The Impact of Medicaid Plans on Access to and Quality of SUD Treatment

项目摘要 医疗补助是美国最大的医疗保险部门，与最脆弱的个体，是最少的- 很好理解。关于州医疗补助计划的结构对获得的影响的研究很少， 护理模式和物质使用障碍（SUD）护理的结果。各州提供医疗补助福利， 通过公共管理的收费服务（FFS）系统或通过与私人医疗补助管理 护理（MMC）计划。尽管MMC被广泛采用，但其作用，特别是其效果， 关于SUD治疗和服务差异。很少有人知道SUD治疗之间的任何差异 传统的FFS Medicaid和私人MMC计划或不同类型的管理式医疗计划之间的差异 用不同的方法来治疗SUD。这项研究利用了创新的随机分配 解决医疗补助领域这一挑战的方法。在拟议的项目中，我们采用了一组精选的 评估SUD治疗的访问、护理模式和结局的指标，以描述 纽约的系统、健康计划和提供者团体。然后我们按种族/民族进行分层分析， 确定哪些方案和计划取得了更好的成果，并确定是否有服务 差距。我们的项目使用定性方法，通过深入访谈来帮助解释我们的结果， 提供对调查结果的解释的见解，并提出实践和政策变化的建议。

PROJECT SUMMARY Medicaid, the largest health insurance sector in the U.S., with the most vulnerable individuals, is the least- well understood. There is little research on the effects of the structure of state Medicaid programs on access, patterns of care and outcomes of substance use disorder (SUD) care. States provide Medicaid benefits either through publicly managed Fee-for-Service (FFS) systems or by contracting with private Medicaid Managed Care (MMC) plans. Despite widespread adoption of MMC, its role is not well-understood, especially its effects on SUD treatment and service disparities. Little is known about any differences in SUD treatment between traditional FFS Medicaid and private MMC plans or differences across different types of managed care plans with different approaches to SUD treatment. The proposed study makes use of innovative random assignment methods to address this challenge in the Medicaid sector. In the proposed project, we apply a select group of metrics for assessing access, patterns of care and outcomes of SUD treatment, to describe the performance of systems, health plans, and provider groups in New York. We then conduct stratified analysis by race/ethnicity, gender, and rurality to identify which programs and plans have better outcomes and identify if there are service disparities. Our project uses qualitative methods to help interpret our results through in-depth interviews, and to provide insight on the interpretation of findings and suggest practice and policy changes.