Evidence-based prescribing of antibiotics for children: role of socioeconomic status and physician characteristics
Bibliographic record
Abstract
BACKGROUND: Evidence-based guidelines for antibiotic use are well established, but nonadherence to these guidelines continues. This study was undertaken to determine child, household and physician factors predictive of nonadherence to evidence-based antibiotic prescribing in children. METHODS: The prescription and health care records of 20 000 Manitoba children were assessed for 2 criteria of nonadherence to evidence-based antibiotic prescribing during the period from fiscal year 1996 (April 1996 to March 1997) to fiscal year 2000: receipt of an antibiotic for a viral respiratory tract infection (VRTI) and initial use of a second-line agent for acute otitis media, pharyngitis, pneumonia, urinary tract infection or cellulitis. The likelihood of nonadherence to evidence-based prescribing, according to child demographic characteristics, physician factors (specialty and place of training) and household income, was determined from hierarchical linear modelling. Child visits were nested within physicians, and the most parsimonious model was selected at p < 0.05. RESULTS: During the study period, 45% of physician visits for VRTI resulted in an antibiotic prescription, and 20% of antibiotic prescriptions were for second-line antibiotics. Relative to general practitioners, the odds ratio for antibiotic prescription for a VRTI was 0.51 (95% confidence interval [CI] 0.42-0.62) for pediatricians and 1.58 (95% CI 1.03-2.42) for other specialists. The likelihood that an antibiotic would be prescribed for a VRTI was 0.99 for each successive 10,000 Canadian dollars increase in household income. Pediatricians and other specialists were more likely than general practitioners to prescribe second-line antibiotics for initial therapy. Both criteria for nonadherence to evidence-based prescribing were 40% less likely among physicians trained in Canada or the United States than among physicians trained elsewhere. INTERPRETATION: The links that we identified between nonadherence to evidence-based antibiotic prescribing in children and physician specialty and location of training suggest opportunities for intervention. The independent effect of household income indicates that parents also have an important role.
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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".