Service-level Selection: Strategic Risk Selection in Medicare Advantage in Response to Risk Adjustment
Year: 2017
Type: report
Abstract: The Centers for Medicare and Medicaid Services (CMS) has phased in the Hierarchical Condition Categories (HCC) risk adjustment model during [2004][2005][2006] to more accurately estimate capitated payments to Medicare Advantage (MA) plans to reflect each beneficiary's health status.However, it is debatable whether the CMS-HCC model has led to strategic evolutions of risk selection.We examine the competing claims and analyze the risk selection behavior of MA plans in response to the CMS-HCC model.We find that the CMS-HCC model reduced the phenomenon that MA plans avoid high-cost beneficiaries in traditional Medicare plans, whereas it led to increased disenrollment of high-cost beneficiaries, conditional on illness severity, from MA plans.We explain this phenomenon in relation to service-level selection.First, we show that MA plans have incentives to effectuate risk selection via service-level selection, by lowering coverage levels for services that are more likely to be used by beneficiaries who could be unprofitable under the CMS-HCC model.Then, we empirically test our theoretical prediction that compared to the pre-implementation period (2001)(2002)(2003), MA plans have raised copayments disproportionately more for services needed by unprofitable beneficiaries than for other services in the post-implementation period (2007)(2008)(2009).This induced unprofitable beneficiaries to voluntarily dis-enroll from their MA plans.Further evidence supporting this selection mechanism is that those dissatisfied with out-of-pocket costs were more likely to dis-enroll from MA plans.We estimate that such strategic behavior led MA plans to save $5.2 billion by transferring the costs to the federal government.
DOI: 10.3386/w24038
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: green
Funders: AcademyHealth, University of Washington
OpenAlex ID: W2769276546