Establishing a fault management system for da Vinci robot-assisted laparoscopic surgery: identification, troubleshooting, and rapid resumption.

To develop a fault identification, troubleshooting, and rapid recovery system for da Vinci robot-assisted laparoscopic surgery (referred to as the "robot") to enhance clinical decision-making and ensure patient safety during robotic procedures. We retrospectively analyzed 4,784 surgeries performed using the "Si" robot at our hospital from September 2014 to May 2023, identifying 105 fault instances, and 776 surgeries using the "Xi" robot from April 2022 to May 2023, with 18 fault instances. Fault repair videos, images, and data from both robots were collected, supplemented by technical support from Chindex Medical Limited and related literature. Based on these data, we established a fault identification, troubleshooting, and rapid recovery system. The system's effectiveness was evaluated by comparing fault rates, fault categories, nurses' accuracy in fault identification and troubleshooting, and repair times before and after system implementation. Significant differences were observed in fault rates, fault categories, nurses' accuracy in fault identification and troubleshooting, and repair times before and after system implementation for both the "Si" and "Xi" robots (all P < 0.05). The "Si" robot showed a significant reduction in non-recoverable fault rates (P < 0.05), while the "Xi" robot demonstrated a significant improvement in recoverable fault rates (P < 0.05). The developed system improved nurses' adherence to operational standards, enhanced fault identification accuracy, reduced repair times, increased robotic surgery efficiency, and improved nursing collaboration quality.