Adverse Events in Healthcare: learning from mistakes
Large national reviews of patient charts estimate that approximately 10% of hospital admissions are associated with an adverse event (defined as an injury resulting in prolonged hospitalisation, disability or death, caused by healthcare management). Apart from having a significant impact on patient morbidity and mortality, adverse events also result in increased healthcare costs due to longer hospital stays. Furthermore, a substantial proportion of adverse events are preventable. Through identifying the nature and rate of adverse events, initiatives to improve care can be developed. A variety of methods exist to gather adverse event data both retrospectively and prospectively but these do not necessarily capture the same events and there is variability in the definition of an adverse event. For example, hospital incident reporting collects only a very small fraction of the adverse events found in retrospective chart reviews. Until there are systematic methods to identify adverse events, progress in patient safety cannot be reliably measured. This review aims to discuss the need for a safety culture that can learn from adverse events, describe ways to measure adverse events, and comment on why current adverse event monitoring is unable to demonstrate trends in patient safety.
Funding
Health Research Board of Ireland, INAES/2013/1.
History
Comments
This is a pre-copyedited, author-produced PDF of an article accepted for publication in QJM: An International Journal of Medicine following peer review. The version of record Rafter N, Hickey A, Condell S, Conroy R, O'Connor P, Vaughan D, Williams D. Adverse Events in Healthcare: learning from mistakes. Quarterly Journal of Medicine. First published online: 30 July 2014 is available at: http://qjmed.oxfordjournals.org/content/early/2014/08/09/qjmed.hcu145.Published Citation
Rafter N, Hickey A, Condell S, Conroy R, O'Connor P, Vaughan D, Williams D. Adverse Events in Healthcare: learning from mistakes. Quarterly Journal of Medicine. First published online: 30 July 2014.Publication Date
2014-01-01External DOI
PubMed ID
25078411Department/Unit
- Data Science Centre
- Health Psychology
- Medicine
- Public Health and Epidemiology