ArticleJournal of the American Medical Informatics Association : JAMIA2016
Automated integration of continuous glucose monitor data in the electronic health record using consumer technology.
Article in Journal of the American Medical Informatics Association : JAMIA, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 76 papers, 1 of them a synthesis 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
76 citing papers in PubMed, 1 synthesis or guideline pooled it, 138 citations in OpenAlex.
- Continuous Glucose Monitors and Automated Insulin Dosing Systems in the Hospital Consensus Guideline.Journal of diabetes science and technology · 2020Guideline
- Efficacy of Personalized Diabetes Self-care Using an Electronic Medical Record-Integrated Mobile App in Patients With Type 2 Diabetes: 6-Month Randomized Controlled Trial.Journal of medical Internet research · 2022Trial
- Electronic blood glucose monitoring impacts on provider and patient behavior.Journal of the American Medical Informatics Association : JAMIA · 2022Trial
- Factors Influencing Physician Adherence to Venous Thromboembolism Risk Assessment Model Recommendations: A Best-Worst Scaling.American journal of cardiovascular drugs : drugs, devices, and other interventions · 2026Article
- Metabolic Responses to Exercise and Nutritional Strategies in Type 1 Diabetes Using Automated Insulin Delivery Systems: A Narrative Review.Metabolites · 2026Review
- Natural Language Processing for Automated Extraction of Continuous Glucose Monitoring Data.Diabetes care · 2025Article
- Operationalizing Decentralized Clinical Trials: Technology Insights from the Trials@Home RADIAL Proof-of-Concept Trial.Clinical pharmacology and therapeutics · 2025Article
- Establishment of a Diabetes-Tailored Data Intelligence Platform Enhances Clinical Care, Enables Risk-Based Monitoring, and Facilitates Population-Health-Based Approaches at a Pediatric Diabetes Network.Journal of diabetes science and technology · 2025Article
- Artificial intelligence-enhanced pain management: the NXTSTIM EcoAI platform.Pain management · 2025Review
- Integrating Mobile Health App Data Into Electronic Medical or Health Record Systems and Its Impact on Health Care Delivery and Patient Health Outcomes: Scoping Review.JMIR mHealth and uHealth · 2025Article
- Integration of Continuous Glucose Monitoring Data into an Electronic Health Record System: Single-Center Implementation.Journal of diabetes science and technology · 2025Article
- Postprandial Glucose: A Variable in Continuum.Clinical medicine insights. Endocrinology and diabetes · 2025Review
- Article
- New Horizons for Consumer-Mediated Health Information Exchange.Yearbook of medical informatics · 2024Review
- Defining and Improving Outcomes Measurement for Virtual Care: Report from the VHA State-of-the-Art Conference on Virtual Care.Journal of general internal medicine · 2024Review
- Evaluating Pharmacists' Time Collecting Self-Monitoring Blood Glucose Data.Federal practitioner : for the health care professionals of the VA, DoD, and PHS · 2023Article
- Direct-to-patient digital diagnostics in primary care: Opportunities, challenges, and conditions necessary for responsible digital diagnostics.The European journal of general practice · 2023Article
- Article
- Visualization of Patient-Generated Health Data: A Scoping Review of Dashboard Designs.Applied clinical informatics · 2023Article
- Real-World Evidence of a Hospital-Linked Digital Health App for the Control of Hypertension and Diabetes Mellitus in South Korea: Nationwide Multicenter Study.JMIR formative research · 2023Article
16 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
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The diabetes healthcare provider plays a key role in interpreting blood glucose trends, but few institutions have successfully integrated patient home glucose data in the electronic health record (EHR). Published implementations to date have required custom interfaces, which limit wide-scale replication. We piloted automated integration of continuous glucose monitor data in the EHR using widely available consumer technology for 10 pediatric patients with insulin-dependent diabetes. Establishment of a passive data communication bridge via a patient's/parent's smartphone enabled automated integration and analytics of patient device data within the EHR between scheduled clinic visits. It is feasible to utilize available consumer technology to assess and triage home diabetes device data within the EHR, and to engage patients/parents and improve healthcare provider workflow.
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.