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Introduction Training for mass casualty incident (MCI) response is critical to ensure that resource allocation and treatment priorities limit preventable mortality. Previous research has investigated the use of immersive virtual environments as an alternative to high fidelity MCI training, which is expensive and logistically challenging to implement. While these have demonstrated positive early results, they still require complex technology deployment, dedicated training facilities, and significant time from instructors and facilitators. This study explores the feasibility of a smartphone-based application for trauma care training and MCI triage to fill the gap between classroom learning and high-fidelity simulation. The goals of this investigation were to evaluate clinician perceptions of a virtual MCI training simulator’s usability, acceptability, fidelity, functionality, and pacing. Materials and Methods This study used a smartphone-based training simulation called Extensible Field and Evacuation Care Training in a Virtual Environment (EFECTIVE), which presents virtual patient scenarios in a gamified, but visually high-fidelity environment. A total of 21 participants were recruited as a convenience sample of medical students, paramedics, nurses, and emergency medicine resident and attending physicians at University of Massachusetts Memorial Medical Center, an urban tertiary care medical center. Participants completed a brief tutorial and then performed a series of virtual patient scenarios and 1 MCI scenario on the simulator, each of which was 5 minutes in duration. Then, each participant completed a survey assessing the perceived usability, acceptability, fidelity, functionality, and pacing of the virtual training simulator. The research protocol was approved by the University of Massachusetts Chan Medical School Institutional Review Board. Results 48% of participants disagreed that a virtual simulator could completely replace live MCI training, though 71% agreed that app-based simulations could effectively supplement live MCI training and 67% felt that they could be used to learn how to order medical interventions in care under fire scenarios. 80% of participants agreed that the simulation could be used to practice MCI triage and to gain experience with coordinating movement of casualties to casualty collection points. 67% of participants believed that use of virtual simulators would increase their MCI preparedness. 76% agreed that the clinical cases depicted were medically realistic and that the clinical cases presented accurately represented the scenarios described. In addition, despite being presented on a smartphone as opposed to virtual reality, 62% of participants rated the experience immersive. Conclusions This study provides encouraging evidence that easy to deploy smartphone–based simulations may be an effective way to supplement MCI and care under fire training. Although the study is limited by a small sample size, there was strong agreement among participants from a wide variety of emergency medicine roles that such a simulation could train core topics associated with MCI triage. Because app-based simulations are easily deployable and can be executed quickly and frequently, they could be used as a more flexible training model compared to large scale live or virtual reality–based simulations. The results of this investigation also indicate that a sufficient level of medical realism can be achieved without live simulation.
Introduction Training for mass casualty incident (MCI) response is critical to ensure that resource allocation and treatment priorities limit preventable mortality. Previous research has investigated the use of immersive virtual environments as an alternative to high fidelity MCI training, which is expensive and logistically challenging to implement. While these have demonstrated positive early results, they still require complex technology deployment, dedicated training facilities, and significant time from instructors and facilitators. This study explores the feasibility of a smartphone-based application for trauma care training and MCI triage to fill the gap between classroom learning and high-fidelity simulation. The goals of this investigation were to evaluate clinician perceptions of a virtual MCI training simulator’s usability, acceptability, fidelity, functionality, and pacing. Materials and Methods This study used a smartphone-based training simulation called Extensible Field and Evacuation Care Training in a Virtual Environment (EFECTIVE), which presents virtual patient scenarios in a gamified, but visually high-fidelity environment. A total of 21 participants were recruited as a convenience sample of medical students, paramedics, nurses, and emergency medicine resident and attending physicians at University of Massachusetts Memorial Medical Center, an urban tertiary care medical center. Participants completed a brief tutorial and then performed a series of virtual patient scenarios and 1 MCI scenario on the simulator, each of which was 5 minutes in duration. Then, each participant completed a survey assessing the perceived usability, acceptability, fidelity, functionality, and pacing of the virtual training simulator. The research protocol was approved by the University of Massachusetts Chan Medical School Institutional Review Board. Results 48% of participants disagreed that a virtual simulator could completely replace live MCI training, though 71% agreed that app-based simulations could effectively supplement live MCI training and 67% felt that they could be used to learn how to order medical interventions in care under fire scenarios. 80% of participants agreed that the simulation could be used to practice MCI triage and to gain experience with coordinating movement of casualties to casualty collection points. 67% of participants believed that use of virtual simulators would increase their MCI preparedness. 76% agreed that the clinical cases depicted were medically realistic and that the clinical cases presented accurately represented the scenarios described. In addition, despite being presented on a smartphone as opposed to virtual reality, 62% of participants rated the experience immersive. Conclusions This study provides encouraging evidence that easy to deploy smartphone–based simulations may be an effective way to supplement MCI and care under fire training. Although the study is limited by a small sample size, there was strong agreement among participants from a wide variety of emergency medicine roles that such a simulation could train core topics associated with MCI triage. Because app-based simulations are easily deployable and can be executed quickly and frequently, they could be used as a more flexible training model compared to large scale live or virtual reality–based simulations. The results of this investigation also indicate that a sufficient level of medical realism can be achieved without live simulation.
Medical educators have acknowledged the importance of simulation training in developing procedural skills. While simulation training in other disciplines has benefitted from evaluations of users’ skill acquisition, the majority of medical training simulators continue to be developed from overly simplified descriptions of procedures, such as techniques prescribed by existing instructional material. Our objective was to use a modeling framework to characterize the skill of various users in applying junctional tourniquets in order to design an effective training simulator. We recorded 46 medical first responders performing training exercises applying a junctional tourniquet and used coded video and sensor data to identify the hierarchy of actions they performed in the process. The model provides several insights into trainee performance, such as the way in which advanced users perform more tasks in parallel, or areas where advanced users employ situational awareness to identify ways they can deviate from recommended protocol to improve outcomes. The model successfully identifies variations in tourniquet application technique that correlates with improvement on clinically relevant metrics including application speed, pressure applied, and tourniquet placement stability. This methodology can improve medical training simulations by indicating changes during the course of learning a new task, such as helpful deviations from instructional protocol.
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