Pharmacist-led antimicrobial stewardship at transitions of care from inpatient hospital to home: a scoping review
Bibliographic record
Abstract
Objective: To summarize available literature and highlight research gaps pertaining to the role of a pharmacist in providing antimicrobial stewardship (AMS) interventions for antibiotics at transitions of care (TOC) from inpatient hospital settings to home. Design: Scoping review. Methods: This scoping review follows the Arksey and O'Malley methodological framework. The literature search was conducted using the MEDLINE (OVID) database. Results: The MEDLINE (OVID) search returned 45 results. Of these, 26 were excluded during title and abstract screening and 11 were excluded after full-text review. Overall, eight studies were included in this scoping review. In six of the studies, AMS interventions were pharmacist-led. In two studies, they were led by an AMS team which included a pharmacist. Six of the studies used a similar intervention where a pharmacist led the review of antibiotics prior to patient discharge and made recommendations to change therapy where appropriate. The details of how these interventions were carried out vary between studies. Conclusions: Overall, all studies included in this scoping review concluded that pharmacists have a role in providing AMS interventions at TOC. This scoping review summarized available literature pertaining to the role of the pharmacist in providing AMS interventions for antibiotics at TOC. Research gaps that were highlighted are optimal level of AMS training for pharmacists providing AMS interventions, optimal workflow, ideal method of communication to the prescriber, and quality improvement metrics.
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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 | 0.026 | 0.111 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.020 | 0.018 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".