Integrating Medicare and Medicaid coverage in managed care: effects on quality, utilization, and disparities

项目总结/摘要 政策制定者正在寻求战略，以整合覆盖双重杀手-个人与医疗保险和 医疗补助-更好地协调这些计划的护理。双重合格特殊需求计划（D-SNPs） 专门服务于双胞胎的医疗保险优势计划已经成为最大的计划类别 作为一个整合的平台。然而，D-SNP在其整合水平上与 医疗补助。虽然许多D-SNP仅满足最低水平的整合（主要与护理相关）， 协调），越来越多的计划通过覆盖Medicare和Medicaid实现了更大的整合 为同样的病人花钱。CMS继续完善D-SNP和决策者的整合标准 呼吁制定这些标准，以提高对双a型患者的护理质量、效率和公平性。 考虑到这一人群的医疗和社会脆弱性，然而，几乎没有证据表明， D-SNPs之间的差异，包括影响融合的计划属性和国家政策，与 质量、驱动支出的护理模式或差异。此外，没有证据表明政策杠杆 扩大D-SNPs综合治疗的注册人数。其中一个杠杆就是默认注册--一种机制 允许某些医疗补助管理式医疗计划自动将医疗补助受益人纳入综合医疗保险计划， 当D-SNP成为双杀伤时（例如，65岁）。虽然只有一些D-SNP被允许使用 默认注册，有兴趣扩大这一机制。为了宣传政策，该项目将提供新的 关于D-SNPs性能变化的证据，包括影响这些计划水平的因素， 医疗补助整合（目标1）;评估计划绩效和弱势亚组的差异， 包括黑人和西班牙裔美国人、残疾人和有行为健康问题的人（目标2）; 并研究使用默认注册来整合覆盖范围的效果， 计划允许使用这种机制和准实验差异设计（目标3）。到 衡量与整合相关的计划绩效的关键方面，我们将使用Medicaid T-MSIS数据、Medicare 优势就诊数据和护理设施评估数据在受益人层面上相关联（目标1-3）， CAHPS患者体验调查（目标1-2）。这些数据的不断更新使我们能够监测 在新的D-SNP集成标准中，CMS阶段的性能变化，使我们能够评估和 为不断发展的政策提供信息。这一项目通过其与人权问题咨询委员会的优先事项和优先人口直接相关的活动， 重点关注D-SNPs的设计-一种新兴的复杂患者管理式护理模式-如何影响质量， 效率和公平的照顾。为了最大限度地发挥这一项目的影响，我们将与政策咨询委员会合作， 来自政府、研究和保险部门的融合政策专家， 将卫生服务研究转化为政策信息的记录。

PROJECT SUMMARY / ABSTRACT Policymakers are pursuing strategies to integrate coverage for dual-eligibles—individuals with Medicare and Medicaid—to better coordinate care across these programs. Dual-Eligible Special Needs Plans (D-SNPs)— Medicare Advantage plans that exclusively serve duals—have emerged as the largest category of plans intended to serve as a platform for integration. However, D-SNPs vary in their level of integration with Medicaid. While many D-SNPs meet only a minimum level of integration (primarily related to care coordination), a growing number of plans have attained greater integration by covering Medicare and Medicaid spending for the same patients. CMS continues to refine integration standards for D-SNPs and policymakers have called for designing these standards to improve the quality, efficiency, and equity of care for duals—a priority given this population’s medical and social vulnerability. Yet little evidence exists about the extent to which differences among D-SNPs, including plan attributes and state policies affecting integration, are linked to quality, care patterns that drive spending, or disparities. Further, there is no evidence about how policy levers to expand enrollment in integrated D-SNPs affect care. One such lever is default enrollment—a mechanism that allows certain Medicaid managed care plans to automatically enroll Medicaid beneficiaries into integrated D-SNPs when they become dual eligibles (e.g., at age 65). Although only some D-SNPs are permitted to use default enrollment, there is interest in expanding this mechanism. To inform policy, this project will provide new evidence about variations in the performance of D-SNPs, including by factors affecting these plans’ level of Medicaid integration (Aim 1); assess plan performance and disparities in vulnerable subgroups of duals, including Black and Hispanic duals, duals with a disability, and those with behavioral health conditions (Aim 2); and investigate the effects of using default enrollment to integrate coverage, leveraging variation between plans permitted to use this mechanism and a quasi-experimental difference-in-differences design (Aim 3). To measure key aspects of plan performance relevant to integration, we will use Medicaid T-MSIS data, Medicare Advantage encounter data, and nursing facility assessment data linked at the beneficiary level (Aims 1-3) and CAHPS patient experience surveys (Aims 1-2). Continuous updating of these data allows us to monitor changes in performance as CMS phases in new D-SNP integration standards, enabling us to evaluate and inform evolving policy. This project is directly related to AHRQ priorities and priority populations through its focus on how the design of D-SNPs—an emerging managed care model for complex patients—affects quality, efficiency, and equity of care. To maximize this project’s impact, we will work with a Policy Advisory Committee of experts in integration policy from the government, research, and insurance sectors, building on the team’s track record of translating health services research to inform policy.