The effectiveness of a novel, algorithm-based difficult airway curriculum for air medical crews using human patient simulators

Prehosp Emerg Care. 2007 Jan-Mar;11(1):72-9. doi: 10.1080/10903120601023370.

Abstract

Introduction: Airway management is one of the most important skills possessed by flight crews. However, few data exist about the efficacy of various educational approaches. Traditional models for airway training, including cadaver labs, operating room exposure, and clinical apprenticeships, are scarce and offer variable educational quality. The objective of this analysis was to evaluate the effectiveness of a simulator-based difficult airway curriculum in a large, aeromedical company.

Methods: Simulation training was integrated into existing airway training for all crew members; an original difficult airway algorithm was used to guide scenarios. To evaluate its effectiveness, rapid sequence intubation (RSI) success before and after curriculum implementation was determined. In addition, crew members rated their confidence with various aspects of airway management before and after exposure to the airway workshops.

Results: First attempt and overall ETI success improved from 71.3% and 89.3% before (n=261) to 87.5% and 94.6% after (n=504) implementation of the algorithm and simulation training, whereas the incidence of hypoxic arrests during RSI decreased from 2.7% to 0.2% (p<0.01 for all comparisons). Crew members reported improvements in confidence with regard to all aspects of airway management following participation in the simulation workshops.

Conclusions: A novel, integrated airway management curriculum using treatment algorithms and simulation appeared to be effective for improving RSI success among air medical crews in this program.

Publication types

  • Comparative Study

MeSH terms

  • Air Ambulances*
  • Airway Obstruction / therapy*
  • Algorithms*
  • California
  • Curriculum*
  • Emergency Medical Technicians / education*
  • Humans
  • Inservice Training
  • Intubation, Intratracheal / methods
  • Nevada
  • Patient Simulation*