Measurement of antibiotic consumption: A practical guide to the use of the Anatomical Thgerapeutic Chemical classification and Definied Daily Dose system methodology in Canada
Bibliographic record
Abstract
Despite the global public health importance of resistance of microorganisms to the effects of antibiotics, and the direct relationship of consumption to resistance, little information is available concerning levels of consumption in Canadian hospitals and out-patient settings. The present paper provides practical advice on the use of administrative pharmacy data to address this need. Focus is made on the use of the Anatomical Therapeutic Chemical classification and Defined Daily Dose system. Examples of consumption data from Canadian community and hospital settings, with comparisons to international data, are used to incite interest and to propose uses of this information. It is hoped that all persons responsible for policy decisions regarding licensing, reimbursement, prescribing guidelines, formulary controls or any other structure pertaining to antimicrobial use become conversant with the concepts of population antibiotic consumption and that this paper provides them with the impetus and direction to begin accurately measuring and comparing antibiotic use in their jurisdictions.
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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 | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.015 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.008 |
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".