Sparklinglight Transactions on Artificial Intelligence and Quantum Computing
Abstract
Student registered nurse anesthetists (SRNAs) must swiftly recognize and treat high-risk, low-incidence complications in a high-stress environment. Most SRNAs do not experience high mortality or rare emergencies throughout their training. This project involves developing and implementing two high-fidelity simulations for airway fire and venous air embolism (VAE) to help SRNAs improve their skills in a safe learning environment. Objectives for this project include examining current evidenced-based literature to determine the efficacy of high-fidelity simulation on the SRNA’s knowledge and performance post-simulation, determining the incidence, pathophysiology, and treatments for airway fires and VAE, creating two high-fidelity simulation scenarios, and integrating the scenarios into the SRNAs’ curriculum. The project was conducted at a doctoral nurse anesthesia program in southern Illinois. The project aimed to prepare SRNAs for low-incidence, high-mortality perioperative complications
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