Simulation-Based Training for Anesthesia Machine Set-up

Background and Review of Literature: The presurgical anesthesia machine check is a critical procedure that all anesthesia providers must be capable of performing. Failing to perform an anesthesia machine check increases morbidity and mortality during patient care. Simulation training for anesthesia providers is a safe and effective educational pathway allowing providers to improve their skills prior to beginning clinical practice. Optimizing learning by modifying simulation practices to follow INACSL practice standards will enhance the learning for future anesthesia providers. Purpose: This DNP project was a quality improvement project to examine the effect on SRNA knowledge, confidence, and satisfaction of learning when comparing anesthesia machine checklist versus simulation-based training. Methods: This DNP project utilized a quality improvement design and was evaluated by the Student Satisfaction and Self-confidence in Learning instrument and a post-test knowledge assessment. Implementation Plan/Procedure: A total of 24 SRNA’s enrolled in Marian University’s nurse anesthesia simulation course were divided into 2 groups. Group one participated in the current practice of an anesthesia machine checkoff, while group two participated in the current practice and the anesthesia machine set-up simulation. Both groups underwent the same checkoff for the current anesthesia machine checkoff. Both groups were given a post-test of the Student Satisfaction and Self-confidence in Learning instrument. Finally, both groups also completed a post-test knowledge assessment. Implications/Conclusion: Overall, the participants in the experimental group scored higher in agreement in the satisfaction (U = 28.0 , p = 0.032 ) and self-confidence of student learning (U = 43.5 , p = 0.273). The experimental group scored higher in the knowledge section. If current practice is modified to incorporate INACSL best practice standards for simulation, nurse anesthesia educational programs will be able to increase confidence and safety of SRNAs as they progress through their anesthesia training.

Creator

• Keesler, Nicholas

Language

• English

Mot-clé

• INACSL
• Anesthesia Machine
• Simulation
• SRNA
• Jeffries Simulation Model

Date created

• 2022

Resource type

• Research Paper

Rights statement

• http://rightsstatements.org/vocab/InC/1.0/