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Using Latent Class Analysis to Identify Sophistication Categories of Electronic Medical Record Systems in U.S. Acute Care Hospitals

机译: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

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摘要

Many believe that electronic medical record 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 electronic medical record systems. The purpose of this study was to identify classes of Electronic Medical Record (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 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.
机译:许多人认为电子病历系统有望改善医疗保健服务的质量。但是,有关此主题的研究仍处于初期阶段,部分原因是测量电子病历系统功能的挑战。这项研究的目的是确定医院中电子病历(EMR)系统的复杂程度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)。样本包括美国有50张或更多病床的急诊医院。我们使用潜在类别分析来识别复杂性类别,并使用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复杂程度的累积类别:基于辅助的,辅助/数据聚合以及辅助到床边。农村医院的EMR可能是基于辅助的,而网络中的医院则可能具有基于辅助的或床旁的EMR。未来的研究应探索网络成员资格对EMR系统开发的影响。

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