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Adverse events—“instances which indicate or may indicate that a patient has received poor quality care”1—are used widely in healthcare quality measurement and improvement activities. Many commonly employed quality improvement mechanisms, such as incident reporting, occurrence screening, significant event auditing, processes for dealing with complaints, and (in the UK) the national confidential enquiries into various areas of clinical care are essentially focused on such adverse events. Even traditional medical quality improvement mechanisms such as mortality and morbidity conferences or death and complications meetings are predicated on the idea that by identifying and examining adverse events, we can learn lessons and change practice in ways that will make such events less likely in future and hence improve the quality of health care.
The principle that studying adverse events can produce information which leads to quality improvements is far from new and has been much used outside of health care.2, 3 It has an intuitive power—after all, we all learn much as individuals from our own mistakes, and it seems reasonable to hypothesise that organisations can also learn a great deal from their errors. However, it is easy to overlook the complexities of measurement involved in defining, classifying, identifying, describing, and analysing such adverse events.4 Like any other measurement tools, those used with adverse events need to be tested to ensure that they work. This article presents an analysis of the issues involved in defining adverse events, the sources of data which can be used to identify such events, and the validity and reliability of measures of quality based on adverse events in health care.
The idea that it would be useful or important to study the incidence, circumstances, or causes of adverse events in health care arises from various different but related schools of thought. For example, …
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