The potential economic impact of restricted access to angiotensin-receptor blockers
Bibliographic record
Abstract
BACKGROUND: The use of angiotensin-receptor blockers increased by more than 4000% in Canada from 1996 to 2006. The benefit of these medications over angiotensin-converting-enzyme (ACE) inhibitors has not been proven aside from a reduction in dry cough. We estimated the potential cost savings that might have been achieved had access to angiotensin-receptor blockers been restricted. METHODS: We performed a cost-minimization analysis with a decision-tree model using a societal perspective over a one-year period. Sources of data for model parameters included IMS Health Canada data collected from one-third of all retail pharmacies for the cost and use of angiotensin-receptor blockers and ACE inhibitors in each province, as well as published studies for administrative costs and incidence of dry cough. We used Monte Carlo simulations with 10 000 iterations to test the impact of several model parameters (e.g., drug prices, administrative costs and the incidence of dry cough). All data are in 2006 Canadian dollars. RESULTS: A policy that would have restricted access to angiotensin-receptor blockers might have saved more than $77 million in Canada in 2006. The simulations yielded similar savings for the year (mean $58.3 million, 95% confidence interval $29.3 million to $90.8 million). Every simulation showed a cost savings. INTERPRETATION: Had access to angiotensin-receptor blockers been restricted, the potential cost savings to the Canadian health care system might have been more than $77 million in 2006, likely without any adverse effect on cardiovascular health.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.004 | 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".