Cost-effectiveness of telemonitoring screening for diabetic foot ulcer: a mathematical model
Bibliographic record
Abstract
BACKGROUND: One of the most common (and costly) complications of diabetes are diabetic foot ulcers, which often result in lower-extremity amputation. Regular foot care can reduce complications; however, roughly half of Canadians with diabetes do not participate in screening. We sought to evaluate the economic effects of using telemonitoring for diabetic foot ulcer prevention using mathematical modelling. METHODS: We used Markov modelling to compare current screening standards (standard care) to population-wide and targeted (high-risk) telemonitoring programs in a hypothetical cohort of Canadian patients aged 60 years. We varied the effectiveness (or outcome), defined as the proportion of diabetic foot ulcers prevented, to explore cost-effectiveness using model parameters from published literature and clinical experts. RESULTS: At 20%-40% effectiveness, population-based prevention resulted in 0.00399-0.00790 quality-adjusted life years (QALYs) gained per person over 5 years and an incremental cost of $479-$402 compared to standard care. At 15%-40% effectiveness, high-risk prevention resulted in a cost decrease per person over 5 years ($1.26-$25.55), with health benefits of 0.000207-0.00058 QALYs gained. INTERPRETATION: The use of telemonitoring in the diabetic lower extremity can offer patients better quality of life and can be cost-effective compared to current Canadian screening practices. Future work should focus on developing and validating technologies based on objective outcome measures for remote monitoring of the diabetic foot.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".