POINT COUNTERPOINT Should Hospital Pharmacy Drug Budgets Be the Responsibility of Each Individual Department in an Institution, or Should Such Budgets Be Controlled Centrally by the Pharmacy Department?
Bibliographic record
Abstract
It is the position of our group that the responsibility for drug budgets should lie with each individual department and not solely with the pharmacy department. This approach may lead to an improvement in evidence-based practice, better patient outcomes, lower overall costs, and less wastage of medications, all without compromising the high quality of service that institutional pharmacies provide. Putting the individual departments closest to the patients in control of drug budgets can promote patient-specific decisions based on efficacy and evidence rather than cost. 1 Evidence-based practice is aimed at reducing inappropriate care and drug use, improving patient outcomes, and reducing admissions to hospital. 2,3 Giving departments the authority to manage their own drug budgets tends to increase physicians ’ awareness of evidence-based practice. Ohlsson and Merlo4 investigated whether prescribing practices changed when physicians were made aware of the economic implications of their choices. They found that when the drug budget was decentralized, adherence to evidence-based, cost-effective practices for prescription of statins improved continuously over the 25-month duration of the study. In addition to increasing compliance with evidence-based practice, decentralization of drug budgets allows for overall cost savings. Rising drug expenditures are outpacing inflation, which is creating an unsustainable health care system. 5 Total drug spending in Canada was estimated to have reached $29.8 billion
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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 | 0.009 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.013 | 0.014 |
| Insufficient payload (model declined to judge) | 0.031 | 0.006 |
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".