ArticleJournal of diabetes science and technology2025
Integration of Continuous Glucose Monitoring Data into an Electronic Health Record System: Single-Center Implementation.
Article in Journal of diabetes science and technology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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
6 citing papers in PubMed.
- Comprehensive blood glucose level prediction from HbAScientific reports · 2026Article
- Natural Language Processing for Automated Extraction of Continuous Glucose Monitoring Data.Diabetes care · 2025Article
- A personalized federated learning-based glucose prediction algorithm for high-risk glycemic excursion regions in type 1 diabetes.Scientific reports · 2025Article
- Practical Considerations and Implementation of Automated Insulin Delivery Systems.Journal of diabetes science and technology · 2025Review
- Practical Considerations and Implementation of Automated Insulin Delivery Systems.Diabetes technology & therapeutics · 2025Review
- Bridging the digital divide: student-led literacy initiatives in diabetes management.Frontiers in clinical diabetes and healthcare · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Managing data from continuous glucose monitoring (CGM) systems presents challenges to health care provider teams that rely on the electronic health record (EHR) during patient visits. A method of integrating CGM data with the EHR that relies on the Dexcom API was developed by Northwestern Medicine and Dexcom to address these challenges. Here, we describe the data management steps and user interface of the integrated system. Providers can access patients' historical and latest daily CGM data in the form of modal day plots and stacked columns showing time in various glucose concentration ranges. The integration facilitates the acquisition, storage, analysis, and display of CGM data within an EHR system and may be appropriate for deployment in other health care facilities.
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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.