Risk Management of Clinical Reference Dosimetry of a Large Hospital Network Using Statistical Process Control.

Seng-Boh Lim, Thomas LoSasso, Maria Chan, Laura Cervino, Dale Michael Lovelock
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Abstract

Managing TG-51 reference dosimetry in a large hospital network can be a challenging task. The objectives of this study are to investigate the effectiveness of using Statistical Process Control (SPC) to manage TG-51 workflow in such a network. All the sites in the network performed the annual reference dosimetry in water according to TG-51. These data were used to cross-calibrate the same ion chambers in plastic phantoms for monthly QA output measurements. An energy-specific dimensionless beam quality cross-calibration factor, k q n S W , was derived to monitor the process across multiple sites. The SPC analysis was then performed to obtain the mean, k q n S W , standard deviation, σ k , the Upper Control Limit (UCL) and Lower Control Limit (LCL) in each beam. This process was first applied to 15 years of historical data at the main campus to assess the effectiveness of the process. A two-year prospective study including all 30 linear accelerators spread over the main campus and seven satellites in the network followed. The ranges of the control limits (±3σ) were found to be in the range of 1.7% - 2.6% and 3.3% - 4.2% for the main campus and the satellite sites respectively. The wider range in the satellite sites was attributed to variations in the workflow. Standardization of workflow was also found to be effective in narrowing the control limits. The SPC is effective in identifying variations in the workflow and was shown to be an effective tool in managing large network reference dosimetry.

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基于统计过程控制的大型医院网络临床参考剂量学风险管理
在大型医院网络中管理TG-51参考剂量测定可能是一项具有挑战性的任务。本研究的目的是调查在这种网络中使用统计过程控制(SPC)来管理TG-51工作流程的有效性。网络中的所有站点都按照TG-51进行了年度参考剂量测定。这些数据用于交叉校准塑料模型中相同的离子室,用于每月QA输出测量。导出了能量特定的无因次光束质量交叉校准因子kq n S W,以监测跨多个站点的过程。然后进行SPC分析,得到每根梁的平均值、< k q n S W >、标准差、σ k、上控制限(UCL)和下控制限(LCL)。该流程首先应用于主校区15年的历史数据,以评估该流程的有效性。随后进行了一项为期两年的前瞻性研究,包括分布在主校区的所有30个线性加速器和网络中的7颗卫星。控制范围(±3σ)分别为主校区的1.7% ~ 2.6%和卫星站点的3.3% ~ 4.2%。卫星站点的范围较宽归因于工作流程的变化。工作流程的标准化也被发现在缩小控制范围方面是有效的。SPC在识别工作流程中的变化方面是有效的,并且被证明是管理大型网络参考剂量学的有效工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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