PURPOSE: Quality assurance (QA) programs aim to identify inconsistencies that may compromise patient care. Radiation treatment planning is a well-documented source of variation in radiation oncology, leading many organizations to recommend the implementation of QA rounds in which radiation therapy plans are peer reviewed. This study evaluates the outcome of QA rounds that have been conducted by a radiation therapy department since 2004. METHODS AND MATERIALS: Prospectively documented records of QA rounds, from 2004 to 2010, were obtained. During rounds, randomly selected radiation therapy plans were peer reviewed and assigned a grade of A (adequate), B (minor suggestions of change to a plan for a future patient), or C (significant change required before the next fraction). The proportion of plans that received each recommendation was calculated, and the relationship between recommendations for each plan, tumor site, and mean years of experience of the radiation oncologist (RO) were explored. Chart reviews were performed for each plan that received a C. RESULTS: During the study period, 1247 plans were evaluated; 6% received a B and 1% received a C. The mean RO years of experience were lower for plans graded C versus those graded A (P=.02). The tumor sites with the highest proportion of plans graded B or C were gastrointestinal (14%), lung (13%), and lymphoma (8%). The most common reasons for plans to receive a grade of C were inadequate target volume coverage (36%), suboptimal dose or fractionation (27%), errors in patient setup (27%), and overtreatment of normal tissue (9%). CONCLUSIONS: This study demonstrated that QA rounds are feasible and an important element of a radiation therapy department's QA program. Through peer review, plans that deviate from a department's expected standard can be identified and corrected. Additional benefits include identifying patterns of practice that may contribute to inconsistencies in treatment planning and the continuing education of staff members who attend.
PURPOSE: Quality assurance (QA) programs aim to identify inconsistencies that may compromise patient care. Radiation treatment planning is a well-documented source of variation in radiation oncology, leading many organizations to recommend the implementation of QA rounds in which radiation therapy plans are peer reviewed. This study evaluates the outcome of QA rounds that have been conducted by a radiation therapy department since 2004. METHODS AND MATERIALS: Prospectively documented records of QA rounds, from 2004 to 2010, were obtained. During rounds, randomly selected radiation therapy plans were peer reviewed and assigned a grade of A (adequate), B (minor suggestions of change to a plan for a future patient), or C (significant change required before the next fraction). The proportion of plans that received each recommendation was calculated, and the relationship between recommendations for each plan, tumor site, and mean years of experience of the radiation oncologist (RO) were explored. Chart reviews were performed for each plan that received a C. RESULTS: During the study period, 1247 plans were evaluated; 6% received a B and 1% received a C. The mean RO years of experience were lower for plans graded C versus those graded A (P=.02). The tumor sites with the highest proportion of plans graded B or C were gastrointestinal (14%), lung (13%), and lymphoma (8%). The most common reasons for plans to receive a grade of C were inadequate target volume coverage (36%), suboptimal dose or fractionation (27%), errors in patient setup (27%), and overtreatment of normal tissue (9%). CONCLUSIONS: This study demonstrated that QA rounds are feasible and an important element of a radiation therapy department's QA program. Through peer review, plans that deviate from a department's expected standard can be identified and corrected. Additional benefits include identifying patterns of practice that may contribute to inconsistencies in treatment planning and the continuing education of staff members who attend.
Authors: Murat Surucu; Amishi Bajaj; John C Roeske; Alec M Block; Jennifer Price; William Small; Abhishek A Solanki Journal: Adv Radiat Oncol Date: 2019-03-21
Authors: Anis Ahmad; Lakshmi Santanam; Abhishek A Solanki; Laura Padilla; Erina Vlashi; Patrizia Guerrieri; Michael M Dominello; Jay Burmeister; Michael C Joiner Journal: J Appl Clin Med Phys Date: 2020-11-24 Impact factor: 2.243