Health Care Professionals’ Clinical Perspectives & Satisfaction with a Blood Glucose Meter and Mobile App featuring a Dynamic Color Range Indicator and Blood Sugar Mentor: Online Evaluation in the United Kingdom, France, Germany, India, Algeria, Canada and the United States (Preprint)
Bibliographic record
Abstract
BACKGROUND Despite many new therapies and technologies becoming available in the last decade, people with diabetes continue to struggle to achieve good glycemic control. Innovative and affordable solutions are needed to support healthcare professionals (HCPs) to improve patient outcomes OBJECTIVE To gather current self-management perceptions of HCPs in seven countries and investigate HCP satisfaction with a new glucose meter and mobile app featuring a dynamic color range indicator and a blood sugar mentor METHODS A total of 355 HCPs, including 142 endocrinologists, 108 primary care physicians, and 105 nurses, were recruited from the United Kingdom (n=50), France (n=50), Germany (n=50), India (n=54), Algeria (50), Canada (n=51) and the United States (n=50). HCPs experienced the OneTouch Verio Reflect glucose meter and OneTouch Reveal mobile app online from their own office computer using interactive demonstrations (via webpages and multiple animations). After providing demographic and clinical practice insights, HCPs responded to statements about the utility of the system. RESULTS Concerning current practice, 83% (295/355) of HCPs agreed poor numeracy or health literacy was a barrier for their patients. 86% (305/355) and 92% (327/355) of HCPs responded that type 2 (T2D) and type 1 (T1D) patients were aware what represented a low, in-range or high blood glucose result. Only 62% felt current glucose meters made it easy for patients to understand if results were in-range. 50% (178/355) and 78% (277/35) were confident that T2D and T1Ds took action for low or high results. 87% (309/355) agreed the ColorSure Dynamic Range Indicator could help them teach patients how to interpret results and 89% (323/355) agreed it made them more aware of hyper and hypoglycemic results so they could take action. 86% (305/355) agreed the Blood Sugar Mentor feature, gave personalized guidance, insight, and encouragement so patients could take action. 86% (305/355) also agreed the Blood Sugar Mentor provided real-time guidance to reinforce the goals HCPs had set, so patients could take steps to manage diabetes between office visits. After experiencing the full system, 86% (305/355) agreed it was beneficial for patients with lower numeracy or health literacy, 96% (341/355) that it helped patients understand when results were low, in-range or high and 91% (323/355) agreed the way it displayed diabetes information would make patients more inclined to act upon results. 89% (316/355) agreed it would be helpful for agreeing appropriate in-range goals for their patients next clinic visit. CONCLUSIONS This multi-country online study provides evidence that HCPs were highly satisfied with the OneTouch Verio Reflect meter and OneTouch Reveal mobile app, which each use color-coded information and a Blood Sugar Mentor feature to assist patients with interpreting, analyzing and acting upon their blood glucose results, which is particularly beneficial to keep patients on track between scheduled office visits CLINICALTRIAL none
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".