Surgery has changed significantly in recent years due to the introduction of advanced technologies, resulting in increased system complexity at the technical, human and organisational levels, which may lead to higher variability of patient outcome due to new error pathways. Current approaches towards a safer surgery are largely based on ex-post analysis of events and process monitoring (e.g. root cause analysis, safety checklists, safety audits). However, adopting a proactive approach enables the prior identification of critical factors and the design of safer sociotechnical systems, thanks to a multi-level (or mesoergnomics) perspective. In this paper, a methodology for performing mesoergonomics analysis of surgical procedures is proposed. It is a methodology for Dynamic Human Reliability Analysis in Robotic Surgery based on a modified version of human error assessment and reduction technique (HEART) integrated with a method for incorporating uncertainties related to the influence of personal and organisational factors on the execution of a surgical procedure. The pilot application involves a robot-assisted radical prostatectomy procedure, and the results reveal that team-related factors have the greatest impact on patient outcome variability.

近年来，由于引入了先进技术，外科手术发生了显着变化，导致技术，人员和组织层面的系统复杂性增加，这可能由于新的错误途径而导致患者结果的差异更大。当前更安全的手术方法主要基于事后分析和过程监控（例如根本原因分析，安全清单，安全审核）。但是，由于具有多层次（或中观人体工程学）的观点，采用主动的方法可以事先确定关键因素并设计更安全的社会技术系统。在本文中，提出了一种进行手术程序的人体工学分析的方法。它是一种基于人为错误评估和减少技术（HEART）改进版的机器人手术动态人类可靠性分析方法，该方法与一种方法结合在一起，该方法将与个人和组织因素对手术过程的影响有关的不确定性纳入其中。该试点应用程序涉及机器人辅助的根治性前列腺切除术程序，结果表明与团队相关的因素对患者结局变异性的影响最大。