Quality, availability and suitability of antimicrobial stewardship guidance: a multinational qualitative study
Bibliographic record
Abstract
Background: Antimicrobial stewardship (AMS) programmes are established across the world to treat infections efficiently, prioritize patient safety, and reduce the emergence of antimicrobial resistance. One of the core elements of AMS programmes is guidance to support and direct physicians in making efficient, safe and optimal decisions when prescribing antibiotics. To optimize and tailor AMS, we need a better understanding of prescribing physicians' experience with AMS guidance. Objectives: To explore the prescribing physicians' user experience, needs and targeted improvements of AMS guidance in hospital settings. Methods: Semi-structured interviews were conducted with 36 prescribing physicians/AMS guidance users from hospital settings in Canada, Germany, Israel, Latvia, Norway and Sweden as a part of the international PILGRIM trial. A socioecological model was applied as an overarching conceptual framework for the study. Results: Research participants were seeking more AMS guidance than is currently available to them. The most important aspects and targets for improvement of AMS guidance were: (i) quality of guidelines; (ii) availability of infectious diseases specialists; and (iii) suitability of AMS guidance to department context. Conclusions: Achieving prudent antibiotic use not only depends on individual and collective levels of commitment to follow AMS guidance but also on the quality, availability and suitability of the guidance itself. More substantial commitment from stakeholders is needed to allocate the required resources for delivering high-quality, available and relevant AMS guidance to make sure that the prescribers' AMS needs are met.
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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 | 0.017 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".