Classifying patient safety incidents involving digital health

  1. Macquarie University
  2. Faculty of Medicine, Health and Human Sciences
  3. Departments and schools
  4. Australian Institute of Health Innovation
  5. Our research centres
  6. Health Informatics
  7. Our research
  8. Classifying patient safety incidents involving digital health
Professor Farah Magrabi Explore a community of AI in healthcare researchers

Research to improve IT systems in healthcare

Our classification of human factors and technical problems that contribute to IT incidents in healthcare has been used by multiple government agencies and patient safety organisations.

Project sponsor: National Health and Medical Research Council Project Grant (APP1022946, 630583)

A person wearing scrubs, a hair net and a face mask pointing at a hospital screen with a patient laying on a table in the background.

About the project

The systematic analysis of critical incidents is well-established in medical practice. Incidents can trigger root-cause analyses in health services, or provide early warnings of unexpected drug reactions or infectious outbreaks. Our research has extended these methods to incidents associated with digital health (ie patient harm due to an IT problem or difficulty in using software).

Project goals

The aim of this project was to:

  • detect IT incidents
  • develop a robust classification for IT incidents
  • use the classification to track the evolving causes of IT-related harm in Australia
  • promulgate the classification internationally.

We have developed a classification for problems associated with IT systems in healthcare that takes a bottom-up approach and was developed by examining 'natural categories' of problems described in incidents from a range of health care settings in Australia, the USA and England.

The classification was initially based on incidents reported to a state-wide system in Australia, and then expanded with new categories for software problems using incidents from the US Food and Drug Administration over a 30-month period. It was subsequently validated with 850 incidents reported in the English National Health Service over a six-year period, and a further 90 incidents reported by Australian GPs over a 19-month period.

The classification was further validated by a 2017 systematic review of problems with health IT which found that no new categories were required to code the IT problems, information errors, and contributing factors identified in the 34 studies included in this review.

Beyond the published literature, this classification was endorsed by the American Nursing Informatics Association in their 2015 position paper on IT safety.

We welcome enquiries about our classification and are happy to assist individuals and organisations who wish to use the schema to analyse digital health incidents. A guide to the classification is also available.

Project lead: Professor Farah Magrabi

Other members and collaborators
  • Professor Marie-Catherine Beuscart-Zéphir, Université de Lille Nord de France, France
  • Professor Michael Kidd, Faculty of Medicine, Nursing and Health Sciences, Flinders University
  • Professor Siaw-Teng Liaw, School of Public Health and Community Medicine, UNSW Medicine
  • Professor Christian Nohr, Danish Centre for Health Informatics, Department of Development and Planning, Aalborg University, Denmark
  • Professor Bill Runciman, University of South Australia and Australian Patient Safety Foundation
  • Professor Dean Sittig, University of Texas – Memorial Hermann Center for Healthcare Quality & Safety, Houston, Texas