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Understanding Decision Making in Airway Management Using a Cognitive Task Analysis Approach: A Case Study in the
1Department of Medical Education, The Academy, Great Western Hospital, Swindon, GBR.
Background:
Healthcare advances are rapid, as are the changes in human factors approaches to healthcare, such as designing safer workplaces and improving communication and teamwork. It is necessary for work to be done to improve the congruency of these for patient safety and the efficiency of systems. Emergency departments (EDs) are rapidly changing environments, so it is difficult for staff to adapt to them.
Objectives:
This project explores critical themes where applying a human factors approach to decision-making during emergency airway management in the ED resuscitation area (ED resus) can enhance patient safety, optimise team performance, and improve overall system efficiency.
Methods:
A homogenous sample of 25 frontline staff from operating theatres and ED at Queen's Medical Centre, Nottingham, England, were interviewed using a cognitive task analysis (CTA) technique to determine what affects decision-making regarding emergency airway management in resus. Transcripts were coded using NVivo 12 software (QSR International, Burlington, MA, USA) and analysed using thematic analysis techniques to identify key themes for areas of improvement.
Results:
The themes that emerged from analysis were split into system components and decision-making factors about emergency airway management. System components consisted of the equipment present and the training that staff receive. Decision-making factors included cognitive elements, planning, policies and guidelines, and teamwork. The emergent themes reflected the use of healthcare systems frameworks in terms of the human factors approach.
Conclusions:
This study exhibits the use of human factors and the CTA method to discover specific recommendations for the improvement of patient safety and systems efficiency regarding emergency airway management in ED resus. These recommendations need to first be reviewed by a high-level systems approach before being implemented in the clinical setting.
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