Di Qi1, Adam Ryason2, Nicholas Milef2, Samuel Alfred2, Mohamad Rassoul Abu-Nuwar3, Mojdeh Kappus3, Suvranu De2, Daniel B Jones3. 1. Center for Modeling, Simulation, and Imaging in Medicine, Rensselaer Polytechnic Institute, Troy, NY, USA. qid@rpi.edu. 2. Center for Modeling, Simulation, and Imaging in Medicine, Rensselaer Polytechnic Institute, Troy, NY, USA. 3. Department of Surgery, Beth Israel Deaconess Medical Center, Harvard School of Medicine, Boston, MA, USA.
Abstract
BACKGROUND: Operating room (OR) fires are uncommon but disastrous events. Inappropriate handling of OR fires can result in injuries, even death. Aiming to simulate OR fire emergencies and effectively train clinicians to react appropriately, we have developed an artificial intelligence (AI)-based OR fire virtual trainer based on the principle of the "fire triangle" and SAGES FUSE curriculum. The simulator can predict the user's actions in the virtual OR and provide them with timely feedback to assist with training. We conducted a study investigating the validity of the AI-assisted OR fire trainer at the 2019 SAGES Learning Center. METHODS: Fifty-three participants with varying medical experience were voluntarily recruited to participate in our Institutional Review Board approved study. All participants were asked to contain a fire within the virtual OR. Participants were then asked to fill out a 7-point Likert questionnaire consisting of ten questions regarding the face validation of the AI-assisted OR fire simulator. Shapiro-Wilk tests were conducted to test normality of the scores for each trial. A Friedman's ANOVA with post hoc tests was used to evaluate the effect of multiple trials on performance. RESULTS: On a 7-point scale, eight of the ten questions were rated a mean of 6 or greater (72.73%), especially those relating to the usefulness of the simulator for OR fire-containing training. 79.25% of the participants rated the degree of usefulness of AI guidance over 6 out of 7. The performance of individuals improved significantly over the five trials, χ2(4) = 119.89, p < .001, and there was a significant linear trend of performance r = .97, p = 0.006. A pairwise analysis showed that only after the introduction of AI did performance improve significantly. CONCLUSIONS: The AI-guided OR fire trainer offers the potential to assess OR personnel and teach the proper response to an iatrogenic fire scenario in a safe, repeatable, immersive environment.
BACKGROUND: Operating room (OR) fires are uncommon but disastrous events. Inappropriate handling of OR fires can result in injuries, even death. Aiming to simulate OR fire emergencies and effectively train clinicians to react appropriately, we have developed an artificial intelligence (AI)-based OR fire virtual trainer based on the principle of the "fire triangle" and SAGES FUSE curriculum. The simulator can predict the user's actions in the virtual OR and provide them with timely feedback to assist with training. We conducted a study investigating the validity of the AI-assisted OR fire trainer at the 2019 SAGES Learning Center. METHODS: Fifty-three participants with varying medical experience were voluntarily recruited to participate in our Institutional Review Board approved study. All participants were asked to contain a fire within the virtual OR. Participants were then asked to fill out a 7-point Likert questionnaire consisting of ten questions regarding the face validation of the AI-assisted OR fire simulator. Shapiro-Wilk tests were conducted to test normality of the scores for each trial. A Friedman's ANOVA with post hoc tests was used to evaluate the effect of multiple trials on performance. RESULTS: On a 7-point scale, eight of the ten questions were rated a mean of 6 or greater (72.73%), especially those relating to the usefulness of the simulator for OR fire-containing training. 79.25% of the participants rated the degree of usefulness of AI guidance over 6 out of 7. The performance of individuals improved significantly over the five trials, χ2(4) = 119.89, p < .001, and there was a significant linear trend of performance r = .97, p = 0.006. A pairwise analysis showed that only after the introduction of AI did performance improve significantly. CONCLUSIONS: The AI-guided OR fire trainer offers the potential to assess OR personnel and teach the proper response to an iatrogenic fire scenario in a safe, repeatable, immersive environment.
Entities:
Keywords:
Artificial intelligence; Medical training; OR fire; Validation; Virtual reality
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