Differences and over‐time changes in levels of prescription opioid analgesic dispensing from retail pharmacies in Canada, 2005–2010
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: To examine qualitative and quantitative levels and trends of prescription opioid analgesics ("opioids") use and the potential impact of prescription monitoring programs (PMPs), in the 10 Canadian provinces, for 2005-2010. METHODS: Opioid dispensing data from a representative sample of 2700 retail pharmacies were obtained. Individual opioid dispensing values were translated into defined daily doses per day/1000 population and categorized into "weak opioids" and "strong opioids" by standardized methods. Opioid prescription rates between provinces and over time, as well as the impact of PMPs, were examined using regression analyses techniques (i.e., Poisson, ANOVAs). RESULTS: Significant differences between provinces in the overall standardized rates of dispensing for total opioids, as well as for "weak opioids" and "strong opioids" categories, were found. The majority of provinces featured increases or curvilinear trends in the standardized amounts of opioids dispensed over time, mainly driven by increases in "strong opioids" use. In addition, significant inter-provincial differences in the levels of dispensing of individual opioids were found. Comparisons of changes in opioid dispensing between provinces with and without PMPs did not indicate significant differences. CONCLUSIONS: Opioid use featured significant quantitative and qualitative differences between provinces in Canada and showed an overall increasing trend mainly driven by changes in "strong opioids" in the study period. Reasons for the observed differences are not clear yet require systematic examination to allow evidence-based interventions in the interest of equitable pain treatment as well as the reduction of high levels of opioid-related morbidity and mortality in Canada.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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 it