Public Comments

Status: Original and derived artifacts are available for this document.

Download: pdf

MEMORANDUM
To:
From:
Date:
Re:

Hon. Robert F. Kennedy, Jr., Secretary, US Department of Health and
Human Services
Dr. Mehmet Oz, Administrator, Centers for Medicare and Medicaid Services
Andrew Langer, Director, Center for Regulatory Freedom
April 14, 2026
Comments to US Department of Health and Human Services Centers for
Medicare and Medicaid Services (CMS) in response to an Information
Collection Request, “CMS-10488 (QHP Enrollee Survey, CMS-R-284 (TMSIS), CMS-10407 (SBC),” Docket #CMS-2026-0596, Fed. Reg. 2026-02871,
Published February 13, 2026

Below are comments of the American Conservative Union Foundation's (d/b/a. Conservative
Political Action Coalition Foundation) (hereinafter “CPAC Foundation”) Center for Regulatory
Freedom (hereinafter “CRF”), in response to an Information Collection Request, “CMS-10488
(QHP Enrollee Survey, CMS-R-284 (T-MSIS), CMS-10407 (SBC),” Docket #CMS-2026-0596,
Fed. Reg. 2026-02871, published February 13, 2026.
CRF is a project of the CPAC Foundation, a non-profit, non-partisan 501(c)(3) research and
education foundation. Our mission is to inject a common-sense perspective into the regulatory
process, to ensure that the risks and costs of regulations are fully based on sound scientific and
economic evidence, and to ensure that the voices, interests, and freedoms of Americans, and
especially of small businesses, are fully represented in the regulatory process and debates.
Finally, we work to ensure that regulatory proposals address real problems, that the proposals
serve to ameliorate those problems, and, perhaps most importantly, that those proposals do not,
in fact, make public policy problems worse.
INTRODUCTION
The CPAC Foundation Center for Regulatory Freedom (CRF) submits these comments in
response to the request by the Centers for Medicare & Medicaid Services (CMS) for public input
on the proposed information collections under the Paperwork Reduction Act (PRA). CRF
appreciates the opportunity to provide feedback on these collections at this stage of review,
particularly given the central role that information collection plays in the administration of
federal health programs. The PRA establishes an important framework intended to ensure that
1

federal agencies collect only that information which is necessary, useful, and appropriately
calibrated to minimize burden. In practice, however, the effectiveness of that framework depends
on rigorous engagement—both by agencies and stakeholders—with the design, scope, and
implementation of specific collections. These comments are therefore offered with the objective
of promoting disciplined, analytically grounded information collection practices that enhance
program performance while avoiding unnecessary or counterproductive administrative burdens.
Information collections are often characterized as purely administrative or operational tools,
designed to facilitate program management and oversight. While this characterization is partially
accurate, it is increasingly incomplete. In modern regulatory and programmatic contexts,
information collections function not only as mechanisms for data gathering, but also as
instruments that shape behavior across regulated entities, influence incentives, and structure
interactions between government and the marketplace. As such, they occupy a dual role: they are
both operational inputs and policy levers. This dual role has become more pronounced as
agencies rely more heavily on data-driven frameworks to inform decision-making, evaluate
performance, and communicate information to consumers. In the context of CMS programs in
particular, information collections are now embedded in core program functions, including plan
comparison, quality measurement, payment adjustment, and long-term policy development.
The collections at issue in this notice illustrate the extent to which information collection
activities can shape real-world outcomes. Data gathered through these instruments influences
how consumers evaluate coverage options, how providers and plans allocate resources, and how
regulators assess compliance and performance. In this sense, information collections do not
merely reflect underlying market conditions—they actively participate in shaping them. They
can alter incentives, affect competitive dynamics, and contribute to the formation of regulatory
expectations, even in the absence of formal rulemaking. For these reasons, it is essential that
such collections be designed and implemented with a level of analytical rigor comparable to that
applied in traditional regulatory processes. Absent such rigor, there is a risk that information
collection frameworks will produce unintended distortions, impose disproportionate burdens, or
generate data that is of limited practical utility.
The PRA provides a clear statutory framework intended to guide agencies in the development
and implementation of information collections. At its core, the PRA requires agencies to
demonstrate that proposed collections are necessary for the proper performance of agency
functions, that they have practical utility, and that they minimize burden on respondents to the
greatest extent practicable. These requirements are not merely procedural—they are substantive
constraints designed to ensure that information collection remains disciplined, targeted, and
efficient. However, in practice, there is often a tendency to treat these requirements as formalities
rather than as binding analytical standards. As a result, burden estimates may fail to capture the
full scope of compliance costs, including system modifications, staff training, and operational
adjustments, while assertions of utility may be framed in broad or generalized terms that do not
clearly distinguish between primary and secondary uses of the data.
CRF’s comments focus on three information collections included in this notice: the Qualified
Health Plan (QHP) Enrollee Experience Survey (CMS–10488), the Transformed Medicaid
Statistical Information System (T-MSIS) data collection (CMS–R–284), and the Summary of
2

Benefits and Coverage (SBC) and Uniform Glossary requirements (CMS–10407). These
collections were selected for detailed analysis based on their scale, their integration into core
program functions, and their potential to influence market behavior and policy outcomes. Other
collections included in the notice are more limited in scope and do not raise the same systemic
considerations. By focusing on these three collections, CRF seeks to engage where the potential
impact—both positive and negative—is most significant, and where disciplined design and
implementation can yield meaningful improvements in program performance and administrative
efficiency.
Across these collections, several recurring concerns emerge. First, there is evidence of
methodological drift over time, as collections are modified incrementally without sufficient
attention to the implications for longitudinal consistency and comparability. Second, burden
estimates frequently appear to understate the full range of costs imposed on respondents,
particularly with respect to information technology systems, data integration, and ongoing
compliance processes. Third, there is a pattern of data-use expansion, in which information
initially collected for one purpose is subsequently used for additional functions—such as
regulatory oversight or public reporting—without a corresponding reassessment of necessity and
utility. Finally, there is a lack of clearly articulated limiting principles governing the scope and
evolution of information collections, raising concerns about cumulative burden and the potential
for mission creep.
CRF supports CMS’s broader objectives of promoting transparency, improving consumer access
to information, and enhancing the performance of federal health programs. Information
collection plays an essential role in achieving these objectives, and well-designed data systems
can contribute significantly to more efficient and effective program administration. At the same
time, these benefits are not automatic. They depend on the extent to which information
collections are carefully calibrated to align with clearly defined purposes, supported by sound
methodology, and implemented in a manner that minimizes unnecessary burden. Accordingly,
the recommendations set forth in these comments are intended not to constrain CMS’s ability to
collect and use data, but to ensure that such activities are carried out in a disciplined, analytically
rigorous manner that advances statutory objectives while preserving flexibility, efficiency, and
accountability.
EXECUTIVE SUMMARY
Information collections administered by the Centers for Medicare & Medicaid Services (CMS)
increasingly function not merely as administrative tools, but as mechanisms that shape market
behavior, influence consumer decision-making, and inform regulatory oversight. In this respect,
they operate as a form of quasi-regulation, exerting material effects on regulated entities and
program outcomes without undergoing the same level of scrutiny typically applied to formal
rulemaking. This dynamic heightens the importance of ensuring that such collections are
designed and implemented with clearly bounded scope and strong methodological integrity.
Absent these guardrails, information collections risk imposing unnecessary burden, generating
data of limited utility, and introducing distortions into program administration and market
dynamics. CRF’s comments therefore focus on reinforcing the need for disciplined analytical
3

frameworks, transparent design choices, and a consistent alignment between the stated purposes
of data collection and their real-world application.
Our arguments are laid out as follows:
CMS–10488 (QHP Enrollee Experience Survey)
•
•
•
•

The survey functions as a de facto regulatory lever, shaping plan behavior and
influencing consumer choice beyond its stated purpose as a measurement tool
Proposed revisions risk breaking longitudinal comparability and introducing
measurement bias, undermining the reliability of trend analysis and benchmarking
Expanded oversampling authority lacks sufficient guardrails, creating the potential
for distorted comparisons and unintended bias
Assertions of burden reduction are not supported by the proposed changes, which
introduce additional outreach and screening mechanisms

CMS–R–284 (T-MSIS)
•
•
•

•

The expansion of data fields proceeds without clearly defined use cases, raising
concerns about necessity and scope discipline
The addition of immigration-related identifiers requires a more explicit justification
tied to programmatic need and statutory authority
The claim of “no burden change” likely understates the operational and compliance
costs imposed on states, particularly with respect to system updates and data
integration
There is a need for stronger data minimization principles and governance discipline
to ensure that the collection remains targeted and efficient

CMS–10407 (Summary of Benefits and Coverage)
•
•

•

Standardization of disclosure formats does not, in itself, guarantee usability or
meaningful consumer comprehension
There is a risk of achieving formal compliance without delivering substantive
consumer benefit, particularly if materials are not effectively used in real-world
decision-making
The ongoing administrative burden associated with these requirements should be
periodically reassessed relative to demonstrated utility

Taken together, these issues underscore the need to pair ongoing modernization efforts with a
disciplined approach to information collection. As CMS continues to refine and expand its data
systems, it is essential that such efforts be grounded in analytical rigor, guided by clearly defined
use-case limitations, and calibrated to ensure that the burden imposed on regulated entities is
proportionate to the utility of the information collected.

4

I. CROSS-CUTTING PRA CONCERNS
The information collections addressed in this notice raise a set of common issues that extend
beyond any single instrument and instead reflect broader patterns in the design and evolution of
CMS data collection practices. While each collection serves a distinct programmatic purpose,
they share structural characteristics that warrant cross-cutting analysis under the Paperwork
Reduction Act (PRA). Evaluating these collections in isolation risks overlooking systemic
concerns that, taken together, shape the overall burden imposed on regulated entities and the
quality and utility of the data produced. Accordingly, this section identifies and examines those
recurring issues, with the goal of providing a coherent analytical framework that can be applied
across CMS information collection activities. Such a framework is necessary to ensure that
incremental changes to individual collections do not cumulatively result in disproportionate
burden or diminished effectiveness.
A central consideration in this analysis is the recognition that information collection is not a
neutral administrative exercise. Data collection requirements influence the behavior of regulated
entities, shape incentives, and affect how organizations allocate resources and structure their
operations. When entities are required to report specific data elements, they often adjust internal
processes to ensure compliance, sometimes prioritizing measurable activities over those that may
be equally or more important but less readily captured. In this way, information collections can
operate as implicit policy tools, steering behavior without the formal processes associated with
rulemaking. This dynamic underscores the need for careful design and clear justification, as even
seemingly minor changes to data requirements can have meaningful downstream effects on
program participation and market behavior.
One of the most persistent challenges in the PRA context is the tendency to underestimate the
true burden associated with information collection. Official burden estimates often focus on the
time required to complete forms or submit data, but they frequently exclude the broader set of
activities necessary to comply with reporting requirements. These include modifications to
information technology systems, integration of new data fields into existing workflows,
development of compliance infrastructure, and training of personnel. In many cases, these
indirect costs exceed the direct time burden associated with data submission. Failure to account
for these factors can result in a significant understatement of the real-world impact of
information collection requirements, undermining the PRA’s objective of minimizing burden to
the greatest extent practicable.
Relatedly, the resources devoted to compliance with information collection requirements carry
meaningful opportunity costs. Time, capital, and personnel allocated to data reporting are
resources that cannot be used for other purposes, including patient care, service delivery, or
innovation. Particularly in resource-constrained environments, these tradeoffs are not
theoretical—they directly affect organizational priorities and outcomes. When information
collection requirements are not carefully calibrated to deliver commensurate utility, they risk
diverting resources away from activities that provide more direct value to beneficiaries and the
healthcare system as a whole. A disciplined approach to information collection must therefore
incorporate an explicit consideration of these opportunity costs, ensuring that the benefits of data
collection justify the resources expended.
5

Another recurring issue is the ambiguity surrounding the utility of collected data. CMS often
describes information collections in terms of multiple potential uses, including program
administration, consumer information, regulatory oversight, and research. While each of these
uses may be valid, they are not always clearly distinguished, and the relative importance of each
is seldom articulated. This aggregation of purposes can obscure whether specific data elements
are necessary for the primary function of the collection or are being retained to support
secondary or speculative uses. Without clear differentiation between primary and secondary
uses, it becomes difficult to assess whether the scope of the collection is appropriately limited or
whether certain data elements could be modified or eliminated without impairing core program
functions.
Over time, information collections tend to expand in both scope and function, a phenomenon
commonly referred to as scope creep. Additional data fields are added, new reporting
requirements are layered onto existing frameworks, and previously collected data are repurposed
for new uses. While such evolution may be driven by legitimate programmatic needs, it often
occurs incrementally and without a comprehensive reassessment of the overall collection. As a
result, collections can become more complex and burdensome over time, even if each individual
change appears modest in isolation. The absence of periodic, holistic review increases the risk
that information collections will drift away from their original purpose and impose cumulative
burdens that are disproportionate to their utility.
Frequent revisions to information collections also raise concerns regarding longitudinal integrity.
Many CMS data systems are used to track trends over time, evaluate program performance, and
inform policy decisions. Changes to survey instruments, data definitions, or reporting
methodologies can disrupt these analyses by introducing discontinuities or altering the meaning
of key variables. When such changes are not carefully managed and documented, they can
reduce the comparability of data across time periods and undermine the reliability of conclusions
drawn from the data. Maintaining longitudinal consistency, or at a minimum clearly accounting
for changes that affect comparability, is essential to preserving the analytical value of CMS data
collections.
A related concern is the absence of clearly articulated limiting principles governing the scope
and duration of information collections. The PRA establishes general requirements regarding
necessity and burden minimization, but it does not, in practice, impose a structured framework
for determining when data collection should be reduced, modified, or discontinued. As a result,
once data elements are incorporated into a collection, they are rarely removed, even if their
utility diminishes over time. This dynamic contributes to the accumulation of requirements and
reinforces the need for a more explicit approach to data governance—one that includes criteria
for both the addition and the removal of data elements based on demonstrated need and
performance.
In light of these cross-cutting concerns, CRF recommends that CMS adopt a more disciplined
and transparent approach to information collection design and management. This approach
should include the implementation of burden-to-utility calibration, ensuring that each data
element is justified by a clearly defined and demonstrable use case. CMS should also establish
explicit limitations on the scope of data collection, including mechanisms to prevent the
6

expansion of collections beyond their original purpose without formal reassessment. Finally,
periodic reviews should be conducted to evaluate the continued necessity and effectiveness of
existing collections, with a willingness to streamline or eliminate requirements that no longer
serve a meaningful function. By incorporating these principles, CMS can better align its
information collection activities with the objectives of the PRA while enhancing the efficiency
and effectiveness of its programs.
II. CMS–10488: QHP ENROLLEE EXPERIENCE SURVEY
Among the information collections addressed in this notice, the Qualified Health Plan (QHP)
Enrollee Experience Survey (CMS–10488) is the most significant in terms of its scale, its
integration into core program functions, and its influence on both market behavior and regulatory
outcomes. Administered by the Centers for Medicare & Medicaid Services, the survey serves as
a central component of the Exchanges’ consumer information infrastructure and is increasingly
embedded in broader performance evaluation frameworks. As such, changes to the design,
administration, or interpretation of this survey carry implications that extend well beyond data
collection itself, affecting how plans compete, how consumers make decisions, and how CMS
evaluates program performance.
The stated purposes of the QHP Enrollee Experience Survey are multifaceted. It is intended to
provide consumers with actionable information to compare health plans, to offer plans feedback
that can be used to improve performance, and to supply regulators and accreditation bodies with
data to support oversight and evaluation. Each of these functions is significant in its own right,
and together they position the survey as a central node in the Exchange ecosystem. However, the
combination of these roles also introduces complexity, as the survey must simultaneously serve
as a consumer-facing tool, a quality improvement mechanism, and an input into regulatory
processes. This multiplicity of purposes heightens the importance of ensuring that the survey’s
design is methodologically sound and appropriately bounded.
In practice, the QHP Enrollee Experience Survey functions not only as a measurement
instrument but also as a market signal and an implicit regulatory mechanism. The metrics
derived from the survey influence plan ratings, affect consumer choice, and can shape how plans
allocate resources to improve perceived performance. Plans may adjust operational priorities in
response to survey domains, emphasizing areas that are measured while potentially deprioritizing
those that are not. In this way, the survey exerts a normative effect on plan behavior, effectively
guiding market outcomes without the formal processes associated with rulemaking. This
dynamic underscores the need for heightened analytical rigor, as changes to the survey can have
cascading effects throughout the system.
CMS proposes several modifications to the survey instrument and its administration. These
include the removal of questions related to tobacco use, revisions to demographic questions to
align with updated federal standards, updates to telehealth-related items, and the addition of gate
questions designed to screen respondents out of inapplicable follow-up items. CMS also
proposes changes to sampling protocols, including expanded flexibility for oversampling, as well
as modifications to outreach efforts, such as additional email reminders and extended telephone
7

follow-up periods. While each of these changes may be individually justified, their combined
effect warrants careful evaluation, particularly with respect to their impact on data consistency
and respondent burden.
One of the primary concerns associated with these proposed changes is the potential disruption
of longitudinal comparability. The QHP Enrollee Experience Survey has historically been used
to track trends over time, enabling comparisons across plan years and supporting benchmarking
efforts. Modifications to survey questions, response options, or sampling methodologies can
introduce discontinuities that complicate or undermine these analyses. Even relatively minor
changes can alter how respondents interpret questions or how responses are categorized, leading
to shifts in measured outcomes that reflect methodological changes rather than actual differences
in performance. Preserving the integrity of longitudinal data is essential to maintaining the
survey’s value as a tool for trend analysis and performance evaluation.
Closely related is the issue of measurement integrity. Changes to survey content and structure
can affect the underlying constructs being measured, potentially leading to inconsistencies in
how key concepts are defined and interpreted over time. For example, revisions to telehealth
questions or demographic categories may alter the scope or meaning of these variables, making it
more difficult to compare results across survey administrations. Without careful validation and
documentation, such changes can introduce ambiguity into the data, reducing its reliability and
limiting its usefulness for both internal and external stakeholders. Ensuring that measurement
constructs remain stable—or that any changes are clearly understood and accounted for—is
critical to preserving the survey’s analytical value.
The proposed expansion of oversampling flexibility raises additional concerns. While
oversampling can be a useful tool for ensuring adequate representation of specific populations, it
also introduces the potential for distorted comparisons if not properly controlled. Differences in
sampling strategies across plans or regions can affect survey results, particularly if weighting
methodologies are not transparent or consistently applied. Moreover, expanded discretion in
oversampling could create opportunities for gaming or unintended bias, as entities may have
incentives to structure sampling in ways that improve reported outcomes. To mitigate these risks,
clear guardrails and disclosure requirements are necessary to ensure that oversampling practices
do not compromise the comparability or integrity of the data.
CMS asserts that the proposed changes will reduce respondent burden, but this claim warrants
closer scrutiny. While the introduction of gate questions may reduce the number of follow-up
items for some respondents, the overall survey process includes additional outreach efforts,
including a third email reminder and an extended telephone contact period. These changes may
increase the total number of interactions between survey administrators and respondents,
potentially offsetting any reductions in survey length. Additionally, the implementation of
revised survey instruments may impose transition costs on plans and vendors, including updates
to systems, training, and quality control processes. A comprehensive assessment of burden
should account for these factors, rather than focusing solely on the number of survey questions.
Increased outreach efforts also raise the issue of survey fatigue. As respondents are contacted
more frequently through multiple channels, there is a risk that response quality may decline, even
8

if response rates increase. Repeated contacts can lead to disengagement, rushed responses, or
selective participation, all of which can introduce nonresponse bias and reduce the reliability of
the data. Survey fatigue is a well-documented phenomenon in survey research, and its effects can
be particularly pronounced in populations that are already subject to multiple data collection
efforts. CMS should carefully evaluate whether the marginal gains in response rates justify the
potential tradeoffs in data quality.
Another important consideration is the expansion of the survey’s use beyond its original
consumer-facing purpose. While the survey was initially designed to provide information to help
consumers compare plans, it is now also used for regulatory oversight, accreditation, and
performance evaluation. This expansion of use increases the stakes associated with survey results
and may amplify the consequences of measurement error or bias. When data are used for
multiple purposes, particularly those with financial or regulatory implications, it becomes even
more important to ensure that the underlying methodology is robust and that limitations are
clearly understood. Absent such safeguards, there is a risk that the survey will be used in ways
that exceed its design capabilities.
To address these concerns, CRF recommends that CMS adopt enhanced methodological
transparency requirements. Specifically, CMS should provide detailed documentation of all
proposed changes to the survey instrument and administration, including the rationale for each
change, the expected impact on data collection and analysis, and any steps taken to preserve
comparability with prior survey administrations. Where feasible, CMS should conduct and
publish impact analyses that assess how proposed changes may affect key metrics. This level of
transparency is essential to enabling stakeholders to understand and evaluate the implications of
survey modifications.
CRF also recommends the establishment of stability requirements governing the frequency and
scope of survey revisions. While periodic updates may be necessary to reflect evolving program
priorities or external standards, frequent or substantial changes can undermine the survey’s value
as a longitudinal tool. CMS should consider implementing guidelines that limit the frequency of
major revisions and encourage the use of pilot testing or phased implementation for significant
changes. By promoting stability, CMS can enhance the reliability of the data and support more
meaningful comparisons over time.
With respect to oversampling, CMS should define clear parameters and disclosure requirements
to ensure that sampling practices are consistent, transparent, and analytically sound. This should
include guidance on acceptable oversampling strategies, standardized weighting methodologies,
and requirements for reporting sampling approaches in a manner that allows for independent
evaluation. Establishing these guardrails will help mitigate the risk of bias and ensure that survey
results remain comparable across plans and populations.
Finally, CRF recommends reforming the approach to burden accounting for the QHP Enrollee
Experience Survey. Burden estimates should reflect the full lifecycle costs associated with
survey implementation, including instrument redesign, system updates, vendor coordination,
training, and ongoing administration. By adopting a more comprehensive approach to burden

9

assessment, CMS can better align its estimates with real-world impacts and make more informed
decisions regarding the design and scope of the survey.
In sum, the QHP Enrollee Experience Survey remains a valuable tool for advancing
transparency, supporting consumer choice, and informing program oversight. However, its
effectiveness depends on the extent to which it is designed and implemented in a disciplined,
stable, and transparent manner. By addressing the concerns outlined above and adopting the
recommended guardrails, CMS can enhance the survey’s utility while minimizing unintended
consequences and ensuring that it continues to serve its intended purposes effectively.
III. CMS–R–284: T-MSIS
The Transformed Medicaid Statistical Information System (T-MSIS) data collection (CMS–R–
284) occupies a uniquely important position within the federal healthcare data architecture. As a
comprehensive, national-level dataset maintained by the Centers for Medicare & Medicaid
Services, T-MSIS serves as the primary repository for information on Medicaid and CHIP
enrollment, utilization, and expenditures. Its scale, scope, and integration into federal and state
program administration make it a foundational element of policy analysis and decision-making.
Accordingly, changes to the structure, content, or governance of T-MSIS have implications that
extend well beyond data collection, influencing how policymakers, analysts, and stakeholders
understand and evaluate the performance of Medicaid and CHIP programs.
T-MSIS data are used extensively as the basis for policy analysis and actuarial projections.
Federal and state officials rely on these data to assess program trends, estimate future costs, and
inform legislative and regulatory initiatives. Researchers and external stakeholders also depend
on T-MSIS to evaluate program outcomes and identify areas for improvement. Because of this
central role, the integrity, consistency, and clarity of T-MSIS data are critical. Any changes to
the dataset must be evaluated not only in terms of their immediate administrative impact but also
in terms of their effects on downstream analytical uses. Even incremental modifications can
influence projections, alter baseline assumptions, and affect the interpretation of program
performance.
A key insight in evaluating T-MSIS is that the structure of the data itself shapes the conclusions
that can be drawn from it. The selection of data fields, the definitions applied to those fields, and
the relationships among them all influence how analysts interpret program dynamics. In this
sense, data architecture is not neutral—it embeds assumptions and priorities that can affect
policy outcomes. For example, the inclusion or exclusion of specific identifiers can enable or
constrain certain types of analysis, while changes to data definitions can shift how trends are
measured over time. Recognizing this dynamic is essential to ensuring that modifications to TMSIS are made deliberately, with a clear understanding of their analytical implications.
CMS proposes several updates to the T-MSIS data collection, including the addition of new data
elements such as identifiers related to beneficiary status and program participation. While such
additions may be justified in certain contexts, they raise important questions regarding necessity
and scope. Each new data field imposes additional reporting requirements on states and increases
10

the complexity of data management. Absent a clearly articulated use case, the expansion of data
collection risks introducing unnecessary burden without delivering commensurate benefits. It is
therefore critical that CMS provide explicit justification for each new identifier, including how it
will be used, why existing data are insufficient, and how it aligns with statutory and
programmatic objectives.
The proposed removal of certain data elements, including those related to sexual orientation and
gender identity (SOGI), presents a different but equally important set of considerations. Changes
of this nature can affect the continuity of the dataset and complicate longitudinal analyses. When
data elements are removed, analysts may lose the ability to track trends over time or to compare
results across periods. This can introduce gaps in the data and limit the ability to evaluate
program performance in a consistent manner. Accordingly, decisions to remove data elements
should be accompanied by a clear explanation of the rationale, as well as an assessment of the
impact on existing analytical frameworks and reporting capabilities.
CMS asserts that the proposed updates to T-MSIS will not result in any change in reporting
burden. This assertion warrants careful examination. While the formal burden estimate may
remain unchanged, the practical impact on states may be more substantial. The addition of new
data elements, even if offset by the removal of others, can require updates to state information
systems, modifications to data collection processes, and additional validation and quality
assurance efforts. These activities involve time, resources, and coordination across multiple
stakeholders. As a result, the claim of “no burden change” may not fully capture the operational
realities faced by states, particularly in the near term as systems are adapted to accommodate the
revised requirements.
The federal-state dynamic inherent in T-MSIS further amplifies these concerns. While CMS
establishes the data requirements, states are responsible for collecting, validating, and submitting
the data. This effectively shifts the burden of implementation to state agencies, which must
absorb the costs associated with system changes and ongoing compliance. States vary in their
technical capacity and resource availability, and changes to T-MSIS can have uneven impacts
across jurisdictions. A disciplined approach to data collection must therefore take into account
not only the federal perspective but also the practical implications for state partners, ensuring
that requirements are feasible, proportionate, and supported by adequate guidance and resources.
To address these issues, CRF recommends that CMS adopt a defined use-case framework for TMSIS data elements. Under this approach, each data field included in the collection should be
linked to a specific, clearly articulated purpose, whether related to program administration,
statutory reporting, or analytical needs. This framework should distinguish between primary
uses, which are essential to the operation of the program, and secondary uses, which may be
beneficial but are not strictly necessary. By requiring explicit justification for each data element,
CMS can ensure that the scope of the collection remains targeted and aligned with its core
objectives.
In addition, CRF recommends that CMS implement a process for periodic review and
reassessment of T-MSIS data elements. Such reviews should evaluate the continued necessity
and utility of each field, with a willingness to sunset or modify elements that no longer serve a
11

meaningful function. This process should be transparent and involve input from state partners
and other stakeholders. Regular reassessment will help prevent the accumulation of unnecessary
data requirements and support a more dynamic, responsive approach to data governance.
T-MSIS is an indispensable tool for understanding and managing Medicaid and CHIP programs,
but its effectiveness depends on disciplined data governance. Expanding the dataset without clear
purpose, underestimating the burden on states, or failing to maintain continuity over time can
undermine its value. By emphasizing data minimization, clearly defined use cases, and ongoing
reassessment, CMS can strengthen the integrity and utility of T-MSIS while ensuring that it
remains a sustainable and effective component of the nation’s healthcare data infrastructure.
IV. CMS–10407: SUMMARY OF BENEFITS AND COVERAGE
The Summary of Benefits and Coverage (SBC) and Uniform Glossary requirements (CMS–
10407) remain an important component of the consumer information framework administered by
the Centers for Medicare & Medicaid Services. These requirements were developed to improve
transparency in health coverage by providing standardized information about plan benefits, costsharing obligations, and key terms. CRF recognizes the importance of this objective and supports
efforts to ensure that consumers have access to clear, consistent information when evaluating
health coverage options. At the same time, the effectiveness of the SBC framework depends not
only on the availability of information, but on its usability and its impact on real-world decisionmaking.
The central purpose of the SBC is to enable consumers to compare health plans in a meaningful
and informed manner. By standardizing the format and content of disclosures, CMS seeks to
reduce complexity and facilitate side-by-side evaluation of coverage options. In theory, this
approach should enhance consumer understanding and support more efficient market outcomes.
However, the degree to which standardized disclosures achieve these goals depends on how
consumers interact with the information provided. Standardization alone does not guarantee that
the information is accessible, comprehensible, or actionable for the intended audience.
A critical insight in evaluating the SBC framework is that standardization is not synonymous
with usability. While uniform formats can reduce variation across plans, they do not necessarily
address the underlying challenges that consumers face in interpreting complex health insurance
information. If disclosures are overly dense, technical, or disconnected from the decision-making
context, consumers may struggle to extract meaningful insights, regardless of how consistently
the information is presented. In such cases, the result may be formal compliance with disclosure
requirements without a corresponding improvement in consumer understanding or behavior.
This dynamic raises important questions about the relationship between burden and benefit. The
SBC requirements impose significant compliance obligations on issuers and plan sponsors,
including the need to generate standardized documents, update them in response to plan changes,
and distribute them to consumers in a timely manner. These activities involve administrative,
operational, and technological costs that are not insignificant. At the same time, the marginal
benefit of additional standardization—particularly in the absence of demonstrated improvements
12

in consumer comprehension—may be limited. A disciplined PRA analysis should therefore
examine whether the incremental benefits of maintaining and updating these requirements justify
the ongoing burden imposed on regulated entities.
Empirical and behavioral evidence suggests that consumers do not consistently utilize
standardized disclosures in the manner envisioned by policymakers. Many consumers rely on
simplified heuristics, recommendations, or prior experience when selecting health coverage,
rather than conducting detailed comparisons of plan documents. Even when SBC materials are
available, they may not be fully read or understood, particularly if they are perceived as complex
or time-consuming to review. This reality does not negate the value of transparency, but it does
suggest that the current approach may not fully align with how consumers actually make
decisions. As a result, there is a risk that the SBC framework emphasizes form over function,
prioritizing compliance with disclosure requirements over meaningful engagement.
In light of these considerations, CRF recommends that CMS place greater emphasis on
simplification, readability, and real-world usability in the design and implementation of SBC
requirements. This includes exploring opportunities to streamline content, reduce redundancy,
and present information in a manner that is more intuitive for consumers. CMS should also
consider incorporating user-centered design principles and conducting empirical testing to
evaluate how consumers interact with SBC materials in practice. Such testing can provide
valuable insights into which elements are most useful and which may be unnecessary or
counterproductive. By focusing on how information is actually used, rather than how it is
theoretically structured, CMS can enhance the effectiveness of the SBC framework.
Ultimately, the continued success of the SBC requirements depends on their ability to deliver
meaningful value to consumers while maintaining a reasonable balance between burden and
benefit. As CMS moves forward with this information collection, it should take the opportunity
to reassess the effectiveness of the current framework and to consider whether adjustments are
needed to better align with real-world behavior and program objectives. A more targeted, userfocused approach—grounded in evidence and responsive to stakeholder input—can help ensure
that the SBC continues to serve its intended purpose without imposing unnecessary or
disproportionate burdens.
CONCLUSION
CRF appreciates the opportunity to provide comments to the Centers for Medicare & Medicaid
Services on the proposed information collections under the Paperwork Reduction Act. The PRA
process serves as an important mechanism for ensuring that federal data collection activities
remain transparent, justified, and subject to meaningful stakeholder input. Engagement at this
stage is particularly valuable given the central role that information collection plays in the
administration of federal healthcare programs and the increasing reliance on data-driven
frameworks to guide policy and operational decisions.
CRF strongly supports the use of data to inform policymaking, improve program performance,
and enhance transparency for consumers and stakeholders. Well-designed information
13

collections can provide critical insights into program operations, support more effective
oversight, and enable more informed decision-making across the healthcare system. At the same
time, the value of data-driven policymaking depends on the quality, relevance, and integrity of
the underlying data, as well as the extent to which data collection efforts are aligned with clearly
defined objectives. Ensuring that information collections meet these standards is essential to
realizing their full potential.
A central theme of these comments is that the design of information collections ultimately
determines their value. The selection of data elements, the structure of collection instruments,
and the methodologies used to gather and interpret data all influence the utility of the resulting
information. Thoughtful design can enhance comparability, improve accuracy, and support
meaningful analysis, while poorly calibrated approaches can introduce bias, create unnecessary
complexity, and limit the usefulness of the data. As CMS continues to refine its information
collection activities, careful attention to design considerations will be critical to ensuring that
these efforts produce reliable and actionable insights.
At the same time, CRF remains concerned about the potential for the expansion of information
collection activities without sufficient discipline or clear limiting principles. As collections
evolve over time, there is a tendency to add new data elements, expand use cases, and increase
reporting requirements, often without a comprehensive reassessment of necessity and burden.
This incremental growth can result in cumulative burdens that are disproportionate to the
benefits achieved, particularly when data are collected for purposes that are not clearly defined
or are only marginally related to core program functions. Addressing this dynamic requires a
more deliberate and structured approach to managing the scope of information collections.
The importance of these issues extends beyond individual collections to the broader healthcare
system. Data collected by CMS play a significant role in shaping market behavior, informing
policy decisions, and influencing cost structures across federal healthcare programs. They affect
how plans compete, how providers deliver care, and how resources are allocated. As such, the
design and implementation of information collections have system-level implications that
warrant careful consideration. Ensuring that these collections are efficient, targeted, and
analytically sound is essential to maintaining the integrity and effectiveness of the programs they
support.
Looking forward, CRF encourages CMS to adopt an approach to information collection that
emphasizes calibration, transparency, and restraint. Calibration requires aligning the scope and
detail of data collection with clearly defined purposes and demonstrated utility. Transparency
involves providing clear documentation of methodologies, assumptions, and changes to
collection instruments, enabling stakeholders to understand and evaluate the data. Restraint
entails exercising discipline in expanding data requirements and being willing to streamline or
eliminate elements that no longer serve a meaningful function. Together, these principles can
help ensure that information collection activities remain both effective and sustainable.
In sum, the continued modernization of CMS data systems presents an opportunity to enhance
program performance and improve outcomes for beneficiaries. Realizing this opportunity will
depend on the extent to which modernization efforts are guided by disciplined design and
14

grounded in a clear understanding of both benefits and costs. By incorporating the
recommendations outlined in these comments, CMS can strengthen the analytical foundation of
its information collection activities while reducing unnecessary burden and preserving flexibility
for future innovation.
The effectiveness of CMS’s information collection activities will not be determined by the
volume of data collected or the breadth of reporting requirements imposed, but by whether those
collections are designed and implemented in a manner that is analytically rigorous, operationally
efficient, and appropriately bounded to serve clearly defined statutory and programmatic
objectives.
Sincerely,

Andrew M. Langer
Director
CPAC Foundation Center for Regulatory Freedom

15

PUBLIC SUBMISSION

As of: 5/7/26, 10:15 AM
Received: April 14, 2026
Status: Draft
Category: Individual
Tracking No. mnz-981k-uu47
Comments Due: April 14, 2026
Submission Type: Web

Docket: CMS-2026-0595
Consumer Experience Survey Data Collection (CMS-10488)
Comment On: CMS-2026-0595-0001
Agency Information Collection Activities; Proposals, Submissions, and Approvals
Document: CMS-2026-0595-DRAFT-0004
Comment on CMS-2026-0595-0001

Submitter Information
Name: Christian Price
Address:
Maitland, 
FL, 
32754

General Comment
I’m believe it is fair for information to be collected so long as it is stated openly and done fairly.

PUBLIC SUBMISSION

As of: 5/7/26, 10:16 AM
Received: April 05, 2026
Status: Posted
Posted: April 08, 2026
Category: Health Care Industry - PI015
Tracking No. mnl-vins-gldh
Comments Due: April 14, 2026
Submission Type: Web

Docket: CMS-2026-0595
Consumer Experience Survey Data Collection (CMS-10488)
Comment On: CMS-2026-0595-0001
Agency Information Collection Activities; Proposals, Submissions, and Approvals
Document: CMS-2026-0595-0002
Comment on CMS-2026-0595-0001

Submitter Information
Name: Nakul Karkare
Address:
Stony Brook, 
NY, 
11790
Email: [email protected]
Phone: 6319812663

General Comment
T-MSIS is described as the only national-level source for Medicaid utilization data,
enrollment, expenditures, and actuarial forecasting. The QHP Enrollee Survey aims to
produce comparable, actionable performance data across competing health plans. Both
goals rest on a foundation that is structurally compromised: procedure coding that
permits two clinicians performing the same service to submit different codes —
legitimately.
When the underlying procedural data is inconsistent, no downstream analysis —
utilization trends, expenditure modeling, cross-plan comparisons, fraud detection — can
be fully trusted. The noise is baked in at the source.
I have developed a deterministic procedure coding system that eliminates this variability
entirely. Every code derives automatically from data elements already present in the
claim. No clinician discretion. No ambiguity. Same service, same documentation, same
code — across every provider, every payer, every setting. Every component is fully
auditable and traceable to its source.
This system is complete, tested, and available without licensing fees. It is directly
applicable to improving the integrity of both T-MSIS data and QHP comparative
analytics.
Nakul Karkare MD
https://www.newyorkhipknee.com/
https://www.cortho.org

August 13, 2026

Centers for Medicare & Medicaid Services
7500 Security Boulevard
Baltimore, Maryland 21244 –1850
Submitted Electronically: https://www.reginfo.gov/public/do/PRAMain
Re: Consumer Experience Survey Data Collection
Dear Sir/Madam:
UnitedHealthcare (UHC) is pleased to submit comments to the Centers for Medicare & Medicaid Services (CMS) in
response to the information collection request for the Consumer Experience Survey Data Collection (91 FR 43093).
UHC offers a full range of health benefits, enabling affordable coverage, simplifying the health care experience, and
delivering access to high -quality care. UnitedHealthcare is the health benefits business of UnitedHealth Group, a
health care and well -being company working to help build a modern, high -performing health system through
improved access, affordability, outcomes, and experiences. We are committed to a future where every person has
access to high -quality, affordable health care and a modern, hig h-performing health system that improves outcomes
and lessens the burden of disease.
Overall, UHC is supportive of the enhancements CMS is planning for the QRS and QHP Enrollee Experience Survey,
especially those that would reduce burden on enrollees and streamline their ability to respond. In what follows, we
offer technical input on oper ational impacts related to proposed changes to the telephone survey protocol,
considerations around modifications to the QRS scoring methodology, and additional questions for future updates
to the survey questionnaire, among other recommendations.
Proposed Removal of Tobacco

-Usage Questions

CMS proposes to remove four questions related to tobacco -usage which are used to calculate the Medical
Assistance with Smoking and Tobacco Use Cessation measure, and to instead transition to collecting this
information through digital quality measures.
UHC supports CMS's proposal to remove the four tobacco -usage questions used to calculate the Medical
Assistance with Smoking and Tobacco Use Cessation measure beginning with the 2027 survey administration,
consistent with NCQA's retirement of the underlyin g measure and its move toward an electronic clinical data –based
replacement rather than self -reporting. This change may reduce respondent burden while keeping the QHP Enrollee
Survey aligned with the broader measures landscape.

Revising Race/Ethnicity Questions to Align With Federal Standards
CMS proposes to revise the current race and ethnicity questions to align with federal standards. UHC supports
combining the current two separate race and ethnicity questions into one single question as proposed in this
Consumer Experience Survey Data Colle ction.
Revisions to the QHP Enrollee Survey Questionnaire and Materials
CMS proposes adding five screener questions that would allow respondents to skip follow
up questions that do not
apply to them (customer service contact, forms, access to a personal doctor, test ordering, specialist visits).
UHC supports the overall intent to reduce respondent burden through clearer logic and improved routing. The
current survey already incorporates logic embedded within response options; moving routing eligibility into
standalone screener questions may make survey flow cleaner —particularly for telephone administration —and may
reduce the awkwardness of asking respondents to evaluate experiences they did not have.
UHC also recommends that CMS monitor how these changes affect denominators for impacted items, given
potential implications for year over year comparability.
Modification s to the Telephone Protocol of the QHP Enrollee Survey
CMS proposes refinements to the survey fielding protocol to improve response rates, including extending the
telephone follow‑up window (from 19 to 25 calendar days), initiating telephone calls to nonrespondents earlier
(beginning on Day 48 rather than Day 55), and adding a third email reminder (on Day 40).
UHC supports efforts to improve response rates and agrees that refinements to outreach strategy may be helpful. At
the same time, we recommend CMS carefully consider operational effects of beginning calls earlier in the fielding
timeline.
Starting calls earlier may increase the apparent nonrespondent pool at the point of first dial, because a shorter
period of mail and web collection may mean more sampled enrollees still appear as nonrespondents when calls
begin. Slower postal delivery and mail processing timelines may result in situations where an enrollee returns a
completed survey, but it has not yet been received and logged by the vendor —creating a risk that vendors call
individuals who have already responded. This may be a poor respondent experience and operational inefficiency. If
earlier calling increases call volume without a proportional increase in completed surveys, it may also increase
administration costs over time.
In addition, UHC supports the proposal to add a third email reminder on Day 40. Email is a lower cost touchpoint
than telephone, and a Day 40 reminder is a n outreach that may convert some potential phone respondents before
the telephone phase begins, partially offsetting the call volume concerns noted above.
Oversampling
CMS proposes to update the QHP Enrollee Survey sampling protocol to allow oversampling at any level.
UHC
supports CMS's proposal to update the QHP Enrollee Survey sampling protocol to allow oversampling at any level.
Given the length and complexity of the survey, achieving adequate response volumes can be challenging. Providing
health plans with greater fl exibility to increase sample sizes will help mitigate low response rates and support the
collection of higher rates of completed surveys. This approach can enhance the reliability and stability of survey
results by ensuring a broader representation of member experiences, while also reducing the impact of
nonresponse bias. Ultimately, allowing oversampling at any level will strengthen the value of the survey data used to
assess plan performance and inform quality improvement efforts. To support comparability and validity across

issuers and markets, UHC further recommends that CMS continue applying appropriate weighting and
methodological safeguards when implementing expanded oversampling flexibility.

Thank you for your thoughtful consideration of our comments. Should you have any questions, please do not
hesitate to contact me.

Sincerely,

Nicole Brady, MD, MBA
Chief Medical Officer & Vice President Individual & Specialty
UnitedHealthcare Employer & Individual