Cognitive Informatics in Health and Biomedicine. Case studies on Critical Care Complexity and Errors

Abstract

Our earlier studies show that physicians’ ability to detect errors in clinical problems in the intensive medical care domain is limited when tested individually in laboratory-based conditions (Chaps. 3 and 6 ). We extended this study to explore the mechanism of error detection and recovery when working in teams, using (a) semi-naturalistic and (b) naturalistic empirical paradigms. The data were collected in an intensive care unit and were analyzed to reveal the process of patient management and the frequency and the nature of errors generated and corrected. The results show that teams perform better than individuals, due to advantages conferred by the distribution of cognitive task across multiple team members. Attending and trainee clinicians were found to generate most errors as well as recover from most of them in real world, as compared to other conditions. Error detection and correction in a situation closer to complex real world practice appears to induce certain urgency for quick action resulting in rapid detection and correction. Furthermore, teams working at the bedside in real world optimize performance with little room for explicating any mistakes and thus little learning from errors. There is a close relationship between competency in delivery of patient care and the need to minimize errors. This is juxtaposed with the competing demand for learning from errors, an essential part of the apprentice training process. The challenge of managing the balance between these two modes, professional practice and learning, for delivery of efficient and safe care in complex critical care settings, are discussed.