Rodgers, LauraFrenette, ZacharyPytlak, Brendan2026-08-272026-08-27https://hdl.handle.net/10323/22195Background/Purpose: Management of a cannot-intubate, cannot-ventilate (CICV) scenario remains a core anesthesia competency; however, technical, and human factors, rooted in certified registered nurse anesthetists (CRNA) perceptions and skill proficiency, contribute to poor success rates and negative outcomes related to reestablishing an airway via cricothyrotomy (Boet et al., 2011; Silverio et al., 2021). Despite the rarity of CICV events requiring cricothyrotomy (1 in 50,000), they result in 25% of anesthesia-related deaths, with more than two-thirds performed too late to change outcome (Onrubia et al., 2018; Wittwer et al., 2019). Traditional simulation cannot adequately fill education demands due to cost; therefore, augmented reality (AR) was introduced as a novel, yet promising, extension to simulation for healthcare education (Hauze et al. 2019). When asked, CRNAs noted a desire for proficiency in this skill, therefore we investigated whether CRNAs would demonstrate greater confidence, knowledge, and skill in performing a cricothyrotomy, after simulation using AR technology. Method: This quality improvement project took place at the Michigan Association of Nurse Anesthetist’s Fall 2022 Conference at the Grand Traverse Resort in Acme, Michigan. Using the Lumis AR platform, an educational module was developed around a CICV scenario requiring cricothyrotomy and was built into an AR-based simulation workshop for CRNA enrollees. Paper-based data collection packets were distributed to each participant to measure pre- and post-education knowledge and confidence, as well as skill performance. A Wilcoxon matched-pairs signed rank test was conducted to determine if there was a significant difference between participants’ pre- and post-education knowledge and confidence. Skill competence was assessed using a standardized skill checklist and descriptive statistics. Results: This workshop provided 24 eligible participants for data analysis. Analysis revealed a statistically significant difference in participant’s composite pre- and post-educational confidence scores (Mean 2.90 to 4.26, p < .001) and knowledge scores (Mean 6.04 to 8.68/10, p < .001). Skill competence, assessed via checklist, revealed an average score of 7.36 (out of 8). Discussion/Conclusion: Findings suggest that AR-based simulation is a reasonable educational technique for improving a CRNA’s perception and ability to safely perform a cricothyrotomy. Additional benefits may include improving independent provider practice and increasing adherence to the difficult airway algorithm, which can reduce time delays for reestablishing the failed airway and improve patient outcomes.cricothyrotomyskillknowledgeCRNAconfidencecertified registered nurse anesthetistsimulationaugmented realityanesthesiaskillperceptions