Review article: A systematic review of emergency department incident classification frameworks

Emerg Med Australas. 2018 Jun;30(3):293-308. doi: 10.1111/1742-6723.12864. Epub 2017 Oct 11.

Abstract

As in any part of the hospital system, safety incidents can occur in the ED. These incidents arguably have a distinct character, as the ED involves unscheduled flows of urgent patients who require disparate services. To aid understanding of safety issues and support risk management of the ED, a comparison of published ED specific incident classification frameworks was performed. A review of emergency medicine, health management and general medical publications, using Ovid SP to interrogate Medline (1976-2016) was undertaken to identify any type of taxonomy or classification-like framework for ED related incidents. These frameworks were then analysed and compared. The review identified 17 publications containing an incident classification framework. Comparison of factors and themes making up the classification constituent elements revealed some commonality, but no overall consistency, nor evolution towards an ideal framework. Inconsistency arises from differences in the evidential basis and design methodology of classifications, with design itself being an inherently subjective process. It was not possible to identify an 'ideal' incident classification framework for ED risk management, and there is significant variation in the selection of categories used by frameworks. The variation in classification could risk an unbalanced emphasis in findings through application of a particular framework. Design of an ED specific, ideal incident classification framework should be informed by a much wider range of theories of how organisations and systems work, in addition to clinical and human factors.

Keywords: classification; emergency medicine; incidents; medical errors.

Publication types

  • Review
  • Systematic Review

MeSH terms

  • Emergency Service, Hospital / classification*
  • Emergency Service, Hospital / trends
  • Humans
  • Medical Errors / statistics & numerical data
  • Risk Management / methods*
  • Risk Management / standards