A Cognitive Modeling Approach to Decision Support Tool Design for Anesthesia Provider Crisis Management.

Area of Science:

• Human-Computer Interaction
• Anesthesiology
• Medical Informatics

Background:

• Existing operating room (OR) patient monitors offer limited decision support for anesthesia providers during critical events.
• Current crisis management decision support tools (DSTs) often lack treatment recommendations, highlighting a need for enhanced functionality.

Purpose of the Study:

• To design and develop a human-centered crisis management DST for anesthesia providers.
• To improve prompt and accurate decision-making during OR crises through advanced cognitive modeling and interface design.

Main Methods:

• Conducted hierarchical task analysis and cognitive task analysis to understand anesthesia provider procedures and information needs during critical incidents.
• Developed a computational cognitive model using Goals, Operators, Methods, Selection rules (GOMS) Language.
• Prototyped an OR monitor interface based on ecological interface design principles to present DST output.

Main Results:

• A DST prototype was developed, integrating cognitive modeling with an intuitive interface.
• Preliminary assessment by anesthesiology and usability experts indicated a willingness to use the tool.
• Experts recommended the DST for junior anesthesia providers in the perioperative setting.

Conclusions:

• The human-centered design approach shows promise for developing effective crisis management DSTs.
• The DST has the potential to enhance anesthesia provider performance during OR crises.
• Further research is needed for formal validation and comparison with actual clinical decision-making.