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Exploring Anesthesia Provider Preferences for Precision Feedback: Preference Elicitation Study.
Zach Landis-Lewis1, Chris A Andrews2, Colin A Gross3
1Department of Learning Health Sciences, University of Michigan, Ann Arbor, MI, United States.
Anesthesia providers have diverse preferences for precision feedback, finding it beneficial for continuous learning. Tailoring feedback is key, as a one-size-fits-all approach is insufficient for improving healthcare performance.
Area of Science:
- Healthcare professional development
- Medical education technology
- Clinical quality improvement
Background:
- Continuous learning is crucial for healthcare professionals due to rapid biomedical knowledge expansion.
- Clinical quality dashboards offer feedback but often suffer from low engagement.
- Personalized feedback, responsive to individual needs and preferences, is largely absent in current systems.
Purpose of the Study:
- To explore anesthesia provider preferences for precision feedback.
- To understand how to enhance the effectiveness of performance feedback in healthcare.
Main Methods:
- Developed precision feedback messages across four performance scenarios.
- Employed an experimental design to compare message versions.
- Recruited anesthesia providers to elicit preferences and rate perceived benefits on a 5-point Likert scale.
Main Results:
- Thirty-five anesthesia providers participated, showing diverse yet internally consistent preferences.
- Preferences for message temporality and display format were consistent within individuals.
- Preferred messages received high ratings for perceived benefit to clinical practice (mean 4.27/5).
Conclusions:
- Healthcare professionals exhibit varied but consistent preferences for precision feedback.
- A "one-size-fits-most" feedback strategy is inadequate.
- Precision feedback systems show promise for enhancing continuous learning by accommodating individual preferences.
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