Anesthesia takes place in a complex, high-stakes environment where humans and technologies interact to provide medical care to patients. Providing adequate decision support for individuals and teams in anesthesia emergencies is important because emergencies are infrequent and complex. Current designs of decision support in airway management are not context specific and lack a consideration of how decisions are made under time pressure. To fill this gap, this study used frameworks from cognitive systems engineering to explore decisions of experienced anesthesia providers. The goal was to identify the decision pathways used in challenging airway management situations. The critical decision method was employed to interview anesthesia providers about a challenging incident they had experienced. Results illustrated that decisions were based on prior experience and made through a process of recognition. The vast majority of decisions were recognition primed, characterized by a direct link between cue familiarity and action generation. A few decisions involved concurrent option comparison, which was still based on situation recognition. Different cues received through teamwork, technologies, and patients contributed to the decisions. As different cognitive pathways may require different design solutions, the findings of this study are being used to help develop decision support tools in anesthesia.
|Number of pages||18|
|Journal||Journal of Cognitive Engineering and Decision Making|
|Publication status||Published - 1 Dec 2017|
- cognitive systems engineering
- cognitive task analysis
- health care delivery
- recognition-primed decision making