Investigating health information systems-induced errors

Abstract

Purpose The purpose of this paper is to present a review of health information system (HIS)-induced errors and its management. This paper concludes that the occurrence of errors is inevitable but it can be minimised with preventive measures. The review of classifications can be used to evaluate medical errors related to HISs using a socio-technical approach. The evaluation could provide an understanding of errors as a learning process in managing medical errors. Design/methodology/approach A literature review was performed on issues, sources, management and approaches to HISs-induced errors. A critical review of selected models was performed in order to identify medical error dimensions and elements based on human, process, technology and organisation factors. Findings Various error classifications have resulted in the difficulty to understand the overall error incidents. Most classifications are based on clinical processes and settings. Medical errors are attributed to human, process, technology and organisation factors that influenced and need to be aligned with each other. Although most medical errors are caused by humans, they also originate from other latent factors such as poor system design and training. Existing evaluation models emphasise different aspects of medical errors and could be combined into a comprehensive evaluation model. Research limitations/implications Overview of the issues and discourses in HIS-induced errors could divulge its complexity and enable its causal analysis. Practical implications This paper helps in understanding various types of HIS-induced errors and promising prevention and management approaches that call for further studies and improvement leading to good practices that help prevent medical errors. Originality/value Classification of HIS-induced errors and its management, which incorporates a socio-technical and multi-disciplinary approach, could guide researchers and practitioners to conduct a holistic and systematic evaluation.