Evidence map›Paper›PMID 41466955›Full record

ArticleCureus2025

Understanding Decision Making in Airway Management Using a Cognitive Task Analysis Approach: A Case Study in the Emergency Department Resuscitation Area.

Daniella Cooper

Abstract read
In one paragraph

Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Daniella CooperDepartment of Medical Education, The Academy, Great Western Hospital, Swindon, GBR.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHealthcare 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.

objectivesThis 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.

methodsA 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.

resultsThe 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.

conclusionsThis 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.

Indexed as

cognitive task analysisdecision makingemergency airway managementemergency departmenthuman factors

Identifiers

PMID41466955
PMCPMC12744515

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.