CMS Launches Medicaid Quality Pledge With 37 States: What Health Plans Should Prepare For

The voluntary initiative could influence future state contracts, quality measures and data requirements. Health plans can begin preparing while continuing to meet existing obligations.

The Centers for Medicare & Medicaid Services announced a partnership with 37 states on September 25 to reshape how Medicaid and the Children’s Health Insurance Program measure quality. Called Investing in Health Outcomes, the initiative asks participants to prioritize measurable improvements in prevention, chronic disease management and behavioral health.

For Medicaid health plans, the immediate task is to assess how their quality programs connect reporting, clinical information and care delivery. The implications will become more concrete as states translate the pledge into program decisions.

The distinction matters: signing the pledge is voluntary. The announcement does not establish a new nationwide reporting deadline or a single mandatory replacement measure set.

CMS says participating states will use the principles to develop health-outcome targets and identify opportunities in their quality strategies and upcoming procurements. It also plans workshops later in 2026.

The pledge’s four commitments

The framework sets out four priorities:

• Give greater weight to health outcomes.
• Simplify overlapping measure inventories while preserving accountability.
• Expand digital measurement using timely information where feasible.
• Connect financial accountability to outcomes.

Medicaid.gov lists 37 participating states as of September 24. Across those states, the agency reports approximately 56 million Medicaid and CHIP beneficiaries and roughly $701 billion in fiscal-year 2024 Medicaid spending. These figures describe the participating programs’ scale; they are not new funding awards.

Why measurement is under scrutiny

CMS’s May 2026 analysis of Medicaid managed-care contracts across 42 states and programs identified approximately 450 quality-reporting requirements representing 258 distinct measures. The agency describes an opportunity to reduce duplication and place more emphasis on beneficiaries’ health.

However, consolidating measures requires attention to their definitions. Two measures can address the same condition while counting different patients, applying different exclusions or using different observation periods.

CMS’s measure-development guidance identifies the population, calculation logic, data sources and collection instructions as central parts of a specification. It also warns that population-definition errors can produce misleading conclusions about quality.

For a health plan, this makes a detailed inventory more useful than a simple count of reports.

Existing quality obligations still apply

Medicaid managed-care quality requirements already operate through state contracts. Under 42 CFR 438.330, states must require covered managed-care organizations to maintain quality-assessment and performance-improvement programs, collect performance information and conduct improvement projects.

The regulation also requires annual performance reporting or submission of the information states need to calculate performance. The voluntary pledge does not itself amend those requirements. Plans should continue following applicable rules and contracts while reviewing subsequent state instructions.

A state’s participation therefore provides a reason to begin a planning discussion. Any operational change needs to be tied to the relevant specification, contract provision or implementation guidance.

Start with an inventory that explains the work

US Health Insights’ assessment is that plans should begin by bringing quality, clinical, contracting and data teams into the same review.

For each measure, document:

• Who requires it and which contract or program applies.
• The eligible population, exclusions and measurement period.
• The information needed and where it originates.
• The reporting frequency and responsible team.
• Any associated payment or performance consequences.

This exercise can identify measures that share data needs without assuming they are interchangeable. It can also reveal duplicated extraction work, inconsistent definitions and reports that arrive too late to support intervention.

The result should be a practical map of current obligations and improvement opportunities. Decisions to retire or replace required measures should follow the applicable approval process.

Test whether clinical information is usable

Digital measurement is part of a broader CMS direction. Through Meaningful Measures 2.0, the agency supports interoperable information exchange, greater use of electronic measures and alignment across quality programs. Its strategy includes FHIR-based standards and APIs for exchanging clinical information.

Technology teams should assess more than whether a connection exists. A useful readiness review asks whether incoming records can be matched to the correct person, interpreted consistently and traced to their source.

Consider a hypothetical diabetes measure. A laboratory result without a reliable patient match, collection date or usable value may arrive electronically yet remain unsuitable for the calculation. Faster transmission alone does not resolve those gaps.

Plans can test a small sample from source record to final score, documenting missing information and manual corrections before expanding the workflow. Our guide to healthcare data models provides additional background on organizing information across systems.

Connect each metric to an operational response

A quality dashboard becomes more useful when a team knows what to do with its findings.

For an existing chronic-condition measure, a plan could examine which members require outreach, who receives the work, how clinical follow-up is documented and when progress is reassessed. This is a suggested planning approach, not a new CMS requirement.

The review should also distinguish missing documentation from a confirmed care gap. Those situations may need different responses.

Where performance affects payment, contracting teams should understand how targets are calculated and how results will be validated. The broader relationship between reimbursement and performance is explained in our fee-for-service versus value-based care guide.

Judge improvement with comparable information

A higher score can reflect better care, more complete records or a change in the population being measured. Evaluations should account for those possibilities.

CMS’s guidance treats measure testing as an assessment of reliability, validity and potential threats to sound conclusions, including differences in data sources and population definitions.

Before comparing results across periods, plans should document whether specifications, data coverage or membership changed. An improvement claim is stronger when the organization can explain both the clinical activity and the measurement conditions behind it.

The next documents worth watching are state quality-strategy revisions, procurement materials and contract amendments. Until those details emerge, a concrete preparation step is to select one existing measure and trace its entire path from the contractual requirement through the source data to the action taken for a member.