Wearable sensors for modeling and assessing nontechnical skills in surgery

摘要 非技术（NT）技能包括团队合作，沟通，决策，领导力和情境 意识，是手术室（OR）中安全护理交付的关键方面。非技术技能 手术已被确定为影响患者死亡率的前哨事件的最常见原因， 手术疼痛和生活质量。沟通、团队合作和领导力方面的失误已被证明是 占围手术期主要并发症的60%，其中大部分与沟通失败有关。给定 由于NT和团队技能与患者安全之间存在密切联系， 专门为手术团队验证。然而，它们需要训练有素的观察员在场或追溯 回顾视频。这样的方法是耗时和资源密集的获得。重要的是这些 评估受到观察者的多重评估偏见的影响，这威胁到评估的客观性， 值不需要专家观察员进行实时观察的自动化工具不需要 时间密集型的音频视频分析，并可以提供客观的，可量化的，和连续的测量， 因此，非常需要NT技能，可以更广泛地实施NT技能培训。 本项目的目标是：1）研究和开发预测模型，将客观传感器- 基于个人和团队非技术技能的数据流，2）测试非侵入式传感设备， 模拟手术团队对执业专业人员的模拟培训，以及3）测试传感器的精度， 区分有和没有TeamSTEPPS培训的团队。为了实现这些目标，我们提出了三个具体目标。 被提议。目标1将验证我们的多模态传感系统，用于测量手术模拟中的NT技能。 由人为因素工程师和外科医生教育者组成的协作团队将进行总结性可用性测试 使用系统可用性量表和技术接受模型评估和确定可用性。为宗旨 2、我们的团队将在经过充分验证的手术模拟中使用传感器， 团队随着传感器不断收集数据，基于计算机的非技术技能评估工具将被 进行实时和视频记录。将进行分析、数据融合和回归分析， 使用黄金标准评级为传感器指标建模。最后，我们将评估传感器是否能够区分 有/无TeamSTEPPS培训的团队之间的团队技能差异。预期的交付成果将 包括非侵入式感测系统可用性验证和用于自动化技能的分析框架 可以在手术模拟中实施的评估。如果通过建议的 工作，我们的客观NT技能评估可以在未来用于评估团队培训的有效性 并提供结构化的、个性化的反馈，以提高医疗保健提供者的NT技能。因此，这项工作 最终可以减少由于NT技能差而导致的错误，并提高患者安全性。

Abstract Non-technical (NT) skills encompass teamwork, communication, decision-making, leadership, and situational awareness and are critical aspects for safe care delivery in the operating room (OR). Non-technical skills of surgery have been identified as the most frequent causes for sentinel events that impact patient mortality, post- operative pain, and quality of life. Lapses in communication, teamwork, and leadership have been shown to account for 60% of major perioperative complications, most of which are related to communication failures. Given this strong link between NT and team skills and patient safety, several NT skills assessment tools have been validated specifically for surgical teams. However, they require the presence of trained observers or retrospective review of videos. Such methods are time-consuming and resource intensive to obtain. Importantly, these assessments are subject to multiple assessment biases of the observer which threatens their objectivity and value. Automated tools that do not require an expert observer to conduct real-time observations, do not need time-intensive audio-video analysis, and could provide objective, quantifiable, and continuous measurements of NT skill are, thus, highly needed and could allow for the more widespread implementation of NT skills training. The objectives of the current project are to 1) investigate and develop predictive models linking objective sensor- based data streams with individual and team non-technical skills, 2) test non-intrusive sensing devices in simulated surgical team simulation training for practicing professionals, and 3) test sensor's accuracy in distinguishing teams with and without TeamSTEPPS training. To achieve these objectives, three specific aims are proposed. Aim 1 will validate our multi-modal sensing system for measuring NT skills in surgical simulation. A collaborative team of human factors engineers and surgeon educators will perform summative usability evaluation and determine usability with the System Usability Scale and Technology Acceptance Model. For Aim 2, our team will implement sensors in well-validated surgical simulations with experienced and inexperienced teams. As sensors continuously collect data, observer-based non-technical skill assessment tools will be performed real-time and video recorded. Analytics, data fusion, and regression analysis will be performed to model sensor metrics with gold-standard ratings. Finally, we will evaluate whether sensors can distinguish differences in team skills between teams with/without TeamSTEPPS training. The expected deliverables will include usability validation of a non-intrusive sensing system and analytics framework for automated skill assessment that can be implemented in surgical simulation. If proven valid and acceptable through the proposed work, our objective NT skill assessments could be used in the future to assess effectiveness of team training and provide structured, individually-tailored feedback to enhance healthcare providers' NT skills. Thus, this work could ultimately reduce errors due to poor NT skills and enhance patient safety.