Medicine reimbursement recommendations in Canada, Australia, and Scotland.
Bibliographic record
Abstract
OBJECTIVE: This study was undertaken to compare the recommendations made by the Canadian Common Drug Review (CDR) regarding whether drugs should be listed on provincial and federal formularies with recommendations made by similar bodies in other countries. STUDY DESIGN: Retrospective cohort analysis. METHODS: All recommendations made by CDR until September 30, 2006, were accessed. Two comparable agencies, the Australian Pharmaceutical Benefits Advisory Committee (PBAC) and the Scottish Medicines Consortium (SMC), were identified, and recommendations were obtained from the Web sites of all 3 agencies. We examined whether each of the agencies put equal proportions of drugs into each of 3 categories: unrestricted listing, listing with criteria, and do not list. Second, we compared recommendations on individual drugs. RESULTS: CDR made recommendations on 47 drugs. PBAC and SMC made recommendations about 31 and 29 of these products, respectively. There was no statistically significant difference in the percentage of drugs assigned to each category of recommendation in comparisons between CDR and PBAC, and between CDR and SMC. There was moderate agreement between CDR and PBAC for recommendations on individual drugs and poor agreement between CDR and SMC. CONCLUSIONS: CDR is no different from other similar agencies in terms of the number of drugs recommended for full or restricted listing, or against listing. There is a relatively low level of agreement on recommendations about individual drugs among the different agencies. These differences appear to be because of pharmacoeconomic evaluations and likely reflect discrepancies between countries in national markets and health systems.
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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 | 0.010 | 0.062 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| 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) | 0.002 | 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".