Use of intelligent assignment to Medicare Part D plans for people with schizophrenia could produce substantial savings.
Medicare insures about half of the people in the United States diagnosed with schizophrenia. More than 90 percent of these beneficiaries are eligible for a low-income subsidy for their Part D prescription drug benefit, and the great majority of them are randomly assigned to a stand-alone drug plan. We simulated savings from replacing random assignment with an "intelligent assignment" algorithm that would assign beneficiaries to the least expensive plan in 2010 based on their drug usage in the previous year. Doing so generated projected annual drug savings of $379 per dual-eligible (those enrolled in both Medicaid and Medicare) beneficiary with a low-income subsidy; $404 per non-dual eligible with the subsidy; and $604 per beneficiary for those without the subsidy who chose their own plans. This translates into savings of $466 per beneficiary with schizophrenia. Intelligent assignment could have saved about $150 million for Medicare and beneficiaries with schizophrenia combined in 2010. We recommend that Medicare use intelligent assignment as the default approach for all beneficiaries with schizophrenia who receive a low-income subsidy, and consider it as an option for all Part D beneficiaries, regardless of their income.
Yuting Zhang (ytzhang@pitt.edu) is an associate professor of health economics and director of the Pharmaceutical Economics Research Group, both in the Department of Health Policy and Management, at the University of Pittsburgh, in Pennsylvania. She is serving as an unpaid consulting adviser to the Centers for Medicare and Medicaid Services, from December 2014 through November 2015.
Yuting
Y
Zhang
Seo Hyon Baik is a statistician in the Pharmaceutical Economics Research Group, Department of Health Policy and Management, University of Pittsburgh.
Seo Hyon
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Baik
Joseph P. Newhouse is the John D. MacArthur Professor of Health Policy and Management, Division of Health Policy Research and Education, at Harvard University, in Cambridge, Massachusetts.
Joseph P
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Newhouse
D000328:Adult; D000368:Aged; D017046:Cost Savings; D003430:Cross-Sectional Studies; D003657:Decision Making; D016527:Drug Costs / Q000706:statistics & numerical data*; D011307:Drug Prescriptions / Q000191:economics* / Q000706:statistics & numerical data; D004608:Eligibility Determination / Q000379:methods; D005260:Female; D062265:Health Insurance Exchanges; D006801:Humans; D008297:Male; D054524:Medicare Part D / Q000191:economics* / Q000706:statistics & numerical data; D008875:Middle Aged; D010342:Patient Acceptance of Health Care / Q000706:statistics & numerical data; D012559:Schizophrenia / Q000175:diagnosis / Q000188:drug therapy* / Q000191:economics; D014481:United States
Medicare; Pharmaceuticals