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.
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.
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.
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.
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The research reported in this article was supported by the NIH/NIBIB under Award Number 2R01EB005807, 5R01EB010037, 1R01EB009362, 1R01EB014305, 1R01EB025241; NIH/NHLBI under Award Number 5R01HL119248; NIH/NCI under Award Number 1R01CA197491; and NIH under Award Number R44OD018334.
Dr. Daniel B. Jones has no relevant conflicts related to this manuscript and is on the advisory board of Allurion Technologies Inc. Drs. Di Qi, Adam Ryason, Nicholas Milef, Samuel Alfred, Mohamad Rassoul Abu-Nuwar, Mojdeh Kappus, and Suvranu De have no conflicts of interest or financial ties to disclose.
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Qi, D., Ryason, A., Milef, N. et al. Virtual reality operating room with AI guidance: design and validation of a fire scenario. Surg Endosc 35, 779–786 (2021). https://doi.org/10.1007/s00464-020-07447-1
- OR fire
- Virtual reality
- Artificial intelligence
- Medical training