Human Reliability Modeling of Radiotherapy Procedures by Bayesian Networks and Expert Opinion Elicitation

The purpose of this paper is to highlight and model the most important steps in cases of human failure in radiotherapy (teletherapy and brachytherapy) procedures by identifying possible modes of human failure. An approach via Bayesian networks (BNs) to model and highlight the most relevant steps of teletherapy and brachytherapy was used. Finally, as a technique for the quantification of BNs, an expert opinion elicitation procedure was used since no database is available.

In the case of teletherapy, observing only the stages of prescription, planning, and execution, it appears that the step that most increases the success probability, after consideration of preventive measures, is execution. This is in agreement with cases of errors and accidents reported in the literature, considering that more than 50% of these cases are related to the implementation phase. Related to brachytherapy, the most relevant factor was the use of equipment, whose increase in success probability after consideration of preventive measures was 17.2%, demonstrating the importance of a continuous specific training.

It is important to mention that the purpose of this study was not to calculate the risk associated with radiotherapy treatments but rather to check how accident prevention influences the success procedure and observe the relationship among all stages. An uncertainty analysis was performed of the expert data by considering that data scattering followed a normal or a lognormal distribution, due to data ranges considered. This analysis revealed that data scattering was better represented by normal distributions, and the results are consistent with pointwise estimates initially made.