Identifying Upcoding in Markets with Adverse Selection: An Application to Medicare
We model upcoding in the presence of adverse selection. Our model delivers a novel strategy for empirically separating upcoding from selection in aggregate, market-level data. The intuition behind our approach is that if the same individual generates a higher risk score in one plan than another, then as the market share of the more intensively coded plan increases, the overall level of reported risk in that market should increase. Such a pattern can not be due to selection, because all enrollees are included in the calculation of the market-level risk score, regardless of the plan they selected into. We apply this strategy to analyze upcoding by Medicare Advantage plans. The results show that enrollees in Medicare Advantage plans generate 5% higher risk scores than what the same enrollees would generate under Traditional Medicare. Absent a coding inflation correction, this implies a distortion in seniors’ choice between Medicare Advantage and Traditional Medicare, and excess payments to Medicare Advantage of around $6 billion annually. Our findings also have implications for the geographic distribution of Medicare's resources, as Medicare Advantage penetration rates vary widely across localities.