Population-Based Surveillance of Antibiotic Dispensing in Alberta, Canada
Bibliographic record
Abstract
Objectives Over use or misuse of antibiotics can lead to antibiotic resistance leading to an inability to effectively treat bacterial infections. Our objective was to establish public health surveillance related to the of antibiotics in Alberta, Canada. Methods The province of Alberta maintains a publicly funded, universally available health care system. As part of managing the system, the Ministry of Health maintains a number of population-based databases that are all linkable. Data were extracted from the Alberta Pharmacy Information Network (PIN) database for 2012. Over 95% of pharmacies in Alberta contribute data to PIN on prescriptions dispensed. The data include a personal health number, birth date, gender, pharmacy location, drug identification number (DIN), Anatomical Therapeutic Chemical classification (ATC) code, dispense date, quantity, and dosage. All events under the ATC rubric J01 were extracted. Using the full ATC code, the data were organized into 22 groupings. Population data were extracted from the Alberta Health Care Insurance Plan Central Stakeholder Registry which contains a record for all residents of the province. Age-specific dispensing rates, by antibiotic class, were computed. Results In 2012, there were 2.69 million prescriptions for an antibiotic dispensed in Alberta. Overall, 29.1% of the population (n = 1,151,602) had one or more prescriptions filled for antibiotic. The most commonly prescribed antibiotics included macrolides, beta-lactam antibacterials (pencillin), and fluoroquinolones with 8.7%, 8.6%, and 4.6% of the population filling a prescription, respectively. Pencillins were most commonly used in younger age groups with 20% of children under 5 years of age filling a prescription. Dispensing of fluoroquinolones increased with age with 14% of those over age 70 filling at least one prescription in 2012. The use of macrolides showed little variation in use for those aged 20 to 80 with approximately 9% of the population using these antibiotics. Conclusions Antibiotic use is common with close to 30% of the population in Alberta filling one or more prescriptions. The use of antibiotics varied by class and patient age. Further review of the high use of fluoroquinolones in older populations is required to determine the appropriateness of use and opportunities to improve prescribing behaviours. Key messages There may be opportunities to improve the appropriate use of antibiotics. Dispensing patterns can be used to better understand the use of antibiotics at the population level to help inform policy and practice.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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, 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".