ArticleJournal of diabetes science and technology2014
Mobile Diabetes Intervention for Glycemic Control: Impact on Physician Prescribing.
Article in Journal of diabetes science and technology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02919033 (A Coordinated PCP-Cardiologist Telemedicine Model), which is not on this map. Cited by 16 papers, 5 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.
A Coordinated PCP-Cardiologist Telemedicine Model (PCTM) in China's Community Hypertension Care: Study Protocol for a Randomized Controlled Trial
Who cites it
16 citing papers in PubMed, 5 syntheses or guidelines pooled it, 27 citations in OpenAlex.
- Digital tracking, provider decision support systems, and targeted client communication via mobile devices to improve primary health care.The Cochrane database of systematic reviews · 2025Pooled it
- Consideration of inequalities in effectiveness trials of mHealth applications - a systematic assessment of studies from an umbrella review.International journal for equity in health · 2024Pooled it
- The Comparative Effectiveness of Mobile Phone Interventions in Improving Health Outcomes: Meta-Analytic Review.JMIR mHealth and uHealth · 2019Pooled it
- T2DM Self-Management via Smartphone Applications: A Systematic Review and Meta-Analysis.PloS one · 2016Pooled it
- Mobile Phone and Smartphone Technologies for Diabetes Care and Self-Management.Current diabetes reports · 2015Pooled it
- Effects of mobile phone application combined with or without self-monitoring of blood glucose on glycemic control in patients with diabetes: A randomized controlled trial.Journal of diabetes investigation · 2019Trial
- Trial
- Analysis of Effectiveness and Psychological Techniques Implemented in mHealth Solutions for Middle-Aged and Elderly Adults with Type 2 Diabetes: A Narrative Review of the Literature.Journal of clinical medicine · 2021Review
- Article
- User Centered Design to Improve Information Exchange in Diabetes Care Through eHealth : Results from a Small Scale Exploratory Study.Journal of medical systems · 2019Article
- Technology to overcome therapeutic inertia.mHealth · 2019Article
- An mHealth Diabetes Intervention for Glucose Control: Health Care Utilization Analysis.JMIR mHealth and uHealth · 2018Article
- Diabetes Educators' Insights Regarding Connecting Mobile Phone- and Wearable Tracker-Collected Self-Monitoring Information to a Nationally-Used Electronic Health Record System for Diabetes Education: Descriptive Qualitative Study.JMIR mHealth and uHealth · 2018Article
- The Impact of a Mobile Diabetes Health Intervention on Diabetes Distress and Depression Among Adults: Secondary Analysis of a Cluster Randomized Controlled Trial.JMIR mHealth and uHealth · 2017Article
- Older Adult Self-Efficacy Study of Mobile Phone Diabetes Management.Diabetes technology & therapeutics · 2015Article
- 'Pushed' self-tracking using digital technologies for chronic health condition management: a critical interpretive synthesis.Digital healthReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
Of adults with type 2 diabetes, 84% take antihyperglycemic medication. Successful treatment requires active monitoring and medication dose adjustment by health providers. The objective of this study was to determine how a mobile-phone-based coaching system for diabetes management influences physician prescribing behavior. This secondary data analysis is based on a cluster randomized clinical trial that reported patients provided with mobile self-management had reduction in glycated hemoglobin (HbA1c) of 1.9% over 1 year, compared to 0.7% in control patients (P < .001). Participants were primary care patients with type 2 diabetes randomized at physician practice level into a control group (n = 55) and intervention group (n = 62). Main study measures were patients' medication records (medication, dose, frequency, start and end date) abstracted at baseline and study end. Antihyperglycemic medications, including sulfonylureas or thiazolidinediones, and antihypertensive and antilipemic medications were analyzed. A higher percentage of patients in the intervention group had modification and intensification of incretin mimetics during the 1-year study period (9.7% vs 0.0% and 8.1% vs 0.0%, both P = .008). A higher percentage of patients in the intervention group had modification and intensification of metformin (24.2% vs 7.3%, P = .033). The overall difference in physician prescribing of oral antihyperglycemic medications was not statistically significant. Our results suggest mobile diabetes interventions can encourage physicians to modify and intensify antihyperglycemic medications in patients with type 2 diabetes. Differences in physician prescribing behavior were modest, and do not appear to be large enough to explain a 1.2% decrease in HbA1c.
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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.