Center for Biomedical Informatics Research, School of Medicine, Stanford University (A.C., N.H.S.).
Division of Hospital Medicine, School of Medicine, Stanford University (J.H.C.).
Ann Intern Med. 2020 Jun 2;172(11 Suppl):S79-S84. doi: 10.7326/M19-0873.
Electronic health records (EHRs) are an increasingly important source of real-world health care data for observational research. Analyses of data collected for purposes other than research require careful consideration of data quality as well as the general research and reporting principles relevant to observational studies. The core principles for observational research in general also apply to observational research using EHR data, and these are well addressed in prior literature and guidelines. This article provides additional recommendations for EHR-based research. Considerations unique to EHR-based studies include assessment of the accuracy of computer-executable cohort definitions that can incorporate unstructured data from clinical notes and management of data challenges, such as irregular sampling, missingness, and variation across time and place. Principled application of existing research and reporting guidelines alongside these additional considerations will improve the quality of EHR-based observational studies.
电子健康记录 (EHR) 是观察性研究中越来越重要的真实医疗保健数据来源。出于研究以外的目的而收集的数据进行分析,需要仔细考虑数据质量以及与观察性研究相关的一般研究和报告原则。一般观察性研究的核心原则也适用于使用 EHR 数据的观察性研究,这些原则在先前的文献和指南中已有充分论述。本文为基于 EHR 的研究提供了额外的建议。基于 EHR 的研究特有的考虑因素包括评估可以纳入来自临床记录的非结构化数据的计算机可执行队列定义的准确性,以及管理数据挑战,如不规则采样、缺失和随时间和地点的变化。在这些额外考虑因素的基础上,原则性地应用现有的研究和报告指南将提高基于 EHR 的观察性研究的质量。