Identifying Quality Indicators for Substance Use Disorders

确定药物使用障碍的质量指标

• 批准号: 8519401
• 负责人: Teresa Jo Hudson
• 金额: $ 22.09万
• 依托单位: UNIV OF ARKANSAS FOR MED SCIS
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-08-01 至 2015-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8519401
• 关键词: Accountability; Accreditation; Administrator; Alcohol or Other Drugs use; Caring; Characteristics; Cohort Studies; Comorbidity; Consensus; Data; Data Analyses; Data Set; Development; Disease; Effectiveness; Ensure; Face; Foundations; Future; Guidelines; Health Policy; Individual; Institute of Medicine (U.S.); Level of Evidence; Link; Literature; Maps; Measures; Mental Health; Methods; Outcome; Patients; Performance; Policy Maker; Population; Practice Guidelines; Prevalence; Process; Process Measure; Program Evaluation; Property; Provider; Public Health; Public Policy; Quality Indicator; Quality of Care; Research; Research Personnel; Resources; Services; Substance Use Disorder; Substance abuse problem; Sum; Surveys; System; Testing; To specify; Treatment outcome; United States; United States Substance Abuse and Mental Health Services Administration; Veterans; Washington; base; behavioral health; cohort; effective therapy; financial incentive; health administration; improved; innovation; physical conditioning; prospective; public health relevance; substance abuse treatment; validation studies

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.

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，以发展最强的证据支持相关且可行的QIS。开发相关，可行和有效的质量质量是关键的公共政策优先事项，在任何地方都不需要大于药物滥用治疗。在615个国家质量论坛认可标准中，只有一个特定于物质使用。尽管这两种类型的合并症患病率都普遍存在，但仍未采取共同发生的MH＆SA疾病（MCOD）或同时发生的身体健康和SA疾病（PCOD）的措施。我们提出了一个二级数​​据分析，以确定具有最佳表现指标特征的物质使用障碍（SUD）和M/P COD的潜在QI。我们将使用我们的研究团队对退伍军人卫生管理局的计划评估，使用独特的数据集（包括管理数据的丰富组合，患者调查和服务系统管理员的调查）。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以及有关指标可靠性和可行性的数据创建的60多个QI。尽管这60个候选QIS中的每一个都经过精心制定的规格，但在预期的队列中测试所有这些QIS效率低下且昂贵。这种二次分析将使我们能够将一系列可能的措施归结为最有前途和强大的候选人，这些候选者可以在随后的研究中对更广泛的人群进行严格测试。因此，该二次数据分析代表了关键的第一步，这将为广泛的公共和私人服务系统中的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质量质量质量质量 患者和高质量护理最好被描述为许多个人过程的总和。我们的具体目的是：目标1：。评估SUDS个体的个体QIS和结果之间的关联，并以表现最佳的指标特征识别QI。目标2：。评估具有M/P COD的个体的单个QIS和结果之间的关联，并识别具有最佳性能指标特征的QI。目标3：。为了表征使用复合质量质量质量为患者提供的所有MH/SA治疗的质量，并评估其与结果的关联。据我们所知，该二级数据分析是第一个在广泛的结果中对60多种QI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。这是创新研究议程中发展相关且可行的QIS的第一步，并得到了最强的证据支持。