Evaluation of the Do Bugs Need Drugs? Program in British Columbia: Can We Curb Antibiotic Prescribing?
Bibliographic record
Abstract
OBJECTIVE: Antibiotic resistance is accelerated by the overuse of antibiotics. Do Bugs Need Drugs? is an educational program adapted in British Columbia to target both the public and health care professionals, with the aim of reducing unnecessary prescribing. The current article presents a descriptive evaluation of the impact of the program over the first four years. METHOD: Program implementation was measured by the amount of educational material distributed and the level of participation in educational sessions. The impact of the program was assessed by measuring changes in knowledge and prescribing habits of participating physicians, and by investigating provincial trends in antibiotic use. METHOD: Program implementation was measured by the amount of educational material distributed and the level of participation in educational sessions. The impact of the program was assessed by measuring changes in knowledge and prescribing habits of participating physicians, and by investigating provincial trends in antibiotic use. RESULTS: A total of 51,367 children, assisted‐living residents and health care professionals have participated in the program since its inception in the fall of 2005. Pre‐ and postcourse assessments of participating physicians indicated significant improvements in clinical knowledge and appropriate antibiotic treatment of upper respiratory tract infections. Overall rates of antibiotic use in the province have stabilized since 2006. The rates of consumption of fluoroquinolones and macrolides have levelled off since 2005. Utilization rates for acute bronchitis are at the same level as when the program was first implemented, but rates for other acute upper respiratory tract infections of interest have declined. CONCLUSIONS: The Do Bugs Need Drugs? program significantly improves physician antibiotic prescription decisions and is ecologically associated with desirable change in population antibiotic consumption patterns.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".