Surgical Innovation Center, Department of Surgery and Cancer, Imperial College London, St. Mary's Hospital, London, UK.
Department of Surgical Research and Innovation, The Royal College of Surgeons of England, London, UK.
Ann Surg. 2020 May;271(5):868-874. doi: 10.1097/SLA.0000000000003164.
To present a novel network-based framework for the study of collaboration in surgery and demonstrate how this can be used in practice to help build and nurture collaborations that foster innovation.
Surgical innovation is a social process that originates from complex interactions among diverse participants. This has led to the emergence of numerous surgical collaboration networks. What is still needed is a rigorous investigation of these networks and of the relative benefits of various collaboration structures for research and innovation.
Network analysis of the real-world innovation network in robotic surgery. Hierarchical mixed-effect models were estimated to assess associations between network measures, research impact and innovation, controlling for the geographical diversity of collaborators, institutional categories, and whether collaborators belonged to industry or academia.
The network comprised of 1700 organizations and 6000 links. The ability to reach many others along few steps in the network (closeness centrality), forging a geographically diverse international profile (network entropy), and collaboration with industry were all shown to be positively associated with research impact and innovation. Closed structures (clustering coefficient), in which collaborators also collaborate with each other, were found to have a negative association with innovation (P < 0.05 for all associations).
In the era of global surgery and increasing complexity of surgical innovation, this study highlights the importance of establishing open networks spanning geographical boundaries. Network analysis offers a valuable framework for assisting surgeons in their efforts to forge and sustain collaborations with the highest potential of maximizing innovation and patient care.
提出一种新的基于网络的手术协作研究框架，并展示如何在实践中使用它来帮助建立和培养促进创新的协作关系。
外科创新是一个源自不同参与者之间复杂互动的社会过程。这导致了许多外科协作网络的出现。目前仍需要对这些网络以及各种协作结构对研究和创新的相对益处进行严格的调查。
对机器人手术中的真实创新网络进行网络分析。使用层次混合效应模型来评估网络指标、研究影响力和创新之间的关联，同时控制合作者的地理多样性、机构类别以及合作者是否来自工业界或学术界。
该网络包含 1700 个组织和 6000 个链接。在网络中，通过少数几步就可以与许多其他人联系（接近中心性）、建立地理上多样化的国际网络（网络熵），以及与工业界合作，都与研究影响力和创新呈正相关。而封闭结构（聚类系数），即合作者之间也相互合作，与创新呈负相关（所有关联的 P 值均<0.05）。
在全球外科手术时代和外科创新日益复杂的背景下，本研究强调了建立跨越地理边界的开放网络的重要性。网络分析为外科医生提供了一个有价值的框架，帮助他们建立和维持具有最大创新和患者护理潜力的合作关系。
