Electronic Health Record Use Issues and Diagnostic Error: A Scoping Review and Framework

J Patient Saf. 2023 Jan 1;19(1):e25-e30. doi: 10.1097/PTS.0000000000001081.

Abstract

Background: Diagnostic errors are a major source of patient harm, most of which are caused by cognitive errors and biases. Despite research showing the relationship between software systems and cognitive processes, the impact of the electronic health record (EHR) on diagnostic error remains unknown.

Methods: We conducted a scoping review of the scientific literature to (1) survey the association between aspects of the EHR and diagnostic error, and (2) through a human-systems integration lens, identify the types of EHR issues and their impact on the stages of the diagnostic process.

Results: We analyzed 11 research articles for the relationship between EHR use and diagnostic error. These articles highlight specific technical, usability, and workflow issues with the EHR that pose risks for diagnostic error at every stage of the diagnostic process.

Discussion: Although technical problems such as EHR interoperability and data integrity pose critical issues for the diagnostic process, usability and workflow issues such as poor display design, and inability to track test results also hamper clinicians' ability to track, process, and act in the diagnostic process. Current research methods have limited coverage over clinical settings, are not standardized, and rarely include measures of patient harm.

Conclusions: The available evidence shows that EHRs pose risks for diagnostic error throughout the diagnostic process, with most issues involving their incompatibility with providers' cognitive processing. A structured and systematic model of collecting and reporting on these errors is needed to understand how the EHR shapes the diagnostic process and improve diagnostic accuracy.

Publication types

  • Review
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Diagnostic Errors / prevention & control
  • Electronic Health Records*
  • Humans
  • Patient Harm*
  • Software
  • Surveys and Questionnaires