IT incident detection and classification

IT incident detection and classification

Centre for Health Informatics

Research Stream: Patient Safety Informatics

Our classification of human factors and technical problems that contribute to IT incidents.

IT incident detection

Project members

Associate Professor Farah Magrabi - Associate Professor

Dr Ying Wang - Research Fellow

Dr Mei-Sing Ong - Honorary Research Fellow

Project main description

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 extends these methods to incidents associated with e‑health (i.e. patient harm due to an IT problem or difficulty in using software), and we are pioneering this approach internationally.

The goals of this project are 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.

To detect IT incidents in general practice we have developed and trialeda new incident-monitoring system called TechWatch. Incidents can be reported to TechWatch either online or over the phone to trained operators. Since 2009 we have analysed 1,385 IT incidents in Australia, the United States and the United Kingdom. The methods our research has generated have become the de facto international standard to detect and classify IT incidents.

Our classification had been used to examine 4,883 incidents, including by governments in the US and UK. In 2012 the Pennsylvania Patient Safety Authority used our classification system to examine one of the largest repositories of incidents in the US, and issued a Patient Safety Advisory with specific recommendations for the procurement, implementation and use of IT systems. At the same time the ECRI Institute, a US federal patient safety organisation, used our classification to undertake an in-depth analysis of incidents nationally (called a Deep Dive™).

In the UK our classification system was used by the National Health Servicein Wales and we collaborated with the Health and Social Care Information Centre in England to examine incidents from one of the largest civilian IT programs ever undertaken worldwide. Most recently our classification was implemented into the provincial incident monitoring system in British Columbia, Canada - BC Patient Safety & Learning System (BC PSLS).

We welcome enquiries about our classification and are happy to assist individuals and organisations who wish to use the schema to analyse IT incidents.

Further information

Media Links

IT problems in general practice could be putting patient safety at risk


  1. Magrabi F, Liaw ST, Arachi D, Runciman W, Coiera, E, Kidd, MR. Identifying patient safety problems associated with information technology in general practice: an analysis of incident reports. BMJ Quality and Safety, November 2015
  2. Magrabi F, Baker M, Sinha I, Ong MS, Harrison S, Kidd MR, et al. Clinical safety of England's national programme for IT: A retrospective analysis of all reported safety events 2005 to 2011. Int J Med Inform. 2015;84(3):198-206.
  3. Magrabi F, Ong MS, Runciman W, Coiera E. Using FDA reports to inform a classification for health information technology safety problems. J Am Med Inform Assoc. 2012;19(1):45-53.
  4. Magrabi F, Ong MS, Runciman W, Coiera E. Patient safety problems associated with heathcare information technology: an analysis of adverse events reported to the US Food and Drug Administration. AMIA Annu Symp Proc. 2011;2011:853-7.
  5. Magrabi F, Ong MS, Runciman W, Coiera E. An analysis of computer-related patient safety incidents to inform the development of a classification. J Am Med Inform Assoc. 2010;17(6):663-70.

Project sponsors

NHMRC Project Grant APP1022946, 630583

Collaborative partners

Professor Bill Runciman, University of South Australia and Australian Patient Safety Foundation
Professor Ric Day, St Vincent’s Clinical School, UNSW Medicine
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 Marie-Catherine Beuscart-Zéphir, Université de Lille Nord de France, France,
Professor Dean Sittig, University of Texas – Memorial Hermann Center for Healthcare Quality & Safety, Houston, Texas
Professor Christian Nohr, Danish Centre for Health Informatics, Department of Development and Planning, Aalborg University, Denmark

Related projects

Automated identification of incident reports

Automated surveillance of IT systems

E-health safety governance

Project status


Centres related to this project

Centre for Health Informatics

Content owner: Australian Institute of Health Innovation Last updated: 22 Jun 2020 1:43pm

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