Appl Clin Inform 2022; 13(02): 380-390
DOI: 10.1055/s-0042-1744388
CIC 2021

Design, Usability, and Acceptability of a Needs-Based, Automated Dashboard to Provide Individualized Patient-Care Data to Pediatric Residents

Julia K.W. Yarahuan
1   Division of Pediatric Hospital Medicine, Department of Pediatrics, Boston Children's Hospital, Boston, Massachusetts, United States
Huay-Ying Lo
2   Section of Pediatric Hospital Medicine, Department of Pediatrics, Baylor College of Medicine/Texas Children's Hospital, Houston, Texas, United States
Lanessa Bass
2   Section of Pediatric Hospital Medicine, Department of Pediatrics, Baylor College of Medicine/Texas Children's Hospital, Houston, Texas, United States
Jeff Wright
3   Information Services, Texas Children's Hospital, Houston, Texas, United States
Lauren M. Hess
2   Section of Pediatric Hospital Medicine, Department of Pediatrics, Baylor College of Medicine/Texas Children's Hospital, Houston, Texas, United States
› Author Affiliations
Funding None.


Background and Objectives Pediatric residency programs are required by the Accreditation Council for Graduate Medical Education to provide residents with patient-care and quality metrics to facilitate self-identification of knowledge gaps to prioritize improvement efforts. Trainees are interested in receiving this data, but this is a largely unmet need. Our objectives were to (1) design and implement an automated dashboard providing individualized data to residents, and (2) examine the usability and acceptability of the dashboard among pediatric residents.

Methods We developed a dashboard containing individualized patient-care data for pediatric residents with emphasis on needs identified by residents and residency leadership. To build the dashboard, we created a connection from a clinical data warehouse to data visualization software. We allocated patients to residents based on note authorship and created individualized reports with masked identities that preserved anonymity. After development, we conducted usability and acceptability testing with 11 resident users utilizing a mixed-methods approach. We conducted interviews and anonymous surveys which evaluated technical features of the application, ease of use, as well as users' attitudes toward using the dashboard. Categories and subcategories from usability interviews were identified using a content analysis approach.

Results Our dashboard provides individualized metrics including diagnosis exposure counts, procedure counts, efficiency metrics, and quality metrics. In content analysis of the usability testing interviews, the most frequently mentioned use of the dashboard was to aid a resident's self-directed learning. Residents had few concerns about the dashboard overall. Surveyed residents found the dashboard easy to use and expressed intention to use the dashboard in the future.

Conclusion Automated dashboards may be a solution to the current challenge of providing trainees with individualized patient-care data. Our usability testing revealed that residents found our dashboard to be useful and that they intended to use this tool to facilitate development of self-directed learning plans.

Protection of Human and Animal Subjects

Our institutional review board reviewed and approved this study.

Supplementary Material

Publication History

Received: 03 October 2021

Accepted: 05 February 2022

Article published online:
16 March 2022

© 2022. Thieme. All rights reserved.

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

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