Introduction Assessing military medical teams’ ability to respond to large-scale mass casualty (MASCAL) events has become a priority in preparing for future conflicts. MASCAL exercises rely on large numbers of simulated patients with limited medical training. Role-players must be appropriately prepared to ensure that medical exercises adequately assess the expected capabilities of military medical units. The Uniformed Services University of the Health Sciences (USUHS) has evaluated future military providers for decades using a large-scale, multiday, immersive simulation called Bushmaster. 1 Despite a robust casualty training system, the fidelity of the portrayals remained limited. Materials and Methods Through collaboration with national military medical experts, a comprehensive casualty depiction system was developed. This system relied on structured casualty cards linked to time-based illness scripts. Structured casualty cards included an appropriate balance of disease non-battle injuries and trauma, included multi-patient presentations based on shared events (i.e., multiple injured personnel due to an aircraft crash), normal and pathologic combat stress, population/unit considerations, requirements for different roles within the medical unit, and expected clinical outcomes. Illness scripts, supplemented by video guides, included time-based courses of illness/injury and prescribed responses to different typical treatments. An example of a casualty card is depicted in figure 1. This system was piloted during an annual MASCAL exercise (Operation Bushmaster) at USUHS. Clinical faculty were queried on the fidelity of this new system while role-players were evaluated on feasibility. Results Three hundred casualty cards linked to 49 illness scripts were created, peer-reviewed, and piloted at Bushmaster. A total of 170 military members with limited medical training portrayed simulated patients utilizing the new casualty depiction system. Clinical faculty members strongly agreed that the improved casualty depiction system improved the realism of individual patient presentations (96%). Eighty-three percent of role-players strongly agreed that the casualty depiction system was easy to understand. 2 Conclusions This improved casualty depiction system was a feasible approach to enhance the fidelity of a MASCAL exercise. It has since been shared with military medical units around the globe to assist with their MASCAL exercises, making future multisite evaluations of this casualty depiction system possible. This casualty depiction system provided a novel opportunity to assess team-based healthcare delivery based on clinical outcomes. With each simulated patient on a strict timeline for symptom progression, any failure to provide care in a timely manner would result in increased morbidity and mortality. These outcomes could be compared to expected outcomes – providing synthetic insights into overall team performance. Abstract A16 Figure 1 A sample casualty card used for mass casualty exercises References Barry ES, Dong T, Durning SJ, Schreiber-Gregory D, Torre D, Grunberg NE. Medical student leader performance in an applied medical field practicum. Military Medicine . 2019 Nov; 184 (11–12):653–60. Meyer EG, Godshall-Bennett L, Moreno A, Guo G, May N, Spencer CM, Schwartz J, Vojta LR, Rudinsky SL. Improved casualty depiction system for simulated mass casualty exercises. Military medicine . 2025 Jan; 190 (1–2):e388–94. Conflicts of Interest None. Disclosure Views expressed in this article are those of the authors and do not represent those of the U.S. Air Force or the DoD.
Building similarity graph...
Analyzing shared references across papers
Loading...
Eric G. Meyer
United States Air Force
BMJ Military Health
Building similarity graph...
Analyzing shared references across papers
Loading...
Eric G. Meyer (Wed,) studied this question.
synapsesocial.com/papers/68f3d0c11cb4135751d12a2e — DOI: https://doi.org/10.1136/bmjmilitary-2025-nato.16
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: