Lessons for a national pharmaceuticals strategy in Canada from Australia and New Zealand
Bibliographic record
Abstract
BACKGROUND: The provincial formulary review processes in Canada lead to the slow and inequitable availability of new products. In 2004, the exploration of a national pharmaceuticals strategy (NPS) was announced. The pricing policies of New Zealand and Australia have been suggested as possible models for the NPS. OBJECTIVE: To compare health care indexes and health care use information from Canada, Australia and New Zealand. METHODS: The 2006 Organisation for Economic Co-operation and Development health data were used to compare health and health care indexes from Canada, Australia and New Zealand between 1994 and 2002 to 2004. The principal focus of the evaluation was cardiovascular and respiratory disorders. RESULTS: Although the mortality rate from acute myocardial infarction decreased in each country from 1994, it levelled off in New Zealand in 1997, 1998 and 1999. Between 1994 and 2003, the average length of hospital stay for any cause and for cardiovascular disorders was stable in Australia and Canada, but increased in New Zealand, while the rate of hospital discharges for cardiovascular diseases decreased in Canada and Australia, but strongly increased in New Zealand. Over the same period, sales of cardiovascular drugs decreased in New Zealand, while sharply increasing in Canada and Australia. CONCLUSIONS: Although only circumstantial, our results suggest an association between decreasing cardiovascular drug sales and markers of declining cardiovascular health in New Zealand. Careful consideration must be given to the potential consequences of any model for an NPS in Canada, as well as to opportunities provided for discussion and input from health care professionals and patients.
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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 | 0.011 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 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".