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Appl Clin Inform 2026; 17(02): 127-137
DOI: 10.1055/a-2823-4533
Research Article

Qualitative User-Centered Design: Programming Changes in a Self-Management Blood Pressure Application

Authors

  • Shannon M. Canfield 

    1   Department of Family and Community Medicine, University of Missouri-Columbia, Columbia, Missouri, United States

  • Abigail J. Rolbiecki

    2   Department of Family and Community Medicine, University of Missouri-Columbia, Colorado State University, Fort Collins, Colorado, United States

  • Parijat Ghosh

    3   Department of Chemical and Biomedical Engineering, University of Missouri-Columbia, Columbia, Missouri, United States

  • Emma Montgomery

    1   Department of Family and Community Medicine, University of Missouri-Columbia, Columbia, Missouri, United States

  • Victoria A. Shaffer

    4   Department of Psychology, University of Missouri-Columbia, Columbia, Missouri, United States

  • Michelle Bobo

    5   Division of Informatics, Clinical Epidemiology and Translational Data Science, Department of Medicine, Oregon Health and Science University, Portland, Oregon, United States

  • Matthew B. Storer

    5   Division of Informatics, Clinical Epidemiology and Translational Data Science, Department of Medicine, Oregon Health and Science University, Portland, Oregon, United States

  • Aisha Ghumman

    5   Division of Informatics, Clinical Epidemiology and Translational Data Science, Department of Medicine, Oregon Health and Science University, Portland, Oregon, United States

  • LeAnne Michaels

    6   Division of Informatics, Clinical Epidemiology and Translational Data Science, Oregon Health and Science University, Portland, Oregon, United States

  • David A. Dorr   ‡

    6   Division of Informatics, Clinical Epidemiology and Translational Data Science, Oregon Health and Science University, Portland, Oregon, United States

  • Richelle J. Koopman   ‡

    1   Department of Family and Community Medicine, University of Missouri-Columbia, Columbia, Missouri, United States
    • COACH Consortium

Funding Information The Agency for Healthcare Research and Quality/DHHS (AHRQ; grant number: R18 HS028579-01A1) funds the study. The content is solely the authors' responsibility and does not necessarily represent the official views of AHRQ.
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Abstract

Background

Electronic patient-centered clinical decision support enhances chronic disease self-management, yet few studies describe how qualitative user feedback is systematically translated into programming improvements. The Collaboration-Oriented Approach to Controlling High Blood Pressure (COACH) is a patient-facing decision support tool for hypertension management, designed for primary care and integration with electronic health records (EHRs) and patient portals.

Objective

This study aimed to describe how end-user feedback informed COACH programming decisions and the MoSCoW (Must have, Should have, Could have, Won't have) method operationalized prioritization for implementation.

Methods

This secondary analysis draws on qualitative data from a Consolidated Framework for Implementation Research (CFIR)-informed data collected during a preimplementation evaluation of COACH with 70 care team members and 18 patients across three academic health systems using Cerner/Oracle and Epic EHRs. CFIR-coded data were reviewed, and design or usability “recommendations” were translated into discrete programming requirements, prioritized using the MoSCoW, and, where possible, completed before a multisite trial.

Results

Seven themes emerged: (1) Timely, actionable alerts, (2) messaging features for follow-up, (3) motivating patients through feedback, (4) reducing data entry burden, (5) setting blood pressure goals, (6) supporting workflow integration, and (7) equity and accessibility. Of the 35 potential recommendations, 25 were translated into changes and prioritized as “Must have” (12), “Should have” (6), and “Could have” (7). Our team completed 19 high-priority features (e.g., setting the blood pressure goal, structured alerts, messaging templates, and visual feedback) before the trial launch.

Conclusion

This study demonstrates a replicable process for integrating qualitative insights into digital health programming through structured prioritization, advancing implementation-focused clinical informatics, and guiding decision-making for the future integration of patient-generated health data, such as home blood pressure monitoring.

Keywords

process management tools - clinical decision support system - ambulatory care/primary care - cardiology - cardiovascular disease

Protection of Human and Animal Subjects

This study adhered to the principles outlined in the Declaration of Helsinki. Additionally, the study received approval from the University of Missouri Institutional Review Board (2091483), with reliance from Oregon Health and Sciences University and Vanderbilt University Medical Center, ensuring that all ethical guidelines and regulations were followed throughout the research process.


Informed Consent

The authors obtained informed consent from all participants prior to their involvement in the research.


Note

COACH Consortium: William Martinez, (Vanderbilt University Medical Center, Nashville, TN); Adam Wright (Vanderbilt University Medical Center, Nashville, TN); Laura Marcial (RTI International, Research Triangle Park, NC); Blake L. Johnson (Oregon Health and Science University, Portland, OR); Elise Russo (Vanderbilt University Medical Center, Nashville, TN); Julia Skapik (National Association of Community Health Centers, Bethesda, MD); Emma Chase (Oregon Health and Science University, Portland, OR); Amy Yates (Oregon Health and Science University, Portland, OR); Jonathan Soffer (Oregon Health and Science University, Portland, OR); Guilherme Del Fiol (Department of Biomedical Informatics, University of Utah, Salt Lake City, UT); Katherine Putnam (Oregon Health and Science University, Portland, OR); Paul James (University of Washington School of Medicine, Seattle, WA); Sheila Markwardt (Oregon Health and Science University, Portland, OR).


‡ These authors are co-mentoring authors.




Publication History

Received: 18 June 2025

Accepted after revision: 26 February 2026

Article published online:
25 March 2026

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