More than half of Medicare beneficiaries are enrolled in Medicare Advantage (MA), making the program central to how millions of people access care. Ensuring that these beneficiaries receive appropriate services, and that payments and quality measures reflect reality, depends on reliable data.
Encounter data power risk-adjusted payments, the Star Ratings system from the Centers for Medicare & Medicaid Services (CMS), and oversight of who has access to and uses MA services. When those data are incomplete or inaccurate, it becomes harder for policymakers to assess performance, target improvements, and ensure accountability. Strengthening the quality of these data is therefore essential to the effective operation of MA.
That is why CMS’s continued partnership with Mathematica to assess, monitor, and improve the completeness and accuracy of MA encounter data matters—both for MA and as a model for data-driven oversight across public health programs facing similar data quality challenges.
From data submission to action-ready oversight
To support more effective oversight, rigorous analyses of encounter data from MA organizations and Medicare–Medicaid plans will translate complex data into clear, action-ready insights for CMS.
Quarterly report cards and Submission Performance Reports provide CMS with clear, comparable metrics on data completeness, submission patterns, and common errors. Impact reports will help CMS quickly identify contracts that may benefit from outreach or technical assistance.
These efforts demonstrate the value of structured, recurring analytics for program oversight, helping CMS monitor submission performance, identify emerging issues, and strengthen data quality over time. Ensuring the integrity of encounter data is becoming part of the operational infrastructure of the MA program.
Modernizing analytic systems without disruption
At the same time, CMS is navigating a major technology transition in the decommissioning of its legacy analytic platforms. Maintaining continuity during this transition is critical to ensuring that oversight remains stable and trustworthy.
To support this transition, Mathematica will migrate the existing MA encounter data codebase from SAS to Python in a new analytic environment, maintaining continuity of operations and enhancing transparency, flexibility, and scalability.
Large-scale code conversion is not simply a technical exercise. It requires rigorous validation, parallel testing, detailed documentation, and close coordination with agency partners to ensure that metrics remain consistent and trustworthy. This work helps CMS modernize its analytic infrastructure without disrupting mission-critical data products.
Bringing policy and data expertise together
MA encounter data are complex, reflecting nuanced reporting rules, chart review records, risk-adjustment implications, and differences across plan types and services. Designing meaningful completeness and accuracy measures requires technical skill and a deep understanding of how the data are generated and used.
For nearly a decade, Mathematica has supported CMS in analyzing MA encounter data, refining performance metrics, and improving reporting processes. This work integrates Medicare policy expertise with advanced analytics, statistical modeling, and rigorous quality assurance.
By combining research rigor with operational analytics, we help agencies move beyond descriptive reporting toward continuous performance improvement.
Building stronger data foundations across public programs
The implications of this work extend beyond MA. Across health and human services, agencies must ensure that large administrative data sets are complete, accurate, and useable for decision making.
Agencies should ask themselves the following key questions:
- How can my agency measure and improve data completeness and accuracy at scale?
- How can the complex data we produce be translated into clear, action-ready insights for oversight and leadership?
- How can we modernize our analytic systems while safeguarding continuity and transparency?
Mathematica’s work on MA encounter data demonstrates how to address these challenges in practice. By integrating policy expertise, advanced analytics, and modern data engineering, we help agencies strengthen the data foundations that underpin effective program management.
As the healthcare landscape evolves, high-quality data will remain essential to ensuring accountability, fairness, and value. Through this continued partnership with CMS, Mathematica is advancing the integrity of MA encounter data and the broader field of data-informed public program oversight.
