Improving the Quality of Addiction Treatment Quality Measurement

描述（由申请人提供）： 背景和对VA患者护理的预期影响：我们最近完成的HSR& D资助的研究（IIR 07-092-1）揭示了退伍军人健康管理局（VHA）和健康计划雇主数据和信息集（HEDIS）成瘾治疗质量措施的有效性存在三个严重问题：首先，既定过程质量措施和结果之间的假定关联很弱或不存在。其次，VHA和HEDIS用于识别医疗记录中的医疗保健接触的基本策略的有效性通常很差，并且因环境和设施而异。第三，目前 所使用的成瘾治疗质量测量仅集中在过程上并且没有充分地捕获其他重要的质量领域（例如，结构、访问、患者体验和结果）。所有VHA利益相关者都受益于有效的医疗质量措施的存在和正确使用。鉴于现在认识到需要改进和扩大与成瘾有关的质量衡量，拟议的研究有以下目标。目标1.评估目前提出的成瘾治疗质量和结果（预测有效性）的高调措施之间的关联：预测有效性是指 访问或过程质量测量与后续患者结局之间的关联。我们确定了三个来源的41个新开发的，但未经验证的，成瘾治疗质量的措施：18 VA Unform心理健康服务手册，18从最近完成的国会授权的兰德/Altarum评估VA心理健康服务;和5个新开发的指标从华盛顿圈政策组。我们的目的是评估这些措施和结果之间的关联，在四个样本的患者，我们已经存在的结果数据。目标2.检查同期测量的质量指标之间的关联，并调查基础护理识别策略的有效性（并发有效性）。Donabedian认为，质量指标应与基础结构的其他同期测量指标相关联。如果理论上相互联系的质量指标之间的关联很强，这就证明评估方法很强，随后的推论是有效的。相反，如果指标之间的预期关系很弱，则表明质量或计量模式存在问题。因此，我们将评估同时测量的，理论上联系的质量措施之间的关联。同时有效性的另一个方面是质量度量规范在多大程度上准确地识别了可用数据中的目标过程和患者（称为规范策略）。我们之前的HSR& D资助的研究发现，在VHA连续性护理措施（基于VHA诊所停止代码）和2006年版本的HEDIS启动和参与措施（基于诊断/CPT代码组合）中使用的规范策略中存在几个问题。我们建议进行一个类似的验证研究，大大不同的2010年HEDIS规格策略，以及规格策略中使用的新的OMHS指标。第二目标1。评估可能影响预测或并发有效性的诊断和设置因素的影响。考虑到我们的团队和其他人发现，护理模式和结果之间的关系因诊断和设置因素而异，我们将评估这些潜在的调节因子，这些调节因子对目标1和目标2中检查的预测有效性和并发有效性有影响。第二目标2评价将联合收割机经验证的质量检验结果结合成具有临床和操作意义的信息的方法。我们建议探索各种手段相结合的质量指标到复合措施，然后评估这些复合材料与结果的关联。

DESCRIPTION (provided by applicant): Background and Anticipated Impacts on VA Patient Care: Our recently completed HSR&D-funded research (IIR 07-092-1) revealed three serious problems with the validity of Veterans Health Administration (VHA) and Health Plan Employer Data and Information Set (HEDIS) measures of addiction treatment quality: First, the presumed associations between established process quality measures and outcomes are weak or non-existent. Second, the validity of underlying strategies used at VHA and HEDIS for identifying health care encounters in the medical record is generally poor and varies substantially by setting and facility. Third, currently utilized addiction treatment quality measures focus exclusively on process and do not adequately capture other important domains of quality (e.g., structure, access, patient experiences, and outcomes). All VHA stakeholders benefit from the existence and proper use of valid healthcare quality measures. In light of the now recognized need to improve and expand addiction-related quality measurement, the proposed study has the following objectives. Aim 1. Evaluate the Associations between Currently Proposed, High-Profile Measures of Addiction Treatment Quality and Outcomes (predictive validity): Predictive validity refers to the strength of association between access or process quality measures and subsequent patient outcomes. We identified three sources of 41 newly developed, but unvalidated, addiction treatment quality measures: 18 VA Unform Mental Health Services Handbook Metrics, 18 from the recently completed congressionally-mandated RAND/Altarum evaluation of VA mental health services; and 5 newly developed metrics from the Washington Circle policy group. Our aim is to evaluate the associations between these measures and outcomes, in four samples of patients for whom we have pre-existing outcome data. Aim 2. Examine the Associations Among Contemporaneously Measured Quality Indictors and Investigate the Validity of Underlying Care Identification Strategies (Concurrent Validity). According to Donabedian, quality indicators should be associated to other contemporaneously measured indicators of the underlying construct. If the association between theoretically linked quality indicators is strong, this is evidence that the method of assessment is strong and the subsequent inferences are valid. Conversely if the expected relationships between indicators are weak, this suggests problems with the quality or measurement model. Therefore, we will assess the associations between contemporaneously measured, theoretically linked quality measures. Another aspect of concurrent validity is the extent to which quality measure specifications accurately identify the targeted processes and patients in available data (termed specification strategy). Our previous HSR&D-funded research found several problems in the specification strategies used in both the VHA Continuity of Care measure (based on VHA clinic stop codes), and the 2006 version of HEDIS Initiation and Engagement measures (based on diagnosis/CPT code combinations). We propose to conduct a similar validation study of the substantially different 2010 HEDIS specification strategy, as well as specification strategies used in the new OMHS metrics. Secondary Aim1. Evaluate the Impact of Diagnostic and Setting Factors that May Moderate Predictive or Concurrent Validity. Given the finding by our team and others that relationships between patterns of care and outcomes vary by diagnostic and setting factors, we will evaluate these potential moderators of the predictive and concurrent validity examined in Aims 1 and 2. Secondary Aim 2. Evaluate Methods to Combine Validated Quality Metrics into Information that is Clinically and Operationally Meaningful. We propose to explore various means of combining the quality metrics into composite measures, and then evaluate the association of these composites with outcomes.