Clinical and Economic Assessment of MyDiaCare, Digital Tools Combined With Diabetes Nurse Educator Support, for Managing Diabetes in South Africa: Observational Multicenter, Retrospective Study Associated With a Budget Impact Model
Bibliographic record
Abstract
Background In South Africa, diabetes prevalence is expected to reach 5.4 million by 2030. In South Africa, diabetes-related complications severely impact not only patient health and quality of life but also the economy. Objective The Diabetes Nurse Educator (DNE) study assessed the benefit of adding the MyDiaCare program to standard of care for managing patients with type 1 and type 2 diabetes in South Africa. An economic study was also performed to estimate the budget impact of adding MyDiaCare to standard of care for patients with type 2 diabetes older than 19 years treated in the South African private health care sector. Methods The real-world DNE study was designed as an observational, retrospective, multicenter, single-group study. Eligible patients were older than 18 years and had at least 6 months of participation in the MyDiaCare program. The MyDiaCare program combines a patient mobile app and a health care professional platform with face-to-face visits with a DNE. The benefit of MyDiaCare was assessed by the changes in glycated hemoglobin (HbA1c) levels, the proportion of patients achieving clinical and biological targets, adherence to care plans, and satisfaction after 6 months of participating in the MyDiaCare program. A budget impact model was performed using data from the DNE study and another South African cohort of the DISCOVERY study to estimate the economic impact of MyDiaCare. Results Between November 25, 2019, and June 30, 2020, a total of 117 patients (8 with type 1 diabetes and 109 with type 2 diabetes) were enrolled in 2 centers. After 6 months of MyDiaCare, a clinically relevant decrease in mean HbA1c levels of 0.6% from 7.8% to 7.2% was observed. Furthermore, 54% (43/79) of patients reached or maintained their HbA1c targets at 6 months. Most patients achieved their targets for blood pressure (53/79, 67% for systolic and 70/79, 89% for diastolic blood pressure) and lipid parameters (49/71, 69% for low-density-lipoprotein [LDL] cholesterol, 41/71, 58% for high-density-lipoprotein [HDL] cholesterol, and 59/71, 83% for total cholesterol), but fewer patients achieved their targets for triglycerides (32/70, 46%), waist circumference (12/68, 18%), and body weight (13/76, 17%). The mean overall adherence to the MyDiaCare care plan was 93%. Most patients (87/117, 74%) were satisfied with the MyDiaCare program. The net budget impact per patient with type 2 diabetes, older than 19 years, treated in the private sector using MyDiaCare was estimated to be approximately South African Rands (ZAR) 71,023 (US $4089) during the first year of introducing MyDiaCare. Conclusions The results of using MyDiaCare program, which combines digital tools for patients and health care professionals with DNE support, suggest that it may be a clinically effective and cost-saving solution for diabetes management in the South African private health care sector.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".