Outpatient antibiotic use in British Columbia, Canada: reviewing major trends since 2000
Bibliographic record
Abstract
BACKGROUND: With 90% of all antibiotics in Canada being used in the community setting, tracking outpatient prescribing is integral to mitigate the issue of antimicrobial resistance. In 2005, a provincial programme was launched in British Columbia (BC) to disseminate information regarding the judicious use of antibiotics. These efforts include educational campaigns, updated practitioner guidelines and academic detailing. The impact of provincial stewardship on community prescribing requires ongoing evaluation. OBJECTIVES: This study examines outpatient prescribing to quantify rates of antibiotic use, evaluate major trends over time and identify new targets for stewardship. METHODS: A retrospective cohort design using population-level data. RESULTS: This study included over 3.5 million unique individuals with a total of 51 367 938 oral antibiotic prescriptions dispensed over a 19 year period (2000-18). Overall antibiotic utilization decreased by 23% over the course of the study period. This trend in the reduction of antibiotic prescription was observed across all major antibiotic classes, apart from the class of other antibacterials, which was mostly related to use of nitrofurantoin. The largest magnitudes of decreased prescribing were observed in the paediatric population. Prescribing across two distinct eras of provincial stewardship reaffirmed preliminary findings of programme efficacy, when compared with pre-stewardship levels of antibiotic use. CONCLUSIONS: Outpatient prescribing in BC is decreasing overall, and this study confirms an association between provincial stewardship interventions and improvements in antibiotic use. Pronounced declines in paediatric populations are promising, and further research is underway to examine prescribing quality.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.017 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".