ArticleJMIR human factors2016
Integrating Patient-Generated Health Data Into Clinical Care Settings or Clinical Decision-Making: Lessons Learned From Project HealthDesign.
Article in JMIR human factors, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 89 papers, 5 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
89 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Use of Patient-Generated Health Data From Consumer-Grade Devices by Health Care Professionals in the Clinic: Systematic Review.Journal of medical Internet research · 2024Pooled it
- How patient-generated health data and patient-reported outcomes affect patient-clinician relationships: A systematic review.Health informatics journal · 2020Pooled it
- Remote symptom monitoring integrated into electronic health records: A systematic review.Journal of the American Medical Informatics Association : JAMIA · 2020Pooled it
- A Systematic Review of Patient-Facing Visualizations of Personal Health Data.Applied clinical informatics · 2019Pooled it
- Converging and diverging needs between patients and providers who are collecting and using patient-generated health data: an integrative review.Journal of the American Medical Informatics Association : JAMIA · 2018Pooled it
- Integrating Consumer-Grade Wearable Devices and Patient-Generated Health Data into Clinical Care: Perspectives from Healthcare Professionals at a Learning Health System.Journal of general internal medicine · 2026Article
- Barriers and Enablers to Integrating Patient-Generated Health Data in Shared Decision-Making From Health Care Professional and Patient Perspectives: Scoping Review.JMIR mHealth and uHealth · 2026Article
- Implementation and Evaluation of a Social Networking Service-Based Mobile Patient-Generated Health Data System With Direct Electronic Medical Record Integration: Prospective Observational Study.JMIR medical informatics · 2026Observational
- Patient and Care Team Perspectives of Barriers to and Facilitators for the Implementation of a Digital Health Program for Depression in Primary Care: Qualitative Study.Journal of medical Internet research · 2026Article
- From data to action: the FRAME conceptual framework for translating consumer wearable feedback into behavior change support.Frontiers in digital health · 2026Article
- Visualization of Experience Sampling Method Data in Mental Health: Qualitative Study of the Physicians' Perspective in Germany.Journal of medical Internet research · 2025Article
- The Impact of Patient-Generated Health Data From Mobile Health Technologies on Health Care Management and Clinical Decision-Making: Narrative Scoping Review.Journal of medical Internet research · 2025Article
- Impact of multidisciplinary nursing interventions and blood glucose control on diabetic foot ulcer healing, patient emotions, and satisfaction.World journal of psychiatry · 2025Article
- 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
- "Everyone Has a Role in This": Evaluating Organizational Readiness for a Digital Solution to Support Hypertension Care Teams and Patients.Applied clinical informatics · 2025Article
- A sociotechnical approach to defining clinical responsibilities for patient-generated health data.NPJ digital medicine · 2025Article
- Attitudes of healthcare professionals and researchers toward wearable and app derived patient generated health data.NPJ digital medicine · 2025Article
- Application of Patient-Generated Health Data Among Older Adults With Cancer: Scoping Review.Journal of medical Internet research · 2025Article
- Streamlining wearable data integration for EHDS: a case study on advancing healthcare interoperability using Garmin devices and FHIR.Frontiers in digital health · 2025Article
- Artificial intelligence and science of patient input: a perspective from people with multiple sclerosis.Frontiers in immunology · 2025Article
29 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPatient-generated health data (PGHD) are health-related data created or recorded by patients to inform their self-care and understanding about their own health. PGHD is different from other patient-reported outcome data because the collection of data is patient-driven, not practice- or research-driven. Technical applications for assisting patients to collect PGHD supports self-management activities such as healthy eating and exercise and can be important for preventing and managing disease. Technological innovations (eg, activity trackers) are making it more common for people to collect PGHD, but little is known about how PGHD might be used in outpatient clinics.
objectiveThe objective of our study was to examine the experiences of health care professionals who use PGHD in outpatient clinics.
methodsWe conducted an evaluation of Project HealthDesign Round 2 to synthesize findings from 5 studies funded to test tools designed to help patients collect PGHD and share these data with members of their health care team. We conducted semistructured interviews with 13 Project HealthDesign study team members and 12 health care professionals that participated in these studies. We used an immersion-crystallization approach to analyze data. Our findings provide important information related to health care professionals' attitudes toward and experiences with using PGHD in a clinical setting.
resultsHealth care professionals identified 3 main benefits of PGHD accessibility in clinical settings: (1) deeper insight into a patient's condition; (2) more accurate patient information, particularly when of clinical relevance; and (3) insight into a patient's health between clinic visits, enabling revision of care plans for improved health goal achievement, while avoiding unnecessary clinic visits. Study participants also identified 3 areas of consideration when implementing collection and use of PGHD data in clinics: (1) developing practice workflows and protocols related to PGHD collection and use; (2) data storage, accessibility at the point of care, and privacy concerns; and (3) ease of using PGHD data.
conclusionsPGHD provides value to both patients and health care professionals. However, more research is needed to understand the benefit of using PGHD in clinical care and to identify the strategies and clinic workflow needs for optimizing these tools.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.