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新型联合生物计量学、射频识别和表面成像系统预防放射治疗偏差。

Prevention of Radiation Therapy Treatment Deviations by a Novel Combined Biometric, Radiofrequency Identification, and Surface Imaging System.

机构信息

University of Utah, Salt Lake City, Utah.

University of Utah, Salt Lake City, Utah.

出版信息

Pract Radiat Oncol. 2021 Mar-Apr;11(2):e229-e235. doi: 10.1016/j.prro.2020.08.006. Epub 2020 Sep 9.

Abstract

PURPOSE

To evaluate the impact of Varian Identify, a novel combined radiofrequency identification, biometric and surface-matching technology, on its potential for patient safety and prevention of radiation therapy treatment deviations.

METHODS AND MATERIALS

One hundred eight radiation therapy treatment deviation reports at our facility over the past 8 years were analyzed. Three major categories were defined based on the time point of occurrence: physician order deviations (19.4%), treatment-planning deviations (24.1%), and machine treatment deviations (56.5%). The impact of Identify on potential prevention of machine treatment deviations was analyzed. A failure mode and effects analysis was performed on the 5 most frequently occurring errors preventable with Identify. Safety analysis of the Identify system was reported based on 3.5 years of clinical data post-Identify system installation on 3 treatment vaults.

RESULTS

Of the 61 machine treatment deviations, 47 (77%) were interpreted as being preventable by using Identify. Our failure mode and effects analysis showed reductions in all risk priority numbers post-Identify application. Safety analysis of the Identify system from our direct observation that for approximately 7 cumulative years of Identify use in 3 different treatment vaults, where 9 deviations would have been expected to occur over this combined period, zero machine treatment events occurred.

CONCLUSIONS

The combination of Identify biometric, radiofrequency identification, and surface-matching technologies was observed to enable an effective process for enhancing safety and efficiency of radiation therapy treatment. A significant reduction in machine-related deviations was observed.

摘要

目的

评估瓦里安 Identify 系统(一种新型的射频识别、生物识别和表面匹配技术)在提高患者安全性和预防放疗治疗偏差方面的潜在影响。

方法与材料

分析了过去 8 年来我们机构发生的 108 例放疗治疗偏差报告。根据发生时间点,将其分为三大类:医生医嘱偏差(19.4%)、治疗计划偏差(24.1%)和机器治疗偏差(56.5%)。分析了 Identify 系统在预防机器治疗偏差方面的潜在作用。对可通过 Identify 系统预防的 5 种最常见错误进行失效模式和影响分析。根据 Identify 系统安装后 3.5 年的临床数据,报告了 Identify 系统的安全性分析。

结果

在 61 例机器治疗偏差中,有 47 例(77%)被认为可以通过使用 Identify 系统来预防。失效模式和影响分析显示,在使用 Identify 系统后,所有风险优先数都有所降低。从我们的直接观察来看,Identify 系统在 3 个不同的治疗室中使用了约 7 年,在这段时间内预计会发生 9 例机器治疗偏差,但实际上并未发生。

结论

Identify 系统的生物识别、射频识别和表面匹配技术的组合被观察到可有效提高放疗治疗的安全性和效率。机器相关偏差显著减少。

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