Optimizing Medicare Part D Plan Choice by Beneficiaries with Schizophrenia

优化精神分裂症受益人的 Medicare D 部分计划选择

• 批准号: 8635037
• 负责人: Yuting Zhang
• 金额: $ 18.79万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-12-01 至 2015-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8635037
• 关键词: Algorithms; Antipsychotic Agents; Caring; Computer software; Cost Sharing; Data; Drug Prescriptions; Enrollment; Formularies; General Population; Government; Hospitalization; Low income; Marketing; Medical; Medicare; Mental disorders; Methods; Outcome; Patients; Pharmaceutical Preparations; Pharmacy facility; Prevalence; Psyche structure; Qualifying; Randomized; Savings; Schizophrenia; Simulate; Utilization Review; Wit; base; beneficiary; copayment; cost; improved; prevent; prior authorization; programs; public health relevance; residence

Potential Savings from Optimized Plan Choice in Medicare Beneficiaries with Schizophrenia Abstract The Medicare prescription drug benefit (Part D) relies on private market mechanisms to deliver care: a typical beneficiary can choose from between 45 and 57 private stand-alone Part D plans (PDP) in 2009, depending on his/her region of residence. It is known that beneficiaries do not choose plans based on their medication needs; and that the ability to choose plans is poorer among beneficiaries with mental disorders. The purpose of this study is to simulate personalized plan choice based on patient medication needs in schizophrenia and quantify potential improvement in patient drug coverage and potential savings to the government. Part D provides substantial premium and cost-sharing assistance to beneficiaries qualifying for the low-income subsidy (LIS) program. About 93% of PDP enrollees with schizophrenia received the LIS in 2007, whereas 40% of all PDP enrollees did. The majority of LIS enrollees are randomly assigned to PDP plans with premiums at or below the regional average. Random assignment does not assign enrollees to plans based on their medication needs and has caused severe problems including disruptions in plan coverage for 5.9 million between 2007 and 2010; and high beneficiary and government spending for those assigned to plans requiring high copayments. Our study will develop intelligent assignment algorithms based on beneficiaries' medication needs and dynamics of plan features in the Part D market. The algorithms can be easily implemented each year after an initial setup of software without substantial costs. The intelligent assignment method can be used by the government to assign/reassign beneficiaries or provide personalized assistance to help beneficiaries with schizophrenia to choose plans. The intelligent assignment method has the potential to substantially reduce government spending while improving patient outcomes.

患有精神分裂症的医疗保险受益人从优化计划选择中获得的潜在储蓄 摘要 医疗保险处方药福利（D部分）依赖于私人市场机制， 提供护理：一个典型的受益人可以从45至57个私人独立D部分中选择 2009年，根据他/她的居住地区，他/她将参加PDP计划。据了解，受益人 不根据他们的药物需求选择计划;选择计划的能力较差 有精神障碍的受益人。本研究的目的是模拟 基于精神分裂症患者用药需求的个性化方案选择和量化 潜在的改善病人的药物覆盖面和潜在的节省政府。 D部分向符合条件的受益人提供大量保险费和费用分摊援助 低收入补贴（LIS）计划。约93%的PDP登记者患有精神分裂症 在2007年接受了LIS，而40%的PDP注册者接受了LIS。大多数LIS注册者是 随机分配到保费等于或低于区域平均水平的PDP计划。随机 分配不会根据他们的药物需求将登记者分配到计划中， 严重问题，包括2007年至2010年期间590万人的计划覆盖中断; 高受益人和政府支出的那些分配到计划需要高 共付额 我们的研究将开发基于受益人的智能分配算法 D部分市场的药物需求和计划功能的动态。算法可以是 每年在软件初始设置后轻松实施，无需大量成本。的 政府可使用智能分配方法分配/重新分配受益人 或提供个人化协助，协助精神分裂症受益人选择计划。的 智能分配方法有可能大大减少政府开支 同时改善患者的预后。