Unpacking Disparities in Opioid Use Disorder Treatment Quality

项目摘要 据估计，目前有超过200万人患有阿片类药物使用障碍（OUD）。美国的医疗保健系统 努力应对这一挑战，因为对OUD治疗的需求远远超过合格临床医生的供应 谁可以开处方和监测阿片类药物使用障碍（MOUD）的药物。MOUD有效减少 过量死亡和改善的结果，但远远没有得到充分利用，只有25-40%的成人OUD 接收MOUD。OUD的发生率在医疗补助计划的注册者中特别高，医疗补助计划是最大的 OUD治疗服务的付款人。研究表明，种族，民族，地理和年龄差异， 过量死亡率，阿片类药物使用和OUD的模式以及治疗模式。然而，很少有研究 采取更细致入微的方法来检查OUD护理的质量， 这可能会在种族、性别和年龄组等维度上复合，称为交叉性。 观察到的差异可能反映了现有治疗提供者的区域限制以及 诊断和治疗的上游途径（例如，过量用药后的护理，获得初级保健）。 使用来自北卡罗来纳州的实时医疗补助索赔数据，并辅以来自医疗保险和私人医疗保险的索赔数据， 保险（这些来源加起来占所有北卡罗来纳州居民的四分之三以上）将 使我们能够描述每个提供者跨支付方提供的OUD护理的质量。我们将研究 OUD护理质量的交叉状态的差异，并检查这些差异的关键驱动因素。我们的第一 目的是通过交叉状态评估OUD护理质量的差异。我们还将研究 其他慢性行为健康和医疗状况的存在缓解了OUD护理中的这些差异 质量是交叉的状态。我们的第二个目标是评估在多大程度上， 高质量的OUD护理的交叉状态是由于提供者的可用性差异， 按地理区域分列的高质量OUD治疗。最后，我们的第三个目标是比较差异， 在北卡罗来纳州过渡之前、期间和之后接受高质量OUD护理的交叉状态 其医疗补助计划将于2021年7月从按服务收费改为按人头收费。我们将使用国家医疗补助数据， 将北卡罗来纳州的OUD护理质量模式与整个国家进行比较。我们还将探索使用 电子健康记录数据，以提供OUD护理质量的替代评估， 临床医生记录、医嘱和实验室测试。通过交叉了解OUD护理质量的差异 地位以及造成和驱动这些差异的因素，对于实现公平、高质量的 医疗保健系统。我们的研究结果将指导旨在改善OUD护理参与的政策和实践， 对所有人的质量。

PROJECT SUMMARY Over 2 million people are now estimated to have an opioid use disorder (OUD). The U.S. health care system is struggling to meet this challenge, as the need for OUD treatment far exceeds the supply of qualified clinicians who can prescribe and monitor medications for opioid use disorder (MOUD). MOUD are effective at reducing overdose deaths and improving outcomes, but are vastly underused, with only 25-40% of adults with OUD receiving MOUD. Rates of OUD are particularly high among Medicaid enrollees, and Medicaid is the largest payor of OUD treatment services. Studies have demonstrated racial, ethnic, geographic, and age differences in overdose death rates, patterns of opioid drug use and OUD, and patterns of treatment. Yet, few studies have undertaken more nuanced approaches to examining the quality of OUD care that take into account differences that may compound across dimensions such as race, gender, and age groups, referred to as intersectionality. Observed disparities may reflect regional limitations in available treatment providers as well as differences in upstream pathways to diagnosis and treatment (e.g., care after an overdose, access to primary care). Using real-time Medicaid claims data from North Carolina, supplemented by claims from Medicare and private insurance (with these sources together accounting for over three-quarters of all North Carolina residents) will allow us to characterize the quality of OUD care delivered by each provider across payers. We will examine differences in OUD care quality by intersectional status and examine key drivers of those differences. Our first aim is to assess differences in the quality of OUD care by intersectional status. We will also examine whether the presence of other chronic behavioral health and medical conditions moderate these disparities in OUD care quality by intersectional status. Our second aim is to assess the extent to which differences in the receipt of high-quality OUD care by intersectional status are due to differences in the availability of providers who provide high-quality OUD treatment, by geographic areas. Finally, our third aim is to compare differences by intersectional status in the receipt of high-quality OUD care before, during, and after North Carolina transitions its Medicaid program from fee-for-service to capitation in July 2021. We will use national Medicaid data to compare patterns of OUD care quality in North Carolina to the country as a whole. We will also explore the use of electronic health record data to provide an alternative assessment of OUD quality of care by examining clinician notes, orders, and lab tests. Understanding the differences in OUD care quality by intersectional status and the factors underlying and driving those differences is critical to attaining an equitable, high-quality health care system. Our results will guide policy and practice aimed at improving OUD care engagement and quality for all individuals.