Flow disruptions in robotic-assisted abdominal sacrocolpopexy: does robotic surgery introduce unforeseen challenges for gynecologic surgeons?
- 30 April 2019
- journal article
- research article
- Published by Springer Science and Business Media LLC in International Urogynecology Journal
- Vol. 30 (12), 2177-2182
- https://doi.org/10.1007/s00192-019-03929-6
Abstract
Introduction and hypothesis The purpose of this study was to apply a human factors research approach to identify flow disruptions, deviations in the optimal course of care, in robotic abdominal sacrocolpopexy procedures with the ultimate goal of developing system interventions to improve the safety and efficiency of robotic surgery. Methods Twenty-four robotic abdominal sacrocolpopexy procedures were observed for flow disruptions. Surgeries were divided into four phases: (1) patient arrival and induction of anesthesia; (2) port placement and robot docking; (3) console time; (4) undocking of robot, incision closure, and patient exiting the OR. Results Flow disruptions were observed at a rate of 10.9 ± 5.1 per hour. The most frequently observed flow disruptions involved training issues (2.8 ± 2.4 flow disruptions per hour), equipment (2.2 ± 1.6 flow disruptions per hour), and poor coordination (2.0 ± 1.3 flow disruptions per hour). The rate of flow disruptions was highest in phase 2 (19.2 ± 14.4 flow disruptions per hour). Cases with more experienced surgeons involved shorter console times by 1.5 h (95% CI: 0.1, 3.0, p = 0.033) and 1.8 fewer (95% CI: 1.2, 2.6, p = 0.001) flow disruptions per hour. Surgeries were 1 h shorter on average (95% CI: 0.1, 1.9, p = 0.034) in cases in which the patient was > 65 years old. Da Vinci S console times were 0.8 h longer (95% CI: 0.01, 1.5, p = 0.047) than Si. Conclusions Flow disruptions in robotic abdominal sacrocolpopexy surgery occur about every 6 min. Flow disruption rates are highest during the most complex portions of the surgery. More experienced surgeons have lower flow disruption rates and operate more quickly.Keywords
Funding Information
- National Institute of Biomedical Imaging & Biomedical Engineering Award (R03EB017447)
- UCLA Medical Student Training in Aging Research Program—the National Institute on Aging (T35AG026736)
- John A. Hartford Foundation
- Lillian R. Gleitzman Foundation
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