User-Centered Design of a Machine Learning Dashboard for Prediction of Postoperative Complications
Authors' conclusion
Incorporating user needs and preferences into the design of a machine learning dashboard results in a display interface that clinicians rate as highly usable.
Study context
- Population
- Anesthesiology clinicians (attending anesthesiologists, resident physicians, certified registered nurse anesthetists)
- Participants
- 25 clinicians
- Outcome
- Usability of ML dashboard for postoperative complication prediction
Methodological details3-phase, focus groups, card sorting, simulated patient evaluation, think-aloud, thematic analysis
- 3-phase
- Focus groups
- Card sorting
- Simulated patient evaluation
- Think-aloud
- Thematic analysis
Main finding
As reported in the abstract
System Usability Scale score, mean (SD 10.5)
82.5
Original publication
User-Centered Design of a Machine Learning Dashboard for Prediction of Postoperative Complications. Anesth Analg. Published 20 June 2023. doi:10.
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