STRATUS Center for Medical Simulation, Brigham and Women's Hospital, USA; Department of Emergency Medicine, Harvard Medical School, USA.
Medical Robotics and Computer Assisted Surgery (MRCAS) Laboratory, Division of Cardiothoracic Surgery, Veterans Affairs Boston Healthcare System, USA; Department of Surgery, Harvard Medical School, USA.
J Biomed Inform. 2019 Aug;96:103250. doi: 10.1016/j.jbi.2019.103250. Epub 2019 Jul 8.
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.
手术室（OR）是一个高风险且复杂的环境，多个专业的医疗人员需要作为一个团队共同协作，为需要手术干预的患者提供有效的护理。手术任务对手术室工作人员的认知能力要求较高，认知过载可能对团队表现和患者安全产生不利影响。本研究旨在探讨一种新的方法学方法的可行性，该方法通过测量实时心脏手术期间心率变异性参数的同步性和熵来描述团队认知负荷的动态变化。通过使用非侵入性可穿戴心率传感器从三名团队成员（外科医生、麻醉师和灌注师）捕获心搏间期（IBI），并实时传输到智能手机应用程序，来测量认知负荷。还收集了临床数据和手术室音频/视频记录，以提供行为和上下文信息。我们通过将每个团队成员的 IBI 数据与自己和他人进行比较，为个体团队成员（个体认知状态 - ICS）和整体团队（团队认知状态 - TCS）开发了瞬时认知状态的符号表示。通过手术期间 TCS 符号的分布，我们能够显示和分析团队认知负荷的时间状态和动态变化。计算香农熵来估计团队组织的变化水平，并检测由于各种认知需求和/或特定情况（例如医疗错误、紧急情况、流程中断）而导致的波动。来自真实心脏手术团队的一个说明性示例展示了在实际接近错过药物事件后，团队认知负荷模式如何迅速发生变化，导致团队更加有序和同步。本研究中描述的方法学方法为团队生理同步性的评估提供了一种测量技术，该技术可应用于许多其他基于团队的环境。未来的研究应收集更多的有效性证据，以支持团队认知负荷测量的建议方法。
