ArticleJMIR diabetes2019
Design and Prestudy Assessment of a Dashboard for Presenting Self-Collected Health Data of Patients With Diabetes to Clinicians: Iterative Approach and Qualitative Case Study.
Article in JMIR diabetes, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- mHealth-Enabled Stroke Screening for Pediatric Sickle Cell Disease in Low-Resource Settings: Systematic Literature Review of Critical Barriers, Emerging Technologies, and AI-Driven Solutions.JMIR pediatrics and parenting · 2026Review
- Exploring Clinician Experiences With a Digital Platform Supporting Orthopedic Care That Integrates Patient-Generated Health Data: Qualitative Study of Early Users.JMIR human factors · 2025Article
- Improving the Implementation of Patient-Reported Outcome Measure in Clinical Practice: Tackling Current Challenges With Innovative Digital Communication Technologies.Journal of medical Internet research · 2025Article
- Developing and Evaluating SEE-Diabetes: A Patient-Centered Educational Decision Support System for Diabetes Care.Journal of evaluation in clinical practice · 2025Article
- Development, Implementation, and Evaluation Methods for Dashboards in Health Care: Scoping Review.JMIR medical informatics · 2024Article
- Usability of the IDDEAS prototype in child and adolescent mental health services: A qualitative study for clinical decision support system development.Frontiers in psychiatry · 2023Article
- New Standards for Clinical Decision Support: A Survey of The State of Implementation.Yearbook of medical informatics · 2021Review
- Human Factors and Organizational Issues.Yearbook of medical informatics · 2020Review
- Graphical Presentations of Clinical Data in a Learning Electronic Medical Record.Applied clinical informatics · 2020Article
- Measuring the Effects of Sharing Mobile Health Data During Diabetes Consultations: Protocol for a Mixed Method Study.JMIR research protocols · 2020Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIntroducing self-collected health data from patients with diabetes into consultation can be beneficial for both patients and clinicians. Such an initiative can allow patients to be more proactive in their disease management and clinicians to provide more tailored medical services. Optimally, electronic health record systems (EHRs) should be able to receive self-collected health data in a standard representation of medical data such as Fast Healthcare Interoperability Resources (FHIR), from patients systems like mobile health apps and display the data directly to their users-the clinicians. However, although Norwegian EHRs are working on implementing FHIR, no solution or graphical interface is available today to display self-collected health data.
objectiveThe objective of this study was to design and assess a dashboard for displaying relevant self-collected health data from patients with diabetes to clinicians.
methodsThe design relied on an iterative participatory process involving workshops with patients, clinicians, and researchers to define which information should be available and how it should be displayed. The assessment is based on a case study, presenting an instance of the dashboard populated with data collected from one patient with diabetes type 1 (in-house researcher) face-to-face by 14 clinicians. We performed a qualitative analysis based on usability, functionality, and expectation by using responses to questionnaires that were distributed to the 14 clinicians at the end of the workshops and collected before the participants left. The qualitative assessment was guided by the Standards for Reporting Qualitative Research.
resultsWe created a dashboard permitting clinicians to assess the reliability of self-collected health data, list all collected data including medical calculations, and highlight medical situations that need to be investigated to improve the situation of the patients. The dashboard uses a combination of tables, graphs, and other visual representations to display the relevant information. Clinicians think that this type of solution will be useful during consultations every day, especially for patients living in remote areas or those who are technologically interested.
conclusionsDisplaying self-collected health data during consultations is not enough for clinicians; the data reliability has to be assured and the relevant information needs to be extracted and displayed along with the data to ease the introduction during a medical encounter. The prestudy assessment showed that the system provides relevant information to meet clinicians' need and that clinicians were eager to start using it during consultations. The system has been under testing in a medical trial since November 2018, and the first results of its assessment in a real-life situation are expected in the beginning of next year (2020).
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