An Exploratory Analysis of Predictors of Concordance Between Canadian Common Drug Review Reimbursement Recommendations and the Subsequent Decisions by Ontario, British Columbia and Alberta
Bibliographic record
Abstract
BACKGROUND: Concordance between Common Drug Review (CDR) recommendations and provincial plans has been studied previously. However, no study has, to the best of the authors' knowledge, examined the characteristics of CDR recommendations that may be associated with concordance. METHODS: Recommendation-decision pairs were collected from the CDR and the provincial plans of Ontario, British Columbia and Alberta. Concordance was evaluated by province. Characteristics of each CDR recommendation were collected, and associations with concordance were evaluated by logistic regression. RESULTS: Recommendation-listing concordance was high. Positive references to cost and clinical outcomes compared to placebo were statistically associated with concordance. Negative references to cost and to the consistency and certainty of economic evidence were statistically associated with discordance. However, these findings were inconsistent across the jurisdictions studied. CONCLUSION: Although concordance was high, the ability of recommendation characteristics to explain the relationship between province and CDR listing decisions was limited. This exploratory study highlights the complexity of the reimbursement process and possible reasons for drug listing differences across jurisdictions.
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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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".