Cost-effectiveness of Freestyle Libre Systems for People with Type 2 Diabetes Mellitus on Basal Insulin Therapy in the Netherlands: An Economic Evaluation from a Societal Perspective Within a Publicly Funded Healthcare System
Bibliographic record
Abstract
Healthcare expenditure for the treatment of type 2 diabetes mellitus (T2DM) in the Netherlands is high, mainly due to the cost of treating diabetes-related complications. Guidelines recommend sensor-based glucose monitoring systems for people living with T2DM and using insulin, but these are not reimbursed in the Netherlands for those using basal insulin only. The objective of this study was to assess the cost-effectiveness of glucose monitoring with FreeStyle Libre systems (FSL), compared with capillary-based self-monitoring of blood glucose (SMBG), for people living with T2DM on basal insulin, from the perspective of the Dutch publicly funded healthcare system. The patient-level microsimulation model DEDUCE (DEtermination of Diabetes Utilities, Costs, and Effects) was used to estimate the incidence of complications and acute diabetes events (ADEs; hypoglycemia and diabetic ketoacidosis). The effect of FSL was modeled as a 0.5% reduction in glycated hemoglobin level, which DEDUCE translates to a lower rate of complications, and as reductions in ADEs and absenteeism. Costs (in 2024 euros) and utilities were discounted at 3% and 1.5%, respectively. Outcomes were assessed as quality-adjusted life years (QALYs). FSL was associated with 0.53 more QALYs than SMBG (12.77 vs. 12.24), at an additional cost of €8021. The resulting incremental cost-effectiveness ratio (ICER) for FSL versus SMBG was €15,181/QALY. The increased acquisition cost of FSL (€19,738) was partially offset by reductions in costs associated with complications, ADEs, and absenteeism. Probabilistic sensitivity analysis showed that FSL was 52% likely to be cost-effective at a willingness-to-pay threshold of €20,000/QALY, and > 99% likely at thresholds ≥ €40,000/QALY. FSL had an ICER of below €50,000/QALY in all scenarios investigated. From a Dutch publicly funded healthcare system perspective, FSL can be considered to be cost-effective compared with SMBG for people living with T2DM on basal insulin therapy. Effective glucose monitoring is important for people living with type 2 diabetes mellitus, reducing the risk of experiencing high or low blood sugar levels and of developing long-term complications. Glucose monitoring can be done using finger sticks and test strips or sensor-based devices such as the FreeStyle Libre systems (FSL). In this study, we modeled the cost-effectiveness of FSL in people with type 2 diabetes mellitus on basal insulin in the Netherlands. FSL use was considered to reduce the risk of acute events related to high or low blood sugar and of diabetes complications, both based on published studies. The modeled costs included the costs of glucose monitoring, of treating complications, and of time off work due to diabetes. FSL use was predicted to lead to better outcomes for people with type 2 diabetes mellitus, measured as quality-adjusted life years (a measure of health which combines life expectancy with quality of life), while reducing the costs of treating acute events and complications. Overall, FSL is likely to be considered to be a cost-effective use of Dutch healthcare system resources.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".