ArticleBioinformatics (Oxford, England)2019
PatientExploreR: an extensible application for dynamic visualization of patient clinical history from electronic health records in the OMOP common data model.
Article in Bioinformatics (Oxford, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.
What it found
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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
18 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Toward an Interdisciplinary Approach to Constructing Care Delivery Pathways From Electronic Health Care Databases to Support Integrated Care in Chronic Conditions: Systematic Review of Quantification and Visualization Methods.Journal of medical Internet research · 2023Pooled it
- The Sandbox Approach and its Potential for Use in Health Technology Assessment: A Literature Review.Applied health economics and health policy · 2021Pooled it
- ViMDT: a clinical data visual analysis tool for multi-disciplinary treatment of lung cancer.Clinical and experimental medicine · 2026Article
- Establishment of a visualization platform for ADR query and analysis: an example of severe skin adverse reactions caused by sulfonylureas.European journal of clinical pharmacology · 2025Article
- Kineret: Israel's Largest Hospital Network Transformed into the OMOP common data model for collaborative research.PloS one · 2025Article
- Hospital Length of Stay Prediction for Planned Admissions Using Observational Medical Outcomes Partnership Common Data Model: Retrospective Study.Journal of medical Internet research · 2024Article
- Implementation of the Observational Medical Outcomes Partnership Model in Electronic Medical Record Systems: Evaluation Study Using Factor Analysis and Decision-Making Trial and Evaluation Laboratory-Best-Worst Methods.JMIR medical informatics · 2024Article
- Harnessing EHR data for health research.Nature medicine · 2024Review
- VisualSphere: a Web-based Interactive Visualization System for Clinical Research Data.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2024Article
- Review
- Observational
- ricu: R's interface to intensive care data.GigaScience · 2022Article
- Review
- Enhancing Diagnosis Through Technology: Decision Support, Artificial Intelligence, and Beyond.Critical care clinics · 2022Review
- FIBER: enabling flexible retrieval of electronic health records data for clinical predictive modeling.JAMIA open · 2021Article
- Evaluation of the Privacy Risks of Personal Health Identifiers and Quasi-Identifiers in a Distributed Research Network: Development and Validation Study.JMIR medical informatics · 2021Article
- Artificial Intelligence in Cancer Research and Precision Medicine.Cancer discovery · 2021Review
- Blockchain-Authenticated Sharing of Genomic and Clinical Outcomes Data of Patients With Cancer: A Prospective Cohort Study.Journal of medical Internet research · 2020Article
Corrections and comments
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Authors and funding
22 authors.
Funding
Abstract
motivationElectronic health records (EHRs) are quickly becoming omnipresent in healthcare, but interoperability issues and technical demands limit their use for biomedical and clinical research. Interactive and flexible software that interfaces directly with EHR data structured around a common data model (CDM) could accelerate more EHR-based research by making the data more accessible to researchers who lack computational expertise and/or domain knowledge.
resultsWe present PatientExploreR, an extensible application built on the R/Shiny framework that interfaces with a relational database of EHR data in the Observational Medical Outcomes Partnership CDM format. PatientExploreR produces patient-level interactive and dynamic reports and facilitates visualization of clinical data without any programming required. It allows researchers to easily construct and export patient cohorts from the EHR for analysis with other software. This application could enable easier exploration of patient-level data for physicians and researchers. PatientExploreR can incorporate EHR data from any institution that employs the CDM for users with approved access. The software code is free and open source under the MIT license, enabling institutions to install and users to expand and modify the application for their own purposes. AVAILABILITY AND IMPLEMENTATION: PatientExploreR can be freely obtained from GitHub: https://github.com/BenGlicksberg/PatientExploreR. We provide instructions for how researchers with approved access to their institutional EHR can use this package. We also release an open sandbox server of synthesized patient data for users without EHR access to explore: http://patientexplorer.ucsf.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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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.