As part of her doctoral dissertation, Dr. Noa Segall (under the direction of Dr. David Kaber, North Carolina State University, and guidance of Dr. Wright and Dr. Taekman in the Duke Human Simulation and Patient Safety Center) developed a computerized system for detection, diagnosis, and treatment of perioperative myocardial ischemia and infarction (MI).
The development approach involved:
- Performing a hierarchical task analysis to identify anesthetist procedures in detecting, diagnosing and treating MI.
- Carrying out a goal-directed task analysis to elicit goals, decisions, and information requirements of anesthetists during this crisis management procedure.
- Coding the information collected in the task analyses using a computational cognitive model.
- Prototyping an interface to present output from the cognitive model using ecological interface design principles.
Validation of the decision support tool involved subjective evaluations of the tool and its interface design through an applicability assessment and a usability inspection. For the applicability assessment, three expert anesthesiologists were recruited to observe the tool perform during two hypothetical scenarios, hypotension and MI. They provided feedback on the clinical accuracy of the information presented and all three experts indicated that, further refined, they would use the tool in the operating room. Heuristic evaluation was employed to inspect the usability of the interface. Two usability experts and the three anesthesiologists were asked to identify human-computer interaction design heuristics that were violated in the interface and to describe the problems identified. The reviewers commented on the use of fonts and colors, medical terminology, organization of information, and more. Future efforts by our research team will incorporate the use of more flexible interface design software to develop user interfaces with a wider range of presentation and interaction methods.
Funding: Department of Anesthesiology, Duke University Medical Center; Department of Industrial Engineering, North Carolina State University