Physiological synchronization and entropy as measures of team cognitive load

• Published in: Journal of biomedical informatics 2019-08, Vol.96, p.103250-103250, Article 103250
• Main Authors: Dias, Roger D., Zenati, Marco A., Stevens, Ronald, Gabany, Jennifer M., Yule, Steven J.
• Format: Article
• Language: English
• Subjects: Cognitive load; Heart rate variability; Physiological synchronization; Surgery; Teamwork
• ISSN: 1532-0464; 1532-0480
• DOI: 10.1016/j.jbi.2019.103250

[Display omitted] •The operating room (OR) is a high-risk and complex environment.•Cognitive overload imposed by surgical tasks may impair team performance.•This study describes a novel approach to measure team cognitive load.•Physiological synchronization and entropy can be used to measure team cognitive load. The operating room (OR) is a high-risk and complex environment, where multiple specialized professionals work as a team to effectively care for patients in need of surgical interventions. Surgical tasks impose high cognitive demands on OR staff and cognitive overload may have deleterious effects on team performance and patient safety. The aim of the present study was to investigate the feasibility and describe a novel methodological approach to characterize dynamic changes in team cognitive load by measuring synchronization and entropy of heart rate variability parameters during real-life cardiac surgery. Cognitive load was measured by capturing interbeat intervals (IBI) from three team members (surgeon, anesthesiologist and perfusionist) using an unobtrusive wearable heart rate sensor and transmitted in real-time to a smartphone application. Clinical data and operating room audio/video recordings were also collected to provide behavioral and contextual information. We developed symbolic representations of the transient cognitive state of individual team members (Individual Cognitive State – ICS), and overall team (Team Cognitive State – TCS) by comparing IBI data from each team member with themselves and with others. The distribution of TCS symbols during surgery enabled us to display and analyze temporal states and dynamic changes of team cognitive load. Shannon’s entropy was calculated to estimate the changing levels of team organization and to detect fluctuations resulting from a variety of cognitive demands and/or specific situations (e.g. medical error, emergency, flow disruptions). An illustrative example from a real cardiac surgery team shows how cognitive load patterns shifted rapidly after an actual near-miss medication event, leading the team to a more organized and synchronized state. The methodological approach described in this study provides a measurement technique for the assessment of team physiological synchronization, which can be applied to many other team-based environments. Future research should gather additional validity evidence to support the proposed methods for team cognitive load measurement.