Stephen L Breen1, Beibei Zhang. 1. Radiation Medicine Program, Princess Margaret Hospital, Toronto, Canada. Stephen.Breen@rmp.uhn.on.ca
Abstract
PURPOSE: To assess the effect of adding an automated checklist to the treatment planning process for head and neck intensity-modulated radiotherapy. METHODS: Plans produced within our treatment planning system were evaluated at the planners' discretion with an automated checklist of more than twenty planning parameters. Plans were rated as accepted or rejected for treatment, during regular review by radiation oncologists and physicists as part of our quality control program. The rates of errors and their types were characterised prior to the implementation of the checklist and with the checklist. RESULTS: Without the checklist, 5.9% of plans were rejected; the use of the checklist reduced the rejection rate to 3.1%. The checklist was used for 64.7% of plans. Pareto analysis of the causes of rejection showed that the checklist reduced the number of causes of rejections from twelve to seven. CONCLUSIONS: The use of an automated checklist has reduced the need for reworking of treatment plans. With the use of the checklist, most rejections were due to errors in prescription or inadequate dose distributions. Use of the checklist by planners must be increased to maximise improvements in planning efficiency.
PURPOSE: To assess the effect of adding an automated checklist to the treatment planning process for head and neck intensity-modulated radiotherapy. METHODS: Plans produced within our treatment planning system were evaluated at the planners' discretion with an automated checklist of more than twenty planning parameters. Plans were rated as accepted or rejected for treatment, during regular review by radiation oncologists and physicists as part of our quality control program. The rates of errors and their types were characterised prior to the implementation of the checklist and with the checklist. RESULTS: Without the checklist, 5.9% of plans were rejected; the use of the checklist reduced the rejection rate to 3.1%. The checklist was used for 64.7% of plans. Pareto analysis of the causes of rejection showed that the checklist reduced the number of causes of rejections from twelve to seven. CONCLUSIONS: The use of an automated checklist has reduced the need for reworking of treatment plans. With the use of the checklist, most rejections were due to errors in prescription or inadequate dose distributions. Use of the checklist by planners must be increased to maximise improvements in planning efficiency.
Authors: Elizabeth L Covington; Xiaoping Chen; Kelly C Younge; Choonik Lee; Martha M Matuszak; Marc L Kessler; Wayne Keranen; Eduardo Acosta; Ashley M Dougherty; Stephanie E Filpansick; Jean M Moran Journal: J Appl Clin Med Phys Date: 2016-11-08 Impact factor: 2.102
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Authors: Ping Xia; Danielle LaHurd; Peng Qi; Anthony Mastroianni; Daesung Lee; Anthony Magnelli; Eric Murray; Matt Kolar; Bingqi Guo; Tim Meier; Samual T Chao; John H Suh; Naichang Yu Journal: J Appl Clin Med Phys Date: 2020-07-17 Impact factor: 2.102