Improving the treatment cascade of MAT initiation and retention for opioid use disorder

项目概述：高质量的证据支持药物辅助治疗(MAT)作为第一线 阿片使用障碍(OUD)的治疗，特别是丁丙诺啡或 作为美沙酮的长期维护至少一年。然而，患者辍学(通常在6个月时为50%)， 提供者的耐药性仍然是有效治疗的主要障碍。到目前为止，很少有研究检查 影响治疗开始、稳定和长期保留的关键步骤的患者特征 丁丙诺啡。大多数已发表的研究只评估了2-3个月积极治疗的结果 临床试验中选定的患者。我将借鉴以下有影响力的、连续的“级联护理”框架 艾滋病毒/艾滋病领域作为确定丁丙诺啡持续治疗阶段特定障碍的概念模型 通过适应的OUD治疗级联进行治疗。更好地了解每个序列中的障碍 级联的阶段包括1)丁丙诺啡的启动，2)阿片类药物使用的稳定，以及3)保留 长期的治疗反应，可能有助于临床努力改善结果和死亡率。 在医疗改革和医疗补助计划的重新设计下，越来越多的患者获得保险 药物滥用治疗的报销。我建议将电子健康记录中的临床数据联系起来 (EHR)保险索赔数据，以评估促进级联护理连续性的患者因素。 这一战略将获取关键信息(急诊就诊、诊断、治疗服务、死亡率)，这些信息包括 在一个特定的临床地点的记录之外。保险索赔数据的优势是提供了近乎完整的 不依赖自我报告并反映现实世界临床复杂性的随访和客观结果。 为了实现这些目标，实现我长期发展的培训目标 在定量方法、流行病学、管理和推理分析方面的专业知识 观察性数据集，我阐明了五个连续的培训目标：1)流行病学和统计数据 分析方法2)服务研究、方案评估和模型设计3)保险索赔数据 分析4)用观测数据进行推理的方法，5)授权书的撰写和管理。为了实现我的 研究目标，我将整合来自一家大容量、多站点垫子提供商的电子记录，该公司已经开始 自2009年以来，有18,000名患者服用丁丙诺啡，并经常进行内部尿液药物检测。这项研究将 确定与丁丙诺啡成功启动、稳定和保留相关的患者特征 并将在治疗级联的每个阶段建立障碍模型。通过这些发现，我还试图评估 通过模拟每个阶段的治疗效果和改善程度之间的关系来评估每个阶段的临床实用性 临床结果。这些结果将基于一个大的、高度概括的、以社区为基础的样本 将评估长期服用MAT的临床后果 维护并帮助指导质量改进计划。

Project Summary: High quality evidence supports medication assisted treatment (MAT) as the first line treatment for opioid use disorder (OUD), especially opioid substitution therapy with buprenorphine or methadone as long-term maintenance of at least one year. Yet patient dropout (typically >50% at six months), and provider resistance remain major impediments to effective treatment. To date, few studies have examined patient characteristics that influence key steps in treatment initiation, stabilization, and long-term retention with buprenorphine. Most published studies assess outcomes for only 2-3 months of active treatment among highly selected patients in clinical trials. I will draw from the influential, sequential “cascade of care” framework from the HIV/AIDS field as a conceptual model to identify stage-specific barriers to continuity of buprenorphine treatment through an adapted OUD treatment cascade. A greater understanding of barriers at each sequential stage of the cascade including 1) initiation of buprenorphine, 2) stabilization of opioid use, and 3) retention with long-term treatment response, may inform clinical efforts to improve outcomes and mortality. Under healthcare reform and Medicaid redesign, increasing numbers of patients receive insurance reimbursement for substance abuse treatment. I propose to link clinical data from electronic health records (EHR) to insurance claims data to assess patient factors that promote continuity of care along the cascade. This strategy will capture critical information (ED visits, diagnoses, treatment services, mortality) that are outside of a given clinical site's records. Insurance claims data have the advantage of providing near complete follow up and objective outcomes that do not rely on self-report and reflect real-world clinical complexities. In order to accomplish these goals and achieve my long-term training objectives of developing expertise in quantitative methods, epidemiology, and the management and inferential analysis of large observational data sets, I have articulated five sequential training goals: 1) epidemiologic and statistical data analysis methods 2) services research, program evaluation, and model design 3) insurance claims data analysis 4) inferential methods with observational data, and 5) grant writing and administration. To fulfill my research aims, I will incorporate electronic records from a high-volume, multi-site MAT provider that has started 18,000 patients on buprenorphine since 2009 with frequent in-house urine drug testing. The research will identify patient characteristics associated with successful buprenorphine initiation, stabilization, and retention and will model barriers at each stage of the treatment cascade. With these findings, I also seek to evaluate the clinical utility of each stage by modeling associations between attaining each stage of treatment and improved clinical outcomes. The results, which will be based on a large, highly generalizable, community-based sample of adults with OUD presenting for treatment, will evaluate the clinical consequences of long-term MAT maintenance and help guide quality improvement initiatives.