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Related Experiment Video

Updated: May 20, 2026

Simulator Training for Endovascular Neurosurgery

Simulator Training for Endovascular Neurosurgery

Published on: May 6, 2020

High-fidelity simulation for continuing education in nurse anesthesia.

M Roseann Cannon-Diehl¹, Susan M Rugari, Terri S Jones

¹Texas Christian University Harris College of Nursing and Health Sciences, School of Nurse Anesthesia, Forth Worth, Texas, USA. roseann.cannon@tcu.edu

|August 2, 2012

Summary

This summary is machine-generated.

High-fidelity simulation (HFS) offers valuable continuing education for anesthesia providers. Nurse anesthetists identified advanced cardiac life support, machine malfunctions, and malignant hyperthermia as key simulation training areas.

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Published on: August 9, 2024

Area of Science:

Healthcare Education
Medical Simulation
Anesthesiology

Background:

Simulation is transforming healthcare education, yet continuing education opportunities for anesthesia providers using simulation are limited.
High-fidelity simulation (HFS) presents a potential avenue for enhancing anesthesia provider training and skill maintenance.

Purpose of the Study:

To explore the perceived usefulness of HFS for continuing education among nurse anesthetists.
To assess nurse anesthetists' current exposure to and desired simulation training scenarios.

Main Methods:

A needs assessment was conducted with 22 practicing nurse anesthetists.
Participants ranked their experience with 11 anesthesia events and identified preferred events for simulation-based continuing education.

Main Results:

71% of participants favored HFS for advanced cardiac life support, anesthesia machine mishaps, and malignant hyperthermia scenarios.
81% viewed simulation as a valuable competency assessment tool, though opinions on its use for recertification were mixed.

Conclusions:

HFS is perceived as a valuable tool for continuing education and competency assessment in nurse anesthesia.
Further development of HFS continuing education programs is warranted, with specific scenarios identified as high priority.