Failure mode and effects analysis: A community practice perspective

PURPOSE: To report our early experiences with failure mode and effects analysis (FMEA) in a community practice setting. METHODS: The FMEA facilitator received extensive training at the AAPM Summer School. Early efforts focused on department education and emphasized the need for process evaluation in the context of high profile radiation therapy accidents. A multidisciplinary team was assembled with representation from each of the major department disciplines. Stereotactic radiosurgery (SRS) was identified as the most appropriate treatment technique for the first FMEA evaluation, as it is largely self‐contained and has the potential to produce high impact failure modes. Process mapping was completed using breakout sessions, and then compiled into a simple electronic format. Weekly sessions were used to complete the FMEA evaluation. Risk priority number (RPN) values > 100 or severity scores of 9 or 10 were considered high risk. The overall time commitment was also tracked. RESULTS: The final SRS process map contained 15 major process steps and 183 subprocess steps. Splitting the process map into individual assignments was a successful strategy for our group. The process map was designed to contain enough detail such that another radiation oncology team would be able to perform our procedures. Continuous facilitator involvement helped maintain consistent scoring during FMEA. Practice changes were made responding to the highest RPN scores, and new resulting RPN scores were below our high‐risk threshold. The estimated person‐hour equivalent for project completion was 258 hr. CONCLUSIONS: This report provides important details on the initial steps we took to complete our first FMEA, providing guidance for community practices seeking to incorporate this process into their quality assurance (QA) program. Determining the feasibility of implementing complex QA processes into different practice settings will take on increasing significance as the field of radiation oncology transitions into the new TG‐100 QA paradigm.