a href="https://doi.org/10.1155/2021/1302811">https://doi.org/10.1155/2021/1302811</a>.
\35\ Wey, A., Hart, A., Salkowski, N., Skeans, M., Kasiske, B.
L., Israni, A. K., & Snyder, J. J. (2020). Posttransplant outcome
assessments at listing: Long-term outcomes are more important than
short-term outcomes. American Journal of Transplantation, 20(10),
2813-2821. <a href="https://doi.org/10.1111/ajt.15911">https://doi.org/10.1111/ajt.15911</a>
\36\ Senanayake, S., Kularatna, S., Healy, H., Graves, N.,
Baboolal, K., Sypek, M. P., & Barnett, A. (2021). Development and
validation of a risk index to predict kidney graft survival: the
kidney transplant risk index. BMC Medical Research Methodology,
21(1). <a href="https://doi.org/10.1186/s12874-021-01319-5">https://doi.org/10.1186/s12874-021-01319-5</a>
\37\ Scheffner, I., Gietzelt, M., Abeling, T., Marschollek, M.,
& Gwinner, W. (2020). Patient Survival After Kidney Transplantation:
Important Role of Graft-sustaining Factors as Determined by
Predictive Modeling Using Random Survival Forest Analysis.
Transplantation, 104(5), 1095-1107. <a href="https://doi.org/10.1097/tp.0000000000002922">https://doi.org/10.1097/tp.0000000000002922</a>.
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We considered, but did not propose, a direct standardization risk-
adjustment approach (90 FR 57607). This method applies standard
population risk profiles \38\ to all IOTA participants.
[[Page 32799]]
Advantages to this method include simple interpretation and precedence
in Care Compare.\39\ Disadvantages are that it requires large sample
sizes and is less precise for smaller kidney transplant hospitals. We
chose not to propose this method because it could disadvantage smaller
IOTA participants.
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\38\ Standard population risk profiles represent a
methodological framework that establishes a reference population to
enable fair and meaningful comparisons between healthcare centers
when patient populations exhibit different risk characteristics. The
methodology employs all patients from all providers as the reference
population, creating a uniform baseline against which all centers
can be evaluated equitably. The process involves estimating the
relationship between patient characteristics (represented as a
vector of covariates X reflecting potential risk factors) and
clinical outcomes for each healthcare center. This established
relationship is then applied to all patients within the reference
population to calculate expected outcomes as if every patient in the
reference population had received treatment at each specific center
under evaluation. Mathematically, this direct standardization
approach can be expressed as d_c = (1/N) x [Sigma] p_c(X_i), where
d_c represents the standardized outcome for center c, N denotes the
total number of patients in the reference population, and p_c(X_i)
represents the estimated probability for patient i's characteristics
at center c.
\39\ Schokkaert, E., & Van De Voorde, C. (2008). Direct versus
indirect standardization in risk-adjustment. Journal of Health
Economics, 28(2), 361-374. <a href="https://doi.org/10.1016/j.jhealeco.2008.10.012">https://doi.org/10.1016/j.jhealeco.2008.10.012</a>.
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We considered, but did not propose, an indirect standardization
(observed-to-expected ratios) risk-adjustment approach, which compares
observed outcomes to expected outcomes based on a risk model (90 FR
57607). Advantages to this method are that it preserves competitive
scoring while ensuring fairness, works well with small sample sizes,
provides precise estimates, and has precedence with the ESRD Quality
Incentive Program (QIP) Standardized Mortality Ratio
(SMR).<SUP>40 41</SUP> We chose not to propose this approach because of
the complexity of designing a robust risk model.
---------------------------------------------------------------------------
\40\ Ibid.
\41\ Scheffner, I., Gietzelt, M., Abeling, T., Marschollek, M.,
& Gwinner, W. (2020). Patient Survival After Kidney Transplantation:
Important Role of Graft-sustaining Factors as Determined by
Predictive Modeling Using Random Survival Forest Analysis.
Transplantation, 104(5), 1095-1107. <a href="https://doi.org/10.1097/tp.0000000000002922">https://doi.org/10.1097/tp.0000000000002922</a>.
---------------------------------------------------------------------------
We considered, but did not propose, a hierarchical logistic
regression approach with indirect standardization (90 FR 57607). This
approach models graft survival probability at the individual transplant
recipient level and accounts for kidney transplant hospital-level
clustering effects.<SUP>42 43</SUP> It produces observed-to-expected
ratios for fair comparison and is compatible with cumulative measure
calculation. The hierarchical logistic regression statistical model
structure we considered using is illustrated in Equation 1:
---------------------------------------------------------------------------
\42\ Hoffman, J. I. (2015). Survival analysis. In Elsevier
eBooks (pp. 621-643). <a href="https://doi.org/10.1016/b978-0-12-802387-7.00035-4">https://doi.org/10.1016/b978-0-12-802387-7.00035-4</a>
\43\ Hoffman, J. I. (2015a). Logistic regression. In Elsevier
eBooks (pp. 601-611). <a href="https://doi.org/10.1016/b978-0-12-802387-7.00033-0">https://doi.org/10.1016/b978-0-12-802387-7.00033-0</a>.
[GRAPHIC] [TIFF OMITTED] TR01JN26.183
This equation risk-adjusts for age, diabetes status, dialysis
vintage, Kidney Donor Profile Index (KDPI), Donation after Cardiac
Death (DCD), which describes donors who are declared dead based on the
cessation of circulatory and respiratory functions, and Panel Reactive
Antibody (PRA). While we acknowledged that this approach demonstrates
substantial technical merit, we believed that the level of complexity
inherent in a hierarchical logistic regression statistical model
structure would introduce operational risks and administrative burden.
Transplant hospital-level variation may not be significant enough to
warrant the added complexity,\44\ as such, we did not believe this was
appropriate to propose for the IOTA Model.
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\44\ Leyland, A. H., & Groenewegen, P. P. (2020b). Multilevel
Modelling for Public Health and Health Services Research. In
Springer eBooks. Springer Nature. <a href="https://doi.org/10.1007/978-3-030-34801-4">https://doi.org/10.1007/978-3-030-34801-4</a>.
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We further considered, but did not propose, using machine learning-
based risk-adjustment methodology, which uses ensemble methods (random
forests, gradient boosting) for risk prediction (90 FR 57607). Machine
learning-based risk-adjustment methodology captures complex
interactions and has high predictive accuracy, but we chose not to
propose it due to concerns that stakeholders may resist the ``black
box'' machine learning-based risk-adjustment methodology and the
limited
[[Page 32800]]
precedence in quality measurement or at CMS.\45\
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\45\ Weissman, G.E., & Maddox, K.E.J. (2023). Guiding risk-
adjustment models toward machine learning methods. JAMA, 330(9),
807. <a href="https://doi.org/10.1001/jama.2023.12920">https://doi.org/10.1001/jama.2023.12920</a>.
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We sought comment on the alternatives considered. Although we did
not propose to include a risk-adjustment methodology that also accounts
for time-to-event data, we sought comment on whether a risk-adjustment
methodology that considers transplant recipient and donor
characteristics in addition to time-to-event data would be appropriate
for calculating the composite graft survival rate in the quality domain
and the best approach to use. We also sought comments on whether the
proposed risk-adjustment methodology should also include a time-to-
event model when calculating the composite graft survival rate in the
quality domain.
In the 2024 Final Rule (89 FR 96364), we finalized inclusion and
exclusion criteria for the numerator and denominator when calculating
the composite graft survival rate at Sec. 512.428(b)(1)(iii) and
(iv)(A). As stated in the 2025 Proposed Rule, since publication, many
IOTA participants have asked CMS to clarify whether multi-organ
transplants are included in both the numerator and denominator when
calculating the composite graft survival rate (90 FR 57608).
Specifically, questions surrounded the current regulation at Sec.
512.428(b)(1)(iii)(E), which states that CMS will exclude offers to
multi-organ candidates (except for kidney/pancreas candidates that are
also listed for kidney alone) from the numerator. We clarified that
this exclusion pertains to the offer phase of the transplant process.
The actual transplant outcomes, when including a kidney, remain within
the measurement scope. This interpretation ensures standardized
application of the exclusion criterion while maintaining the measure's
intended focus on kidney transplant outcomes, regardless of concurrent
multi-organ status. We also noted that the denominator calculation, as
finalized in the 2024 Final Rule, does not contain exclusions for
multi-organ transplants, which allows for comprehensive tracking of all
kidney transplant outcomes. Since CMS clarified that multi-organ
transplants are included in the calculation of the composite graft
survival rate, many IOTA participants have urged CMS to exclude them
from the metric due to the additional complexity of multi-organ
transplantation.
In the 2025 Proposed Rule, we proposed to update the regulation at
Sec. 512.428(b)(1)(iii)(E) to exclude multi-organ transplants (except
for kidney/pancreas transplants) from the numerator (90 FR 57598). As a
result, we also proposed to update the provision at Sec.
512.428(b)(1)(iv)(A) to read as follows: When calculating the composite
graft survival rate, CMS only includes single-organ kidney transplants
and kidney/pancreas transplants for transplant recipients who are 18
years of age and older at the time of the kidney transplant or kidney/
pancreas transplant in the number of kidney transplants performed by
the IOTA participant during each PY in the denominator. For purposes of
the model, we proposed at Sec. 512.402 to define ``single-organ kidney
transplant'' as a procedure in which a kidney alone is surgically
transplanted from a living or deceased donor. We sought comment on our
proposed definition of single-organ kidney transplant at proposed Sec.
512.402.
As stated in the 2025 Proposed Rule, we proposed to exclude multi-
organ transplants--procedures in which a kidney is surgically
transplanted from deceased donor to a transplant recipient along with
one or more organs transplanted simultaneously--except for kidney/
pancreas transplants from the composite graft survival rate metric in
recognition of the increased complexity of clinical outcomes associated
with these procedures (90 FR 57608).\46\ In acknowledgment that multi-
organ transplantation represents a distinct clinical scenario with
potentially different risk profiles, complication rates, and outcomes
compared to single-organ kidney transplantation, we believe it would be
methodologically sound to analyze multi-organ transplant recipients
separately from single-organ kidney transplant and kidney/pancreas
transplant recipients. We proposed to include kidney/pancreas
transplants because, although these procedures are associated with
greater surgical complexity and higher perioperative risk, clinical
evidence demonstrates improved recipient survival compared with kidney
transplantation alone among patients with Type 1 Diabetes Mellitus.\47\
Kidney/pancreas transplantation offers a potential cure for both
diabetes and kidney failure in this population.\48\ Additionally, the
inclusion of kidney/pancreas transplants within the composite graft
survival rate metric aligns with established SRTR methodology, which
includes kidney/pancreas transplants while excluding other multi-organ
transplant procedures from their graft survival criteria.\49\ We
further note that including kidney/pancreas transplants in the
composite graft survival rate metric is consistent with the efficiency
domain as described at Sec. 512.426(b)(1)(iii)(E) where multi-organ
kidney transplant offers (except for kidney/pancreas candidates that
are also listed for kidney alone) are excluded from the organ offer
acceptance rate ratio measure calculation.
---------------------------------------------------------------------------
\46\ Schold, J.D., & Mohan, S. (2021). A deeper dive into the
impact of multiple-organ transplant policy on kidney transplant
candidate prognoses. American Journal of Transplantation, 21(6),
2004-2006. <a href="https://doi.org/10.1111/ajt.16508">https://doi.org/10.1111/ajt.16508</a>.
\47\ Ibid.
\48\ Nagendra, L., Fernandez, C.J., & Pappachan, J.M. (2023).
Simultaneous pancreas-kidney transplantation for end-stage renal
failure in type 1 diabetes mellitus: Current perspectives. World
Journal of Transplantation, 13(5), 208-220. <a href="https://doi.org/10.5500/wjt.v13.i5.208">https://doi.org/10.5500/wjt.v13.i5.208</a>.
\49\ Technical methods for the Program-Specific reports. (n.d.-
b). <a href="https://www.srtr.org/about-the-data/technical-methods-for-the-program-specific-reports/">https://www.srtr.org/about-the-data/technical-methods-for-the-program-specific-reports/</a>.
---------------------------------------------------------------------------
We sought comment on our proposals at proposed Sec.
512.428(b)(1)(iii)(E) and (b)(1)(iv)(A) to exclude multi-organ
transplants except for kidney/pancreas transplants from the numerator
and denominator when calculating the composite graft survival rate in
the quality domain.
We considered retaining the inclusion of multi-organ
transplantation in the calculation of the composite graft survival rate
and solely revising the text of the regulation for clarification
purposes (90 FR 57609). From 2000 to 2020 deceased donor kidney
transplant volume doubled, while multi-organ transplants involving
kidneys increased 6-fold during the same period. Including multi-organ
transplants in metrics could allow for more robust monitoring of multi-
organ transplant outcomes and provide a more comprehensive assessment
of transplant hospital capabilities and outcomes across all transplant
types, ensuring a fair comparison of overall program performance.
However, we chose not to propose including multi-organ transplants
because it would require rigorous analysis considering organ scarcity,
dynamic decision-making, and heterogeneous practice patterns to develop
risk-adjustment methodologies to account for multi-organ transplant
allocation policies.
We considered excluding all multi-organ transplants, including
kidney/pancreas transplants, from the composite graft survival rate due
to the increased surgical complexity and
[[Page 32801]]
perioperative complications (90 FR 57609). However, we chose not to
propose excluding all multi-organ transplants because we believe that
the improved clinical outcomes for kidney/pancreas transplants compared
to kidney transplantation alone for Type 1 Diabetes Mellitus patients
outweighed the added surgical complexity and potential perioperative
complications.
We sought comment on the alternatives considered. We also sought
comment on whether CMS should include multi-organ transplants in the
numerator and denominator and which multi-organ transplants should CMS
include or exclude.
The following is a summary of the public comments received on all
of the calculation of metric proposals and alternatives considered set
out in this section and our responses:
Comment: Many commenters expressed support for including risk-
adjustment in the composite graft survival measure. Commenters stated
that risk-adjustment promotes fairness and accuracy in performance
measurement, prevents IOTA participants serving medically complex
patient populations from being penalized, and aligns incentives with
the goal of expanding transplant access. Commenters also noted that
risk-adjustment facilitates meaningful comparisons across IOTA
participants and may reduce risk averse behavior. Several commenters
emphasized that risk-adjustment is critical to achieving the goals of
the IOTA Model.
Some of these commenters noted that without risk-adjustment, IOTA
participants may face unintended pressure to avoid higher risk donors
or recipients in order to protect performance scores, which could be
counterproductive to the model's objectives of increasing kidney
transplant volume and reducing waitlist mortality.
Response: We appreciate the feedback from commenters, and we agree
about the importance of including a risk-adjustment methodology in the
calculation of the composite graft survival rate metric in the quality
domain. As stated in the 2025 Proposed Rule (90 FR 57606), we believe
that including a risk-adjustment methodology for the composite graft
survival rate to account for inherent donor and transplant recipient
conditions that significantly influence graft survival, independent of
care quality, supports meaningful and equitable performance
measurement.
Comment: Many commenters urged CMS to adopt the existing SRTR risk-
adjustment methodology rather than developing a separate approach for
the IOTA Model, citing concerns that the proposed risk-adjustment
methodology lacked sufficient clinical input and validation, may be
complex to implement, could incentivize risk-averse behavior, and may
not meaningfully affect a cumulative measure over time while
potentially failing to keep pace with evolving clinical practice.
In the context of alternative considerations, several commenters
stated that SRTR has the expertise and access to national data
necessary to support development of a composite graft survival model
that incorporates clinically validated variables and can be updated
regularly to reflect evolving practices and emerging factors. In
addition, a commenter noted that using SRTR data could reduce
administrative burden because transplant programs and organ procurement
organizations already submit these data through existing reporting
systems. The commenter further cited prior analysis estimating the cost
of additional data collection and emphasized the importance of
considering such burden when evaluating alternative approaches.
Commenters also stated that the SRTR risk-adjustment methodology is
validated, evidence-based, and widely used in the transplant community.
Commenters noted that it aligns with existing standards, includes
established processes for data review and correction, reduces
duplicative reporting burden, and is updated on a regular basis with
input from clinical experts.
Response: Given the numerous concerns from stakeholders regarding
the proposed risk-adjustment methodology for calculating the composite
graft survival rate, we recognized an updated risk-adjustment
methodology may be necessary to strengthen the model. As indicated in
the 2025 Proposed Rule (90 FR 57606) and discussed in the preamble of
this final rule, we considered using SRTR's adult kidney graft survival
first-year post-transplant models for both deceased donor and living
donor kidney transplants,\50\ as well as a simplified approach
utilizing a more limited set of characteristics than those employed by
SRTR. Ultimately, for the reasons set forth in the 2025 Proposed Rule,
we decided against either approach because, despite its sophistication
and empirical support, it introduces substantial operational complexity
and stronger incentives for risk aversion that could undermine the IOTA
Model's goal of increasing kidney transplant volume. Additionally, we
believed that these approaches could require extensive interpretive
effort and additional resources from transplant hospitals, OPOs, and
national partners. Instead, in the 2025 Proposed Rule, we constructed,
and proposed, a risk-adjustment methodology to ensure that the
composite graft survival rate accurately reflects true differences in
quality of care by controlling for well established, nonmodifiable
kidney transplant recipient and donor risk factors that meaningfully
influence graft survival, thereby promoting equitable comparisons
across IOTA participants and reducing incentives to avoid higher risk
patients. We direct readers to section II.B.2.b(2)(a) of this final
rule for a full discussion on the risk-adjustment methodology proposed
in the 2025 Proposed Rule. However, we recognize that there may be a
more appropriate balance between the more complex methodologies we
considered and the simpler methodology we proposed, which aims to
reduce complexity while supporting a more attainable and practical
approach for IOTA participants.
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\50\ Technical methods for the Program-Specific reports. (n.d.-
b). <a href="https://www.srtr.org/about-the-data/technical-methods-for-the-program-specific-reports/">https://www.srtr.org/about-the-data/technical-methods-for-the-program-specific-reports/</a>
---------------------------------------------------------------------------
We conducted additional analysis that examined one of the risk-
adjustment methodologies that we considered for calculating composite
graft survival rate as described in section II.B.2.b(2)(a) of the 2025
Proposed Rule. Specifically, based on public comment, we reexamined
whether we could incorporate SRTR's risk-adjustment methodology into
the composite graft survival rate. We compared this methodology to what
we proposed, as described in this section of this final rule, to
determine whether an alternative risk-adjustment methodology for
calculating the composite graft survival rate would be potentially more
attainable.
Based on additional analysis and the commenters' concerns about the
proposed risk-adjustment methodology, we are finalizing an updated
risk-adjustment methodology in the calculation of the composite graft
survival rate as follows:
Beginning in PY 2, for each PY, CMS will risk-adjust the observed
graft survival rate to account for differences across IOTA participants
in donor and candidate characteristics expected to influence graft
survival. First, CMS will calculate the observed composite graft
survival rate using the following equation (see Equation 2), where the
observed composite graft survival rate is
[[Page 32802]]
the IOTA participant's actual composite graft survival rate, as
finalized in Equation 1 to Paragraph (b)(1) at Sec. 512.428, with a
Bayesian adjustment applied for statistical reliability.
[GRAPHIC] [TIFF OMITTED] TR01JN26.184
To enhance the statistical reliability of the composite graft
survival rate, particularly for IOTA participants with a small volume
of kidney transplants, a +2 Bayesian adjustment will be applied to the
observed composite graft survival rate. This is a form of statistical
smoothing that addresses instability that occurs when calculating rates
from small transplant volume numbers. For instance, at a kidney
transplant hospital with very few kidney transplants, a single poor
outcome can cause its observed survival rate to be an extreme and
potentially misleading value (for example, 0 percent). This volatility
can obscure the IOTA participant's true underlying performance. The +2
Bayesian adjustment helps correct this.
The adjustment works by adding two ``pseudo-events'' to each IOTA
participant's actual data before calculating their composite graft
survival rate. This technique prevents an IOTA participant's score from
swinging dramatically based on just one or two outcomes. By
implementing this Bayesian adjustment, the risk-adjustment model
ensures that performance scores are more reliable across all IOTA
participants, preventing smaller volume kidney transplant hospitals
from being unfairly penalized due to random chance.
Next, CMS would calculate the risk score for each IOTA participant
using the following equation (see Equation 3), which is a ratio that
quantifies each IOTA participant's risk of graft failure relative to
the national graft failure rate. It compares each IOTA participant's
expected graft failure rate to the national graft failure rate.
[GRAPHIC] [TIFF OMITTED] TR01JN26.185
A risk score greater than 1.0 indicates the IOTA participant's
kidney transplant patients are estimated, on average, to have a higher
risk of graft failure compared to the national graft failure rate. A
risk score less than 1.0 means their kidney transplants are estimated,
on average, to have a lower risk of graft failure. Multiplying the
observed composite graft survival rate by the risk score (see Equation
6) adjusts the performance on this metric upward for IOTA participants
taking on more risk and downward for IOTA participants with kidney
transplants, on average, with less risk of graft failure, allowing for
a more equitable comparison of performance.
To calculate the expected graft failure rate needed for the risk
score, CMS would use SRTR's adult kidney graft survival first-year,
post-transplant risk-adjustment models for both deceased donor and
living donor kidney transplants \51\ which employs a Cox proportional
hazards regression model to perform a time-to-event (TTE) analysis (see
Equation 4).
---------------------------------------------------------------------------
\51\ <a href="https://www.srtr.org/transplant-professionals/program-specific-report/posttransplant-outcomes-risk-adjustment/">https://www.srtr.org/transplant-professionals/program-specific-report/posttransplant-outcomes-risk-adjustment/</a>
[GRAPHIC] [TIFF OMITTED] TR01JN26.186
In the equation for calculating the expected graft failure rate,
S<INF>0</INF>(t) equals the baseline survival function and [beta]X
equals the linear predictor computed from SRTR's adult kidney graft
survival first-year post-transplant risk-adjustment models variables
and model coefficients. We note that this statistical approach is
consistent with the core of the SRTR framework but by risk-adjusting
the observed composite graft survival rate it has been adapted for the
cumulative structure of the composite graft survival rate metric, as
illustrated in Table 1.
[[Page 32803]]
[GRAPHIC] [TIFF OMITTED] TR01JN26.187
This risk-adjustment methodology would use the most recently
available comprehensive and validated set of risk factors and
coefficients from SRTR's adult kidney graft survival first-year post-
transplant risk-adjustment models for both deceased donor and living
donor kidney transplants.\52\ These include dozens of donor, transplant
recipient, and transplant characteristics, such as donor and transplant
recipient age, transplant recipient diabetes status, Calculated Panel
Reactive Antibody (CPRA), Donation after Circulatory Death (DCD)
status, cold ischemic time, and Kidney Donor Profile Index (KDPI)
components. By using SRTR's established factors, the model aligns with
commenters' requests for a robust, clinically validated system, and
avoids issues identified in the initial proposal, such as the use of
less reliable variables like estimated Glomerular Filtration Rate
(eGFR) for dialysis patients. We note that we intend to analyze and
monitor the variables and coefficients, and if analysis warrants
updated coefficients, we may propose a new or updated policy through
future comment and notice rulemaking as appropriate.
---------------------------------------------------------------------------
\52\ <a href="https://www.srtr.org/transplant-professionals/program-specific-report/posttransplant-outcomes-risk-adjustment/">https://www.srtr.org/transplant-professionals/program-specific-report/posttransplant-outcomes-risk-adjustment/</a>.
---------------------------------------------------------------------------
CMS would calculate the national graft failure rate for the
relevant PY by dividing the number of graft failures, as defined by
SRTR, among kidney transplants furnished to patients 18 years of age or
older and performed during the given PY by the number of kidney
transplants furnished to patients 18 years of age or older and
performed during the given PY (see Equation 5). SRTR counts a graft as
failed when follow-up information indicates that one of the following
occurred before the reporting time point: (1) graft failure (except for
heart and liver, when re-transplant dates are used instead); (2) re-
transplant (for all transplants except heart-lung and lung); or (3)
death.\53\ CMS would identify graft failures in accordance with Sec.
512.428(b)(1)(iv)(B). All kidney transplant hospitals, except for
pediatric kidney transplant hospitals as defined at Sec. 512.402,
would be included in the numerator and denominator. By limiting both
the numerator and denominator to kidney transplants performed during
the relevant PY, this calculation is temporally aligned with each IOTA
participant's expected graft failure rate calculation, ensuring a
consistent and comparable time horizon across both rates. Once
calculated, the resulting amount is the national graft failure rate for
kidney transplants performed for the relevant PY. The risk score would
be normalized to provide a national mean of 1.0.
---------------------------------------------------------------------------
\53\ Technical Methods for the Program-Specific Reports. (n.d.).
<a href="http://Www.srtr.org">Www.srtr.org</a>. Retrieved December 3, 2022, from <a href="https://www.srtr.org/transplant-professionals/program-specific-report/technical-methods-for-the-program-specific-reports/">https://www.srtr.org/transplant-professionals/program-specific-report/technical-methods-for-the-program-specific-reports/</a>; OPTN. (2022). OPTN Enhanced
Transplant Program Performance Metrics. <a href="https://optn.transplant.hrsa.gov/media/r5lmmgcl/mpsc_performancemetrics_3242022b.pdf">https://optn.transplant.hrsa.gov/media/r5lmmgcl/mpsc_performancemetrics_3242022b.pdf</a>.
[GRAPHIC] [TIFF OMITTED] TR01JN26.188
[[Page 32804]]
Lastly, the risk-adjusted composite graft survival rate for an IOTA
participant would be calculated by multiplying its observed composite
graft survival rate by a calculated risk score (see Equation 6). This
approach maintains the risk-adjusted composite graft survival rate
metric as an intuitive survival rate, directly adjusted for expected
graft failure risk.
[GRAPHIC] [TIFF OMITTED] TR01JN26.189
We clarify that, in the risk-adjustment methodology that we are
finalizing and as described above, CMS would not round any numerical
values derived from any of the calculations.
The following simplified example demonstrates how the risk-
adjustment methodology works for two IOTA participants in PY2, IOTA
participant A and IOTA participant B:
<bullet> Calculate observed composite graft survival rate. Table 2
contains the example number of kidney transplants, and the observed and
adjusted graft survival rates.
[GRAPHIC] [TIFF OMITTED] TR01JN26.190
<bullet> Calculate Risk Score: Using SRTR's adult kidney graft
survival first-year post-transplant risk-adjustment models for both
deceased donor and living donor kidney transplants,\54\ we compute the
expected 1-year graft survival rates for IOTA participant A and IOTA
participant B as well as the national 1-year graft survival rate, and
the risk score for each IOTA participant, as illustrated in Table 3.
---------------------------------------------------------------------------
\54\ <a href="https://www.srtr.org/transplant-professionals/program-specific-report/posttransplant-outcomes-risk-adjustment/">https://www.srtr.org/transplant-professionals/program-specific-report/posttransplant-outcomes-risk-adjustment/</a>
[GRAPHIC] [TIFF OMITTED] TR01JN26.191
<bullet> Composite Graft Survival Rate Risk-Adjusted Calculation:
As illustrated in Table 4, the composite graft survival risk rate risk-
adjusted score would be calculated by using the risk score, calculated
in step 2, to risk-adjust the Bayesian-adjusted observed composite
graft survival rate (see Table 2, step 4) that was calculated in step 1
to arrive at the risk-adjusted composite graft survival rate, as
illustrated in Table 4, step 7. In this example, the final risk-
adjusted composite graft survival rate: 0.824 (observed composite graft
survival rate) x 0.967 (risk score) = 0.797 for IOTA participant A, and
0.882 (observed composite graft survival rate) x 1.053 (risk score) =
0.929 for IOTA participant B.
[[Page 32805]]
[GRAPHIC] [TIFF OMITTED] TR01JN26.192
Initially, IOTA participant B (88 percent composite graft survival
rate) appeared to perform better than IOTA participant A (82 percent
composite graft survival rate). However, after risk-adjustment, the
difference is amplified. IOTA participant A's performance is adjusted
downward because its kidney transplants had lower-than-average risk
(risk score < 1.0), meaning a higher survival rate was expected given
its patient mix. IOTA participant B's strong performance is adjusted
upward because it was achieved with higher-risk kidney transplants. The
final risk-adjusted composite graft survival rate provides a more
equitable basis for comparing performance.
We note that while this approach adapts elements from the SRTR
framework rather than fully replicating its hierarchical model, it
establishes a necessary baseline consistent with the IOTA Model's
measure structure, as illustrated in Table 1. We intend to monitor IOTA
participant performance under this methodology and, if necessary,
propose a new or updated policy in future comment and notice
rulemaking.
Comment: A commenter recommended that CMS forgo the inclusion of a
risk-adjustment methodology in the calculation of the composite graft
survival rate altogether, advocating for the exclusion of any risk-
adjustment for donor and recipient characteristics. The commenter
stated that, due to the cumulative year-over-year nature of the metric,
the inclusion of risk-adjustment may have limited impact on results,
particularly in later PYs.
Response: We thank the commenter for their feedback and for their
perspective on the role of risk-adjustment in the composite graft
survival rate metric. However, we respectfully disagree with the
commenter's recommendation to forgo risk adjustment for donor and
recipient characteristics.
We continue to believe that risk adjustment is an essential
component of fair and meaningful performance measurement. Graft
survival outcomes are influenced by a range of clinical factors related
to both donors and recipients that are independent of care quality.
Without appropriate risk adjustment, IOTA participants that serve more
medically complex patient populations or accept higher-risk organs may
be disproportionately penalized, which could create unintended
incentives to avoid such cases.
We acknowledge the commenter's point that the cumulative, year-
over-year structure of the measure may moderate the impact of risk-
adjustment over time. However, we believe that incorporating risk-
adjustment remains important across all PYs to ensure that comparisons
reflect differences in care rather than underlying patient or donor
characteristics.
For these reasons, we are finalizing the inclusion of a risk
adjustment methodology for the composite graft survival rate, as
described in comment responses noted previously in this section, to
support equitable comparisons and align incentives with the model's
goals of improving access and outcomes in kidney transplantation.
Comment: Numerous commenters expressed opposition to the risk-
adjustment methodology as proposed in the 2025 Proposed Rule, raising
concerns similar to those described elsewhere in this section. Several
commenters stated that the proposed methodology includes variables that
are not routinely collected, clinically validated, or commonly used in
transplant practice, may lack appropriate weighting for risk factors,
and omits important validated variables. For example, a commenter
stated that developing risk-adjustment methodologies is inherently
complex and dynamic and expressed concern that the regulatory process
may not be well suited for this purpose. This commenter also suggested
that a simplified risk-adjustment approach could be susceptible to
manipulation, potentially influencing patient and donor selection
practices. Another commenter expressed concern that, because only a
subset of eligible kidney transplant hospitals participate in the IOTA
Model, a model specific to IOTA participants may not reflect national
risk patterns.
In the context of alternative considerations, several commenters
stated that the proposed methodology may not adequately capture the
full range of donor and recipient risk and may lack key variables
necessary for accurate modeling. These commenters also noted the
existence of established and validated frameworks, such as those
developed by OPTN and SRTR, and questioned the need for a separate
risk-adjustment approach within the IOTA Model.
Response: We thank the commenters for their comprehensive and
detailed feedback on the risk-adjustment methodology proposed for
inclusion in the composite graft survival rate calculation in the 2025
Proposed Rule (90 FR 57605). We carefully considered the technical,
clinical, and operational concerns raised, including those related to
variable selection, model validity, implementation complexity, and
alignment with existing transplant frameworks.
As described in comment responses noted previously in this section,
we are not finalizing the risk-adjustment methodology as proposed.
Instead, we are finalizing an updated risk-adjustment methodology for
the composite graft survival rate that is based on an adapted SRTR
framework and tailored to align with the composite structure of the
IOTA measure. This approach reflects our effort to balance the need for
methodological rigor with operational feasibility and clinical
relevance.
We believe that this adapted SRTR-based risk-adjustment methodology
leverages an established and widely used framework that has been
developed with extensive clinical expert input and is subject to
ongoing validation, recalibration, and refinement. By building on this
foundation, we are able to incorporate clinically validated donor and
recipient characteristics that are known to influence graft survival
independent of care quality, while avoiding the need to develop a
wholly new and untested methodology.
Additionally, we believe that aligning with an established
framework supports greater consistency with existing
[[Page 32806]]
transplant evaluation systems and reduces potential confusion or burden
for IOTA participants, who may already be familiar with SRTR-based
approaches. At the same time, adapting the methodology to the composite
structure of the IOTA measure allows us to address the unique design
considerations of the model, including its rolling measurement approach
and performance year structure.
Overall, we believe this updated risk-adjustment methodology
improves the accuracy, fairness, and interpretability of the composite
graft survival rate measure by ensuring that performance differences
more appropriately reflect variation in quality of care rather than
underlying patient or donor risk profiles.
Comment: Some commenters expressed concerns about risk-adjustment
implementation, including concerns about risk aversion, complexity, and
update frequency. In the context of the alternatives considered, a
commenter specifically recommended that CMS prioritize stability in the
risk-adjustment approach during the model performance period,
suggesting the use of a limited set of clearly defined risk-adjusters
with fixed effects across the model performance period, such as donor
type, patient age, dialysis duration, and diabetes status, to allow
IOTA participants to make informed operational and clinical decisions.
This commenter further noted that frequent methodological changes
during a model performance period may create uncertainty and reduce the
ability of IOTA participants to respond effectively to model
incentives.
Response: We thank the commenters for their feedback regarding the
implementation of the risk-adjustment methodology in the composite
graft survival calculation, including concerns related to potential
risk-averse behavior, methodological complexity, and the frequency of
updates. We also appreciate the recommendation to prioritize stability
during the model test period through the use of a limited set of fixed
risk-adjustment factors to support informed operational and clinical
decision-making.
As mentioned in comment responses noted previously in this section,
we are finalizing a modified methodology, in response to public
comments, we are finalizing a modified risk-adjustment methodology for
the composite graft survival rate calculation that is designed to
balance clinical validity, methodological rigor, and operational
feasibility. Specifically, the finalized approach leverages an adapted
SRTR-based risk-adjustment framework that incorporates a comprehensive
and clinically validated set of donor and recipient characteristics and
aligns with the cumulative structure of the IOTA measure.
We acknowledge concerns that risk-adjustment may incentivize risk-
averse behavior. However, we believe that incorporating a robust risk-
adjustment methodology is essential to ensure fair comparisons across
IOTA participants and to mitigate disincentives for accepting higher-
risk organs or treating more complex patients. By adjusting for
expected differences in graft failure risk, the methodology supports
equitable performance assessment and aligns with the model's goal of
expanding transplant access.
We also recognize concerns regarding complexity. While we
considered a more limited set of fixed risk-adjustment factors, we
believe that such an approach would not sufficiently capture the full
range of donor and recipient risk and could reduce the accuracy and
fairness of the measure. By leveraging the established SRTR framework,
which is widely used and familiar to transplant programs, we believe
the finalized methodology appropriately balances complexity with
usability while relying on clinically validated variables.
With respect to stability and update frequency, we agree that
predictability is important for IOTA participants. To address this, the
methodology we are finalizing uses the most recently available
validated SRTR variables and coefficients and does not introduce
frequent or ad hoc methodological changes. We note that we intend to
analyze and monitor the coefficients, and if analysis warrants updated
coefficients, we would propose a new or updated policy through future
comment and notice rulemaking, thereby providing transparency and
stability during the model performance period.
Finally, we note that we have incorporated features to improve
reliability and reduce unintended variability, including a Bayesian
adjustment to stabilize performance for lower kidney transplant volume
IOTA participants. We believe that this approach helps ensure that
performance scores are not disproportionately influenced by small
sample sizes and supports more consistent and actionable results for
IOTA participants. Additionally, we will analyze and monitor the
performance of IOTA participants to assess the impact of this policy.
If our analysis indicates the possible need for a new or revised
policy, we will consider addressing it through future notice and
comment rulemaking. We also intend to analyze and monitor SRTR's
variables and coefficients, and if analysis warrants updated variables
or coefficients, we would propose a new or updated policy through
future comment and notice rulemaking, thereby providing transparency
and stability during the model performance period.
For these reasons, we believe the risk-adjustment methodology that
we are finalizing appropriately addresses commenters' concerns while
maintaining a robust, equitable, and stable framework that enables IOTA
participants to respond effectively to model incentives and supports
the model's goals of improving kidney transplant access and outcomes.
Comment: Many commenters opposed the proposed risk-adjustment
methodology, raising significant concerns about its design and urging
CMS to reconsider or adopt an alternative approach. These commenters
stated that the methodology lacked sufficient clinical input and had
not been adequately validated for use in the transplant population.
Some of these commenters raised concerns about how frequently variables
and coefficients would be updated and whether the methodology would
remain aligned with evolving clinical practice.
Separately, some commenters expressed concerns regarding the
implementation of risk-adjustment. Several noted that any risk-
adjustment methodology, including SRTR's, could incentivize IOTA
participants to be more cautious in accepting higher-risk organs or
patients. A few commenters also highlighted the complexity of the SRTR
methodology and the potential need for additional education and
resources to support its interpretation. A commenter questioned whether
risk-adjustment would meaningfully affect a cumulative measure over
time, particularly in later performance years.
Response: We thank the commenters for their feedback regarding the
proposed risk-adjustment methodology, including concerns related to
clinical input and validation, implementation complexity, potential for
risk-averse behavior, the cumulative nature of the measure, and update
frequency. We note that we are not finalizing the proposed risk-
adjustment methodology and are instead finalizing an updated risk-
adjustment methodology based on an adapted SRTR framework, as described
in previous comment responses in this section. We direct readers to
comment responses noted previously for further discussion.
[[Page 32807]]
Comment: Numerous commenters identified what they believe were
technical errors in the proposal, including the misidentification of
``PRA'' as ``plasma renin activity'' rather than ``Panel Reactive
Antibody,'' a measure of the percentage of cells from a panel of donors
with which a transplant candidate's serum reacts, indicating the degree
of sensitization to potential donor antigens, and the incorrect
inclusion of donor PRA when PRA only applies to recipients. Several
commenters also provided detailed explanations of what PRA actually
measures and its clinical significance in transplant matching. A few
commenters further noted that the current standard in transplant
medicine has largely moved to CPRA, which provides a more precise
measure of sensitization, and recommended that CMS update its
terminology accordingly. Commenters also stated that PRA is clinically
relevant only for transplant recipients, not organ donors. Many
commenters also provided detailed clinical explanations, noting that
donor organs neither transmit nor synthesize donor-specific antibodies
in response to antigen exposure, such that measuring a panel of
reactive antibodies in an organ donor is not clinically indicated. Some
commenters further stated that the inclusion of donor PRA in the
proposed methodology reflects a fundamental misunderstanding of
transplant immunology.
Response: We appreciate the detailed clinical explanations provided
by commenters and agree with this feedback. Subsequent to the
publication of the 2025 Proposed Rule, we acknowledge that we
inadvertently used; we clarify that the term that should have been used
was Panel Reactive Antibody (PRA) levels. We note that we are not
finalizing the proposed risk-adjustment methodology, as described in
this section of this final rule, and are instead finalizing an updated
risk-adjustment methodology based on an adapted SRTR framework, as
described in previous comment responses in this section. We direct
readers to comment responses noted previously for further discussion.
Comment: Several commenters noted that the proposed risk-adjustment
methodology for inclusion in the composite graft survival rate
calculation included donor and transplant recipient variables that are
not routinely collected, are difficult to define consistently, or are
inappropriate for the intended purpose. Specifically, commenters stated
that using eGFR and creatinine for dialysis patients is problematic
because these values reflect dialysis clearance rather than native
kidney function, and creatinine values can fluctuate post-dialysis.
They also identified variables such as ``diabetes status'' and
``hypertension with or without cardiovascular disease'' as not being
consistently documented, subject to varied interpretation, and not
currently reported to the OPTN, which would necessitate additional data
collection. Finally, commenters identified what they believed were
important clinical variables omitted from the proposed methodology and
recommended additional variables for inclusion.
In the context of the alternative considerations, several
commenters provided additional specific recommendations, including
retransplant status, APOL1 genotype, donor viral studies, prior
national organ turndowns (rescue allocation pathways), body mass index
(BMI), warm ischemic time, normothermic regional perfusion (NRP) use,
and socioeconomic factors.
Response: We thank the commenters for their feedback and
acknowledge the concerns raised regarding the proposed risk-adjustment
methodology. As described in comment responses noted previously in this
section, we are not finalizing the proposed risk-adjustment
methodology. Instead, we are finalizing an updated risk-adjustment
methodology for the composite graft survival rate calculation that is
based on an adapted SRTR framework and aligned with the cumulative
structure of the metric. By leveraging SRTR's established variables and
coefficients, we believe the finalized approach aligns with commenters'
requests for a robust, clinically validated methodology and addresses
issues identified in the proposal, including the use of less reliable
or inconsistently defined variables such as ``eGFR'' for dialysis
patients. We direct readers to comment responses noted previously in
this section for further discussion of these changes and our rationale.
Comment: Some commenters identified clinical variables they
considered to be significant omissions from the proposed risk-
adjustment methodology, citing peripheral vascular disease, serum
albumin, dialysis duration, time on waitlist, cold ischemic time,
functional status, Kidney Donor Profile Index (KDPI) or its individual
components, donor type (including living, deceased, and donation after
circulatory death), and ischemic cardiac disease. Many commenters noted
that these variables are incorporated into established models for well-
documented clinical reasons and have been validated as meaningful
predictors of transplant outcomes. Several commenters further
recommended the inclusion of additional variables, such as retransplant
status, APOL1 genotype, donor viral studies, prior national organ
turndowns (that is, rescue allocation pathways), BMI, warm ischemic
time, normothermic regional perfusion (NRP) use, and socioeconomic
factors including insurance status, education level, and employment. A
commenter recommended the incorporation of individual KDPI components
rather than aggregate scores to enhance methodological transparency.
Another commenter suggested the inclusion of the kidney transplant
recipient's geographic accessibility to the kidney transplant hospital
in order to account for access and transportation challenges
encountered in the post-transplant period, particularly among patients
residing in rural areas.
Response: We thank the commenters for their feedback regarding
clinical variables they identified as omitted from the proposed risk-
adjustment methodology. We acknowledge the importance of incorporating
clinically relevant and validated predictors of transplant outcomes. As
described in comment responses noted previously in this section, we are
not finalizing the proposed risk-adjustment methodology and are instead
finalizing an updated risk-adjustment methodology based on an adapted
SRTR framework. This approach incorporates a comprehensive set of
clinically validated donor and recipient characteristics and reflects
established consensus within the transplant community regarding
appropriate risk-adjustment factors. We believe that leveraging the
SRTR-based risk-adjustment methodology addresses many of the concerns
raised by commenters regarding omitted variables while supporting a
robust and clinically grounded approach to performance measurement. We
direct readers to comment responses noted previously in this section
for further discussion of these changes and our rationale.
Comment: Commenters noted problems with using (eGFR) and creatinine
for risk-adjustment. Commenters stated that eGFR is not useful for
patients on dialysis, as most transplant candidates are dialyzed and
the value reflects dialysis clearance rather than native kidney
function. Several commenters noted that creatinine fluctuates post-
dialysis and does not accurately reflect kidney function for risk-
adjustment purposes. Some commenters also noted that eGFR can be
artificially elevated if the transplant candidate was on dialysis,
rendering these values misleading for
[[Page 32808]]
risk assessment. A commenter specifically noted that a transplant
candidate may be in acute renal failure and on dialysis, with measured
serum creatinine and therefore eGFR appearing within normal range, but
purely as an artifact of dialysis machine function rather than actual
kidney function. Another commenter suggested that CMS incorporate BMI
into its kidney function measurement, as creatinine levels carry
different clinical meanings for individuals with varying BMIs.
Response: We thank the commenters for their feedback regarding the
elements included in the risk-adjustment methodology. We note that we
are not finalizing the proposed risk-adjust methodology, as described
in this section of this final rule, and are instead finalizing an
updated risk-adjustment methodology based on an adapted SRTR framework,
as described in previous comment responses in this section, which
includes eGFR and BMI. We direct readers to comment responses noted
previously for further discussion.
Comment: Many commenters requested greater transparency regarding
the proposed risk-adjustment methodology, including the publication of
specific equations, model coefficients, variable definitions, and
weighting approaches. Commenters stated that without this information,
IOTA participants may not be able to fully understand how performance
is evaluated or take meaningful steps to improve outcomes. Several
commenters further recommended that CMS provide a detailed
methodological description and allow for public comment prior to
implementation. These commenters suggested that CMS develop and
evaluate multiple alternative risk-adjustment models, empirically
identify variables for inclusion, validate each approach, and make
comparative results publicly available. In addition, a commenter noted
that without transparency into the risk-adjustment methodology,
including variable selection, weighting, and update frequency, IOTA
participants may have limited ability to monitor performance or respond
effectively to model incentives.
Response: We appreciate this concern and recognize the need for
transparency. To address the comments we received regarding providing
transparency in describing how the risk-adjustment methodology in the
calculation of the composite graft survival rate is calculated and
applied so they can understand and track their kidney transplant
hospitals' performance, we intend to provide sub-regulatory guidance on
the technical specifications for calculating the inclusion of the risk-
adjustment methodology in the composite graft survival rate
calculation. We thank the commenters for their feedback regarding the
proposed risk-adjustment methodology.
Comment: Several commenters expressed concern about the lack of
data review and correction process. Commenters noted that SRTR allows
transplant hospitals to review and correct data before public
reporting, and that incomplete or inaccurate data, particularly data
originating from OPOs, could compromise the accuracy of risk-adjustment
under the proposed approach. Several commenters specifically requested
that IOTA participants be permitted to review, complete, or correct
donor and recipient data used for the risk-adjustment model, noting
that OPOs frequently submit incomplete data that negatively impacts the
accuracy of an IOTA participant's risk-adjustment. Commenters also
requested clarification on how donor and recipient data will be
obtained and validated and expressed concern about the absence of a
formal hospital review and correction process.
Response: We thank the commenters for their feedback. We note that
we are not finalizing the proposed risk-adjustment methodology, as
described in this section of this final rule, and are instead
finalizing an updated risk-adjustment methodology based on an adapted
SRTR framework, as described in previous comment responses in this
section. We note that in accordance with Sec. 512.422(b), we will
utilize data that is available when we calculate final performance
scores for a given PY in accordance with Sec. 512.430(d). We direct
readers to comment responses noted previously for further discussion.
Comment: Several commenters expressed concern that using a
different risk-adjustment methodology for IOTA than SRTR could create
conflicting performance standards. Commenters explained that IOTA
participants could perform well in the IOTA Model but poorly under SRTR
metrics, potentially threatening their COE status, a designation used
by commercial payers to determine network participation, preferred
reimbursement arrangements, and referral eligibility. Since commercial
transplant volume often exceeds Medicare FFS volume for many IOTA
participants, commenters stated that the financial risk of losing COE
status could exceed any IOTA Model payments. Commenters noted that this
could cause IOTA participants to prioritize protecting their SRTR
standings over the IOTA Model goals, potentially reducing overall
kidney transplant volume contrary to the IOTA Model's goals. Commenters
provided specific examples of how this misalignment could affect IOTA
participants, noting that loss or degradation of SRTR performance can
have material downstream consequences, including loss of COE
designation, termination or non-renewal of commercial contracts,
reduced referrals from employer-sponsored and managed care plans, and
significant decreases in commercial transplant volume. Commenters also
noted that the existence of two differing risk-adjusted methodologies
would undermine the goal of increased kidney transplants, as IOTA
participants would continue to prioritize SRTR outcome measures to
protect most of their patient contracts.
Response: We thank the commenters for their feedback regarding the
proposed risk-adjustment methodology, including concerns related to
using a different risk-adjustment methodology for the IOTA Model than
the SRTR; however, we respectfully disagree. We recognize the
importance of COE designations, which are quality tiers used by
commercial health insurers to steer patients to top-performing kidney
transplant hospitals. We also recognize that MA plans operate
similarly, frequently using COE or preferred facility networks to
determine network participation for MA beneficiaries.
We understand the commenters' concern that if the IOTA Model and
SRTR used completely different risk-adjustment formulas, IOTA
participants could face conflicting incentives that might negatively
impact their SRTR metrics, thereby risking their COE status and access
to commercial and MA patients. However, we do not believe participating
in the IOTA Model will jeopardize an IOTA participant's COE status or
MA network inclusion. Insurers and MA plans evaluate a comprehensive
array of metrics--generally post-transplant outcomes and some minimum
number of kidney transplants, rather than a single SRTR data point--
when determining network participation.
Furthermore, as described in comment responses noted previously in
this section, we are not finalizing the proposed risk-adjustment
methodology and are instead finalizing an updated risk-adjustment
methodology based on an adapted SRTR framework. Because the IOTA risk-
adjustment methodology is adapted directly from the SRTR framework, the
metrics are highly aligned, largely eliminating the risk of conflicting
performance standards. We direct readers to comment responses noted
previously in this section for
[[Page 32809]]
further discussion of these changes and our rationale, and to the 2024
Final Rule for further discussion on COE designations.
Comment: Some commenters sought clarification regarding the
frequency with which the proposed risk-adjustment methodology would be
updated and reweighted. Commenters noted that SRTR updates its models
on a semi-annual basis and requested information on how these updates
would be incorporated into the IOTA Model's annual performance
assessments. A commenter specifically asked whether CMS intends to
update risk-adjustment variables and beta coefficients on a rolling
basis and requested additional explanation of the methodology used for
such updates. Another commenter recommended that CMS collaborate with
SRTR to evaluate time-to-event approaches using national data and
clinical expertise to support statistical validity and patient-centered
reporting.
Response: We appreciate these comments. We note that we are not
finalizing the proposed methodology and are instead finalizing an
updated risk-adjustment methodology based on an adapted SRTR framework
using SRTR's adult kidney graft survival first-year post-transplant
models for both deceased donor and living donor kidney transplants and
most recently available set of variables and coefficients. As such, we
believe the risk-adjustment methodology that we are finalizing, as
described in comment responses noted previously in this section,
appropriately addresses the request for clarity SRTR's methodology
updates variables and coefficients on a rolling basis. We direct
readers to comment responses noted previously in this section for
further discussion of these changes and our rationale.
Comment: Some commenters raised concerns about what they
characterized as the misalignment between CMS's approach to measuring
and incentivizing transplant hospital performance under the IOTA Model
and its approach to regulating OPO performance under the Conditions for
Coverage (CFC) Final Rule. Commenters described the CFC framework as
evaluating OPOs against unadjusted, relative performance thresholds,
without adjustments for performance improvement, donor complexity, or
case mix. Commenters argued that this divergence is particularly
striking given CMS's explicit recognition in the 2025 Proposed Rule
that donor and recipient characteristics materially affect transplant
outcomes and therefore warrant risk-adjustment for transplant hospital
performance measures. Commenters stated that CMS's continued position
that similar donor-related factors do not warrant risk-adjustment for
OPO performance metrics is difficult to reconcile with the agency's
stated rationale for risk-adjustment under the IOTA Model and
undermines system-wide coherence in the regulation of the donation and
transplantation system.
Response: We appreciate the commenter's feedback; however, we do
not believe that it is appropriate to directly compare the performance
metrics of OPOs and kidney transplant hospitals. Both OPOs and kidney
transplant hospitals have unique roles in the transplant ecosystem,
requiring different focuses, skills sets and responsibilities. We
acknowledge the different responsibilities of these two parties along
the continuum of care for organ transplantation. Overall, performance
metrics are meant to understand current state, to set goals to create
improvement, to ensure unintended consequences of changes are
identified, and to allow for analysis and evaluation to pivot and
modify metrics when appropriate. With overarching goals to improve
kidney transplant volume while maintaining quality organs and patient
care, we do not believe that CMS has misaligned goals in its different
approaches to OPOs and kidney transplant hospitals.
Comment: Some commenters raised concerns about the potential impact
of the proposed risk-adjustment methodology on smaller and rural kidney
transplant hospitals. Commenters noted that, with only half of all
eligible kidney transplant hospitals enrolled in IOTA, a model unique
to IOTA participants may not represent true national risk and requested
clarification on whether IOTA participant performance would be
benchmarked against IOTA participants only or against all kidney
transplant hospitals nationally. A commenter noted that for small or
rural IOTA participants, the impact of performance scoring is
particularly significant, as the commenter believed there are
insufficient quality organ offers to sustain current volume without the
growth goals imposed by CMS, and that increasing kidney transplant
volume is not feasible when suitable organs are not available.
Response: We appreciate the comments. We recognize that it can be
more difficult for rural patients to receive a kidney transplant.
However, we believe that the raising of the low volume threshold to 15
kidney transplants performed annually during each of the baseline
years, as described and finalized in section II.B.1.b of this final
rule, should remove the lowest-volume kidney transplant hospitals that
would be at most risk from any impact from the IOTA Model.
Additionally, to directly address concerns regarding the reliability of
performance scoring for smaller volume IOTA participants, our risk-
adjustment methodology incorporates a +2 Bayesian adjustment. This
statistical safeguard is specifically intended to avoid instability in
calculating rates from small kidney transplant volumes, ensuring that a
limited number of adverse outcomes do not cause disproportionate swings
in an IOTA participant's performance score. Finally, we note that
performance in the achievement domain is measured based on each IOTA
participant's individual historic kidney transplant volume, meaning
that an IOTA participant will not need to greatly exceed its own
already demonstrated capacity.
Comment: A commenter urged CMS to clarify that the term ``living
donor'' within the proposed definition of single-organ kidney
transplant is not limited to human donors and is sufficiently broad to
encompass xenotransplant organs (animal-to-human transplants) once such
products receive FDA approval and become commercially available. The
commenter noted that should the definition be interpreted as limited
exclusively to human donors, xenotransplant procedures may not be
counted toward transplant volume in the IOTA achievement domain. Given
that participation in the IOTA Model is mandatory for approximately
half of all eligible kidney transplant hospitals, the commenter
suggested that the exclusion of these products would effectively
disincentivize IOTA participants from adopting innovative solutions to
address the organ shortage. The commenter further expressed the view
that if xenotransplant procedures are not included in performance
calculations tied to financial incentives, IOTA participants may be
financially discouraged from utilizing these life-saving products when
available, thereby undermining the model's primary objective of
increasing access to care. As such, the commenter recommended that CMS
explicitly clarify that the definition of single-organ kidney
transplant is not limited to human organs and could include
xenotransplant organ products upon FDA approval and commercial
availability.
Response: We thank the commenter for their feedback and for
requesting clarification regarding whether the term ``living donor''
within the definition of
[[Page 32810]]
single-organ kidney transplant should encompass xenotransplantation
(animal-to-human transplants) upon FDA approval and commercial
availability. We acknowledge the commenter's interest in ensuring that
emerging technologies are appropriately considered within the IOTA
Model.
At this time, xenotransplant organs are not FDA approved or
available for kidney transplantation. We believe that establishing
policy for technologies that are not yet approved would introduce
unnecessary complexity and uncertainty into the model. We also note
that FDA approval alone would not necessarily indicate that
xenotransplant procedures should be treated identically to human organ
transplants for purposes of performance measurement and payment. The
IOTA Model's quality measures, including graft survival, are based on
extensive historical data from human organ transplants.
Xenotransplantation may involve different clinical characteristics,
including variations in survival rates, rejection patterns,
immunosuppression requirements, and long-term outcomes, which could
complicate fair and meaningful performance comparisons across IOTA
participants if included under the same metrics.
For these reasons, we do not believe the definition of single-organ
kidney transplant should be revised to explicitly address
xenotransplant products at this time, and we will finalize this
definition without modification. However, we will continue to monitor
advancements in this area and may consider future policy updates, as
appropriate, through future notice and comment rulemaking, should
xenotransplantation receive FDA approval and become clinically
established and relevant to the IOTA Model.
Comment: Some commenters expressed support for CMS's proposal to
exclude multi-organ transplants except for kidney/pancreas transplants
from the numerator and denominator when calculating the composite graft
survival rate in the quality domain. Commenters acknowledged that
multi-organ transplant procedures entail substantially different care
processes, heightened clinical complexity, and outcome expectations
that differ significantly from those associated with kidney-only
transplants. Some of these commenters further noted that the limited
population of multi-organ transplant recipients presents considerable
challenges for adequate risk-adjustment, and that such complex cases
carry an elevated risk of outlier outcomes that could unduly impact
IOTA participants' performance scores.
Response: We thank the commenters for their support of our proposal
to exclude multi-organ transplants, with the exception of kidney/
pancreas transplants, from the numerator and denominator when
calculating the composite graft survival rate in the quality domain. We
agree that multi-organ transplant recipients represent a clinically
distinct population with unique care requirements and outcome
trajectories that differ from those of kidney-only transplant
recipients.
We additionally recognize that the inherent clinical complexity of
multi-organ transplantation, combined with the relatively limited
number of such procedures performed, presents considerable challenges
for developing robust risk-adjustment methodologies that would permit
fair and accurate performance comparisons across IOTA participants.
However, we believe excluding multi-organ transplants except for
kidney/pancreas transplants from the numerator and denominator when
calculating the composite graft survival rate enhances the validity of
the measure by ensuring that performance assessments more accurately
reflect outcomes pertaining to kidney transplantation, without the
confounding influence of additional organ involvement or the unique
physiological considerations associated with multi-organ procedures. We
further believe this policy supports the IOTA Model's objectives of
promoting increased transplant access while maintaining appropriate
quality standards. For these reasons, we are finalizing our provision
to exclude multi-organ transplants except for kidney/pancreas
transplants from the numerator and denominator when calculating the
composite graft survival rate without modification.
Comment: A commenter noted that multi-organ transplants are more
commonly performed at higher-volume kidney transplant hospitals and
expressed concern that the continued inclusion of kidney/pancreas
transplants could place IOTA participants with active kidney/pancreas
transplant programs at a disadvantage relative to those who perform few
or no kidney/pancreas transplants.
Response: We thank the commenter for raising this concern. We
recognize that multi-organ transplant procedures, including kidney/
pancreas transplants, are often concentrated at larger, specialized
transplant hospitals. As mentioned in comment responses noted
previously in this section, we are finalizing this provision without
modification. We note that, for kidney/pancreas transplants included in
the composite graft survival rate, the measure evaluates kidney graft
survival only. We believe this methodology addresses the concern that
IOTA participants performing higher volumes of kidney/pancreas
transplants could be disadvantaged relative to those performing fewer
such procedures, as performance is assessed based on kidney transplant
outcomes rather than the volume or complexity of pancreas-related care.
Additionally, consistent with Sec. 512.428(b)(1)(iii)(E), the
exclusion of other multi-organ transplants from the composite graft
survival rate calculation further ensures that IOTA participants
performing more complex procedures are not disproportionately affected
in their overall performance scores. For these reasons, we believe the
finalized approach supports fair and equitable comparisons across IOTA
participants while maintaining focus on kidney transplant outcomes.
Comment: Some commenters noted that multi-organ transplants involve
substantially different care processes and outcome expectations
compared to single-organ kidney transplants. These differences include
more complex perioperative management, different long-term challenges,
and outcomes that are not comparable to those of otherwise similar
single-organ kidney transplant recipients.
Response: We agree that multi-organ transplant recipients face
substantially different care processes and outcome expectations
compared to single-organ kidney transplant recipients. Perioperative
management requires coordination across multiple surgical teams and
medical specialties, and long-term care involves managing the function
and potential complications of multiple transplanted organs
simultaneously. We further agree that outcomes for multi-organ
transplant recipients are not comparable to those of otherwise matched
single-organ kidney transplant recipients, reflecting fundamental
clinical distinctions inherent in multi-organ transplantation rather
than differences in case mix alone, and therefore cannot be adequately
addressed through risk-adjustment. We believe these differences
directly support the policies we are finalizing at Sec.
512.428(b)(1)(iii)(E) and 512.428(b)(1)(iv)(A). Specifically, Sec.
512.428(b)(1)(iii)(E) excludes multi-organ transplants other than
kidney/pancreas from the composite graft survival rate, ensuring that
outcomes
[[Page 32811]]
driven by non-kidney organ function do not confound the assessment of
IOTA participant performance. For kidney/pancreas transplants included
pursuant to Sec. 512.428(b)(1)(iv)(A), measuring only kidney graft
survival appropriately focuses the quality metric on kidney-specific
care while acknowledging the additional complexity of simultaneous
kidney/pancreas transplantation.
Comment: Some commenters recommended that all multi-organ
transplants, including kidney/pancreas transplants, should be excluded
from the graft survival measure. These commenters cited significantly
fewer offers for these patients, more restrictive donor acceptance
criteria, and more complex post-transplant care requirements as
justification for complete exclusion. Some commenters expressed concern
that the continued inclusion of kidney/pancreas transplants in the
metric has the potential to confound outcomes, place transplant
hospitals with busy kidney/pancreas transplant programs at a
disadvantage to their peers performing few or no kidney/pancreas
transplants, and discourage IOTA participants from transplanting these
patients. Additionally, a commenter noted that multi-organ transplants
are likely to be performed predominantly at larger volume transplant
hospitals and expressed concern that the continued inclusion of kidney/
pancreas transplants could place IOTA participants with busy kidney/
pancreas transplant programs at a disadvantage compared to their peers
performing few or no kidney/pancreas transplants.
Response: We thank the commenters for raising their concern. We
have carefully considered the recommendation to completely exclude
kidney/pancreas transplants from the composite graft survival rate
calculation. While we recognize the valid concerns raised about the
clinical complexity and differential outcomes associated with these
procedures, we believe that complete exclusion is not appropriate for
several reasons. First, kidney/pancreas transplants represent a
substantial volume of procedures at many transplant hospitals, and
their complete exclusion could significantly reduce the sample size
available for performance assessment at these transplant hospitals.
Second, kidney/pancreas transplantation is an important treatment
option for patients with both end-stage renal disease and diabetes, and
complete exclusion from quality metrics could inadvertently discourage
IOTA participants from offering this valuable service.
We also thank the commenter for raising the concern that the
continued inclusion of kidney/pancreas transplants could place IOTA
participants with busy kidney/pancreas transplant programs at a
disadvantage compared to their peers performing few or no kidney/
pancreas transplants, which we carefully considered in evaluating
alternatives. We recognize that kidney/pancreas transplants are often
concentrated at larger, specialized transplant hospitals. We considered
whether kidney/pancreas transplants should be excluded entirely from
the composite graft survival rate, which would have fully eliminated
the potential peer comparison disadvantage identified by the commenter.
However, we determined that complete exclusion would reduce available
sample sizes at high-volume transplant hospitals and could
inadvertently discourage IOTA participants from offering this important
treatment option. We therefore conclude that the most appropriate
alternative is to include kidney/pancreas transplants while measuring
only kidney graft survival. We believe this approach ensures that
differences in kidney/pancreas transplant volume across IOTA
participants do not create disparities in IOTA Model performance
scores, as IOTA participants will not be penalized for pancreas-
specific complications or failures that do not affect kidney graft
function, thereby preserving a fair basis for peer comparison while
maintaining consistency with the IOTA Model's focus on kidney
transplant performance.
For these reasons, we are finalizing the policy to include kidney/
pancreas transplants in the composite graft survival rate calculation,
with only the kidney graft survival counted toward the quality metric.
We believe this approach addresses the specific concerns raised by
commenters while maintaining appropriate performance assessment for
IOTA participants.
Comment: Some commenters acknowledged that developing appropriate
risk-adjustment methodologies for multi-organ transplants would require
rigorous analysis considering organ scarcity, dynamic decision making,
and heterogeneous practice patterns. The complexity of creating fair
and accurate risk-adjustment for these procedures was cited as a key
reason supporting their exclusion from the composite graft survival
rate calculation. A commenter specifically noted that while the total
number of recipients of multi-organ transplants has grown in recent
years, the total number remains small relative to the total number of
kidney transplants performed.
Response: We thank the commenters and agree that developing robust
risk-adjustment methodologies for multi-organ transplants would require
extensive analysis and would present significant methodological
challenges. We believe heterogeneity in multi-organ transplant
procedures, the relatively small number of cases performed annually,
the wide variation in practice patterns across transplant hospitals,
and the complex interplay between multiple organ systems in determining
patient outcomes all contribute to the difficulty of creating risk-
adjustment models that would allow for fair comparison of IOTA
participant performance.
Given these challenges and the potential for risk-adjustment models
to inadequately account for the full complexity of multi-organ
transplantation, we are finalizing the policy to exclude multi-organ
transplants (other than kidney/pancreas) from the composite graft
survival rate calculation. For kidney/pancreas transplants, only the
kidney graft survival will be counted toward the quality metric. We
believe this decision allows us to focus quality assessment on kidney
transplant performance using risk-adjustment methodologies that are
better suited to the kidney transplant population and that can more
accurately account for the relevant patient and donor characteristics
affecting kidney graft survival. We intend to continue to monitor
outcomes for all transplant types through existing oversight mechanisms
and may consider future refinements to the IOTA Model based on
additional data and stakeholder input as appropriate.
Comment: Some commenters noted that multi-organ transplants involve
substantially different care processes and outcome expectations
compared to single-organ kidney transplants. These differences include
more complex perioperative management, different long-term challenges,
and outcomes that are not comparable to those of otherwise matched
kidney-alone recipients.
Response: We agree that multi-organ transplant recipients face
substantially different care processes and outcome expectations
compared to single-organ kidney transplant recipients, including more
complex perioperative management, different long-term challenges, and
outcomes that are not comparable to those of otherwise matched single-
organ kidney transplant recipients. We believe this last point carries
important methodological implications: because outcome differences
persist even after accounting for patient and donor characteristics,
they cannot be adequately addressed
[[Page 32812]]
through risk-adjustment alone. These clinical distinctions informed our
evaluation of three primary alternatives: (1) including all multi-organ
transplants with updated risk-adjustment; (2) excluding all multi-organ
transplants, including kidney/pancreas; and (3) excluding most multi-
organ transplants while retaining kidney/pancreas with a kidney-only
outcome measure. We rejected the first alternative because the non-
comparability of outcomes even among otherwise matched recipients
confirms that risk-adjustment models designed for the kidney transplant
population would be insufficient to support fair performance
assessment. We rejected complete exclusion because, while supported by
the clinical distinctions raised by commenters, it would unnecessarily
reduce sample sizes and could discourage IOTA participants from
offering kidney/pancreas transplantation. We therefore concluded that
excluding multi-organ transplants other than kidney/pancreas from the
composite graft survival rate, while retaining kidney/pancreas
transplants with only kidney graft survival counted toward the quality
metric, best accounts for the substantially different care processes
and outcome expectations associated with multi-organ transplantation
while maintaining meaningful quality assessment focused on kidney
transplant performance.
After consideration of the public comments we received, for the
reasons set forth in this rule, we are finalizing the proposed
definition of single-organ kidney transplant at Sec. 512.402 without
modification. Furthermore, we are finalizing our proposal to exclude
multi-organ transplants except for kidney/pancreas transplants from the
numerator and denominator when calculating the composite graft survival
rate in the quality domain at proposed Sec. 512.428(b)(1)(iii)(E) and
512.428(b)(1)(iv)(A) without modification.
In response to comments received, we are replacing the risk-
adjustment methodology we had proposed to use for purposes of
calculating performance on the composite graft survival rate in the
quality domain. Specifically, we are codifying in our regulation at
Sec. 512.428(b)(2)(i) that in accordance with paragraphs (b)(1)
through (3) of this section CMS risk-adjusts the composite graft
survival rate using SRTR's adult kidney graft survival first-year
outcomes variables in accordance with Sec. 512.428(b)(2)(ii)(A)
through (C).
We are codifying the risk-adjustment methodology for the composite
graft survival rate that is based on an adapted SRTR framework in our
regulation in sections Sec. 512.428(b)(2)(ii)(A) through (C).
Specifically, we are finalizing our regulation at Sec.
512.428(b)(2)(ii)(A), that in accordance with Sec. 512.428(b)(1), CMS
calculates the observed composite graft survival rate by dividing the
number of functioning grafts plus two by the total number of completed
kidney transplants plus two as described in Equation 1 to paragraph
(b)(2)(ii)(A) at Sec. 512.428.
We are codifying the methodology for calculating the risk score for
each IOTA participant in our regulation at Sec.
512.428(b)(2)(ii)(B)(1) through (3). Under this provision, CMS
calculates each IOTA participant's risk of graft failure relative to
the national graft failure rate. We are finalizing at Sec.
512.428(b)(2)(ii)(B)(1)(i) through (ii) that CMS calculates the
expected graft failure rate using SRTR's methodology as described in
Equation 1 to paragraph (b)(2)(ii)(B)(1)(i) at Sec. 512.428 and SRTR's
adult kidney graft survival first-year post-transplant risk-adjustment
models for both deceased donor and living donor kidney transplants and
the most available set of coefficients. We are also finalizing the
methodology for calculating the national graft failure rate in our
regulation at Sec. 512.428(b)(2)(ii)(B)(2)(i) through (iv). Under this
provision, CMS calculates the national graft failure rate by dividing
the number of graft failures by the number of completed kidney
transplants as described in equation 1 to paragraph (b)(2)(ii)(B)(2) at
Sec. 512.428. For the calculation of the national graft failure rate,
we are codifying at Sec. 512.428(b)(2)(ii)(B)(2)(ii) through (iv) the
following inclusion and exclusion criteria, as outlined in Table 5.
[GRAPHIC] [TIFF OMITTED] TR01JN26.193
We are also finalizing at Sec. 512.428(b)(2)(ii)(B)(3) that CMS
will calculate the risk score for each IOTA participant by dividing
each IOTA participants' expected graft failure rate by the national
graft failure rate for all kidney transplants as described in Equation
1 to paragraph (b)(2)(ii)(B)(3) at Sec. 512.428.
Additionally, we are finalizing at Sec. 512.428(b)(2)(ii)(C) the
calculation of the risk-adjusted composite graft survival rate as
described in Equation 1 to paragraph (b)(2)(ii)(C) at Sec. 512.428.
Under this provision, CMS will multiply the observed composite graft
survival rate, as calculated under Sec. 512.428(b)(2)(ii)(A), by the
risk score calculated under Sec. 512.428(b)(2)(ii)(B).
Lastly, because we are finalizing a risk-adjustment methodology in
the calculation of the composite graft survival rate, as described and
finalized at Sec. 512.428(b)(2), we are updating the regulatory text
at Sec. 512.428(b)(1)(ii). Specifically, we are finalizing at Sec.
512.428(b)(1)(ii) that, for all subsequent PYs, CMS will calculate each
IOTA participant's cumulative composite graft survival rate using the
methodology described in Sec. 512.428(b)(1) and in accordance with the
risk-adjustment methodology finalized at Sec. 512.428(b)(2).
We believe that these revisions, taken together, establish a
comprehensive and
[[Page 32813]]
methodologically sound approach to calculating the composite graft
survival rate that improves accuracy, enhances statistical reliability,
and supports equitable comparisons across IOTA participants by
accounting for differences in donor and recipient risk while
maintaining consistency with established, clinically validated SRTR
methodologies. We note that we will analyze and monitor IOTA
participant performance throughout the model performance period to
ensure we do not unduly disadvantage IOTA participants. If analysis
results warrant a new or updated policy, we will address it pursuant to
future notice and comment rulemaking as appropriate.
(b) Calculation of Points
In the 2024 Final Rule (89 FR 96280) that established the IOTA
Model, we acknowledged commenter concerns about the proposed points
allocation for the composite graft survival rate, arguing that it
unfairly penalizes transplant hospitals that accept higher-risk
patients and suggesting modifications including lowering the threshold
for maximum points from the 80th to 60th percentile for IOTA
participants (89 FR 96365). In response to comments, we finalized an
alternate scoring methodology, such that IOTA participants would be
awarded points based on the national quintiles, as outlined in Table 6,
such that IOTA participants that perform--
<bullet> At or above the 80th percentile would earn 20 points;
<bullet> In the 60th percentile to below the 80th percentile would
earn 18 points;
<bullet> In the 40th percentile to below the 60th percentile would
earn 16 points;
<bullet> In the 20th to below the 40th percentile would earn 14
points;
<bullet> In the 10th to below the 20th percentile would earn 12
points; and
<bullet> Below the 10th percentile would receive 10 points for the
composite graft survival rate.
[GRAPHIC] [TIFF OMITTED] TR01JN26.194
In addition, we stated that we recognized that for PY 2 and future
PYs there would be more events and a longer time horizon and plan to
implement a more robust methodology that could account for both the
likelihood of graft failure based on the donor and the recipient and
could account for relative benefits of transplantation over remaining
on dialysis (89 FR 96365). We direct readers to the 2024 Final Rule for
a full discussion of this policy, our rationale for this approach, and
alternatives considered (89 FR 96364 through 96366).
As stated in the 2025 Proposed Rule, upon further review of our
methodology, we proposed to modify the composite graft survival rate
scoring methodology to allow for a more even scoring distribution for
IOTA participants (90 FR 57609). Specifically, we proposed in Table 1
to paragraph (d) at Sec. 512.428 that points earned would be based on
the IOTA participants' performance on the composite graft survival rate
relative to national ranking, inclusive of all eligible kidney
transplant hospitals, both those selected and not selected as IOTA
participants, as outlined in Table 7.
As described in the 2025 Proposed Rule, we proposed that points
continue to be awarded based on national quintiles, as outlined in
Table 7 (90 FR 57609). We maintained our belief that utilizing
quintiles aligns with the calculation of the upside and downside risk
payments in relation to the final performance score, as described in 42
CFR 512.430(b), where average performance yields half the number of
points. The scoring is normalized, meaning an average performing IOTA
participant earns 10 points out of 20, 50 percent of the total possible
points. We recognized that there is an upper limit to the benefits of
quality, and quintiles combine the highest 20 percent of performers in
a point band.
In accordance with Sec. 512.428, we proposed the following updates
to the allocation of points for the composite graft survival rate in
Table 1 to paragraph (d) at Sec. 512.428, as illustrated in Table 7
(90 FR 57609):
<bullet> IOTA participants in the 80th percentile and above, 20
points.
<bullet> IOTA participants in the 60th to below the 80th percentile
of performers, 15 points.
<bullet> IOTA participants in the 40th to below the 60th percentile
of performers, 10 points.
<bullet> IOTA participants in the 20th to below the 40th percentile
of performers, 5 points.
<bullet> IOTA participants who are below the 20th percentile of
performers, 0 points.
[[Page 32814]]
[GRAPHIC] [TIFF OMITTED] TR01JN26.195
As stated in the 2025 Proposed Rule, utilizing quintiles aligns
with the calculation of the upside and downside risk payments in
relation to the final performance score, as described in 42 CFR
512.430(b), where average performance yields half the number of points
(90 FR 57610). The scoring is normalized, meaning an average performing
IOTA participant earns 10 points out of 20, 50 percent of the total
possible points. We recognized that there is an upper limit to the
benefits of quality, and quintiles combine the highest 20 percent of
performers in a point band.
Additionally, in the 2024 Final Rule (89 FR 96379), we stated that
we would continue to assess our quality domain methodology and how to
best balance incentives in the efficiency domain and quality domain and
address a new or updated policy pursuant to future notice and comment
rule making. Furthermore, as proposed in section II.B.2.b.(2).(a). of
this final rule, we proposed to incorporate a risk-adjustment
methodology to the calculation of the composite graft survival rate
measure. As such, we believed that the proposed allocation of points,
as illustrated in Table 7, is necessary to account for the proposed
composite graft survival rate risk-adjustment methodology, as described
in section II.B.2.b.(2).(a). of this final rule, and best balances
incentives in the quality domain.
We considered applying a two-scoring system in which we would
determine an achievement score and improvement score and award the
point equivalent to the higher value between the two scores; similar to
the organ offer acceptance rate ratio scoring methodology as described
at Sec. 512.426(c) (90 FR 57610). In this considered two-scoring
system, the achievement score would reflect the proposed scoring
approach on the composite graft survival rate, as illustrated in Table
7 of this section. For improvement scoring on the composite graft
survival rate, we considered the following methodologies:
<bullet> In accordance with the organ offer acceptance rate ratio
improvement scoring methodology at Sec. 512.426(c)(2)(ii).
<bullet> Improvement relative to national ranking from previous PY.
<bullet> Improvement over 2 PYs. In this methodology, improvement
scoring would only be awarded twice (PYs 4 and 6) and would measure
improvement by comparing PYs 1-2 to PYs 3-4 and PYs 3-4 to PYs 5-6.
We considered applying a two-scoring system in which we would
determine an achievement score and improvement score and award the
point equivalent to the higher value between the two scores because we
recognized that if an IOTA participant does not do well one PY on the
composite graft survival rate, as described at Sec. 512.428(b)(1),
that it may be difficult for it to improve during the model performance
period (90 FR 57610). However, we chose not to propose this methodology
(two-scoring system) because we still had concerns over our ability to
measure improvement year-over-year due to potentially small numbers.
Furthermore, given that we proposed to incorporate a risk-adjustment
methodology, as proposed in section II.B.2.(b).(2).(a). of the 2025
Proposed Rule, we believed that our proposed scoring approach rewards
both achievement and improvements and is a more rigorous scoring
methodology. Although we did not propose to include this alternative,
we sought comment on whether a two-scoring system methodology would be
appropriate for the composite graft survival rate and the best approach
for measuring improvement.
We sought comment on our proposed composite graft survival rate
scoring methodology at proposed Table 1 to Paragraph (d) at Sec.
512.428 for purposes of assessing quality domain performance for each
IOTA participant. We also sought comments on alternatives considered.
Additionally, we sought comment on whether there is a scoring
methodology on the composite graft survival rate that recognizes IOTA
participants whose post-transplant outcomes are at an acceptable level
and how to define an acceptable level (for example, 1 standard
deviation of the national risk-adjusted rate or some other way).
The following is a summary of the comments we received on all of
the calculation of points proposals and on the alternatives considered
set out in this section and our responses:
Comment: Several commenters recommended that CMS incorporate an
improvement component into the scoring methodology for the composite
graft survival rate metric within the quality domain. Specifically,
these commenters suggested a dual-scoring system whereby CMS would
determine both an achievement score and an improvement score,
subsequently awarding the point value equivalent to the higher of the
two scores. Commenters noted that this approach would recognize IOTA
participants demonstrating meaningful progress, even in instances where
their absolute performance has not yet reached higher percentile
thresholds.
Response: We appreciate commenters' suggestions regarding the
inclusion of improvement scoring on the composite graft survival rate
metric within the quality domain. As discussed at 90 FR 57610 in the
2025 Proposed Rule and in this section of this final rule, we
considered applying a two-scoring system in which we would determine an
achievement score and an improvement score and award the point
equivalent to the higher value between the two scores, similar to the
organ offer acceptance rate ratio scoring methodology described at
Sec. 512.426(c). As described in the preamble of this section of this
final rule, we considered applying a two-scoring system because we
recognize that if an IOTA participant does not perform well in a given
PY on the composite graft survival rate, it may be difficult for the
IOTA participant to demonstrate meaningful improvement during the model
performance period. We direct readers to section II.B.2.b.(2).(b). of
this final rule for a full discussion on the two-scoring system
methodologies we considered for
[[Page 32815]]
calculating points on the composite graft survival rate.
Furthermore, we believe that the updated risk-adjustment
methodology incorporated into the composite graft survival rate
calculation, as described and finalized in section II.B.2.b.(2).(a). of
this final rule, inherently recognizes IOTA participants that improve
their performance by accepting more complex cases, as changes in case
mix complexity over time will be appropriately reflected. We also
believe that the updated scoring methodology for performance on the
composite graft survival rate, as outlined in Table 8 of this section
of this final rule, rewards both achievement and improvement,
constitutes a more rigorous scoring methodology, creates smoother
transitions between scoring thresholds, and reduces the likelihood of a
scenario in which a modest decrease in performance results in a
disproportionate loss of points, as compared to the proposed approach
as described in this section of this final rule.
However, we will continue to assess whether an improvement scoring
methodology for performance on the composite graft survival rate metric
in the quality domain would be appropriate for future PYs and will
monitor IOTA participant performance to evaluate the feasibility of
incorporating one. We remain interested in considering how an
improvement scoring methodology could be incorporated into the
composite graft survival rate and intend to conduct further analysis to
evaluate the feasibility of incorporating a two-scoring system. If
analysis results warrant a new or updated policy, we will address it
pursuant to future rulemaking.
Comment: Many commenters expressed concern that the proposed
updates to the allocation of points for performance on the composite
graft survival rate would create large performance ``cliffs'' \55\
between scoring thresholds. Commenters noted that smaller kidney
transplant hospitals may be disproportionately affected by these gaps
due to greater statistical variability in their composite graft
survival rates. Several commenters suggested more granular scoring
thresholds, such as deciles, to reduce the impact of small variations
in performance.
---------------------------------------------------------------------------
\55\ The cliffs mentioned by commenters refers to the ``cliff
effect'' in scoring, a phenomenon where a small increase or decrease
in performance results in a disproportionate gain or loss in points.
---------------------------------------------------------------------------
Response: We thank the commenters for expressing their concerns and
for their suggestions on our proposed methodology for awarding points
for the purpose of assessing performance on the composite graft
survival rate in the quality domain. We acknowledge the concerns raised
regarding the potential difficulties IOTA participants may face in
achieving a top score on the composite graft survival rate metric. With
respect to the concerns that a small number of adverse outcomes could
significantly skew a kidney transplant hospital's data, we acknowledge
that it is difficult to fully assess the extent to which such concerns
may affect performance measurement across IOTA participants at this
time, given the limited data currently available. However, we recognize
there have been significant improvements in kidney transplantation
outcomes over time due to advances in immunosuppressive therapies,
surgical techniques, and organ preservation methods. We also recognize
that post-transplant outcomes are already incentivized through private
payers' COE programs and OPTN metrics.
We agree that the impact of statistical volatility is important,
particularly for smaller IOTA participants. As such, in response to
comments received, we are updating the methodology for the allocation
of points for performance on the composite graft survival rate in the
quality domain. Specifically, we are finalizing, with modification,
Table 1 to paragraph (d) at Sec. 512.428, to reflect the updated
points allocation, as outlined in Table 8, such that IOTA participants
that perform:
<bullet> IOTA participants in the 87.5th percentile of performers
and above, 20 points.
<bullet> IOTA participants in the 75th to below 87.5th percentile
of performers, 18 points.
<bullet> IOTA participants in the 62.5th to below 75th percentile
of performers, 15 points.
<bullet> IOTA participants in the 50th to below 62.5th percentile
of performers, 13 points.
<bullet> IOTA participants in the 37.5th to below 50th percentile
of performers, 10 points.
<bullet> IOTA participants in the 25th to below 37.5th percentile
of performers, 8 points.
<bullet> IOTA participants in the 12.5th to below 25th percentile
of performers, 5 points.
<bullet> IOTA participants who are below the 12.5th percentile of
performers, zero points.
[GRAPHIC] [TIFF OMITTED] TR01JN26.196
We are adding additional thresholds where points will be based on
national octiles, as illustrated in Table 8 in this section, rather
than quintiles. We believe this approach reflects our partial agreement
with commenters by providing greater granularity than both the current
and proposed point allocation methodologies as described in this
section of the final rule, while preserving greater simplicity than a
full decile system comprising 10 thresholds. Furthermore, we believe
that using 8 thresholds establishes smoother transitions between
scoring thresholds, with increments of 2 or 3 points between most
thresholds, thereby reducing the ``cliff effect'' identified by
[[Page 32816]]
commenters. We believe this strikes an appropriate balance between
granular performance differentiation and administrative feasibility.
Comment: Some commenters expressed concern that the proposal to
assign zero points to IOTA participants falling below the 20th
percentile is excessively punitive, particularly for safety-net
hospitals and those serving high-risk populations and may serve as a
disincentive for kidney transplantation even with risk-adjustment
mechanisms in place.
Response: We appreciate commenters' concerns regarding the
potential impact of awarding zero points to IOTA participants below the
20th percentile, particularly for safety-net hospitals serving
vulnerable populations. We also recognize that risk-adjustment may not
fully capture all challenges faced by safety-net hospitals. We believe
the updated risk-adjustment methodology in the composite graft survival
rate calculation, as described and finalized in section
II.B.2.b.(2).(a). of this final rule, appropriately addresses case mix
differences and ensures fair comparison across IOTA participants with
varying patient populations. We also believe that the updated scoring
methodology for performance on the composite graft survival rate, as
described and finalized in section II.B.2.b.(2).(b). of this final
rule, reduces the likelihood of a scenario in which a small decrease in
performance results in a significant loss of points, compared to the
proposed approach, as described in this section of this final rule. We
note that in the updated composite graft survival rate scoring
methodology, as outlined in Table 8, zero points are awarded only to
IOTA participants below the 12.5th percentile, rather than the 20th
percentile as proposed. We believe that this update addresses the
criticism of being overly punitive while balancing scoring granularity
and administrative feasibility.
Comment: Some commenters requested that CMS establish minimum
performance thresholds based on absolute quality standards for the
composite graft survival rate rather than relative percentile rankings.
Commenters suggested that IOTA participants should be able to meet
objective benchmarks without being penalized simply for falling in the
bottom percentile nationally, regardless of whether their absolute
performance meets acceptable quality standards.
Response: We appreciate the commenters for their feedback and for
raising the consideration of utilizing absolute quality standards for
the composite graft survival rate. We acknowledge the concern that a
purely relative, percentile-based scoring methodology for performance
on the composite graft survival rate may result in IOTA participants
being penalized despite achieving outcomes that could be considered
acceptable from an absolute performance perspective.
We continue to believe that a relative, percentile-based
methodology is appropriate for the purpose of allocating points for
performance on the composite graft survival rate in the IOTA Model, as
it enables comparison of performance across IOTA participants and
supports the model's goal of driving continuous quality improvement. A
relative approach allows CMS to assess performance within the context
of national variation among eligible kidney transplant hospitals and
evolving clinical outcomes, rather than relying on fixed thresholds
that may not reflect ongoing advancements in transplant care.
At the same time, we recognize the importance of ensuring that
performance assessment remains both fair and meaningful. As discussed
in comment responses noted previously in this section, we will be
finalizing an updated composite graft survival rate scoring
methodology, as outlined in Table 8, to reduce sharp performance
differentials between thresholds and to more effectively balance
performance differentiation with stability. We believe these
modifications help mitigate concerns regarding penalizing IOTA
participants whose outcomes meet acceptable clinical standards, while
simultaneously maintaining appropriate incentives for improvement.
However, we will take these comments into consideration as we continue
to evaluate the quality domain methodology and may consider alternative
approaches, including the potential role of absolute benchmarks, in
future notice and comment rulemaking.
After consideration of public comments, for the reasons set forth
in this rule, we are finalizing our proposed scoring methodology for
performance on the composite graft survival rate in the quality domain,
with modification. In response to public comments we received we are
modifying the methodology f
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