In-Hospital Macro-, Meso-, and Micro-Drivers and Interventions for Antibiotic Use and Resistance: A Rapid Evidence Synthesis of Data from Canada and Other OECD Countries
Bibliographic record
Abstract
Hospitals continue to face challenges in reducing incorrect antibiotic use due to social and cultural factors at the level of the health system, the care facility, the provider, and the patient. The objective of this paper is to highlight the social and cultural drivers of antimicrobial use and resistance and targeted interventions for secondary and tertiary care settings in Canada and other OECD countries. This paper is an extension of the synthesis conducted for the Public Health Agency of Canada's 2019 Spotlight Report: Preserving Antibiotics Now and Into the Future. We conducted a systematic review with a few modifications to meet rapid timelines. We conducted a search in Ovid MEDLINE and McMaster University's evidence databases for systematic reviews and then for individual Canadian studies. To cast a wider net, we searched OECD organization websites and screened reference lists from systematic reviews. We synthesized the evidence narratively and categorized the evidence into macro-, meso-, and microlevel. A total of 70 studies were (a) from OCED countries and summarized evidence of potential sociocultural antimicrobial resistance and use barriers or facilitators and/or interventions addressing these challenges; (b) systematic reviews with 50% of included studies that are situated in secondary and tertiary settings; and (c) published in Canada's two official languages, English and French. We found that hospital structures and policies may influence antibiotic utilization and variations in antimicrobial management. Microlevel factors may sway inappropriate prescribing among clinicians. The amount and type of antibiotics used may affect resistance rates. Interventions were mainly comprised of antibiotic stewardship and training that modify clinician behavior and that educate patients and carers. This evidence synthesis illustrates the various drivers of, and interventions for, antimicrobial use and resistance at the macro-, meso-, and microlevel in secondary and tertiary settings. We demonstrate that upstream drivers may lead to downstream events that influence antimicrobial resistance.
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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 | 0.078 | 0.203 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.034 | 0.044 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| 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".