Standardization of Outpatient Procedure (STOP) Narcotics: A Prospective Non-Inferiority Study to Reduce Opioid Use in Outpatient General Surgical Procedures
Bibliographic record
Abstract
BACKGROUND: There has been a dramatic rise in opioid abuse, and diversion of excess, unused prescriptions is a major contributor. We assess the impact of implementing a new standardized pain care bundle to reduce postoperative opioids in outpatient general surgical procedures. STUDY DESIGN: This study was designed to demonstrate non-inferiority for the primary end point: patient-reported average pain in the first 7 postoperative days. We prospectively evaluated 224 patients who underwent laparoscopic cholecystectomy or open hernia repair (inguinal, umbilical) pre-intervention to 192 patients post-intervention. We implemented a multimodal intra- and postoperative analgesic bundle, including promoting co-analgesia, opioid-reduced prescriptions, and patient education designed to clarify patient expectations. Patients completed a brief pain inventory at their first postoperative visit. Groups were compared using chi-square test, Mann-Whitney U test, and independent samples t-test, where appropriate. RESULTS: No difference was seen in average postoperative pain scores in the pre- vs post-intervention groups (2.3 vs 2.1 of 10; p = 0.12). The reported quality of pain control improved post-intervention (good/very good pain control in 69% vs 85%; p < 0.001). The median total morphine equivalents for prescriptions filled in the post-intervention group were significantly less (100; interquartile range 75 to 116 pre-intervention vs 50; interquartile range 50 to 50 post-intervention; p < 0.001). Only 78 of 172 (45%) patients filled their opioid prescription in the post-intervention group (p < 0.001), with no significant difference in prescription renewals (3.5% pre-intervention vs 2.6% post-intervention; p = 0.62). CONCLUSIONS: For outpatient open hernia repair and cholecystectomy, a standardized pain care bundle decreased opioid prescribing significantly and frequently eliminated opioid use, and adequately treating postoperative pain and improving patient satisfaction.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".