Equity and Economic Effects of MTM Services

与药物有关的发病率和死亡率每年花费美国超过1774亿美元， 在老年人中，为了改善药物治疗结果并降低成本， 医疗保险和医疗补助服务（CMS）建立了药物管理治疗（MTM）计划，作为 2006年，医疗保险处方药福利（D部分）。不幸的是，MTM入学率低于CMS 目标主要是由于MTM程序设计中的问题。此外，根据我们之前的政策情景分析， 主要由NIA R 01支持，MTM资格标准可能对种族/少数民族过于限制， 可能会使健康结果中的种族/民族差异永久化，因为MTM资格是基于使用 CMS试图放宽MTM资格门槛，引用我们的 研究，但潜在的差距仍然与使用为基础的资格标准。一个关键的障碍， 有效的MTM改革是缺乏关于MTM对少数民族的实际影响的更强有力的信息 结果，少数民族对MTM的利用，以及MTM的成本效益。我们将填补这一知识空白 通过我们提出的研究与最新可用的MTM数据。我们的长期目标是改善 通过提高药物利用率和减少种族/族裔歧视， 药物使用和健康结果的差异。我们将分析Medicare Part A/B/D数据（2015- （2016），与健康资源档案相关联。我们的预期结果包括新的信息：（1）影响 关于药物利用、卫生服务利用/费用和死亡率方面种族/民族差异的MTM; (2)MTM利用率的度量，例如表现出差异模式的MTM交付方法;以及（3）成本- 从医疗保险和卫生系统的角度来看MTM的有效性。我们将测量药物 使用基于证据的他汀类药物处方和主要由药房开发的其他措施 质量联盟，并采用了星星评级，一个健康计划的质量评估系统与CMS奖金挂钩 D部分计划的付款。服务的利用/费用包括看医生、看急诊、 和住院治疗（例如，源自门诊护理敏感状况的住院治疗）。我们将应用 多元回归模型、差异中的差异策略和负效益回归模型 使用频率论和贝叶斯方法。目标1：检验MTM计划减少了 在药物利用质量、保健服务利用和费用方面的种族/民族差异。目标2：测试 假设非西班牙裔黑人和西班牙裔人比白人接受更少和延迟的MTM服务。 目标3：检验MTM是一个具有成本效益的计划的假设。影响：我们的结果将提供很多- 需要经验证据来指导CMS的MTM决策，并协助NIA/NIH实现其战略目标 为“政策决定”提供信息和“了解健康差距并制定战略， 不同人群中老年人的健康状况。”

Drug-related morbidity and mortality cost the United States over $177.4 billion annually and are especially daunting among the elderly. To improve pharmacotherapy outcomes and reduce costs, the Centers for Medicare & Medicaid Services (CMS) established medication management therapy (MTM) programs as part of the Medicare prescription drug benefits (Part D) in 2006. Unfortunately, MTM enrollment has fallen below CMS targets mainly due to issues in MTM program design. Further, based on our previous policy scenario analysis, primarily supported by an NIA R01, MTM eligibility criteria may be too restrictive for racial/ethnic minorities and may perpetuate racial/ethnic disparities in health outcomes, because MTM eligibility is based on utilization of medications, which minorities tend to use less. CMS attempted to relax MTM eligibility thresholds, citing our research, but potential disparities remain with the utilization-based eligibility criteria. A critical barrier to effective MTM reform is the lack of stronger information about the actual effects of MTM on minorities' outcomes, utilization of MTM by minorities, and the cost-effectiveness of MTM. We will fill this knowledge gap through our proposed research with newly available MTM data. Our long-term goal is to improve the health status of older adults among diverse populations by improving medication utilization and reducing racial/ethnic disparities in medication utilization and health outcomes. We will analyze Medicare Parts A/B/D data (2015- 2016), linked to Area Health Resources Files. Our expected outcomes include new information on: (1) effects of MTM on racial/ethnic disparities in medication utilization, utilization/costs of health services, and mortality; (2) measures of MTM utilization, such as MTM delivery methods, that exhibit disparity patterns; and (3) cost- effectiveness of MTM from the perspectives of Medicare and health system. We will measure medication utilization using evidence-based statin prescribing and other measures primarily developed by Pharmacy Quality Alliance and adopted by Star Ratings, a health-plan-quality evaluation system tied to CMS bonus payments to Part D plans. Utilization/costs of services include those of physician visits, emergency room visits, and hospitalizations (e.g., hospitalizations originating from ambulatory care sensitive conditions). We will apply multivariate regression models, a difference-in-difference strategy and negative benefit regression models using frequentist and Bayesian approaches. Aim 1: Test the hypothesis that MTM programs have reduced racial/ethnic disparities in quality of medication utilization, and health services utilization and costs. Aim 2: Test the hypothesis that non-Hispanic Blacks and Hispanics receive fewer and delayed MTM services than Whites. Aim 3: Test the hypothesis that MTM is a cost-effective program. Impact: Our results will provide much- needed empirical evidence to guide MTM policy-making by CMS, and assist the NIA/NIH in its strategic goals of informing “policy decisions” and “understand(ing) health disparities and develop(ing) strategies to improve the health status of older adults in diverse populations.”