Goldstein Neal D, Olivieri-Mui Brianne, Burstyn Igor
Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, USA.
Department of Microbiology and Immunology, College of Medicine, Drexel University, Philadelphia, PA, USA.
J Gen Intern Med. 2025 Aug 12. doi: 10.1007/s11606-025-09808-9.
There has been a proliferation of large-scale electronic health record (EHR) data platforms that pool across multiple healthcare organizations, such as the National Institutes of Health's All of Us in the federal space and TriNetX and Epic Cosmos in the commercial space. There are unique issues that occur when EHR data are aggregated across disparate healthcare systems beyond the general-and more well known-concerns about secondary analysis of EHR data from a single entity. In this article, we define aggregated EHR data, contrasting it to other real-world data sources, highlight benefits and challenges when working with aggregated EHR data, offer several "good practices" to address these challenges, and conclude by discussing whether it is appropriate to pool these data together or not.
大规模电子健康记录（EHR）数据平台大量涌现，这些平台整合了多个医疗保健组织的数据，比如联邦政府层面美国国立卫生研究院的“我们所有人”项目，以及商业领域的TriNetX和Epic Cosmos。当电子健康记录数据在不同的医疗系统间汇总时，会出现一些独特的问题，这些问题超出了对单个实体电子健康记录数据进行二次分析时常见且广为人知的担忧。在本文中，我们定义了汇总的电子健康记录数据，并将其与其他真实世界数据源进行对比，强调使用汇总电子健康记录数据时的益处和挑战，提供应对这些挑战的若干“良好做法”，并通过讨论将这些数据整合在一起是否合适来得出结论。
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