J Biomed Inform - Recovery at the edge of error: debunking the myth of the infallible expert.


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The notion that human error should not be tolerated is prevalent in both the public and personal perception of the performance of clinicians. However, researchers in other safety-critical domains have long since abandoned the quest for zero defects as an impractical goal, choosing to focus instead on the development of strategies to enhance the ability to recover from error. This paper presents a cognitive framework for the study of error recovery, and the results of our empirical research into error detection and recovery in the critical care domain, using both laboratory-based and naturalistic approaches. Both attending physicians and residents were prone to commit, detect and recover from errors, but the nature of these errors was different. Experts corrected the errors as soon as they detected them and were better able to detect errors requiring integration of multiple elements in the case. Residents were more cautious in making decisions showing a slower error recovery pattern, and the detected errors were more procedural in nature with specific patient outcomes. Error detection and correction are shown to be dependent on expertise, and on the nature of the everyday tasks of the clinicians concerned. Understanding the limits and failures of human decision-making is important if we are to build robust decision-support systems to manage the boundaries of risk of error in decision-making. Detection and correction of potential error is an integral part of cognitive work in the complex, critical care workplace.

Resumo Limpo

notion human error toler preval public person percept perform clinician howev research safetycrit domain long sinc abandon quest zero defect impract goal choos focus instead develop strategi enhanc abil recov error paper present cognit framework studi error recoveri result empir research error detect recoveri critic care domain use laboratorybas naturalist approach attend physician resid prone commit detect recov error natur error differ expert correct error soon detect better abl detect error requir integr multipl element case resid cautious make decis show slower error recoveri pattern detect error procedur natur specif patient outcom error detect correct shown depend expertis natur everyday task clinician concern understand limit failur human decisionmak import build robust decisionsupport system manag boundari risk error decisionmak detect correct potenti error integr part cognit work complex critic care workplac

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