Purpose: Error messages from vendors can often be confusing and lacking in clarity. Our department has implemented an internal “Problem Ticket” website where staff can enter problems with clinical equipment, including error messages encountered on clinical systems. We propose a systematic review of these errors so they can be fully understood in a multidisciplinary manner through including working with radiation oncology staff, vendors, and departmental/hospital IT. The overall goal of this process is to provide staff with appropriate and timely feedback to help mitigate any negative consequences caused by error messages. The purpose of this study is to report on high impact error messages observed within our department.
Methods: TG-100 describes a method to prospectively find/rank failure modes (and associated failure pathways) using process mapping, FMEA, and fault tree analysis. In this study, we perform a systematic review of error messages using FMEA to retrospectively analyze and rank error messages reported at our institution. Reports are categorized and prioritized using FMEA/RPN formalism.
Results: In total, 307 error messages were reviewed from the departmental “Problem Ticket” website and assigned values for Occurrence(O),Severity(S),and Detectability(D) to calculate RPN. Of the 307 messages, 24 were identified with RPN>200 and further analyzed/categorized. Two high-frequency categories were Network/Services and Data Import to the TPS. Both issues caused increases in response time to resolve the error. For both categories, the corrective action/troubleshooting step was not clear from the error message content, so reviewing and communicating the recommended steps to staff has the potential to improve the effectiveness and efficiency in real-time response to both categories.
Conclusion: Development of a systematic and department-wide method to analyze error messages using FMEA can help to fully understand error messages and ensure that appropriate staff are notified, thereby improving both effectiveness and efficiency in troubleshooting error messages in the clinical setting.