From the Department of Radiation Oncology, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.
Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
J Patient Saf. 2023 Jan 1;19(1):e18-e24. doi: 10.1097/PTS.0000000000001071. Epub 2022 Aug 10.
Stereotactic body radiation therapy (SBRT) can improve therapeutic ratios and patient convenience, but delivering higher doses per fraction increases the potential for patient harm. Incident learning systems (ILSs) are being increasingly adopted in radiation oncology to analyze reported events. This study used an ILS coupled with a Human Factor Analysis and Classification System (HFACS) and barriers management to investigate the origin and detection of SBRT events and to elucidate how safeguards can fail allowing errors to propagate through the treatment process.
Reported SBRT events were reviewed using an in-house ILS at 4 institutions over 2014-2019. Each institution used a customized care path describing their SBRT processes, including designated safeguards to prevent error propagation. Incidents were assigned a severity score based on the American Association of Physicists in Medicine Task Group Report 275. An HFACS system analyzed failing safeguards.
One hundred sixty events were analyzed with 106 near misses (66.2%) and 54 incidents (33.8%). Fifty incidents were designated as low severity, with 4 considered medium severity. Incidents most often originated in the treatment planning stage (38.1%) and were caught during the pretreatment review and verification stage (37.5%) and treatment delivery stage (31.2%). An HFACS revealed that safeguard failures were attributed to human error (95.2%), routine violation (4.2%), and exceptional violation (0.5%) and driven by personnel factors 32.1% of the time, and operator condition also 32.1% of the time.
Improving communication and documentation, reducing time pressures, distractions, and high workload should guide proposed improvements to safeguards in radiation oncology.
立体定向体放射治疗(SBRT)可以提高治疗比率和患者便利性,但每部分剂量增加会增加患者伤害的风险。事件学习系统(ILS)在放射肿瘤学中越来越多地被采用来分析报告的事件。本研究使用 ILS 结合人为因素分析和分类系统(HFACS)和障碍管理来调查 SBRT 事件的起源和检测,并阐明如何防止安全措施失效,导致错误在治疗过程中传播。
在 2014 年至 2019 年间,使用内部 ILS 在 4 家机构审查了报告的 SBRT 事件。每家机构都使用了定制的护理路径来描述他们的 SBRT 流程,包括防止错误传播的指定安全措施。根据美国医学物理学家协会任务组报告 275,根据严重程度对事件进行评分。HFACS 系统分析了失效的安全措施。
共分析了 160 起事件,其中 106 起为接近事故(66.2%),54 起为事故(33.8%)。50 起事件被指定为低严重程度,其中 4 起被认为是中等严重程度。事件最常发生在治疗计划阶段(38.1%),并在治疗前审查和验证阶段(37.5%)和治疗实施阶段(31.2%)被发现。HFACS 显示,安全措施失效归因于人为错误(95.2%)、常规违规(4.2%)和特殊违规(0.5%),其中人员因素驱动的安全措施失效占 32.1%,操作人员状态也占 32.1%。
提高沟通和文件记录的质量、减少时间压力、分散注意力和高工作量应指导放射肿瘤学中安全措施的改进。