Self-Monitoring of Blood Glucose Levels: Evaluating the Impact of a Policy of Quantity Limits on Test-Strip Use and Costs
Bibliographic record
Abstract
OBJECTIVES: To evaluate the impact of new quantity limits for blood glucose test strips (BGTS) in August 2013 on utilization patterns and costs in the elderly population of Ontario, Canada. METHODS: We conducted a population-based, cross-sectional time series analysis of all individuals 65 years of age and older who received publically funded BGTSs between August 1, 2010, and July 31, 2015, in Ontario, Canada. The number of BGTSs dispensed and the associated costs were measured for 4 diabetes therapy subgroups-insulin, hypoglycemia-inducing oral agents, non-hypoglycemia-inducing oral agents, and no drug therapy-each month during the study period. We used interventional autoregressive integrated moving average (ARIMA) models to assess the impact of Ontario's policy change on test strip use and costs. RESULTS: In the course of the study period, 657,338,177 test strips were dispensed to elderly patients in Ontario, at a total cost of CAN$482.3 million. Introduction of quantity limits was associated with significant reductions in the number of monthly strips dispensed and the associated costs (p<0.0001). In the year following the policy's implementation, test strip use decreased by 22.2% compared with the prior year (from 145,232,024 test strips to 113,007,795 test strips, a net decrease of 32,224,229 strips), resulting in a 22.5% reduction in costs (from $106.5 million to $82.6 million, a net cost reduction of approximately $24 million). CONCLUSIONS: The introduction of quantity limits, aligned with guidance from the Canadian Diabetes Association, led to immediate significant reductions in BGTS dispensing and costs. More research is needed to assess the impact of this policy on patient outcomes.
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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 | 0.007 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".