What is Encounter Data Submission? Definition, Formula, and Benchmark

Encounter data submission is the process Medicare Advantage (MA) plans use to report detailed claim-level encounter information to CMS through the Encounter Data Processing System (EDPS). CMS introduced encounter data submission to supplement (and progressively replace) the Risk Adjustment Processing System (RAPS) as the source for MA risk adjustment. Encounter data provides richer claim-level detail — service line items, dates, providers, and diagnoses — supporting both risk adjustment and broader program oversight.

Submission mechanics: MA plans submit encounter data in X12 837 format (professional or institutional), mirroring the original claims received from providers. The EDPS validates submissions, processes accepted encounters, and feeds downstream systems including the risk adjustment calculation engine. Plans must meet submission timelines and quality thresholds to ensure encounter data is usable for risk calculation.

Encounter data submission accepts the full claim record as originally adjudicated by the MA plan. Diagnoses on the encounter contribute to HCC identification for risk adjustment. Service line items provide data for plan-level analytics, CMS quality reporting, and regulatory oversight. Some data elements captured in encounter data are not captured in RAPS — encounter data is therefore richer but also more complex to produce.

Quality thresholds: CMS applies submission quality standards — encounter completeness, timeliness, error rates — to determine whether a plan's encounter data is "usable" for risk adjustment. Submissions with high rejection rates or significant data quality issues may be excluded from risk score calculation, with the plan's risk scores instead derived from alternative data sources (RAPS, prior-year data, sampling-based adjustments). Quality issues therefore have direct financial impact.

RAPS-to-EDPS transition: CMS initially introduced EDPS as a supplement to RAPS, then transitioned to EDPS as the primary source for MA risk adjustment. The transition occurred through blended-weight phase-in starting in 2015, with EDPS weight gradually increasing and RAPS weight decreasing. By 2024, risk scores were calculated predominantly or entirely from encounter data rather than RAPS. This transition requires MA plans to maintain high-quality encounter submission capabilities.

Plan-provider workflow implications: MA plans depend on provider claim submissions to generate encounter data. Claim quality issues at the provider level — coding errors, missing data, invalid fields — cascade into encounter data quality issues. Plans therefore invest in provider education, claim scrubbing, and feedback loops to improve upstream claim quality. Plans that fail to submit high-quality encounter data face risk score reductions affecting CMS capitation revenue.

For RCM operations, encounter submission is predominantly a health plan function, but providers have a stake in plan encounter data quality. Provider-level claims must be clean, complete, and accurately reflecting clinical services and diagnoses. Plans provide feedback to providers through claims-adjudication processes, denial-and-rejection feedback, and sometimes structured data-quality scorecards. Providers participating in value-based or capitated arrangements with MA plans have direct financial interest in encounter submission quality.

Encounter data is also used beyond risk adjustment. CMS uses aggregated encounter data for MA program evaluation, Star Rating calculations in some measures, medical loss ratio analysis, and research. Advocacy groups and policy researchers access de-identified encounter data subsets for Medicare Advantage program analysis. Data quality therefore affects not only individual plan risk scores but broader program understanding.