Comparison of United States and Canadian Glaucoma Medication Costs and Price Change from 2006 to 2013
Bibliographic record
Abstract
Objective. Compare glaucoma medication costs between the United States (USA) and Canada. Methods. We modelled glaucoma brand name and generic medication annual costs in the USA and Canada based on October 2013 Costco prices and previously reported bottle overfill rates, drops per mL, and wastage adjustment. We also calculated real wholesale price changes from 2006 to 2013 based on the Average Wholesale Price (USA) and the Ontario Drug Benefit Price (Canada). Results. US brand name medication costs were on average 4x more than Canadian medication costs (range: 1.9x-6.9x), averaging a cost difference of $859 annually. US generic costs were on average the same as Canadian costs, though variation exists. US brand name wholesale prices increased from 2006 to 2013 more than Canadian prices (US range: 29%-349%; Canadian range: 9%-16%). US generic wholesale prices increased modestly (US range: -23%-58%), and Canadian wholesale prices decreased (Canadian range: -38%-0%). Conclusions. US brand name glaucoma medications are more expensive than Canadian medications, though generic costs are similar (with some variation). The real prices of brand name medications increased more in the USA than in Canada. Generic price changes were more modest, with real prices actually decreasing in Canada.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".