HFACS-based human factors analysis of radiotherapy safety incidents and exploration of incident chains
Objective To analyze human factors in radiotherapy safety incidents and identify their correction for the purpose of mining the latent incident chains.Methods A total of 60 radiotherapy safety incidents were included in the Radiation Oncology Incident Learning System(ROILS)for cause identification and frequency statistics using the Human Factors Analysis and Classification System(HFACS).Latent class analysis(LCA)was performed for the result to correlate the incident causes.Results Incidents in the protocol design stage were the most common,accounting for 35％.Adverse organizational climate,inadequate supervision,and personnel factors were the primary causes of incidents at each level of the HFACS,accounting for 4.66％,15.68％,and 16.20％,respectively.Three latent incident chains were identified through LCA,comprising two originating from organizational climate issues and one from organizational process issues,which were passed down via various human factors or"loopholes"Conclusions HFACS assists in tracing the human factors at all levels that lead to radiotherapy safety incidents.The high-frequency causes and three latent chains of radiotherapy incidents found in this study can provide a guide for the development of targeted safety and defense measures.
Human factors analysis and classification systemLatent class analysisHuman factorRadiotherapy incident
NETL
NSTL
万方数据
