Errors are inevitable in all clinical settings, posing substantial risk to patients. Studies have shown detection and correction are essential to error management. This paper documents the use of Opensimulator, a virtual world development platform, to create a virtual Intensive Care Unit where error recovery can be studied in a controlled, yet realistic environment. Subjects participated in rounds presented by computer-generated characters. Errors were embedded in these presentations, and subjects were evaluated for their ability to detect them. Eight subjects were asked to evaluate two cases and answer related knowledge-based questions under two conditions: primed (forewarned of the presence of errors) and un-primed. Subjects frequently failed to detect errors despite having the prerequisite knowledge. Priming significantly improved detection, suggesting a role for interventions that aim to shift clinicians' error detection toward the limits of their knowledge. Such interventions may provide means to decrease adverse events resulting from human error.
|Original language||English (US)|
|Number of pages||10|
|Journal||AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium|
|State||Published - 2011|
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