Overview of Four Prescription Monitoring/Review Programs in Canada
Bibliographic record
Abstract
BACKGROUND: Prescription monitoring or review programs collect information about prescription and dispensing of controlled substances for the purposes of monitoring, analysis and education. In Canada, it is the responsibility of the provincial institutions to organize, maintain and run such programs. OBJECTIVE: To describe the characteristics of four provincial programs that have been in place for >6 years. METHODS: The managers of the prescription monitoring⁄review programs of four provinces (British Columbia, Alberta, Saskatchewan and Nova Scotia) were invited to present at a symposium at the Canadian Pain Society in May 2012. In preparation for the symposium, one author collected and summarized the information. RESULTS: Three provinces have a mix of review and monitoring programs; the program in British Columbia is purely for review and education. All programs include controlled substances (narcotics, barbiturates and psychostimulants); however, other substances are differentially included among the programs: anabolic steroids are included in Saskatchewan and Nova Scotia; and cannabinoids are included in British Columbia and Nova Scotia. Access to the database is available to pharmacists in all provinces. Physicians need consent from patients in British Columbia, and only professionals registered with the program can access the database in Alberta. The definition of inappropriate prescribing and dispensing is not uniform. Double doctoring, double pharmacy and high-volume dispensing are considered to be red flags in all programs. CONCLUSIONS: There is variability among Canadian provinces in managing prescription monitoring⁄review programs.
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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 | 0.012 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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".