Patient and in-hospital predictors of post-discharge opioid utilization: Individualizing prescribing after radical prostatectomy based on the ORIOLES initiative

•Factors strongly correlated with post-discharge opioid utilization for patients after radical prostatectomy include in-hospital opioid use, patient-reported pain scores, prior opioid use, and body mass index.•Based on these data, a predictive model of opioid utilization for individual patients has been developed to facilitate individualized opioid prescribing at hospital discharge.•This model has been implemented as an online calculator to help more reliably meet individual needs while minimizing the risks of both overprescribing and underprescribing. Judicious opioid stewardship would match each patient's prescription to their true medical necessity. However, most prescribing paradigms apply preset quantities and clinical judgment without objective data to predict individual use. We evaluated individual patient and in-hospital parameters as predictors of post-discharge opioid utilization after radical prostatectomy (RP) to provide evidence-based guidance for individualized prescribing. A prospective cohort of patients who underwent open or robotic RP were followed in the Opioid Reduction Intervention for Open, Laparoscopic, and Endoscopic Surgery (ORIOLES) initiative. Baseline demographics, in-hospital parameters, and inpatient and post-discharge pain medication utilization were tabulated. Opioid medications were converted to oral morphine equivalents (OMEQ). Predictive factors for post-discharge opioid utilization were analyzed by univariable and multivariable linear regression, adjusting for opioid reduction interventions performed in ORIOLES. Of 443 patients, 102 underwent open and 341 underwent robotic RP. The factors most strongly associated with post-discharge opioid utilization included inpatient opioid utilization in the final 12 hours before discharge (+39.6 post-discharge OMEQ if inpatient OMEQ was >15 vs. 0), maximum patient-reported pain score (range 0–10) in the 12 hours before discharge (+27.6 OMEQ for pain score ≥6 vs. ≤1), preoperative opioid use (+76.2 OMEQ), and body mass index (BMI; +1.4 OMEQ per 1 kg/m2). A final predictive calculator to guide post-discharge opioid prescribing was constructed. Following RP, inpatient opioid use, patient-reported pain scores, prior opioid use, and BMI are correlated with post-discharge opioid utilization. These data can help guide individualized opioid prescribing to reduce risks of both overprescribing and underprescribing.