Surgeon Postoperative Opioid Prescribing Intensity and Risk of Persistent Opioid Use Among Opioid-naive Adult Patients
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to determine the relationship between surgeon opioid prescribing intensity and subsequent persistent opioid use among patients undergoing surgery. SUMMARY BACKGROUND DATA: The extent to which different postoperative prescribing practices lead to persistent opioid use among surgical patients is poorly understood. METHODS: Retrospective population-based cohort study assessing opioid-naive adults who underwent 1 of 4 common surgeries. For each surgical procedure, the surgeons' opioid prescribing intensity was categorized into quartiles based on the median daily dose of morphine equivalents of opioids dispensed within 7 days of the surgical visit for all the surgeons' patients. The primary outcome was persistent opioid use in the year after surgery, defined as 180 days or more of opioids supplied within the year after the index date excluding prescriptions filled within 30 days of the index date. Secondary outcomes included a refill for an opioid within 30 days and emergency department visits and hospitalizations within 1 year. RESULTS: Among 112,744 surgical patients, patients with surgeons in the highest intensity quartile (Q4) were more likely to fill an opioid prescription within 7 days after surgery compared with those in the lowest quartile (Q1) (83.3% Q4 vs 65.4% Q1). In the primary analysis, the incidence of persistent opioid use in the year after surgery was rare in both highest and lowest quartiles (0.3% Q4 vs 0.3% Q1), adjusted odds ratio (AOR) of 1.18, 95% CI 0.83-1.66). However, multiple analyses using stricter definitions of persistent use that included the requirement of a prescription filled within 7 days of discharge after surgery showed a significant association with surgeon quartile (up to an AOR 1.36, 95% CI 1.25, 1.47). Patients in Q4 were more likely to refill a prescription within 30 days (4.8% Q4 vs 4.0% Q1, AOR 1.14, 95% CI 1.04-1.24). CONCLUSIONS: Surgeons' overall prescribing practices may contribute to persistent opioid use and represent a target for quality improvement. However, the association was highly sensitive to the definition of persistent use used.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".