ABSTRACT
BACKGROUND AND PURPOSE: Incident learning can reveal important opportunities for safety improvement, yet learning from error is challenged by a number of human factors. In this study, incident learning reports have been analyzed with the human factors analysis classification system (HFACS) to uncover predictive patterns of human contributing factors. MATERIALS AND METHODS: Sixteen hundred reports from the Safety in Radiation Oncology incident learning system were filtered for inclusion ultimately yielding 141 reports. A radiotherapy-specific error type was assigned to each event as were all reported human contributing factors. An analysis of associations between human contributing factors and error types was performed. RESULTS: Multiple associations between human factors were found. Relationships between leadership and risk were demonstrated with supervision failures. Skill-based errors (those done without much thought while performing familiar tasks) were found to pose a significant safety risk to the treatment planning process. Errors made during quality assurance (QA) activities were associated with decision-based errors which indicate lacking knowledge or skills. CONCLUSION: An application of the HFACS to incident learning reports revealed relationships between human contributing factors and radiotherapy errors. Safety improvement efforts should include supervisory influences as they affect risk and error. An association between skill-based and treatment planning errors showed a need for more mindfulness in this increasingly automated process. An association between decision and QA errors revealed a need for improved education in this area. These and other findings can be used to strategically advance safety.
