Access to new cardiovascular therapies in Canadian hospitals: a national survey of the formulary process.
Bibliographic record
Abstract
BACKGROUND: Access to new therapies in hospitals depends upon both clinical trial evidence and local Pharmacy and Therapeutics (P&T) committee approval. The process of formulary evaluation by P&T committees is not well-understood. OBJECTIVES: To describe the formulary decision-making process in Canadian hospitals for cardiovascular medications recently made available on the Canadian market. METHODS: Postal survey of hospital pharmacy directors in all Canadian hospitals with more than 50 beds. Target drugs included abciximab, enoxaparin, dalteparin, clopidogrel, eptifibatide and tirofiban. RESULTS: Of 428 surveys mailed, responses were received from 164 P&T committees representing 350 hospitals for an effective response rate of 82%. While physicians make up the largest proportion of committee membership, pharmacists play an influential role. Information most commonly cited as influencing formulary decisions included published clinical trials (97%), regional guidelines (90%), pharmacoeconomic data (84%), decisions at peer hospitals (73%) and local opinion leaders (60%). However, this information was often not required on formulary applications. Approval timelines varied widely for target medications but there were no regional, hospital or P&T committee characteristics that were independent predictors of early formulary application or approval. CONCLUSIONS: There is wide variability in the time taken for Canadian institutions to adopt new cardiovascular therapies, which is not explained by regional, hospital or P&T committee characteristics. Standardization of the formulary application and evaluation processes, including sharing of information amongst institutions, would lead to broader understanding of the applicable issues, more objectivity and improved efficiency.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.003 | 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) | 0.003 | 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".