Optimizing the robotic surgery team: an operations management perspective

Introduction and hypothesis To assess the critical threshold to optimize operating room (OR) time for each surgical team member in robotically assisted sacrocolpopexy (RASCP) and to evaluate the most efficient team compositions. Methods All women who underwent RASCP for pelvic organ prolapse (POP) were prospectively entered in a database. Patients having unrelated concomitant surgery were excluded. Our primary outcome measure was total OR time. We utilized factor analysis, regression analysis, and analysis of variance, OR time mapping, and stochastic optimization to identify ‘optimal’ surgical team configuration. Results The database included 359 consecutive RASCPs, all performed for stage III–IV POP: 156 (43%) were with total and 44 (12%) supracervical hysterectomies and 159 (44%) post-hysterectomy. Mean age was 58.6 ± 9.3 years. Mean parity was 2.8 ± 1.4, and mean body mass index was 28 ± 4.7 kg/m 2 . A total of 4 surgeons, 34 first assistants, 20 circulating nurses, 15 surgical technologists, and 59 anesthesiologist/nurse anesthetists were involved. Optimal experience levels for each team member were achieved at the following number of robotic procedures: surgeon 44; first assistant 13; surgical technologist 66; circulating nurse 56; anesthesia provider 46. Our analysis revealed that the surgical technologist and first assistant played the most significant roles within the team. The surgeon was ranked third followed by the circulating nurse and anesthesia provider, respectively. Conclusion Operating time in robotic surgery is multifactorial. Experience of each member of a robotic surgery team is critical. An optimal team can be composed of a variety of combinations of experience levels among the robotic team members.