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Med Phys. 2016 Jul;43(7):4209. doi: 10.1118/1.4947547.

The report of Task Group 100 of the AAPM: Application of risk analysis methods to radiation therapy quality management.

Author information

1
Department of Radiation Oncology, University of Pittsburgh Cancer Institute and UPMC CancerCenter, Pittsburgh, Pennsylvania 15232.
2
Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, California 90048.
3
Department of Oncology, University of Calgary, Calgary T2N 1N4, Canada.
4
Ochsner Health System, New Orleans, Louisiana 70121.
5
Department of Radiation Physics, UT MD Anderson Cancer Center, Houston, Texas 77030.
6
Department of Radiation Medicine and Applied Sciences, University of California San Diego, San Diego, California 92093-0843.
7
Department of Radiation Oncology, Washington University School of Medicine, St. Louis, Missouri 63110.
8
Department of Radiation Oncology, Virginia Commonwealth University, P.O. Box 980058, Richmond, Virginia 23298.
9
Department of Engineering Professional Development, University of Wisconsin, Madison, Wisconsin 53706.
10
Department of Medical Physics, University of Wisconsin, Madison, Wisconsin 53705-2275.
11
Department of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia 23298-0058.
12
Department of Medical Physics, Memorial Sloan-Kettering Center, New York, New York 10065.

Abstract

The increasing complexity of modern radiation therapy planning and delivery challenges traditional prescriptive quality management (QM) methods, such as many of those included in guidelines published by organizations such as the AAPM, ASTRO, ACR, ESTRO, and IAEA. These prescriptive guidelines have traditionally focused on monitoring all aspects of the functional performance of radiotherapy (RT) equipment by comparing parameters against tolerances set at strict but achievable values. Many errors that occur in radiation oncology are not due to failures in devices and software; rather they are failures in workflow and process. A systematic understanding of the likelihood and clinical impact of possible failures throughout a course of radiotherapy is needed to direct limit QM resources efficiently to produce maximum safety and quality of patient care. Task Group 100 of the AAPM has taken a broad view of these issues and has developed a framework for designing QM activities, based on estimates of the probability of identified failures and their clinical outcome through the RT planning and delivery process. The Task Group has chosen a specific radiotherapy process required for "intensity modulated radiation therapy (IMRT)" as a case study. The goal of this work is to apply modern risk-based analysis techniques to this complex RT process in order to demonstrate to the RT community that such techniques may help identify more effective and efficient ways to enhance the safety and quality of our treatment processes. The task group generated by consensus an example quality management program strategy for the IMRT process performed at the institution of one of the authors. This report describes the methodology and nomenclature developed, presents the process maps, FMEAs, fault trees, and QM programs developed, and makes suggestions on how this information could be used in the clinic. The development and implementation of risk-assessment techniques will make radiation therapy safer and more efficient.

PMID:
27370140
PMCID:
PMC4985013
DOI:
10.1118/1.4947547
[Indexed for MEDLINE]
Free PMC Article

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