Ensuring Accurate Risk Score Payments to a Mid-Sized Health Plan


A regional health plan engaged us to (1) evaluate its risk adjustment processes for program compliance and identify improvement opportunities, and (2) assess the completeness of its data submissions to the Centers for Medicare & Medicaid Services (CMS) for use in risk adjustment calculations. In part one, we identified deficiencies in the client’s process that resulted in omitted data from providers and supplemental sources, with a potential risk score and revenue impact of $90 million. In part two, we analyzed the client’s claims data inputs and outputs. We identified several eligible claim sets that had been omitted from submissions to CMS, resulting in artificially low risk scores with a potential revenue impact of $20 million over two years.

Client Type

Mid-sized regional health plan


A regional health plan solicited our assistance in conducting a technical and procedural review of its processes for collecting claims data from providers, aiming to ensure that it submits more complete and accurate encounter data as efficiently as possible to CMS for its risk score calculations.

The client had also suspected that its processes for submitting claims data to CMS were inadequate, resulting potentially in the omission of claims eligible for inclusion in risk score calculations. The health plan’s claims data collection and submission processes were not optimized for Medicare risk assessment procedures, despite the growing impact of Medicare Advantage (MA) on its business, and although the health plan was not required by CMS to submit all eligible claims, their submission would result in more accurate risk scores and higher payments.


For part one of the project, we reviewed all the client’s documentation (e.g., policies, procedures, and training materials) related to the submission of risk adjustment data and interviewed key staff members involved in those processes. We evaluated those processes and materials using our proprietary encounter data system compliance matrix to identify compliance gaps and operational inefficiencies. We ordered these shortcomings into priority tiers and helped the client develop resolution plans. We also identified provider types and supplemental claims data sources (e.g., unlinked chart review claims) that had not been integrated into the client’s risk adjustment program, with an estimated revenue impact of $90 million, and proposed solutions to address these issues.

For part two of the project, we gathered from the client (1) raw claims data, (2) data in client storage, (3) claims data files submitted to CMS, and (4) complete return files sent by CMS for two recent years. Using our understanding of CMS’s Medicare risk score calculations, we assessed the raw claims data for eligible claims, traced those claims through the storage, submission, and return processes to identify dropped claims, and then processed dropped claims through CMS’s Hierarchical Condition Category risk adjustment model to determine how the inclusion of those claims would have changed the health plan’s risk scores and corresponding payments from CMS.

We documented our findings from each step in the data collection, storage, processing, and submission processes, and provided files containing all dropped claims so that the client could determine the root causes behind each omission. We identified some of these root causes (e.g., use of different patient identification numbers across different tracking systems) and proposed solutions (e.g., use of a global unique identifier for each patient).


The client is following our recommendations to ensure that it submits to CMS all eligible claims in future years to obtain more accurate risk scores and that it receives appropriate risk score payments under the MA program.

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