Many believe that electronic medical record (EMR) systems hold promise for improving the quality of health care services. The body of research on this topic is still in the early stages, however, in part because of the challenge of measuring the capabilities of EMR systems. The purpose of this study was to identify classes of EMR system sophistication in hospitals as well as hospital characteristics associated with the sophistication categories. The data used were from the American Hospital Association (AHA) and the Health Information Management and Systems Society (HIMSS). The sample included acute care hospitals in the United States with 50 beds or more. We used latent class analysis to identify the sophistication classes and logistic regression to identify the relationships between these classes and hospital characteristics. Our study identifies cumulative categories of EMR sophistication: ancillary-based, ancillary/data aggregation, and ancillary-to-bedside. Rural hospital EMRs are likely to be ancillary based, while hospitals in a network are likely to have either ancillary-based or ancillary-to-bedside EMRs. Future research should explore the effect of network membership on EMR system development.

中文翻译：

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使用潜在类别分析来识别美国急诊医院电子病历系统的复杂类别

许多人认为电子病历 (EMR) 系统有望提高医疗保健服务的质量。然而，关于该主题的研究主体仍处于早期阶段，部分原因是测量 EMR 系统的能力存在挑战。本研究的目的是确定医院中 EMR 系统复杂程度的类别以及与复杂程度类别相关的医院特征。使用的数据来自美国医院协会 (AHA) 和健康信息管理与系统协会 (HIMSS)。样本包括美国拥有 50 张或更多床位的急症护理医院。我们使用潜在类别分析来识别复杂度类别和逻辑回归来识别这些类别与医院特征之间的关系。我们的研究确定了 EMR 复杂性的累积类别：基于辅助、辅助/数据聚合和辅助到床边。农村医院的 EMR 可能是基于辅助的，而网络中的医院可能有基于辅助的或辅助到床边的 EMR。未来的研究应该探索网络成员资格对 EMR 系统发展的影响。