Failure mode and effects analysis of linac‐based liver stereotactic body radiotherapy

• DOI: 10.1002/mp.13965
• Publication Date: 2019-12-14T09:52:35Z
• Authors: Iris Rusu; Tarita O. Thomas; John C. Roeske; Ibrahim Mescioglu; Edward Melian; Murat Surucu
• Keywords: 03 medical and health sciences; 0302 clinical medicine; Liver Neoplasms; Humans; Healthcare Failure Mode and Effect Analysis; Particle Accelerators; Safety; Radiosurgery; Tomography, X-Ray Computed; 3. Good health

PurposeAlthough stereotactic body radiation therapy (SBRT) is an attractive noninvasive approach for liver irradiation, it presents specific challenges associated with respiration‐induced liver motion, daily tumor localization due to liver deformation, and poor visualization of target with respect to adjacent normal liver in computed tomography (CT). We aim to identify potential hazards and develop a set of mitigation strategies to improve the safety of our liver SBRT program, using failure mode and effect analysis (FMEA).Materials and methodsA multidisciplinary group consisting of two physicians, three physicists, two dosimetrists, and two therapists was formed. A process map covering ten major stages of the liver SBRT program from the initial diagnosis to posttreatment follow‐up was generated. A total of 102 failure modes (FM), together with their causes and effects, were identified. The occurrence (O), severity (S), and lack of detectability (D) were independently scored using a scale from 1 (lowest risk) to 10 (largest risk). The ranking was done using the risk probability number (RPN) defined as the product of average O, S, and D numbers for each mode. Two fault tree analyses were performed. The failure modes with the highest RPN values as well as highest severity score were considered for investigation and a set of mitigation strategies was developed to address these.ResultsThe median RPN (RPNmed) values for all modes ranged from of 9 to 105 and the highest median S score (Smed) was 8. Fourteen FMs were identified to be significant by both RPNmed and Smed (top ten RPNmed ranked and highest Smed FMs) and 12 of them were considered for risk mitigation efforts. The remaining two were omitted due to either sufficient checks already in place, or lack of practical mitigation strategies. Implemented measures consisted of five physics tasks, two physician tasks, and three workflow changes.ConclusionsThe application of FMEA to our liver SBRT program led to the identification of potential FMs and allowed improvement measures to enhance the safety of our clinical practice.