Appl Clin Inform 2023; 14(05): 996-1007
DOI: 10.1055/s-0043-1777103
Research Article

User-Centered Evaluation and Design Recommendations for an Internal Medicine Resident Competency Assessment Dashboard

Scott Vennemeyer
1   Department of Biomedical Informatics, College of Medicine, University of Cincinnati, Ohio, United States
,
Benjamin Kinnear
2   Department of Pediatrics, College of Medicine, University of Cincinnati, Ohio, United States
5   Department of Internal Medicine, College of Medicine, University of Cincinnati, Ohio, United States
,
Andy Gao
1   Department of Biomedical Informatics, College of Medicine, University of Cincinnati, Ohio, United States
3   Medical Sciences Baccalaureate Program, College of Medicine, University of Cincinnati, Ohio, United States
,
Siyi Zhu
1   Department of Biomedical Informatics, College of Medicine, University of Cincinnati, Ohio, United States
4   School of Design, College of Design, Architecture, Art, and Planning (DAAP), University of Cincinnati, Ohio, United States
,
Anunita Nattam
1   Department of Biomedical Informatics, College of Medicine, University of Cincinnati, Ohio, United States
3   Medical Sciences Baccalaureate Program, College of Medicine, University of Cincinnati, Ohio, United States
,
Michelle I. Knopp
5   Department of Internal Medicine, College of Medicine, University of Cincinnati, Ohio, United States
6   Division of Hospital Medicine, Cincinnati Children's Hospital Medical Center, Department of Pediatrics, College of Medicine, University of Cincinnati, Ohio, United States
,
Eric Warm
5   Department of Internal Medicine, College of Medicine, University of Cincinnati, Ohio, United States
,
Danny T.Y. Wu
1   Department of Biomedical Informatics, College of Medicine, University of Cincinnati, Ohio, United States
2   Department of Pediatrics, College of Medicine, University of Cincinnati, Ohio, United States
3   Medical Sciences Baccalaureate Program, College of Medicine, University of Cincinnati, Ohio, United States
4   School of Design, College of Design, Architecture, Art, and Planning (DAAP), University of Cincinnati, Ohio, United States
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Abstract

Objectives Clinical Competency Committee (CCC) members employ varied approaches to the review process. This makes the design of a competency assessment dashboard that fits the needs of all members difficult. This work details a user-centered evaluation of a dashboard currently utilized by the Internal Medicine Clinical Competency Committee (IM CCC) at the University of Cincinnati College of Medicine and generated design recommendations.

Methods Eleven members of the IM CCC participated in semistructured interviews with the research team. These interviews were recorded and transcribed for analysis. The three design research methods used in this study included process mapping (workflow diagrams), affinity diagramming, and a ranking experiment.

Results Through affinity diagramming, the research team identified and organized opportunities for improvement about the current system expressed by study participants. These areas include a time-consuming preprocessing step, lack of integration of data from multiple sources, and different workflows for each step in the review process. Finally, the research team categorized nine dashboard components based on rankings provided by the participants.

Conclusion We successfully conducted user-centered evaluation of an IM CCC dashboard and generated four recommendations. Programs should integrate quantitative and qualitative feedback, create multiple views to display these data based on user roles, work with designers to create a usable, interpretable dashboard, and develop a strong informatics pipeline to manage the system. To our knowledge, this type of user-centered evaluation has rarely been attempted in the medical education domain. Therefore, this study provides best practices for other residency programs to evaluate current competency assessment tools and to develop new ones.

Protection of Human and Animal Subjects

The study protocol was reviewed by the University of Cincinnati IRB and determined as “Nonhuman subject” research (#2019-1418). All the research data were de-identified.




Publikationsverlauf

Eingereicht: 03. Juni 2023

Angenommen: 25. Oktober 2023

Artikel online veröffentlicht:
20. Dezember 2023

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