Feasibility of Using Qualitative Analysis for Systematic Reviews of Complex Inter

描述（由申请人提供）：本研究的目的是确定在复杂健康干预措施的系统评价中使用定性比较分析（QCA）的可行性，通过识别与有效性相关的关键干预特征来丰富评价结果。系统评价是循证卫生保健的基础，也是临床指南、质量措施和卫生政策的基础。然而，由于在纳入的研究中经常存在很大程度的临床和方法异质性，因此对复杂干预措施的评价具有挑战性。审查研究者需要新的方法来补充现有的复杂干预措施的审查方法。我们希望QCA能够用于分析研究水平的协变量，以更好地探索异质性，并且由于其作为研究复杂现象的方法的起源，可能比现有方法具有优势。QCA是一种基于自变量和因变量之间的集合论因果关系（即集、超集和子集）的面向实例的非概率技术。它具有定量方法和定性方法的共同特点，并通过使用布尔代数的逻辑最小化过程产生结果。我们将把QCA应用于已经完成的卫生保健研究和质量资助的干预措施的比较有效性审查，以改善药物依从性。这篇综述是一篇复杂的干预综述，因为它包括了多种干预目标和药物、不同的干预成分、不同的干预时间和强度的研究。提出的研究是QCA首次应用于系统评价。具体目标是：(1)使用QCA来确定哪些干预特征单独或组合与改善慢性病长期药物治疗的门诊患者的药物依从性有关，以及(2)描述我们在干预措施的系统回顾背景下应用QCA以增加药物依从性的过程。我们将把药物依从性评价中的每一项纳入的研究作为一个分析单元，并将使用QCA来评估研究协变量与治疗效果的关系。在这种情况下，我们将用集合论的必要性和充分性陈述来表达我们的发现。例如，“改善药物依从性的复杂健康干预措施需要成分X和成分A或D中的任何一个，或B和c的组合。”我们期望这项工作将确定在系统评价背景下使用质量认证的初步可行性。如果可行，质量评估将大大加强复杂干预措施的评估方法，因为它除了利用复杂健康干预审查中现有的异质性之外，还采用了一种根本不同的范式（使用集合关系）来评估因果关系。

DESCRIPTION (provided by applicant): The objective of this study is to determine the feasibility of using qualitative comparative analysis (QCA) within systematic reviews of complex health interventions to enrich review results through identification of key intervention features associated with effectiveness. Systematic reviews are the foundation for evidence- based health care, and form the basis for clinical guidelines, quality measures, and health policy. However, reviews of complex interventions are challenging because of the large degree of clinical and methodological heterogeneity that is often present among included studies. Review investigators need new methods to complement existing methods of review for complex interventions. We expect QCA to be used to analyze study-level covariates to better explore heterogeneity, and may offer an advantage over existing methods because of its origins as a method to study complex phenomena. QCA is a case-oriented, nonprobabilistic technique based on set-theoretic causal relationships (i.e., set, superset, and subset) between independent and dependent variables. It shares features of both quantitative and qualitative methods and produces results through a process of logical minimization using Boolean algebra. We will apply QCA to an already completed Agency for Healthcare Research and Quality-funded comparative effectiveness review of interventions to improve medication adherence. This review exemplifies a complex intervention review because it included studies with multiple intervention targets and agents, vastly different intervention components, and differences in duration and intensity of intervention. The proposed study is the first such application of QCA to systematic reviews. The specific aims are to (1) use QCA to determine which intervention features alone or in combination are related to improved medication adherence among outpatients who are prescribed long-term medication therapy for chronic conditions, and (2) describe our process for applying QCA within the context of the systematic review of interventions to increase medication adherence. We will treat each included study within the medication adherence review as a unit of analysis and will use QCA to evaluate study covariates for their relationship to the treatment effect. In this context, we would express our findings in set-theoretic statements of necessity and sufficiency. For example, "Complex health interventions to improve medication adherence require component X and either component A or D, or the combination of B and C." We expect that this work will determine the initial feasibility f using QCA within a systematic review context. If feasible, QCA will significantly enhance review methods for complex interventions because it applies a fundamentally different paradigm (the use of set relationships) for evaluating causal relationships in addition to taking advantage of existing heterogeneity within complex health intervention reviews.