SummaryIn a recent post on the RISE website, Sean Creighton examines the methodology and evidence behind CMS’s proposal to eliminate the Fee-for-Service (FFS) Adjuster from Risk Adjustment Data Validation (RADV) audit methodology.
CMS uses a risk adjustment model, called the CMS Hierarchical Condition Category (CMS-HCC) model, to pay plans appropriately for the health status of their enrollees. The CMS-HCC model is based on diagnoses and program costs for individuals in Medicare FFS. The current RADV methodology includes an offset known as the FFS Adjuster, which was intended to account for the different documentation standard used to develop the MA risk adjustment model.
In their proposed new methodology, CMS does not account for the difference between how this model is developed—in which coding errors are allowed and included—and how money is recovered under a RADV audit—in which each code is held to a 100% accuracy standard. CMS cites a new internal study finding that errors in reporting diagnosis codes in FFS claims data have no meaningful impact on risk adjustment model estimation and, further, do not bias MA plan payment.
The article focuses on methodological approaches in CMS’s study of the impact of the FFS Adjuster on plan payment and discusses the implications of changing the RADV methodology. In short, the design of CMS’s study results in estimates of the rates of error in FFS coding that are much smaller than in practice and then adjusts the results to altogether remove the impact of the error. The article concludes that eliminating the FFS Adjuster would likely have significant implications for plan payment and could change plan incentives and behavior, including plans’ willingness to assume the risk of participating in the program.
Read the full RISE article.
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