Georgia Quality Improvement Programs Multi-Institutional Collection of Postoperative Opioid Data Using ACS-NSQIP Abstraction

• Published in: The American surgeon 2022-07, Vol.88 (7), p.1510-1516
• Main Authors: Codner, Jesse A, Falconer, Elissa A, Ashley, Dennis W, Sweeney, John F, Saeed, Muhammad I, Langer, Jason M, Shaffer, Virginia O, Finley, Charles R, Solomon, Gina, Sharma, Jyotirmay
• Format: Article
• Language: English
• Subjects: Analgesics, Opioid - therapeutic use; Collaboration; Confidence intervals; Data capture; Data collection; Data collection platforms; Georgia; Guidelines; Hernias; Humans; Hypothesis testing; Laparoscopy; Mathematical analysis; Morphine; Narcotics; Opioid-Related Disorders; Opioids; Optimization; Pain management; Pain, Postoperative - drug therapy; Patients; Postoperative period; Practice Patterns, Physicians; Prescriptions; Quality control; Quality Improvement; Quality standards; Retrospective Studies; Surgery; Variables
• ISSN: 0003-1348; 1555-9823
• DOI: 10.1177/00031348221082286

Background Excessive postoperative opioid prescribing contributes to opioid misuse throughout the US. The Georgia Quality Improvement Program (GQIP) is a collaboration of ACS-NSQIP participating hospitals. GQIP aimed to develop a multi-institutional opioid data collection platform as well as understand our current opioid-sparing strategy (OSS) usage and postoperative opioid prescribing patterns. Methods This study was initiated 7/2019, when 4 custom NSQIP variables were developed to capture OSS usage and postoperative opioid oral morphine equivalents (OMEs). After pilot collection, our discharge opioid variable required optimization for adequate data capture and was expanded from a free text option to 4 drop-down selection variables. Data collection then continued from 2/2020-5/2021. Logistic regression was used to determine associations with OSS usage. Average OMEs were calculated for common general surgery procedures and compared to national guidelines. Results After variable optimization, the percentage where a total discharge prescription OME could be calculated increased from 26% to 70% (P < .001). The study included 820 patients over 10 operations. There was a significant variation in OSS usage between GQIP centers. Laparoscopic cases had higher odds of OSS use (1.92 (1.38-2.66)) while OSS use had lower odds in black patients on univariate analysis (.69 (.51-.94)). On average 7 out of the 10 cases had higher OMEs prescribed compared to national guidelines recommendations. Conclusion Developing a multi-institutional opioid data collection platform through ACS-NSQIP is feasible. Preselected drop-down boxes outperform free text variables. GQIP future quality improvement targets include variation in OSS use and opioid overprescribing.