ArticleJMIR mHealth and uHealth2018
Managing Patient-Generated Health Data Through Mobile Personal Health Records: Analysis of Usage Data.
Article in JMIR mHealth and uHealth, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 2 of them syntheses that pooled it.
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Who cites it
33 citing papers in PubMed, 2 syntheses or guidelines pooled it, 64 citations in OpenAlex.
- Functionalities and Issues in the Implementation of Personal Health Records: Systematic Review.Journal of medical Internet research · 2021Pooled it
- Pooled it
- Impact of Personal Health Records and Wearables on Health Outcomes and Patient Response: Three-Arm Randomized Controlled Trial.JMIR mHealth and uHealth · 2019Trial
- Medical and Biomedical Students' Perspective on Digital Health and Its Integration in Medical Curricula: Recent and Future Views.International journal of environmental research and public health · 2025Article
- Perceptions and Willingness of Patients and Caregivers on the Utilization of Patient-Generated Health Data: A Cross-Sectional Survey.International journal of environmental research and public health · 2025Article
- User Engagement with A Multimodal Conversational Agent for Self-Care and Chronic Disease Management: A Retrospective Analysis.Journal of medical systems · 2025Article
- A randomized controlled trial of a digital lifestyle intervention involving postoperative patients with colorectal cancer.NPJ digital medicine · 2025Article
- Impact of encounters on patient app use: results of a tethered mobile personal health record usage pattern analysis.BMC health services research · 2024Article
- Article
- A Novel IMU-Based System for Work-Related Musculoskeletal Disorders Risk Assessment.Sensors (Basel, Switzerland) · 2024Article
- Quality of Care in Hospitals and the Use of Mobile-Based Personal Health Record Applications: An Exploratory Study Using National Hospital Evaluation Data.Healthcare (Basel, Switzerland) · 2024Article
- Patient-Generated Health Data (PGHD): Understanding, Requirements, Challenges, and Existing Techniques for Data Security and Privacy.Journal of personalized medicine · 2024Review
- A qualitative study of factors influencing ePHR adoption by caregivers and care providers of Alzheimer's patients: An extension of the unified theory of acceptance and use of technology model.Health science reports · 2023Article
- Factors Associated with Reducing Disparities in Electronic Personal Heath Records Use Among Non-Hispanic White and Hispanic Adults.Journal of racial and ethnic health disparities · 2023Article
- Patients Managing Their Medical Data in Personal Electronic Health Records: Scoping Review.Journal of medical Internet research · 2022Article
- Study of the factors influencing the use of MyData platform based on personal health record data sharing system.BMC medical informatics and decision making · 2022Article
- HL7 FHIR with SNOMED-CT to Achieve Semantic and Structural Interoperability in Personal Health Data: A Proof-of-Concept Study.Sensors (Basel, Switzerland) · 2022Article
- Assessing Engagement With Patient-Generated Health Data Recording and Its Impact on Health Behavior Changes in Multicomponent Interventions: Supplementary Analysis.JMIR formative research · 2022Article
- Promoting Exercise Training Remotely.Life (Basel, Switzerland) · 2022Review
- Understanding the Current Landscape of Direct-to-Consumer Health Literacy Interventions.Perspectives in health information managemen · 2022Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPersonal health records (PHRs) and mHealth apps are considered essential tools for patient engagement. Mobile PHRs (mPHRs) can be a platform to integrate patient-generated health data (PGHD) and patients' medical information. However, in previous studies, actual usage data and PGHD from mPHRs have not been able to adequately represent patient engagement.
objectiveBy analyzing 5 years' PGHD from an mPHR system developed by a tertiary hospital in South Korea, we aimed to evaluate how PGHD were managed and identify issues in PGHD management based on actual usage data. Additionally, we analyzed how to improve patient engagement with mPHRs by analyzing the actively used services and long-term usage patterns.
methodsWe gathered 5 years (December 2010 to December 2015) of log data from both hospital patients and general users of the app. We gathered data from users who entered PGHD on body weight, blood pressure (BP), blood glucose levels, 10-year cardiovascular disease (CVD) risk, metabolic syndrome risk, medication schedule, insulin, and allergy. We classified users according to whether they were patients or general users based on factors related to continuous use (≥28 days for weight, BP, and blood glucose, and ≥180 days for CVD and metabolic syndrome), and analyzed the patients' characteristics. We compared PGHD entry counts and the proportion of continuous users for each PGHD by user type.
resultsThe total number of mPHR users was 18,265 (patients: n=16,729, 91.59%) with 3620 users having entered weight, followed by BP (n=1625), blood glucose (n=1374), CVD (n=764), metabolic syndrome (n=685), medication (n=252), insulin (n=72), and allergy (n=61). Of those 18,256 users, 3812 users had at least one PGHD measurement, of whom 175 used the PGHD functions continuously (patients: n=142, 81.14%); less than 1% of the users had used it for more than 4 years. Except for weight, BP, blood glucose, CVD, and metabolic syndrome, the number of PGHD records declined. General users' continuous use of PGHD was significantly higher than that of patients in the blood glucose (P<.001) and BP (P=.03) functions. Continuous use of PGHD in health management (BP, blood glucose, and weight) was significantly greater among older users (P<.001) and men (P<.001). In health management (BP, weight, and blood glucose), overall chronic disease and continuous use of PGHD were not statistically related (P=.08), but diabetes (P<.001) and cerebrovascular diseases (P=.03) were significant.
conclusionsAlthough a small portion of users managed PGHD continuously, PGHD has the potential to be useful in monitoring patient health. To realize the potential, specific groups of continuous users must be identified, and the PGHD service must target them. Further evaluations for the clinical application of PGHD, feedback regarding user interfaces, and connections with wearable devices are needed.
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