High levels of opioid analgesic co‐prescription among methadone maintenance treatment clients in British Columbia, Canada: Results from a population‐level retrospective cohort study
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The non-medical use of prescription opioids (PO) has increased dramatically in North America. Special consideration for PO prescription is required for individuals in methadone maintenance treatment (MMT). Our objective is to describe the prevalence and correlates of PO use among British Columbia (BC) MMT clients from 1996 to 2007. METHODS: This study was based on a linked, population-level medication dispensation database. All individuals receiving 30 days of continuous MMT for opioid dependence were included in the study. Key measurements included the proportion of clients receiving >7 days of a PO other than methadone during MMT from 1996 to 2007. Factors independently associated with PO co-prescription during MMT were assessed using generalized linear mixed effects regression. RESULTS: 16,248 individuals with 27,919 MMT episodes at least 30 days in duration were identified for the study period. Among them, 5,552 individuals (34.2%) received a total of 290,543 PO co-prescriptions during MMT. The majority (74.3%) of all PO dispensations >7 days originated from non-MMT physicians. The number of PO prescriptions per person-year nearly doubled between 1996 and 2006, driven by increases in morphine, hydromorphone and oxycodone dispensations. PO co-prescription was positively associated with female gender, older age, higher levels of medical co-morbidity as well as higher MMT dosage, adherence, and retention. CONCLUSION AND SCIENTIFIC SIGNIFICANCE: A large proportion of MMT clients in BC received co-occurring PO prescriptions, often from physicians and pharmacies not delivering MMT. Experimental evidence for the treatment of pain in MMT clients is required to guide clinical 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".