Principal Investigator: Vitaliy Popov
CoPrincipal Investigator(s):
Organization: Regents of the University of Michigan – Ann Arbor
NSF Award Information: Project mTEAM: Advancing Emergency Medicine Trainee Skills using Multimodal Debriefing System in Simulation-based Training
Abstract:
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.
