Department of Radiation Oncology, University of Utah, Salt Lake City, UT, USA.
Avera Cancer Institute, Sioux Falls, SD, USA.
J Appl Clin Med Phys. 2020 Aug;21(8):83-91. doi: 10.1002/acm2.12918. Epub 2020 Jun 25.
To apply failure mode and effect analysis (FMEA) to generate an effective and efficient initial physics plan checklist.
A team of physicists, dosimetrists, and therapists was setup to reconstruct the workflow processes involved in the generation of a treatment plan beginning from simulation. The team then identified possible failure modes in each of the processes. For each failure mode, the severity (S), frequency of occurrence (O), and the probability of detection (D) was assigned a value and the risk priority number (RPN) was calculated. The values assigned were based on TG 100. Prior to assigning a value, the team discussed the values in the scoring system to minimize randomness in scoring. A local database of errors was used to help guide the scoring of frequency.
Twenty-seven process steps and 50 possible failure modes were identified starting from simulation to the final approved plan ready for treatment at the machine. Any failure mode that scored an average RPN value of 20 or greater was deemed "eligible" to be placed on the second checklist. In addition, any failure mode with a severity score value of 4 or greater was also considered for inclusion in the checklist. As a by-product of this procedure, safety improvement methods such as automation and standardization of certain processes (e.g., dose constraint checking, check tools), removal of manual transcription of treatment-related information as well as staff education were implemented, although this was not the team's original objective. Prior to the implementation of the new FMEA-based checklist, an in-service for all the second checkers was organized to ensure further standardization of the process.
The FMEA proved to be a valuable tool for identifying vulnerabilities in our workflow and processes in generating a treatment plan and subsequently a new, more effective initial plan checklist was created.
应用失效模式和效果分析(FMEA)生成有效的初始物理计划清单。
成立了一个物理学家、剂量师和治疗师团队,以重建从模拟开始生成治疗计划所涉及的工作流程。然后,团队在每个流程中识别可能的失效模式。对于每种失效模式,严重性(S)、发生频率(O)和检测概率(D)都被赋予一个值,然后计算风险优先数(RPN)。分配的值基于 TG 100。在分配值之前,团队讨论了评分系统中的值,以减少评分的随机性。使用本地错误数据库来帮助指导频率的评分。
从模拟到最终准备在机器上治疗的批准计划,共确定了 27 个流程步骤和 50 种可能的失效模式。任何平均 RPN 值为 20 或更高的失效模式都被认为“符合条件”,可以列入第二个清单。此外,任何严重程度评分为 4 或更高的失效模式也被考虑列入清单。作为该程序的副产品,实施了诸如自动化和某些流程的标准化(例如剂量限制检查、检查工具)、消除与治疗相关信息的手动转录以及员工教育等安全改进方法,尽管这不是团队的原始目标。在实施新的基于 FMEA 的清单之前,为所有第二检查者组织了一次在职培训,以确保进一步标准化该流程。
FMEA 被证明是识别生成治疗计划工作流程和流程中的弱点的有效工具,随后创建了一个新的、更有效的初始计划清单。