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作 者:贺海萍 彭旭东[1] 罗大双 肖青[1] 李光俊[1] 柏森[1] He Haiping;Peng Xudong;Luo Dashuang;Xiao Qing;Li Guangjun;Bai Sen(Radiotherapy Physics and Technology Center,Cancer Center,West China Hospital of Sichuan University,Chengdu 610041,China)
机构地区:[1]四川大学华西医院肿瘤中心放射物理技术中心,成都610041
出 处:《中华放射医学与防护杂志》2024年第5期386-392,共7页Chinese Journal of Radiological Medicine and Protection
基 金:国家自然科学基金(81972848,12205209)。
摘 要:目的分析放射治疗安全事件中的人为因素并确定这些人为因素之间的关系,寻找放疗安全事件的潜在事故链。方法基于放射肿瘤事件学习系统纳入60例放疗安全事件,利用人为因素分析及分类系统(HFACS)进行致因识别及频率统计分析,基于分析结果采用潜在类别分析(LCA)方法对事故致因的关联性进行研究。结果计划设计阶段的错误是最常见的事件类型,占比35%,组织氛围、监督不充分以及人员因素分别是HFACS各个层级中最主要的事件致因,其频率指数分别为4.66%、15.68%和16.20%。LCA分析确定了3条常见放疗事故链,其中两条事故链起源于组织氛围问题,一条事故链起源于组织过程问题,并通过不同的人为因素“漏洞”向下传递。结论HFACS可帮助溯源导致放射治疗安全事件的各层级人为因素,本研究发现了放疗安全事件的高频致因和3条事故链,可为建立针对性的安全防御措施提供指导。Objective To analyze human factors in radiotherapy safety incidents and identify their correction for the purpose of mining the latent incident chains.Methods A total of 60 radiotherapy safety incidents were included in the Radiation Oncology Incident Learning System(ROILS)for cause identification and frequency statistics using the Human Factors Analysis and Classification System(HFACS).Latent class analysis(LCA)was performed for the result to correlate the incident causes.Results Incidents in the protocol design stage were the most common,accounting for 35%.Adverse organizational climate,inadequate supervision,and personnel factors were the primary causes of incidents at each level of the HFACS,accounting for 4.66%,15.68%,and 16.20%,respectively.Three latent incident chains were identified through LCA,comprising two originating from organizational climate issues and one from organizational process issues,which were passed down via various human factors or"loopholes"Conclusions HFACS assists in tracing the human factors at all levels that lead to radiotherapy safety incidents.The high⁃frequency causes and three latent chains of radiotherapy incidents found in this study can provide a guide for the development of targeted safety and defense measures.
关 键 词:人为因素分析及分类系统 潜在类别分析 人为因素 放疗事件
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