Cognitive Support During High-Consequence Episodes of Care in Cardiovascular Surgery.

Abstract

Despite significant efforts to reduce preventable adverse events in medical processes, such events continue to occur at unacceptable rates. This paper describes a computer science approach that uses formal process modeling to provide situationally aware monitoring and management support to medical professionals performing complex processes. These process models represent both normative and non-normative situations, and are validated by rigorous automated techniques such as model checking and fault tree analysis, in addition to careful review by experts. Context-aware Smart Checklists are then generated from the models, providing cognitive support during high-consequence surgical episodes. The approach is illustrated with a case study in cardiovascular surgery.