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

In: Social science computer review: SSCORE, Volume 31, Issue 2, p. 208-220

Abstract

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.