Demonstrated Cost-Effectiveness of a Telehomecare Program for Gestational Diabetes Mellitus Management
Bibliographic record
Abstract
Background: Prevalence of gestational diabetes mellitus (GDM) has increased steadily in recent years. Pregnant women with GDM are at risk for obstetrical and neonatal complications and require close multidisciplinary follow-up, which implies a significant use of hospital resources. Methods: A prospective noninferiority and controlled clinical trial was designed. The telehomecare (THCa) initiative is a clinical remote patient management project in women with GDM. The main objective was to evaluate the cost-effectiveness of THCa by assessing the direct costs, including the related reduction in medical visits. Secondary outcomes were to evaluate the impact of THCa on diabetes control, GDM-related complications, and patient satisfaction. Results: A total of 161 women were assigned to either an intervention group provided with a THCa system for transmission and online analysis of capillary glucose data ( n = 80) or a control group receiving usual care in the clinic ( n = 81). A decrease in medical visits by 56% ( P < 0.001) in the THCa group was observed. There was no difference between the two groups in diabetes control or maternal and fetal complications. However, results showed a 10-fold increase in nursing interventions in THCa group (mainly by phone calls and e-mails). Satisfaction with care was high. Direct cost analysis revealed savings of 16% in patients followed by THCa compared with the control group. Conclusion: THCa monitoring significantly decreases medical visits and direct costs in GDM women without compromising pregnancy outcomes, quality of care, or patient satisfaction. THCa was shown to be cost-effective despite placing an additional burden on nursing time.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".