Imitating Incidents: How Simulation Can Improve Safety Investigation and Learning From Adverse Events

Macrae, Carl

Abstract

Copyright © 2018 Society for Simulation in Healthcare. One of the most fundamental principles of patient safety is to investigate and learn from the past in order to improve the future. However, healthcare organizations can find it challenging to develop the robust organizational processes and work practices that are needed to rigorously investigate and learn from safety incidents. Key challenges include difficulties developing specialist knowledge and expertise, understanding complex incidents, coordinating collaborative action, and positively changing practice. These are the types of challenges that simulation is commonly used to address. As such, this article proposes that there are considerable opportunities to integrate simulation more deeply and systematically into routine efforts to investigate and learn from safety incidents. This article explores how this might be performed by defining five key areas where simulation could be productively integrated throughout the investigation and learning process, drawing on examples of current practice and analogous applications in healthcare and other industries.

Citation

Macrae, C. (2018). Imitating Incidents: How Simulation Can Improve Safety Investigation and Learning From Adverse Events. Simulation in Healthcare, 13(4), 227-232. https://doi.org/10.1097/SIH.0000000000000315

• Journal Article Type: Article
• Acceptance Date: Feb 21, 2018
• Online Publication Date: Aug 21, 2018
• Publication Date: 2018-08
• Deposit Date: Nov 13, 2019
• Publicly Available Date: Jan 15, 2020
• Journal: Simulation in Healthcare
• Print ISSN: 1559-2332
• Electronic ISSN: 1559-713X
• Publisher: Lippincott, Williams & Wilkins
• Peer Reviewed: Peer Reviewed
• Volume: 13
• Issue: 4
• Pages: 227-232
• DOI: https://doi.org/10.1097/SIH.0000000000000315
• Public URL: https://nottingham-repository.worktribe.com/output/3258846
• Publisher URL: https://insights.ovid.com/crossref?an=01266021-201808000-00002