Clinical Systems Safety Engineering
Clinical IT Systems Safety Engineering
Systems safety is critical to the success of large-scale computerisation being undertaken to improve the quality of health services delivery worldwide.
Our safety research program is focusing on understanding the way in which IT is both an enabler of safer clinical practice, and also understanding the ways in which IT can unintentionally be the generator of new types of error. Our research aims to use this rich understanding of the way IT impacts safety to develop innovative tools and methods to improve the safety of clinical information systems. A focus on record keeping, clinical decision support and messaging functions will ensure that the outcomes of this research will have immediate impact on patient safety in routine care. We also wish to influence policy in this area, and begin a debate about the best mechanisms to ensure that clinical software is safe, and does not inadvertently result in patient harm or misadventure.
Key Publications
- Magrabi F, McDonnell G, Westbrook J, Coiera E (2007), Using Accident Models to Design Safe Electronic Medication Management Systems, 12th World Congress on Medical Informatics (Medinfo) Brisbane, Australia.
- E. Coiera, J. I. Westbrook, J. C. Wyatt. The Safety and Quality of Decision Support Systems. IMIA Yearbook of Medical Informatics 2006. IMIA and Schattauer GmbHa
- E Coiera and JI Westbrook. Should clinical software be regulated? MJA 184 (12): 600-1. 19 June 2006
- JI Westbrook, EW Coiera, AS Gosling. Do Online Information Retrieval Systems Help Experienced Clinicians Answer Clinical Questions? J Am Med Inform Assoc. 2005;12:31521. DOI 10.1197/jamia.M1717.5
- J. S. Ash, M. Berg, E. Coiera, Some Unintended Consequences of Information Technology in Health Care: The Nature of Patient Care Information System Related Errors, Journal American Medical Informatics Association, 11(2),104-112, 2004.
Engineering safe decision support systems for healthcare
ARC Discovery Project DP0772487
Chief Investigator: Dr Farah Magrabi
2007: $ 74,887
2008: $ 82,521
2009: $ 85,781
There is preliminary evidence that poorly implemented clinical decision support systems (CDSS) can lead to increased mortality in some settings. Studies in the US, UK and Australia have found commercial prescribing systems often fail to uniformly detect significant drug interactions, probably because of errors in their knowledge base. Electronic medication management systems may generate new types of error because of user-interface design, but also because of events in the workplace such as distraction affecting the actions of system users.
Another potential source of CDSS influenced errors are automation biases, including errors of omission where individuals miss important data because the system does not prompt them to notice them, and errors of commission where individuals do what the decision aid tells to do, even when this contradicts their training and other available data. Errors of dismissal occur when relevant alerts are ignored.
On-line decision support systems may also result in errors where clinicians come to an incorrect assessment of the evidence, possibly shaped in part by cognitive decision biases.
This three year project will develop a novel accident models of the processes which give rise to failures when decision support systems are used by clinicians in routine clinical tasks. Accident models will be used as a basis to shape the design of safer CDSS to reduce the impact of human error and system failure using controlled experiments and system simulations. The outcomes will have broad potential to guide the design, implementation and regulation of information and communications technology in complex safety-critical environments like healthcare.
