Assessing the Appropriateness of Antimicrobial Prescribing in the Community Setting: A Scoping Review
Bibliographic record
Abstract
Background: This scoping review examined the concept and scope of appropriateness of antimicrobial prescribing in the community setting and how it has been measured. Methods: Utilizing the Joanna Briggs Institute's methodology, we appraised peer-reviewed articles and unpublished studies, focusing on the US, UK, Canada, and Australia, with no limit to date. Results: Four basic components of antimicrobial prescribing to be evaluated during assessment of antimicrobial appropriateness in the community setting were identified: diagnosis for infection or indication for antimicrobial therapy, choice of antimicrobial therapy, dosing, and duration of therapy. The benchmark for definition of appropriateness is crucial in assessing antimicrobial prescribing appropriateness. The use of recommended guidelines as a benchmark is the standard for appropriate antimicrobial therapy, and when necessary, susceptibility testing should be explored. Conclusions: Studies evaluating the appropriateness of antimicrobial prescribing should assess these components of antimicrobial prescribing, and this should be clearly stated in the aim and objectives of the study.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".