Abstract 22: Impact Of Drug Policy On Regional Trends In Ezetimibe Use
Bibliographic record
Abstract
Background: Ezetimibe use has gradually but steadily increased in Canada during the past decade even with the absence of outcomes evidence. Among the 4 most populated provinces in Canada, there is a gradient in the restrictiveness of ezetimibe in the public-funded formularies (most strict to least strict: British Columbia (BC), Alberta (AB), Quebec (QC) and Ontario (ON)). We examined ezetimibe use trends in these 4 provinces in the period before and after the ENHANCE trial, which was published in January 2008 to better understand the association between use and formulary restrictiveness. Methods: We conducted a population-level observational cohort study using the data collected by IMS Health Canada’s CompuScript Audit® from June 1, 2003 to December 31, 2012. The main outcome measure was monthly ezetimibe expenditures, which were used as a proxy for the total number of prescriptions. The differences in ezetimibe-associated expenditures between the 4 provinces were tested using a linear regression model with interaction effects for province and time. Results: The monthly population standardized ezetimibe-associated costs increased in different patterns in the 4 provinces over the past decade. From June 2003 to December 2012, BC had the lowest monthly increasing rate from $ 261 to $21,926 ($190/100,000 population/month), ON had the most rapid monthly increase from $223 to $ 74,030 ($ 647/100,000 population/month) and QC from $ 130 to $ 59,690 ($522/100,000 population/month) and AB from $ 356 to $ 37604 ($327/100,000 population/month) were in between. (P<0.001) The cost for ezetimibe appeared to increase steadily in QC over the study period. In contrast, the increasing rate began declining in BC, AB and ON at the time point which coincided with the publication of ENHANCE. Conclusions: Distinct patterns of ezetimibe use emerged within the 4 biggest provinces in Canada, which was associated with the restrictiveness of their publicly-funded drug formularies. Without the support of clinical outcomes evidence, ezetimibe remains commonly used in the provinces with least strict formularies (QC and ON). In contrast, the use of ezetimibe seemed to plateau post-ENHANCE in BC and AB, which have more restrictive formularies. The strictness of the drug formulary appears to be influencing ezetimibe prescribing in Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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".