Identifying Quality Indicators for Substance Use Disorders

描述（由申请人提供）：拟议的二级数据分析是创新研究议程的第一步，旨在开发由最强证据支持的相关和可行的QIs。制定相关、可行和有效的质量指标是一项关键的公共政策优先事项，没有什么地方比药物滥用治疗更需要质量措施。在615个国家质量论坛认可的标准中，只有一个是针对物质使用的。尽管两种类型的共病都很普遍，但没有对共病的MH和SA疾病（MCOD）或共病的身体健康和SA疾病（PCOD）进行测量。我们提出了一个二次数据分析，以确定潜在的质量指数的物质使用障碍（SUD）和M/P COD与最佳性能指标的特点。我们将使用我们的研究团队为退伍军人健康管理局的项目评估开发的独特数据集（由管理数据、患者调查和服务系统管理员调查的丰富组合组成）。该数据集包含通过研究人员，临床医生和政策制定者的合作努力创建的60多个QIs，以及有关指标可靠性和可行性的数据。虽然这60个候选QIs中的每一个都精心制定了规范，但在前瞻性队列研究中测试所有QIs的效率和成本都很低。这种二次分析将使我们能够筛选出最有希望和最可靠的候选指标，这些指标可以在后续研究中在更广泛的人群中进行严格测试。因此，这种二级数据分析是关键的第一步，将为在广泛的公共和私营服务系统中进行前瞻性验证研究奠定基础。我们还使用创新方法来开发复合质量指标，以表征所有SUD患者提供的护理质量，因为并非所有流程都适用于所有患者。 高质量的护理最好被描述为许多单独过程的总和。我们的具体目标是：目标1：评价个体QIs与SUD个体结局之间的相关性，并确定具有最佳表现指标特征的QIs。目标2：评价M/P COD患者的个体QIs与结局之间的相关性，并确定具有最佳表现指标特征的QIs。目标3：使用复合QI表征向患者提供的所有MH/SA治疗的质量，并评价其与结局的相关性。据我们所知，这种二次数据分析是第一次提出对60多个QIs的过程结果链接进行全面分析，以确定具有最强指标属性的最有希望的候选QIs。这是创新研究议程的第一步，以最强有力的证据支持开发相关和可行的QIs。

DESCRIPTION (provided by applicant): The proposed secondary data analysis is the first step in an innovative research agenda to develop relevant and feasible QIs supported by the strongest level of evidence. Developing relevant, feasible and valid QIs is a key public policy priority, and nowhere is the need for quality measures greater than in substance abuse treatment. Of the 615 National Quality Forum endorsed standards, only one is specific to substance use. There are no measures for co-occurring MH&SA disorders (MCOD) or co-occurring physical health and SA disorders (PCOD), despite the prevalence of both types of co-morbidity. We propose a secondary data analysis to identify potential QIs for substance use disorders (SUDs) and M/P CODs with the best-performing indicator characteristics. We will use a unique data set (consisting of a rich combination of administrative data, patient surveys, and surveys of service system administrators) developed for the Program Evaluation of the Veterans Health Administration by our research team. This data set contains over 60 QIs created through a collaborative effort of researchers, clinicians, and policy makers, as well as data on indicator reliability and feasibility. While each of these 60 candidate QIs has carefully developed specifications, it would be inefficient and costly to test all of them in a prospective cohort stud. This secondary analysis will allow us to winnow down the set of possible measures to the most promising and robust candidates that can be rigorously tested on a broader population in subsequent studies. Therefore, this secondary data analysis represents a critical first step, which will provide a foundation for a prospective validation study in a broad range of public and private service systems. We also use innovative methods to develop composite QIs to characterize the quality of all care provided patients with SUDs, as not all processes apply to all patients, and high-quality care is best described as the sum of many individual processes. Our specific aims are: Aim 1:. To evaluate the association between individual QIs and outcomes for individuals with SUDs and to identify the QIs with the best-performing indicator characteristics. Aim 2:. To evaluate the association between individual QIs and outcomes for individuals with M/P CODs and to identify QIs with the best- performing indicator characteristics. Aim 3:. To characterize the quality of all MH/SA treatment provided to patients using a composite QI and to evaluate its association with outcomes. To our knowledge, this secondary data analysis is the first to propose a comprehensive analysis of process outcome links for over 60 QIs across a broad range of outcomes in order to identify the most promising candidate QIs with the strongest indicator properties. It is the first step in an innovative research agenda to develop relevant and feasible QIs supported by the strongest level of evidence.