Understanding Unintended Consequences of Risk Adjustment and Proposing Alternative Risk Adjustment

dc.contributor.advisorBasu, Anirban
dc.contributor.authorPark, Sungchul
dc.date.accessioned2018-07-31T21:14:00Z
dc.date.issued2018-07-31
dc.date.submitted2018
dc.descriptionThesis (Ph.D.)--University of Washington, 2018
dc.description.abstractTo achieve two goals of improving quality of care and containing costs in the Medicare program, the Centers for Medicare and Medicaid Services (CMS) has reimbursed Medicare Advantage (MA) plans with a capitated amount per beneficiary. CMS uses the Hierarchical Condition Categories (HCC) risk adjustment to reflect each beneficiary’s health status and more accurately estimate capitated payments to Medicare Advantage (MA) plans. However, it is debated whether the HCC model has been effective in reducing risk selection or if it has led to strategic evolutions of risk selection. This research intends to understand the intended and unintended consequences of the HCC model on the MA plans’ risk selection behaviors and propose alternative risk adjustment models from the perspectives of statistics and economics, respectively.
dc.embargo.lift2019-07-31T21:14:00Z
dc.embargo.termsRestrict to UW for 1 year -- then make Open Access
dc.format.mimetypeapplication/pdf
dc.identifier.otherPark_washington_0250E_18822.pdf
dc.identifier.urihttp://hdl.handle.net/1773/42388
dc.language.isoen_US
dc.rightsnone
dc.subjectIncentive
dc.subjectMachine learning
dc.subjectMedicare
dc.subjectMedicare Advantage
dc.subjectRisk adjustment
dc.subjectService-level selection
dc.subjectEconomics
dc.subjectBioinformatics
dc.subjectStatistics
dc.subject.otherHealth services
dc.titleUnderstanding Unintended Consequences of Risk Adjustment and Proposing Alternative Risk Adjustment
dc.typeThesis

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