Impact of robotic surgery on patient flow and resource use intensity in ovarian cancer

• Published in: Journal of robotic surgery 2023-04, Vol.17 (2), p.537-547
• Main Authors: Abitbol, Jeremie, Kucukyazici, Beste, Brin, Sonya, Lau, Susie, Salvador, Shannon, Ramanakumar, Agnihotram V., Kessous, Roy, Kogan, Liron, Fletcher, John D., Pare-Miron, Valerie, Liu, Gilbert, Gotlieb, Walter H.
• Format: Article
• Language: English
• Subjects: Aftercare; Binomial distribution; Blood transfusions; Cancer; Capital costs; Chemotherapy; Cost analysis; Emergency medical care; Emergency medical services; Female; Generalized linear models; Health services; Hospital costs; Hospitals; Humans; Inpatients; Laparoscopy; Laparotomy; Markov chains; Medicine; Medicine & Public Health; Minimally Invasive Surgery; Original Article; Ovarian cancer; Ovarian Neoplasms - surgery; Patient Discharge; Patients; Regression models; Resource utilization; Retrospective Studies; Robotic surgery; Robotic Surgical Procedures - methods; Robotics; Salvage value; Software; Surgery; Urology; Variables
• ISSN: 1863-2491; 1863-2483; 1863-2491
• DOI: 10.1007/s11701-022-01447-0

There is an emerging focus on the role of robotic surgery in ovarian cancer. To date, the operational and cost implications of the procedure remain unknown. The objective of the current study was to evaluate the impact of integrating minimally invasive robotic surgery on patient flow, resource utilization, and hospital costs associated with the treatment of ovarian cancer during the in-hospital and post-discharge processes. 261 patients operated for the primary treatment of ovarian cancer between January 2006 and November 2014 at a university-affiliated tertiary hospital were included in this study. Outcomes were compared by surgical approach (robotic vs. open surgery) as well as pre- and post-implementation of the robotics platform for use in ovarian cancer. The in-hospital patient flow and number of emergency room visits within 3 months of surgery were evaluated using multi-state Markov models and generalized linear regression models, respectively. Robotic surgery cases were associated with lower rates of postoperative complications, resulted in a more expedited postoperative patient flow (e.g., shorter time in the recovery room, ICU, and inpatient ward), and were between $10,376 and $7,421 less expensive than the average laparotomy, depending on whether or not depreciation and amortization of the robotic platform were included. After discharge, patients who underwent robotic surgery were less likely to return to the ER (IRR 0.42, p  = 0.02, and IRR 0.47, p  = 0.055, in the univariate and multivariable models, respectively). With appropriate use of the technology, the addition of robotics to the medical armamentarium for the management of ovarian cancer, when clinically feasible, can bring about operational efficiencies and entails cost savings.