(1084) Choose Your Own Resuscitation: A Pilot of Tabletop Simulation for Critical Care Education

Introduction: Low fidelity simulation is an effective tool for knowledge acquisition in medical education. Table-top is a form of low fidelity simulation that does not involve equipment or physical simulation and is often used for mass casualty/disaster training. We created a table-top simulation tool in a “choose-your-own adventure” format for critical care education so learners can safely test nuanced decision-making in high-stakes resuscitations. To our knowledge, table-top simulation for critical care education has not been previously reported.

Methods: Three clinical cases of respiratory distress, heart failure, and undifferentiated shock were developed. Learners accessed the cases on Google Forms and chose their next steps in resuscitation from a multiple choice list. Each case contained 3 critical decisions for which there was no one correct answer (eg. pressor choice in right heart failure), followed by a case debrief reviewing an approach to these critical decisions. We piloted the cases among emergency medicine residents and faculty at an academic institution. Learners played through each case twice, with the post-test occurring immediately after the debrief. Each possible response was coded as “appropriate = 1”, “neutral = 0”, or “inappropriate = -1” by two independent faculty members. We report on changes in clinical management pre-/post-debrief, demographics, and qualitative feedback.

Results: 38 individual responses were received across 3 cases (14 faculty, 24 residents). Across all responses, the mean pre-test score was 0.75 ± 0.59 vs post-test 0.94 ± 0.27 (p = 0.002). This effect held for both faculty (0.71 ± 0.60 vs 0.93 ± 0.26, p = 0.04) and residents (0.76 ± 0.59 vs 0.94 ± 0.29, p = 0.02). The two groups were not statistically different in the rate of response change or proportion of positive/neutral response change. Qualitative feedback included: the cases were practical, easy to use, and useful for cognitive practice, but lacked nuance due to the multiple choice format.

Conclusions: This innovative table-top simulation tool demonstrated usability for teaching decision making in critical care resuscitations and can be applied in under-/graduate medical education. We next plan to adapt cases to an AI-supported system to enable more flexible learner response.