Method of physician remuneration and rates of antibiotic prescription
Bibliographic record
Abstract
Background: Rates of antibiotic prescription in Canada far exceed generally accepted rates of bacterial infection, which led the authors to postulate that rates of antibiotic prescription depend to some extent on factors unrelated to medical indication. The associations between antibiotic prescription rates and physician characteristics, in particular, method of remuneration and patient volume, were explored. Methods: The authors evaluated all 153 047 antibiotic prescriptions generated by 476 Newfoundland general practitioners and paid for by the Newfoundland Drug Plan over the 1-year period ending Aug. 31, 1996, and calculated rates of antibiotic prescription. Linear and logistic regression models controlling for sev-eral physician characteristics, specifically age, place of education (Canada or elsewhere), location of practice (urban or rural) and proportion of elderly pa-tients seen, were used to analyse rates of antibiotic prescription. Results: Fee-for-service payment (rather than salary) and greater volume of patients were strongly associated with higher antibiotic prescription rates. Fee-for-service
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".