Community pharmacist prescribing of antimicrobials: A systematic review from an antimicrobial stewardship perspective
Bibliographic record
Abstract
Background: Pharmacist prescribing authority is expanding, while antimicrobial resistance is an increasing global concern. We sought to synthesize the evidence for antimicrobial prescribing by community pharmacists to identify opportunities to advance antimicrobial stewardship in this setting. Methods: We conducted a systematic review to characterize the existing literature on community pharmacist prescribing of systemic antimicrobials. We searched MEDLINE, EMBASE and International Pharmaceutical Abstracts for English-language articles published between 1999 and June 20, 2019, as well as hand-searched reference lists of included articles and incorporated expert suggestions. Results: Of 3793 articles identified, 14 met inclusion criteria. Pharmacists are most often prescribing for uncomplicated urinary tract infection (UTI), acute pharyngitis and cold sores using independent and supplementary prescribing models. This was associated with high rates of clinical improvement (4 studies), low rates of retreatment and adverse effects (3 studies) and decreased health care utilization (7 studies). Patients were highly satisfied (8 studies) and accessed care sooner or more easily (7 studies). Seven studies incorporated antimicrobial stewardship into study design, and there was overlap between study outcomes and those relevant to outpatient antimicrobial stewardship. Pharmacist intervention reduced unnecessary prescribing for acute pharyngitis (2 studies) and increased the appropriateness of prescribing for UTI (3 studies). Conclusion: There is growing evidence to support the role of community pharmacists in antimicrobial prescribing. Future research should explore additional opportunities for pharmacist antimicrobial prescribing and ways to further integrate advanced antimicrobial stewardship strategies in the community setting. Can Pharm J (Ott) 2021;154:xx-xx.
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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 | 0.010 | 0.046 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.019 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".