A pragmatic randomized trial of a primary care antimicrobial stewardship intervention in Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: More than 90% of antibiotics are prescribed in primary care, but 50% may be unnecessary. Reducing unnecessary antibiotic overuse is needed to limit antimicrobial resistance. We conducted a pragmatic trial of a primary care provider-focused antimicrobial stewardship intervention to reduce antibiotic prescriptions in primary care. METHODS: Primary care practitioners from six primary care clinics in Toronto, Ontario were assigned to intervention or control groups to evaluate the effectiveness of a multi-faceted intervention for reducing antibiotic prescriptions to adults with respiratory and urinary tract infections. The intervention included provider education, clinical decision aids, and audit and feedback of antibiotic prescribing. The primary outcome was total antibiotic prescriptions for these infections. Secondary outcomes were delayed prescriptions, prescriptions longer than 7 days, recommended antibiotic use, and outcomes for individual infections. Generalized estimating equations were used to estimate treatment effects, adjusting for clustering by clinic and baseline differences. RESULTS: There were 1682 encounters involving 54 primary care providers from January until May 31, 2019. In intervention clinics, the odds of any antibiotic prescription was reduced 22% (adjusted Odds Ratio (OR) = 0.78; 95% Confidence Interval (CI) = 0.64.0.96). The odds that a delay in filling a prescription was recommended was increased (adjusted OR=2.29; 95% CI=1.37, 3.83), while prescription durations greater than 7 days were reduced (adjusted OR=0.24; 95% CI=0.13, 0.43). Recommended antibiotic use was similar in control (85.4%) and intervention clinics (91.8%, p=0.37). CONCLUSIONS: A community-based, primary care provider-focused antimicrobial stewardship intervention was associated with a reduced likelihood of antibiotic prescriptions for respiratory and urinary infections, an increase in delayed prescriptions, and reduced prescription durations. TRIAL REGISTRATION: clinicaltrials.gov ( NCT03517215 ).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".