Smart connected insulin dose monitoring technologies versus standard of care: a Canadian cost–effectiveness analysis
Bibliographic record
Abstract
Aim: There is growing interest in novel insulin management systems that improve glycemic control. This study aimed to evaluate the cost–effectiveness of smart connected insulin re-usable pens or caps for disposable insulin pens versus pens without connected capabilities in the management of adult patients with Type 1 diabetes (T1DM) from a Canadian societal perspective. Materials & methods: The IQVIA Core Diabetes Model was utilized to conduct the analyses. Applying data from a non-interventional study, the connected insulin device arm was assumed to result in greater reductions (-0.67%) in glycated hemoglobin from baseline and fewer non-severe hypoglycemic events (-32.87 events/patient annually). Macro- and micro-vascular risks were predicted using the Epidemiology of Diabetes Interventions and Complications study data. Direct and indirect costs and utilities were sourced from literature. Key model outcomes included life years and quality-adjusted life-years (QALYs). Both costs and effects were annually discounted at 1.5% over a 60-year time horizon. Uncertainty was explored in scenario and probabilistic sensitivity analyses (PSA). Results: The connected insulin pen device was associated with lower mean discounted total costs (CAD221,943 vs 266,199; -CAD44,256), improvement in mean life expectancy (25.78 vs 24.29; +1.49 years) and gains in QALYs (18.48 vs 16.74; +1.75 QALYs) over the patient's lifetime. Most scenario analyses confirmed the base case results. The PSA showed dominance in 99.5% of cases. Conclusion: For adults with T1DM in Canada, a connected insulin pen device is likely to be a cost-effective treatment option associated with greater clinical benefits and lower costs relative to a standard re-usable or disposable pen.
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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 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".