Machine learning can help personalize opioid-sparing strategies for outpatient surgeries.

• In a study of 223 patients, 42% required opioids, using a median of 4 doses post-surgery.
• The machine learning model identified key risk factors like active cancer and age, achieving an AUC of 0.674, with 70% sensitivity and 68% specificity.

Adoption of this model could refine pain management plans in surgical practice, reducing reliance on opioids and minimizing risks of dependence.