Influence of electronic medical records on hospital efficiency: the moderating effects of application contexts

Purpose Electronic medical records (EMRs) hold the potential to improve hospital efficiency, yet it remains unclear whether the benefits vary across application contexts. This study aims to evaluate hospital efficiency comprehensively and to explore the moderating effects of application contexts on the benefits of EMRs on hospital efficiency, thus testing whether such benefits are context-specific. Design/methodology/approach Utilizing the non-radial directional distance function (NDDF), hospital efficiency in Shandong province, China, is measured, and then a hierarchical linear model (HLM) is employed to capture the impacts of different-stage EMR. Based on the tests of hierarchical interaction effects, this study examines the moderating effects of application contexts (technology acceptance in the technology adoption stage and task complexity in the technology use stage). Findings The results of NDDF and HLM indicate the positive effects of high-stage EMR on hospital efficiency. Hospitals with higher technology acceptance (such as academic-affiliated hospitals) can derive more benefits from high-stage EMR, revealing the heterogeneity of the benefits of EMRs driven by technology acceptance. The benefits of EMR are found not to be affected by task complexity (such as case mix index), pointing to the generalizability of EMRs. Practical implications This study investigates the impacts of application contexts on the benefits of EMRs, which demonstrates both the generalizability and heterogeneity of the benefits of EMRs. The results not only strengthen confidence in the application of EMRs but also provide hospital managers with development strategies for EMRs. Originality/value This study identifies the impact of application contexts on the benefits of EMRs, supporting the heterogeneity and generalizability of EMRs’ benefits across hospitals with varying characteristics. Besides, the utilization of NDDF helps to analyze the impacts of EMRs on hospital performance from a more comprehensive perspective.