Kaiser Permanente Department of Research and Evaluation, Pasadena, CA.
Perm J. 2020;24. doi: 10.7812/TPP/18.308.
Retrospective medical record review is often used to answer the "why" questions that statistical modeling cannot. In addition to its utility as an explanatory tool, it can be used to generate hypotheses using available retrospective data and so is a convenient guide for developing future prospective studies. A recent review of articles that used the retrospective medical record review method listed 10 best practices that ought to be followed. However, an issue that is not listed is the use of sampling weights, which are important when one can only conduct retrospective medical record review for a sample of the target population. Although that review acknowledged the importance of carefully selecting a sampling strategy for such a scenario and indeed had outlined 3 commonly used sampling methods (convenience, simple random, and systematic), the authors say nothing of the use of sampling information at the data analysis stage. This article aims to fill that gap and to demonstrate why the use of sample weights ought to be another best practice to add to the list by reviewing well-known theoretical details and some published data analysis examples.
回顾性病历审查通常用于回答统计建模无法回答的“为什么”问题。除了作为解释工具的实用性外，它还可以利用可用的回顾性数据生成假设，因此是开发未来前瞻性研究的便捷指南。最近对使用回顾性病历审查方法的文章进行了审查，列出了应遵循的 10 条最佳实践。但是，未列出的一个问题是使用抽样权重，当只能对目标人群的样本进行回顾性病历审查时，抽样权重很重要。尽管该评论承认在这种情况下仔细选择抽样策略的重要性，并且实际上已经概述了 3 种常用的抽样方法（方便，简单随机和系统），但作者在数据分析阶段并未提及抽样信息的使用。本文旨在填补这一空白，并通过审查著名的理论细节和一些已发表的数据分析示例，证明为什么使用样本权重应该成为添加到列表中的另一个最佳实践。
