Intelligent Interruption Management System to Enhance Safety and Performance in Complex Surgical and Robotic Procedures.
Intelligent Interruption Management System to Enhance Safety and Performance in Complex Surgical and Robotic Procedures.
复制标题
智能中断管理系统，以增强复杂的手术和机器人程序的安全性和性能。
DOI：
10.1007/978-3-030-01201-4_8
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发表时间：
2018-09
期刊：
影响因子：
--
通讯作者：
Zenati MA
中科院分区：
文献类型：
--
作者：
Dias RD;Conboy HM;Gabany JM;Clarke LA;Osterweil LJ;Arney D;Goldman JM;Riccardi G;Avrunin GS;Yule SJ;Zenati MA
继发于中断的程序流程中断在复杂医疗程序中的错误发生中起着关键作用，主要是因为它们增加了团队成员的脑力负担，对团队绩效和患者安全产生负面影响。由于某些类型的中断是不可避免的，因此多任务处理的需求是复杂程序护理所固有的，因此该领域可以受益于能够识别在哪个时刻流量干扰是适当的而不产生中断的智能系统。在本研究中，我们描述了一种新方法，用于识别现实生活中心脏手术期间施加低认知负荷的任务和需要高认知努力的任务。我们使用心率变异性分析作为认知负荷的客观测量，同时以实时且不引人注目的方式从多个团队成员（外科医生、麻醉师和灌注师）捕获数据。使用音频视频记录、行为编码和分层手术过程模型，我们集成了多个数据源来创建交互式手术仪表板，从而能够识别施加低认知负荷的特定步骤、子步骤和任务。中断管理系统可以利用这些低需求情况来指导手术团队进行流程中断的适当性。所描述的方法还使我们能够检测特定条件下（例如紧急情况）或容易出错的情况下随着时间的推移认知负荷的波动。深入理解认知超载状态、任务需求和错误发生之间的关系将推动认知支持系统的发展，该系统可以在高度复杂的过程中有效、主动地识别和减轻错误。
Procedural flow disruptions secondary to interruptions play a key role in error occurrence during complex medical procedures, mainly because they increase mental workload among team members, negatively impacting team performance and patient safety. Since certain types of interruptions are unavoidable, and consequently the need for multitasking is inherent to complex procedural care, this field can benefit from an intelligent system capable of identifying in which moment flow interference is appropriate without generating disruptions. In the present study we describe a novel approach for the identification of tasks imposing low cognitive load and tasks that demand high cognitive effort during real-life cardiac surgeries. We used heart rate variability analysis as an objective measure of cognitive load, capturing data in a real-time and unobtrusive manner from multiple team members (surgeon, anesthesiologist and perfusionist) simultaneously. Using audio-video recordings, behavioral coding and a hierarchical surgical process model, we integrated multiple data sources to create an interactive surgical dashboard, enabling the identification of specific steps, substeps and tasks that impose low cognitive load. An interruption management system can use these low demand situations to guide the surgical team in terms of the appropriateness of flow interruptions. The described approach also enables us to detect cognitive load fluctuations over time, under specific conditions (e.g. emergencies) or in situations that are prone to errors. An in-depth understanding of the relationship between cognitive overload states, task demands, and error occurrence will drive the development of cognitive supporting systems that recognize and mitigate errors efficiently and proactively during high complex procedures.
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影响因子：
3.8
作者：
Gawande, AA;Zinner, MJ;Brennan, TA
通讯作者：
Brennan, TA
影响因子：
4.7
作者：
Baek, Hyun Jae;Cho, Chul-Ho;Woo, Jong-Min
通讯作者：
Woo, Jong-Min
影响因子：
3.7
作者：
Bailey, Brian P.;Iqbal, Shamsi T.
通讯作者：
Iqbal, Shamsi T.
DOI：
10.1007/s00464-015-4239-1
发表时间：
2016-02-01
影响因子：
3.1
作者：
Weigl, Matthias;Stefan, Philipp;Catchpole, Ken
通讯作者：
Catchpole, Ken
影响因子：
2.6
作者：
Wilson, Mark R.;Poolton, Jamie M.;Masters, Rich S. W.
通讯作者：
Masters, Rich S. W.