Formalizing a definition of upcoding behavior relevant to Medicare Advantage beneficiaries

3228 

Contributed Abstract 

Paper 

Oana Enache (1), Sherri Rose (1)

(1) Stanford University, Stanford, California, USA

Sherri Rose  
Stanford University

Oana Enache  
Stanford University

Oana Enache  
N/A

Medicare is a federally funded insurance program that enables essential health services for 60 million older and chronically disabled US adults. The fastest-growing care program in Medicare is Medicare Advantage (MA), whose enrollment surpassed 30 million Americans in 2023. Enrollees in MA buy insurance from contracted private insurers who are reimbursed by the federal government. Reimbursement amounts are determined by a regression that predicts per-patient spending as a weighted risk score of a patient's diagnoses and demographic information. This approach aims to disincentivize insurers from avoiding high-cost enrollees. In practice, this prediction function incentivizes insurers to make their enrollees appear sicker, commonly termed "upcoding." Upcoding has been estimated to cost the government $12-25 billion annually with no clinical benefit to patients. However, a challenge in addressing upcoding is that no formal definition of such behavior exists to evaluate current prediction functions. We address this by developing a formal and operational definition of MA upcoding that can serve as an evaluation metric, so such behavior can be more reliably monitored and corrected.

metrics|evaluation metrics|healthcare|policy|risk adjustment|Medicare

Health Policy Statistics Section

Miscellaneous