The SHEL model: a useful tool for analyzing and teaching the contribution of Human Factors to medical error
Recent reports on the problem of medical error pointed to a discipline that has been until recently, largely disregarded by the medical profession. The interdisciplinary science of Human Factors, the reports argue, provides a pragmatic framework for analyzing and assessing risk and reducing error in...
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Veröffentlicht in: | Academic Medicine 2005-02, Vol.80 (2), p.152-155 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Recent reports on the problem of medical error pointed to a discipline that has been until recently, largely disregarded by the medical profession. The interdisciplinary science of Human Factors, the reports argue, provides a pragmatic framework for analyzing and assessing risk and reducing error in health care. The argument for applying Human Factors analysis to health care is increasingly accepted, and the application of Human Factors systems models for understanding medical error in particular have proved to be especially illuminating. The authors present a conceptual model of Human Factors--the SHEL model (named after the initial letters of its components' names, Software, Hardware, Environment, and Liveware)--that has been used in investigations of error in aviation. The authors use this simple model to examine and elucidate the Human Factors issues in a specific real-life example of medical error. The SHEL model is particularly useful in examining Human Factors issues in microsystems in health care such as the emergency room or the operating theatre; it argues that mismatches at the interface between the components in these health care microsystems are often conducive to medical errors. The authors propose that the SHEL model may have some unexploited potential in analyzing error and in training medical professionals about the science of Human Factors and its application to medical error. Empirical studies are needed, however, to ascertain the optimal amount of training needed to make clinically significant reductions in the occurrence of medical error. |
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ISSN: | 1040-2446 |
DOI: | 10.1097/00001888-200502000-00009 |