Application of risk assessment tools to predict opioid usage after shoulder surgery.

Background: Currently 128 people die daily from opioid-related overdoses in the United States. This burden has instigated a search for viable means to guide postoperative prescription decision-making. The Opioid Risk Tool (ORT) and the Screener and Opioid Assessment for Patient with Pain (SOAPP) are validated risk assessment tools to predict opioid usage in high-risk populations. The purpose of this study was to evaluate the accuracy of these opioid risk assessments and pain intensity scores, including the Patient-Reported Outcomes Measurement Information System (PROMIS), to predict postoperative opioid use and dependence in shoulder surgery. Methods: A retrospective review of 81 patients who underwent shoulder surgery and completed 3 preoperative risk and pain assessments within a single hospital system from 2018 to 2020 was performed. Demographic variables and ORT-O, SOAPP-R (the revised version of the SOAPP assessment), and PROMIS 3a scores were recorded from preoperative assessments. Opioid prescriptions were recorded from Electronic-Florida Online Reporting of Controlled Substances Evaluation. Dependence was defined as opioid prescriptions at or greater than 3 months after surgery. Risk assessment scores were compared and tested against postoperative opioid prescriptions using statistical analyses and logistic regression modeling. Results: In the cohort, there were 36 female and 45 male patients with an average age of 64.5 years and body mass index of 28.0. Preoperatively, the average pain score was 6.2, and 7.8% of patients reported prolonged preoperative narcotics use. The average ORT-O score was 3.0, with 35.8% of patients defined as either medium or high risk, and the average PROMIS pain intensity preoperatively was 10.8. Neither the ORT-O nor the PROMIS pain score were good predictors of postoperative opioid dependence (area under curve = 0.39 and 0.43, respectively). The SOAPP-R performed slightly better (area under curve = 0.70) and was the only assessment with significantly different mean scores between patients with postoperative opioid dependence and those without (33.4 and 24.5, respectively, Conclusion: With recent focus on preoperative risk assessments to predict postoperative opioid use and dependence, it is important to understand how well these tools work when applied to orthopedic patients. While the ORT may be helpful in other fields, it does not seem to be a strong predictor of postoperative opioid use or dependence in patients undergoing various types of shoulder surgery. Future studies are needed to explore the utility of the SOAPP-R in a larger sample and identify tools applicable to the orthopedic population to assist surgeons in screening at-risk patients.