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Record W4220795329 · doi:10.1186/s40545-022-00423-1

Trends in dispensing of individual prescription opioid formulations, Canada 2005–2020

2022· article· en· W4220795329 on OpenAlex
Wayne Jones, Ridhwana Kaoser, David Rudoler, Benedikt Fischer

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Pharmaceutical Policy and Practice · 2022
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsUniversity of TorontoOntario Tech UniversitySimon Fraser University
FundersCanadian Institutes of Health Research
KeywordsHydrocodoneOxycodoneHydromorphoneMedicineOpioidCodeineFentanylMorphinePopulationMedical prescriptionHeroinAnesthesiaPharmacologyInternal medicineDrugEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Canada has experienced a distinctly bifurcated pattern of (strong) opioid utilization post-2000, with multifold increases rendering it one of the world's highest opioid consumption rates, followed by subsequent substantive declines since 2011/2012. Several interventions to control especially high-risk opioid use have been implemented post-2010 at different levels, yet with their effects assessed mostly for overall opioid utilization. Little knowledge exists for over-time patterns of individual opioid formulations. METHODS: Raw information on community-based prescription opioid dispensing for years 2005-2020 were obtained from a large national database based on a stratified sample of 6500 retail pharmacies across Canada (IQVIA/Compuscript), These data were converted into Defined-Daily-Doses/1000 population/day (DDD/1000/day) for individual (strong and weak) opioid formulations-specifically: fentanyl, hydromorphone, hydrocodone, morphine, oxycodone, codeine-per standard methods. Descriptive data on individual opioid dispensing were computed, and segmented regression (or 'broken-stick') analysis was applied to the overtime dispensing towards assessing potentially significant 'breakpoints' interrupting linear utilization trends. Akaike information criterion (AIC) values were computed to assess the resulting models' quality-of-fit. RESULTS: Five of the six opioid formulations featured a lower dispensing level in 2020 compared with 2005, but mostly with peak values in years between, contributing to the overall inversion pattern. For five of the six opioid formulations, a three-segmented model emerged as the best fit for the dispensing observed; only hydrocodone presented a linear (downward) dispensing trend. Among the five interrupted trend models for individual formulations, four (fentanyl, morphine, oxycodone, codeine but not hydromorphone) indicated their initial breakpoint during 2011-2014 introducing a downward dispensing trend. Inconsistently, morphine also featured a recent breakpoint (2018) towards a dispensing increase. CONCLUSIONS: While all opioids showed marked declines, we found heterogeneous patterns of dispensing for individual opioid formulations. While we cannot estimate direct causal effects, opioid control interventions appear to have had differential impacts on dispensing of individual formulations. The earliest breakpoint occurred towards substantive decreases for oxycodone dispensing in 2011; subsequently, there were increases in dispensing of hydromorphone and fentanyl likely due to substitution effects, followed by across-the-board declines post-2015/2016. Recent 'safer opioid' distribution programs to reduce illicit/toxic opioid exposure linked with high levels of poisoning fatalities seem to fuel resurgences in select opioid (e.g., morphine) dispensing.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.609
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.406
Teacher spread0.352 · 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