Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts (S.S., S.V.W.).
Aetion, New York, New York (J.A.R., W.M.).
Ann Intern Med. 2019 Mar 19;170(6):398-406. doi: 10.7326/M18-3079. Epub 2019 Mar 12.
Pharmacoepidemiologic and pharmacoeconomic analysis of health care databases has become a vital source of evidence to support health care decision making and efficient management of health care organizations. However, decision makers often consider studies done in nonrandomized health care databases more difficult to review than randomized trials because many design choices need to be considered. This is perceived as an important barrier to decision making about the effectiveness and safety of medical products. Design flaws in longitudinal database studies are avoidable but can be unintentionally obscured in the convoluted prose of methods sections, which often lack specificity. We propose a simple framework of graphical representation that visualizes study design implementations in a comprehensive, unambiguous, and intuitive way; contains a level of detail that enables reproduction of key study design variables; and uses standardized structure and terminology to simplify review and communication to a broad audience of decision makers. Visualization of design details will make database studies more reproducible, quicker to review, and easier to communicate to a broad audience of decision makers.
药物流行病学和药物经济学分析的医疗保健数据库已成为一个重要的证据来源,以支持医疗保健决策和有效的医疗保健组织管理。然而,决策者往往认为在非随机医疗保健数据库中进行的研究比随机试验更难审查,因为需要考虑许多设计选择。这被认为是对医疗产品有效性和安全性决策的一个重要障碍。纵向数据库研究中的设计缺陷是可以避免的,但在方法部分复杂的散文中可能会无意中被掩盖,方法部分往往缺乏具体性。我们提出了一个简单的图形表示框架,以全面、明确和直观的方式可视化研究设计的实施;包含可再现关键研究设计变量的详细程度;并使用标准化的结构和术语来简化对广泛决策者群体的审查和沟通。设计细节的可视化将使数据库研究更具可重复性,审查速度更快,更容易向广泛的决策者群体进行沟通。