Population-based outpatient antimicrobial use in Newfoundland and Labrador: a retrospective descriptive study
Bibliographic record
Abstract
BACKGROUND: Data that have been reported on antimicrobial use in Newfoundland and Labrador (NL) do not appear to be representative of use at the population level. We sought to use pharmacy network data on prescriptions to describe outpatient antimicrobial use in NL. METHODS: We analyzed all outpatient antimicrobial prescriptions dispensed between June 1, 2017, and June 8, 2021, from the provincial pharmacy network database and translated deidentified data into SPSS. We excluded prescriptions for parenteral and topical antimicrobials, antivirals and antifungals. We described antimicrobial use using the prescription rate and defined daily dose (DDD) rate. RESULTS: Overall, we analyzed 1 586 534 prescriptions dispensed to 394 708 people by 3431 prescribers. The rate of antimicrobial use was 741 prescriptions per 1000 population per year (7161 DDD/1000 population/yr). The median duration of prescriptions was 7 (interquartile range 7-10) days. The prescription rate decreased from 867 to 546 per 1000 population per year (-37%) over the study period, and the mean DDD rate decreased from 8387 to 5356 DDD per 1000 population per year (-36.1%). Antimicrobials with the highest DDD rate were amoxicillin (1568 DDD/1000/yr), doxycycline (864 DDD/1000/yr) and ciprofloxacin (633 DDD/1000/yr). Prescribers wrote a mean of 102 (standard deviation 248) prescriptions per year; 3 prescribers wrote more than 2500 prescriptions per year. Overall, 9203 (2.3%) of the 394 708 people in the study population received 4 or more prescriptions per year. INTERPRETATION: The rate of antimicrobial use in NL is lower than previously described in national surveillance data. Potential targets for stewardship intervention include prolonged duration of prescriptions, high-rate prescribers and high-rate patients, but further research is needed to assess the appropriateness of prescriptions according to diagnosis.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | low |
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".