MP51-09: Examining Post-Operative Opioid Prescribing Patt ... ing an Enterprise-Wide Electronic Medical Record

Examining Post-Operative Opioid Prescribing Patterns Following Urologic Surgery Using an Enterprise-Wide Electronic Medical Record

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INTRODUCTION

Opioid misuse is an accelerating public health crisis in the United States. Increasing attention has been directed towards surgical sources of opioid over-prescription. To better inform efforts to improve the safety of post-operative analgesia, we aimed to examine factors associated with opioid prescribing practices following urological surgery.

METHODS

We used a centralized electronic health record (EHR) system platform at a multi-site academic medical center to identify patients who underwent short stay and ambulatory urologic surgeries from January to December 2016. Dispensed opioid doses were extracted from the Epic EHR. Using standard conversion factors, we calculated equivalents of 5mg of oxycodone, which were characterized as high (> 30 5mg oxycodone tablets) or low (≤ 30). We tabulated and compared clinical, demographic, surgical, and provider characteristics across prescription dose thresholds using descriptive statistics. Multivariable logistic regression was used to assess factors associated with high dose therapy.

RESULTS

A total of 2,571 urologic procedures in 1,970 unique patients were reviewed (Figure 1). Among patients receiving an outpatient opioid prescription, the median dose was 25 (IQR 15-30); when stratified by scale of procedure, median dose prescribed in minor procedures was 20 (IQR 15-30) and in major procedures was 30 (IQR 20-40). 909 patients were not prescribed any opioids. In multivariate analyses, academic setting (OR 2.73, 95% CI, 2.27-3.28), higher BMI (OR 1.24, 95% CI, 1.03-1.50), major procedure (OR 7.26, 95% CI, 4.79-11.00), ER visit within 30 days (OR 1.46, 95% CI, 1.11-1.92), and current smokers (OR 1.34, 95% CI, 1.01-1.92) were more likely to be prescribed opioids. In multivariate analysis adjusted for scale of surgical procedure, lower BMI (OR 1.34, 95% CI, 1.03-1.75), and those with a history of comorbid psychiatric diagnosis (OR 1.39, 95% CI, 1.04-1.87) were prescribed higher doses.

CONCLUSION

Using an enterprise wide EHR clinical informatics tool, we observed significant variation in opioid prescription following urological surgery. Patients with a history of psychiatric diagnosis received higher doses. Efforts are warranted to optimize estimates of opioids required postoperatively to improve safety.

Funding: None