摘要目的:运用复杂网络模型，分析护理隐性安全事件风险因素，为临床护理安全管理提供依据。方法:收集河南省某三级甲等医院2021—2023年404例护理安全不良事件上报资料，采用扎根理论方法提取风险因素，构建复杂网络模型；使用Gephi软件分析网络拓扑结构，计算聚类系数和节点度等参数，并通过TOPSIS法评估节点重要度，识别关键风险因素。结果:获得51个概念(风险因素)和19个主范畴。风险因素网络模型包含51个节点和223条有向边，网络密度为0.087，平均路径长度为2.798，聚类系数为0.308，具有小世界特性。核心制度落实情况总度值(41)和出度值最高(40)，是网络中的核心节点；护士风险意识入度值最大(19)，易受其他节点影响。护士风险意识、患者病情掌握、核心制度落实情况、病房环境、护理中断和操作中断是风险网络的关键节点，贴近度>0.500。结论:护理隐性安全事件发生与风险因素紧密相关，护士风险意识等6个关键节点是风险传导的关键枢纽，医院需对这些节点进行动态管控并阻断传导路径，保障护理安全。

abstractsObjective:To analyze the risk factors for hidden nursing safety incidents using complex network model, so as to provide references for clinical nursing safety management.Methods:Data on 404 adverse nursing safety events reported from 2021 to 2023 at a tertiary hospital in Henan Province were collected. Using grounded theory, risk factors were extracted to construct a directed weighted complex network model. The Gephi software was employed to analyze the network topology, calculating parameters such as clustering coefficient and node degree. The TOPSIS method was employed to evaluate node importance, and identify key risk factors.Results:A total of 51 concepts (risk factors) and 19 main categories were identified. The risk factor network model comprised 51 nodes and 223 directed edges, exhibiting a network density of 0.087, an average path length of 2.798, and a clustering coefficient of 0.308, demonstrating small-world characteristics. The core system implementation degree value (41) and out-degree value (40) were relatively high, indicating it is a core node in the network; the nurse risk awareness in-degree value (19) was the highest, making it susceptible to influence from other nodes. Critical nodes in the risk network included nurse risk awareness, patient condition understanding, core system implementation, ward environment, nursing interruption, and procedure interruption.Conclusions:The occurrence of hidden nursing safety incidents was closely linked to risk factors. Six critical nodes were served as pivotal hubs. Hospitals should implement dynamic management of these nodes and block transmission pathways to guarantee the nursing safety.