BACKGROUND AND PURPOSE: The planning portion of the radiation therapy treatment process at the British Columbia Cancer Agency is efficient but nevertheless contains room for improvement. The purpose of this study is to show how a discrete-event simulation (DES) model can be used to represent this complex process and to suggest improvements that may reduce the planning time and ultimately reduce overall waiting times. MATERIALS AND METHODS: A simulation model of the radiation therapy (RT) planning process was constructed using the Arena simulation software, representing the complexities of the system. Several types of inputs feed into the model; these inputs come from historical data, a staff survey, and interviews with planners. RESULTS: The simulation model was validated against historical data and then used to test various scenarios to identify and quantify potential improvements to the RT planning process. CONCLUSIONS: Simulation modelling is an attractive tool for describing complex systems, and can be used to identify improvements to the processes involved. It is possible to use this technique in the area of radiation therapy planning with the intent of reducing process times and subsequent delays for patient treatment. In this particular system, reducing the variability and length of oncologist-related delays contributes most to improving the planning time.
BACKGROUND AND PURPOSE: The planning portion of the radiation therapy treatment process at the British Columbia Cancer Agency is efficient but nevertheless contains room for improvement. The purpose of this study is to show how a discrete-event simulation (DES) model can be used to represent this complex process and to suggest improvements that may reduce the planning time and ultimately reduce overall waiting times. MATERIALS AND METHODS: A simulation model of the radiation therapy (RT) planning process was constructed using the Arena simulation software, representing the complexities of the system. Several types of inputs feed into the model; these inputs come from historical data, a staff survey, and interviews with planners. RESULTS: The simulation model was validated against historical data and then used to test various scenarios to identify and quantify potential improvements to the RT planning process. CONCLUSIONS: Simulation modelling is an attractive tool for describing complex systems, and can be used to identify improvements to the processes involved. It is possible to use this technique in the area of radiation therapy planning with the intent of reducing process times and subsequent delays for patient treatment. In this particular system, reducing the variability and length of oncologist-related delays contributes most to improving the planning time.
Authors: Bruno Vieira; Erwin W Hans; Corine van Vliet-Vroegindeweij; Jeroen van de Kamer; Wim van Harten Journal: BMC Med Inform Decis Mak Date: 2016-11-25 Impact factor: 2.796
Authors: Bruno Vieira; Derya Demirtas; Jeroen B van de Kamer; Erwin W Hans; Wim van Harten Journal: BMC Med Inform Decis Mak Date: 2019-10-24 Impact factor: 2.796