Impact of Drug Policy on Regional Trends in Ezetimibe Use
Bibliographic record
Abstract
BACKGROUND: Ezetimibe use has steadily increased in Canada during the past decade even in the absence of evidence demonstrating a beneficial effect on clinical outcomes. Among the 4 most populated provinces in Canada, there is a gradient in the restrictiveness of ezetimibe in public-funded formularies (most to least strict: British Columbia, Alberta, Quebec, and Ontario). The effect of formulary policy on the use of ezetimibe over time is unknown. METHODS AND RESULTS: We conducted a population-level cohort study using Intercontinental Marketing Services Health Canada's data from June 2003 to December 2012 to examine ezetimibe use in these 4 provinces to better understand the association between use and formulary restrictiveness. We found regional variations in the patterns of ezetimibe use. From June 2003 to December 2012, British Columbia (most restrictive) had the lowest monthly increasing rate from $261 to $21 926 ($190/100 000 population/mo), whereas Ontario (least restrictive) had the most rapid monthly increase from $223 to $74 030 ($ 647/100 000 population/mo), and Quebec from $130 to $59 690 ($522/100 000 population/mo) and Alberta from $356 to $ 37 604 ($327/100 000 population/mo) were intermediate (P<0.001). CONCLUSIONS: Ezetimibe use remains common, increasing during the past decade. Use steadily increased in provinces with the most lenient formularies. In contrast, use was lower, plateauing since 2008 in British Columbia and Alberta, which have more restrictive formularies. The gradient in ezetimibe use was related to variability in restrictiveness of the provincial formularies, illustrating the potential of a policy response gradient that may be used to more effectively manage medication use.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".