Medicare Claims Data Analysis Case Study: Primary Care Access

What the Medicare claims analysis studied

The Health Affairs Scholar study evaluated whether a multi-payer, full-risk value-based care model helped preserve access to primary care for Traditional Medicare beneficiaries. The analysis compared primary care providers who adopted the model in 2022 with similar providers in the same markets who did not adopt the model.

The key analytic question was not simply whether spending changed. It was whether claims data could show a practical access outcome: whether physicians continued accepting new Traditional Medicare patients as primary care capacity tightened.

Medicare claims data sources and years

• Traditional Medicare claims from 2016 through 2023 to define provider panels, patient history, outcomes, and covariates.
• 2019-2023 claims for the main difference-in-differences access analysis.
• Medicare enrollment data to assign beneficiary geography.
• CMS Doctors and Clinicians data to characterize physician attributes.
• External county rurality data to support market and provider context.

How claims became access measures

Medicare claims do not contain a simple field that says a primary care physician is accepting new patients. The analysis inferred access from observed service patterns. New patient visits were identified from claims for new-patient evaluation and management services and annual wellness visits when prior physician relationships were absent.

• New patients per PCP: annual count of new Traditional Medicare patients attributed to each physician.
• Months accepting new patients: number of months in a year when the physician had claims indicating at least one new Traditional Medicare patient.
• Provider panels: longitudinal physician-patient relationships built from claims history.
• Market comparability: comparison physicians selected from the same counties and relevant primary care specialties.

Study design

The study used a difference-in-differences framework to compare changes before and after value-based care adoption. The exposure group included 208 primary care providers who adopted the supported full-risk model. The comparison group included 3,657 similar primary care providers who maintained their existing payment models.

The design treated 2022 as the transition year and compared pre-adoption years with 2023 outcomes. Sensitivity tests examined pre-period trends and an alternative comparison group to test whether the findings were robust.

What the Medicare claims analysis found

• Adopting providers saw about 8.3 more new Traditional Medicare patients per year than similar nonadopters after adoption.
• Adopting providers kept panels open to new Traditional Medicare patients about 0.71 more months per year than nonadopters.
• The study suggests supported, full-risk value-based care may help sustain primary care access for Traditional Medicare beneficiaries.

Why this matters for Medicare claims analytics

This is a practical example of Medicare claims data analysis moving beyond cost and utilization reporting. Claims were used to measure access, provider behavior, panel openness, market trends, and the potential impact of a payment model on real-world primary care capacity.

The same analytic pattern can support Medicare market intelligence, provider network strategy, value-based care evaluation, access monitoring, ACO analysis, diligence, and policy research.

Reusable claims analytics methods

• Define provider panels from longitudinal claims history.
• Identify new patient relationships from billing patterns and prior service history.
• Create market-matched comparison groups for observational evaluation.
• Measure access, utilization, spending, quality, and provider behavior over time.
• Apply difference-in-differences and sensitivity testing for decision-grade evidence.

Source publication

Kornitzer BS, Yao A, Peikes DN, Rao K. Impact of a multi-payer full-risk model on preserving primary care access for traditional Medicare beneficiaries. Health Affairs Scholar. 2025;3(5):qxaf093. doi:10.1093/haschl/qxaf093.

Read the open-access article or view the related FastHSR summary: Agilon's Model Helps Preserve Access to Primary Care.

Frequently asked questions

How can Medicare claims data measure primary care access?

Medicare claims can identify new patient visits, annual wellness visits, longitudinal patient-provider relationships, provider panels, and the months in which a physician appears to accept new Traditional Medicare patients.

What Medicare claims files were used in this access analysis?

The published study used Traditional Medicare claims from 2016 through 2023, including claims to define provider panels, new patient access outcomes, and physician-level covariates.

What did the claims-based analysis find?

The difference-in-differences analysis found that primary care providers adopting the supported full-risk model saw more new Traditional Medicare patients and kept panels open longer than similar nonadopter physicians.

Why is this a Medicare claims analytics case study?

The study translated raw Medicare claims into decision-ready access measures, comparison groups, longitudinal outcomes, and policy-relevant evidence about value-based care adoption.

For Medicare claims data analysis, value-based care evaluation, provider access measurement, or market intelligence, please email us.

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