ArticleDiabetes technology & therapeutics2018
A Pilot Study of Use of a Software Platform for the Collection, Integration, and Visualization of Diabetes Device Data by Health Care Providers in a Multidisciplinary Pediatric Setting.
Article in Diabetes technology & therapeutics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses 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
16 citing papers in PubMed, 2 syntheses or guidelines pooled it, 31 citations in OpenAlex.
- Artificial Intelligence-Driven Transformation of Pediatric Diabetes Care: A Systematic Review and Epistemic Meta-Analysis of Diagnostic, Therapeutic, and Self-Management Applications.International journal of molecular sciences · 2026Pooled it
- Continuous Glucose Monitors and Automated Insulin Dosing Systems in the Hospital Consensus Guideline.Journal of diabetes science and technology · 2020Guideline
- 7. Diabetes Technology: Standards of Care in Diabetes-2026.Diabetes care · 2026Review
- Tubeless Insulin Pump Combined with a Cloud-Based Data Management Platform: Real-World Evidence from 14,765 French People with Diabetes.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2025Article
- Caregiver experiences of an integrative patient-centered digital health application for pediatric type 1 diabetes care: Findings from a pilot clinical trial.PLOS digital health · 2025Article
- Determinants of implementation of continuous glucose monitoring for patients with Insulin-Treated type 2 diabetes: a national survey of primary care providers.BMC primary care · 2025Article
- Digital Health Technology in Diabetes Management in the Asia-Pacific Region: A Narrative Review of the Current Scenario and Future Outlook.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2025Review
- 7. Diabetes Technology: Standards of Care in Diabetes-2025.Diabetes care · 2025Review
- 7. Diabetes Technology: Standards of Care in Diabetes-2024.Diabetes care · 2024Review
- The Need for Data Standards and Implementation Policies to Integrate CGM Data into the Electronic Health Record.Journal of diabetes science and technology · 2023Review
- 7. Diabetes Technology: Standards of Care in Diabetes-2023.Diabetes care · 2023Review
- Appropriate Use of Telehealth Visits in Endocrinology: Policy Perspective of the Endocrine Society.The Journal of clinical endocrinology and metabolism · 2022Article
- Smart Insulin Pens: Advancing Digital Transformation and a Connected Diabetes Care Ecosystem.Journal of diabetes science and technology · 2022Article
- Telemedicine in cystic fibrosis.Journal of clinical & translational endocrinology · 2021Article
- Clinical Decision Support and Implications for the Clinician Burnout Crisis.Yearbook of medical informatics · 2020Review
- Challenges with Patient Adoption of Automated Integration of Blood Glucose Meter Data in the Electronic Health Record.Diabetes technology & therapeutics · 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
7 authors at 1 institution in 1 country.
Funding
Abstract
backgroundDiabetes devices provide data for health care providers (HCPs) and people with type 1 diabetes to make management decisions. Extracting and viewing the data require separate, proprietary software applications for each device. In this pilot study, we examined the feasibility of using a single software platform (Tidepool) that integrates data from multiple devices. MATERIALS AND
methodsParticipating HCPs (n = 15) used the software with compatible devices in all patient visits for 6 months. Samples of registration desk activity and office visits were observed before and after introducing the software, and HCPs provided feedback by survey and focus groups.
resultsThe time required to upload data and the length of the office visit did not change. However, the number of times the HCP referred to the device data with patients increased from a mean of 2.8 (±1.2) to 6.1 (±3.1) times per visit (P = 0.0002). A significantly larger proportion of children looked at the device data with the new application (baseline: 61% vs. study end: 94%, P = 0.015). HCPs liked the web-based user interface, integration of the data from multiple devices, the ability to remotely access data, and use of the application to initiate patient education. Challenges included the need for automated data upload and integration with electronic medical records.
conclusionsThe software did not add to the time needed to upload data or the length of clinic visits and promoted discussions with patients about data. Future studies of HCP use of the application will evaluate clinical outcomes and effects on patient engagement and self-management.
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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.