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Record W2106148191 · doi:10.1186/1472-6963-14-90

Trends and changes in prescription opioid analgesic dispensing in Canada 2005–2012: an update with a focus on recent interventions

2014· article· en· W2106148191 on OpenAlexafffundabout
Benedikt Fischer, Wayne Jones, Jürgen Rehm

Bibliographic record

VenueBMC Health Services Research · 2014
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsPublic Health OntarioUniversity of TorontoCentre for Addiction and Mental HealthSimon Fraser University
FundersCanadian Institutes of Health ResearchPublic Health Agency of Canada
KeywordsOxycodoneMedicinePsychological interventionMedical prescriptionAnalgesicOpioidDemographyPharmacologyInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Prescription opioid analgesic (POA) utilization has steeply increased globally, yet is far higher in established market economies than elsewhere. Canada features the world's second-highest POA consumption rates. Following increases in POA-related harm, several POA control interventions have been implemented since 2010. METHODS: We examined trends and patterns in POA dispensing in Canada by province for 2005-2012, including a focus on the potential effects of interventions. Data on annual dispensing of individual POA formulations--categorized into 'weak opioids' and 'strong opioids'--from a representative sub-sample of 5,700 retail pharmacies across Canada (from IMS Brogan's Compuscript) were converted into Defined Daily Doses (DDD), and examined intra- and inter-provincially as well as for Canada (total). RESULTS: Total POA dispensing--driven by strong opioids--increased across Canada until 2011; four provinces indicated decreases in strong opioid dispensing; seven provinces indicated decreases specifically in oxycodone dispensing, 2011-2012. The dispensing ratio weak/strong opioids decreased substantively. Major inter-provincial differences in POA dispensing levels and qualitative patterns of POA formulations dispensed persisted. Previous increasing trends in POA dispensing were reversed in select provinces 2011-2012, coinciding with POA-related interventions. CONCLUSIONS: Further examinations regarding the sustained nature, drivers and consequences of the recent trend changes in POA dispensing--including possible 'substitution effects' for oxycodone reductions--are needed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.216
Threshold uncertainty score0.543

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.054
GPT teacher head0.390
Teacher spread0.336 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations85
Published2014
Admission routes3
Has abstractyes

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