Department of Radiation Medicine & Applied Sciences, University of California, San Diego, La Jolla, California.
Icon Cancer Centre, South Brisbane, Queensland, Australia.
Int J Radiat Oncol Biol Phys. 2024 Jul 15;119(4):1307-1316. doi: 10.1016/j.ijrobp.2024.01.223. Epub 2024 Feb 15.
Cone beam computed tomography (CBCT)-based online adaptive radiation therapy (ART) is especially beneficial for patients with large interfractional anatomic changes. However, treatment planning and review decisions need to be made at the treatment console in real-time and may be delegated to clinical staff whose conventional scope of practice does not include making such decisions. Therefore, implementation can create new safety risks and inefficiencies. The objective of this work is to systematically analyze the safety and efficiency implications of human decision-making during the treatment session for CBCT-based online ART.
The analysis was performed by applying the Systems-Theoretical Process Analysis technique and its extension for human decision-making. Four centers of different CBCT-based online ART practice models comprised the analysis team.
The general radiation therapy control structure was refined to model the interactions between routine treatment delivery staff and in-person or remote support staff. The treatment delivery staff perform 6 key control actions. Eighteen undesirable states of those control actions were identified as affecting safety and/or efficiency. In turn, 97 hazardous clinical scenarios were identified, with the control action "prepare and position patient" having the least number of scenarios and "delineate/edit influencer and target structures" having the most. Five of these are specific to either in-person or remote support during the treatment session, and 12 arise from staff support in general.
An optimally safe and efficient online ART program should require little to no support staff at the treatment console to reduce staff coordination. Uptraining of the staff already at the treatment console is needed to achieve this goal. Beyond the essential knowledge and skills such as contour editing and the selection of an optimal plan, uptraining should also target the specific cognitive biases identified in this work and the cognitive strategies to overcome these biases. Additionally, technological and organizational changes are necessary.
基于锥形束计算机断层扫描(CBCT)的在线自适应放疗(ART)特别有益于那些分次间解剖结构变化较大的患者。然而,在治疗时需要在治疗控制台实时做出治疗计划和审查决策,并且可能会将这些决策委派给临床工作人员,而他们的常规实践范围不包括做出此类决策。因此,实施可能会产生新的安全风险和低效率。本研究的目的是系统分析在基于 CBCT 的在线 ART 治疗过程中,人为决策对安全性和效率的影响。
采用系统理论过程分析技术及其对人为决策的扩展,对安全性和效率的影响进行分析。该分析由来自不同基于 CBCT 的在线 ART 实践模式的四个中心的人员组成分析团队。
对常规放疗控制结构进行了细化,以模拟常规治疗实施人员与现场或远程支持人员之间的相互作用。治疗实施人员执行 6 项关键控制操作。确定了这 6 项控制操作的 18 种不良状态,这些状态会影响安全性和/或效率。反过来,确定了 97 种危险的临床场景,其中控制操作“准备和定位患者”的场景数最少,“勾画/编辑影响因素和靶区结构”的场景数最多。其中 5 种场景仅出现在治疗过程中的现场或远程支持中,另外 12 种场景则来自一般的人员支持。
要实现安全且高效的在线 ART 项目,需要在治疗控制台配备最少数量的支持人员,以减少人员协调。需要对已经在治疗控制台的工作人员进行再培训,以实现这一目标。除了轮廓编辑和选择最佳计划等必要的知识和技能外,再培训还应针对本研究中确定的特定认知偏差和克服这些偏差的认知策略。此外,还需要进行技术和组织变革。