Quantifying risk using FMEA: An alternate approach to AAPM TG-100 for scoring failures and evaluating clinical workflow.

PURPOSE: Renovation of the brachytherapy program at a leading cancer center utilized methods of the AAPM TG-100 report to objectively evaluate current clinical brachytherapy workflows and develop techniques for minimizing the risk of failures, increasing efficiency, and consequently providing opportunities for improved treatment quality. The TG-100 report guides evaluation of clinical workflows with recommendations for identifying potential failure modes (FM) and scoring them from the perspective of their occurrence frequency O, failure severity S, and inability to detect them D. The current study assessed the impact of differing methods to determine the risk priority number (RPN) beyond simple multiplication. METHODS AND MATERIALS: The clinical workflow for a complex brachytherapy procedure was evaluated by a team of 15 staff members, who identified discrete FM using alternate scoring scales than those presented in the TG-100 report. These scales were expanded over all clinically relevant possibilities with care to emphasize mitigation of natural bias for scoring near the median range as well as to enhance the overall scoring-system sensitivity. Based on staff member perceptions, a more realistic measure of risk was determined using weighted functions of their scores. RESULTS: This new method expanded the range of RPN possibilities by a factor of 86, improving evaluation and recognition of safe and efficient clinical workflows. Mean RPN values for each FM decreased by 44% when changing from the old to the new clinical workflow, as evaluated using the TG-100 method. This decreased by 66% when evaluated with the new method. As a measure of the total risk associated with an entire clinical workflow, the integral of RPN values increased by 15% and decreased by 31% with the TG-100 and new methods, respectively. CONCLUSIONS: This appears to be the first application of an alternate approach to the TG-100 method for evaluating the risk of clinical workflows. It exemplifies the risk analysis techniques necessary to rapidly evaluate simple clinical workflows appropriately.

Novel and programmatic improvements to the workflow associated with the AccuBoost breast brachytherapy procedure.

PURPOSE: While the noninvasive breast brachytherapy (NIBB) treatment procedure, known as AccuBoost, for breast cancer patients is well established, the treatment quality can be improved by the efficiency of the workflow delivery. A formalized approach evaluated the current workflow through failure modes and effects analysis and generated insight for developing new procedural workflow techniques to improve the clinical treatment process. METHODS AND MATERIALS: AccuBoost treatments were observed for several months while gathering details on the multidisciplinary workflow. A list of possible failure modes for each procedure step was generated and organized by timing within the treatment process. A team of medical professionals highlighted procedural steps that unnecessarily increased treatment time, as well as introduced quality deficiencies involving applicator setup, treatment planning, and quality control checks preceding brachytherapy delivery. Procedural improvements and their impact on the clinical workflow are discussed. RESULTS: The revised clinical workflow included the following key procedural enhancements. Prepatient arrival: Improvement of prearrival preparation requires advance completion of dose calculation documentation with patient-specific setup data. Patient arrival pretreatment: Physicists carry out dwell time calculations and check the plan, while the therapist concurrently performs several checks of the ensuing hardware configuration. TREATMENT: An electronic method to export the associated HDR brachytherapy paperwork to the electronic medical record system with electronic signatures and captured approvals was generated. Posttreatment: The therapist confirms the applicators were appropriately positioned, and treatment was delivered as expected. CONCLUSIONS: The procedural improvements reduced the overall treatment time, improved consistency across users, and eased performance of this special procedure for all participants.

Automated position and size selection of round applicators for AccuBoost breast brachytherapy.

PURPOSE: AccuBoost is a complex non-invasive brachytherapy procedure for breast treatment. This technique requires a radiation oncologist to manually select applicator grid position and size by overlaying transparencies over a mammographic image to encompass surgical clips and resected tumor bed. An algorithm was developed in MATLAB™ to automate the selection of round applicators based on surgical clip position. MATERIAL AND METHODS: A total of 42 mammograms belonging to 10 patients were retrospectively analyzed. Images were pre-processed by masking imprinted localization grid and regions around the grid. A threshold was applied to isolate high-intensity pixels and generate a binary image. A set of morphological operations including region dilation, filling, clearing border structures, and erosion were performed to segment the different regions. A support vector machine classification model was trained to categorize segmented regions as either surgical clips or miscellaneous objects based on different region properties (area, perimeter, eccentricity, circularity, minor axis length, and intensity-derived quantities). Applicator center position was determined by calculating the centroid of detected clips. Size of the applicator was determined with the smallest circle that encompassed all clips with an isotropic 1.0 cm margin. RESULTS: The clip identification model classified 946 regions, with a sensitivity of 96.6% and a specificity of 98.2%. Applicator position was correctly predicted for 20 of 42 fractions and was within 0.5 cm of physician-selected position for 33 of 42 fractions. Applicator size was correctly predicted for 25 out of 42 fractions. CONCLUSIONS: The proposed algorithm provided a method to quantitatively determine applicator position and size for AccuBoost treatments, and may serve as a tool for independent verifications. The discrepancy between physician-selected and algorithm-predicted determinations of applicator position and size suggests that the methodology may be further improved by considering radiomic features of breast tissue in addition to clip position.