Project mTEAM: Advancing Emergency Medicine Trainee Skills using Multimodal Debriefing System in Simulation-based Training

mTEAM 项目：在基于模拟的培训中使用多模式汇报系统提高急诊医学实习生技能

• 批准号: 2202451
• 负责人: Vitaliy Popov
• 金额: $ 84.92万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2202451&HistoricalAwards=false
• 关键词: Project; mTEAM; Advancing; Emergency; Medicine

With the United States population living longer and having more chronic health conditions, the incidence of sudden medical emergencies is continually growing. These acute events create a complex, high-stress environment that requires teams of healthcare professionals to act precisely and quickly to give patients the best chance of survival. The need for knowledge about how to better prepare teams for work in fast-paced, acute care settings is more important than ever. Healthcare professionals need frequent, realistic training opportunities that offer meaningful feedback on the skills that are essential for quality team-based clinical care. The research team has developed a multi-user Virtual Reality (VR) platform for Cardiac Arrest Resuscitation. This platform is designed to create realistic time pressure and rapid workload changes for the training of healthcare professionals. However, existing healthcare simulation training, including VR and manikin–based learning, requires constant and real-time human observation. This limitation results in learners receiving feedback that is of variable quality - often generalized, inconsistent, and highly dependent on simulation instructors. With feedback being essential for learning and development, this limits the effectiveness and scalability of simulation training. To fill this gap, the research team will develop and evaluate a novel debriefing system that aims to capture and visualize multimodal data streams that evaluate learners’ cognitive (e.g., clinical decision-making) and behavioral (e.g., situational awareness, communication) processes to provide data-informed feedback focused on improving team-based care of patients who suffer sudden medical emergencies. Through this new multimodal debriefing system, instructors will be able to provide new insights and personalized feedback to clinicians during post-simulation debriefing sessions to allow for more meaningful reflection, targeted intervention, and rapid development of these complex skills. The project objectives are to: 1) conduct a human-centered design study with trainees and faculty to refine the concept of a multimodal debriefing system 2) engineer and evolve an unobtrusive multi-modal sensor-based data collection system; and 3) conduct a quasi-experimental study to evaluate the potential of this study’s debriefing system to improve clinical knowledge and teamwork skills. The proposed research not only provides a strong path forward to impact the way cardiac arrest training is carried out across institutions, but it will also create knowledge and systems that can be translated to develop data-informed, team-based training programs for other medical domains and other high-risk industries that rely on expert teams.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

随着美国人口寿命的延长和慢性健康状况的增加，突发医疗紧急情况的发生率不断增加。这些急性事件创造了一个复杂的，高压力的环境，需要医疗保健专业人员团队准确，快速地采取行动，为患者提供最佳的生存机会。 对于如何更好地为团队在快节奏的急性护理环境中的工作做好准备的知识的需求比以往任何时候都更加重要。医疗保健专业人员需要频繁，现实的培训机会，提供有意义的反馈的技能是必不可少的质量团队为基础的临床护理。该研究团队开发了一个用于心脏骤停复苏的多用户虚拟现实（VR）平台。该平台旨在为医疗保健专业人员的培训创造现实的时间压力和快速的工作量变化。然而，现有的医疗模拟训练，包括VR和基于人体模型的学习，需要持续和实时的人类观察。这种限制导致学习者收到的反馈质量参差不齐--通常是笼统的、不一致的，并且高度依赖于模拟教师。由于反馈对于学习和发展至关重要，这限制了模拟培训的有效性和可扩展性。为了填补这一空白，研究团队将开发和评估一种新颖的报告系统，旨在捕获和可视化多模态数据流，以评估学习者的认知能力（例如，临床决策）和行为（例如，情境感知、通信）过程，以提供数据知情的反馈，重点是改善对遭受突发医疗紧急情况的患者的基于团队的护理。通过这种新的多模式汇报系统，教师将能够在模拟后汇报会议期间为临床医生提供新的见解和个性化反馈，以便进行更有意义的反思，有针对性的干预以及这些复杂技能的快速发展。该项目的目标是：1）与学员和教师进行以人为本的设计研究，以完善多模态报告系统的概念2）工程师和发展一个不引人注目的多模态传感器数据收集系统;和3）进行准实验研究，以评估本研究的报告系统的潜力，以提高临床知识和团队合作技能。拟议的研究不仅提供了一条强有力的前进道路，以影响跨机构进行心脏骤停培训的方式，而且还将创造可以转化为开发数据信息的知识和系统，为其他医疗领域和其他高水平的医疗机构提供团队培训计划，该奖项反映了NSF的法定使命，并通过使用基金会的学术价值和更广泛的影响审查标准。

项目成果

Understanding Emotion-Cognition Interplay When Processing Feedback During the Standardized Patient Debrief Sessions

了解标准化患者汇报会议期间处理反馈时的情绪认知相互作用

• 发表时间: 2023
• 期刊: Computersupported collaborative learning
• 作者: Popov, Vitaliy;Gabelica, Catherine;Zhang, Zhaoyuan;Yao, Yiqun
• 通讯作者: Yao, Yiqun

Towards Supporting Technical and Non-Technical Skills Development by Using Multimodal Debriefing System After Multi-User VR-Based Simulation Training

在基于 VR 的多用户模拟培训后使用多模式汇报系统支持技术和非技术技能发展

• 发表时间: 2023
• 期刊: Computersupported collaborative learning
• 作者: Popov, Vitaliy;Li, Yaxuan;Cooke, James;Sample, Alanson;Cole, Michael.
• 通讯作者: Cole, Michael.