Department of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona.
Department of Radiation Oncology, University of North Carolina School of Medicine, Chapel Hill, North Carolina.
Pract Radiat Oncol. 2018 Mar-Apr;8(2):123-132. doi: 10.1016/j.prro.2017.10.007. Epub 2018 Jan 9.
The Radiation Oncology Incident Learning System (RO-ILS) receives event reports from facilities across the country. This effort extracted common error pathways seen in the data. These pathways, expressed as fault trees, demonstrate the need for, and opportunities for, preventing these errors and/or limiting their propagation to treatment.
As of the third quarter of 2016, 2344 event reports had been submitted to RO-ILS and reviewed. A total of 396 of the reports judged highest priority were rereviewed and assigned up to 3 keywords to classify events. Based on patterns among the keyword assignments, the data were further aggregated into pathways leading to 3 general error types: "problematic plan approved for treatment," "wrong shift instructions given to therapists," and "wrong shift performed at treatment." Fault trees were created showing how different errors at different stages in the treatment process combine to flow into these general error types.
A total of 173 of the 396 (44%) events were characterized as belonging to 1 of these 3 general error types. Ninety-nine events were defined as "problematic plan approved for treatment," 40 as "wrong shift instructions given to therapists," and 34 as "wrong shift performed at treatment." Seventy-six of these events (44%) resulted in incorrectly delivered treatment. Event discovery was by therapists (n = 76), physicists (n = 45), physicians (n = 23), dosimetrists (n = 15), or not identified (n = 9); 5 events were found as a result of the patient questioning the staff. For the event type "problematic plan approved for treatment," 64 of the 99 (65%) events were attributable to physician error: incorrect target or dosing pattern prescribed.
Data extracted from RO-ILS event reports demonstrate common error pathways in radiation oncology that propagate all the way to treatment. Additional study and coordination of efforts is needed to develop and share best practices to address the sources of these errors and curtail their propagation.
放射肿瘤学事件学习系统(RO-ILS)接收来自全国各地设施的事件报告。这项工作提取了数据中常见的错误路径。这些路径以故障树的形式表示,需要并为防止这些错误和/或限制其传播到治疗中提供了机会。
截至 2016 年第三季度,RO-ILS 已收到并审查了 2344 份事件报告。共有 396 份被评为优先级最高的报告被重新审查,并分配了最多 3 个关键字来对事件进行分类。根据关键字分配中的模式,数据进一步汇总成导致 3 种一般错误类型的路径:“有问题的计划获得治疗批准”、“向治疗师发出错误的轮班指令”和“在治疗时执行错误的轮班”。创建故障树显示了治疗过程中不同阶段的不同错误如何组合成这些一般错误类型。
在 396 份报告中,共有 173 份(44%)被认为属于这 3 种一般错误类型之一。99 份事件被定义为“有问题的计划获得治疗批准”,40 份为“向治疗师发出错误的轮班指令”,34 份为“在治疗时执行错误的轮班”。其中 76 项(44%)事件导致治疗不当。事件的发现是由治疗师(n=76)、物理学家(n=45)、医生(n=23)、剂量师(n=15)或未确定(n=9)发现的;有 5 项事件是由于患者向工作人员提问而发现的。对于“有问题的计划获得治疗批准”这一事件类型,99 份报告中有 64 份(65%)是由于医生的错误:处方的目标或剂量模式不正确。
从 RO-ILS 事件报告中提取的数据显示了放射肿瘤学中常见的错误路径,这些错误路径一直传播到治疗。需要进一步研究和协调努力,以制定和分享最佳实践,以解决这些错误的根源,并遏制其传播。