The Hospital Drug Formulary System: Just a Leftover? Opinions of a Tired but Still Committed Formulary System Manager
Bibliographic record
Abstract
Irecently came across some minutes of the Pharmacy and Therapeutics Committee at our hospital in which the topic of formulary systems was being hotly debated. One member was quoted as saying that “a hospital formulary is too confining and would limit doctors on their choice of drugs”; another stated that “it has value as an educational aid and reference”, and yet another suggested that “it would eliminate some useless drugs and probably decrease drug costs”. The date on those minutes was January 16, 1959, and this documentation marked the birth of the formulary system at Vancouver General Hospital. Amazingly, over 40 years later, the controversy about hospital formulary systems continues. A few decades later, and after more than 10 years of personal experience working on drug management at this institution, I believe that a well-controlled drug formulary system is still and will continue to be a critical element of responsible acute care hospital pharmacy practice. As the godfather of pharmaceutical care has said, “I personally would much rather practice, and receive care, in a hospital with a well-managed formulary system than in one without”. 1 However, like
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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 | 0.016 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.009 |
| Scholarly communication | 0.013 | 0.014 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.024 | 0.041 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".