Association between sustained opioid prescription and frequent emergency department use: a cohort study
Bibliographic record
Abstract
BACKGROUND: Chronic non-cancer pain (CNCP) is common among frequent emergency department (ED) users, although factors underlying this association are unclear. This study estimated the association between sustained opioid use and frequent ED use among patients with CNCP. METHODS: Retrospective cohort study using a Canadian provincial health insurer database (Régie d'Assurance Maladie du Québec). The database included adults with both ≥1 chronic condition and ≥ 1 ED visit in 2012 or 2013. Inclusion in the study further required a CNCP diagnosis, public drug insurance coverage and 1-year survival after the first ED visit in 2012 or 2013 (index visit). Multivariable logistic regression was used to derive ORs of frequent ED use (≥5 visits in the year following the index visit) subsequent to sustained opioid use (≥60 days opioids prescription within 90 days preceding the index visit), adjusting for important covariables. RESULTS: From 576 688 patients in the database, 58 237 were included in the study. Of these, 4109 (7.1%) had received a sustained opioid prescription and 4735 (8.1%) were frequent ED users in the follow-up year. Sustained opioid use was not associated with frequent ED use in the multivariable model (OR: 1.06, 95% CI 0.94 to 1.19). Novel associated covariables were benzodiazepine prescription (OR: 1.21, 95% CI 1.12 to 1.30) and polypharmacy (OR: 1.23, 95% CI 1.13 to 1.34). CONCLUSIONS: Due to confounding by social and medical vulnerability, patients with CNCP with sustained opioid use appear to have a higher propensity for frequent ED use in unadjusted models. However, sustained opioid use was not associated with frequent ED use in these patients after adjustment.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.036 | 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".