Factors Associated with Same Day Discharge after Laparoscopic Surgery in Gynecologic Oncology

Study Objective: To identify factors associated with same day discharge (SDD) after laparoscopic surgery in gynecologic oncology. Design: Retrospective cohort. Setting: Teaching hospital. Patients: Total of 800 patients having minimally invasive surgery in the division of gynecologic oncology during a 20month period. Intervention: Minimally invasive surgery cases were reviewed for determinants of SDD to identify factors that could improve the SDD rate. Measurements and Main Results: During the study period, 800 minimally invasive procedures were performed with a 43.0% SDD rate. Patients who had SDD were younger (52.3 years vs 58.0 years; p <.001), had a lower body mass index (31.1 kg/m 2 vs 33.7 kg/m(2); p <.001), were less likely to have a malignancy (28.2% vs 55.5%; p <.001), had a lower estimated blood loss (36 vs 72 mL; p <.001), and were more likely to have received an enhanced recovery after surgery protocol (49.8% vs 39.3%; p <.003). Total surgical time was shorter in women with SDD (156 minutes vs 208 minutes) as was total narcotic use in morphine equivalents (MEq) (milligram intravenous MEq, 23.1 mg MEq vs 28.8 mg MEq). SDD was also associated with earlier start time (p <.001). Laparoscopic cases were most likely to have SDD (51.4%) as compared with robotic assisted surgery (16.1%) or minilaparotomy (10.5%). There was a wide range of SDD among surgeons ranging from 19.8% to 56.2% (p <.001). In a multivariate analysis, the factors predicting SDD in order of predictive factors were surgical time (p <.001), recovery time (p <.001), start time (p <.001), surgeon (p <.001), age (p <.001), estimated blood loss (p <.001), and type of surgery (p = .005). Conclusion: Multiple factors affect SDD. Modifiable factors for SDD include the start time, surgeon preference, and patient expectations for SDD. Given these data, centers should prioritize surgical order by which patients are more likely to go home, and surgeons should analyze their own data with respect to achieving higher SDD rates. (C) 2021 AAGL. All rights reserved.