POINT COUNTERPOINT Should There Be a Cap on the Number of Patients Under the Care of a Clinical Pharmacist? THE “PRO ” SIDE
Bibliographic record
Abstract
In the ideal health care system, there would be an abundance of resources to ensure timely and comprehensive patient care. However, it is a well-known reality that demands on Canadian hospitals and clinical pharmacy services are escalating because of increases in the number of elderly patients, the acuity of patients ’ conditions, the complexity of drug regimens, and the length of stay in hospital. In addition, there continues to be a shortage of hospital pharmacists. Despite these challenges, patient care should not be compromised. Hence, we believe that there should be a cap on the number of patients under the care of a clinical pharmacist. We outline here the 4 main reasons for this position. First, not limiting the number of patients under the care of a clinical pharmacist may compromise patient care and may actually increase costs. The value of clinical pharmacy services is
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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 | 0.012 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.019 | 0.020 |
| Insufficient payload (model declined to judge) | 0.031 | 0.005 |
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".