ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2017
Point of Care Research: Integrating patient-generated data into electronic health records for clinical trials.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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
5 citing papers in PubMed.
- Therapeutic Drug Monitoring and Point-of-Care Technologies: Opportunities and Current Challenges.Therapeutic drug monitoring · 2026Review
- Point-of-Care Testing and Biomarkers in Biliary Diseases: Current Evidence and Future Directions.Journal of clinical medicine · 2025Review
- Understanding Engagement and the Potential Impact of an Electronic Drug Repository: Multi-Methods Study.JMIR formative research · 2022Article
- Innovation in Precision Cardio-Oncology During the Coronavirus Pandemic and Into a Post-pandemic World.Frontiers in cardiovascular medicine · 2020Article
- Personally Collected Health Data for Precision Medicine and Longitudinal Research.Frontiers in medicine · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Integrating patient-generated data into clinical research would improve the reliability of results, especially when longitudinal, chronic, home-based monitoring is needed. To this end, we designed, implemented, and tested a system that allows integrating patient-generated data into electronic case report form (eCRF), using a standards based architecture that ensured the fulfillment of the major requirements for digital data in clinical studies. The system was tested in a clinical investigation for the optimization of deep brain stimulation therapy in patients with Parkinson's disease that required both the collection of patient-generated data and of clinical and neurophysiological data. The validation showed that the implemented system was able to provide a reliable solution for including the patient as direct digital data source, ensuring reliability, integrity, security, attributability, and auditability of data.
Indexed as
Identifiers
29854195PMC5977649What 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.