(Sunday, 7/14/2019)
Room: ePoster Forums
Purpose: A novel physics on-call scheduling method is developed using Monte Carlo simulation for the emergency radiotherapy program. The on-call schedule was set up based on a probability distribution of the number of on-call cases per day in a week and the credit score approach.
Methods: A probability distribution of the on-call case in a week (Sunday to Saturday) was generated based on the data from 2010 to 2018 in our cancer centre. The schedule used the “most credit first� criteria: the more credit a physicist uses, the lower their credit scores and the more they are pushed further back in the queue to be scheduled. Monte Carlo simulation was used to predict the workload for the assignment of credit for all on-call physicists. To validate the effectiveness of the new method, on-call schedules in 2010 - 2018 were redone, and the workload of every physicist from the new schedule was compared to the original one done manually.
Results: For the weekly on-call duty assigned to all physicists according to the original schedule, it is found that 6 out of 32 physicists had their workload greater than 30% of the mean. Using the new Monte Carlo method with the credit score approach to reschedule the physicists, it is seen that nobody has workload greater than 30% of the mean, basing on the old data. Moreover, the mean numbers of shifts and treatment cases per physicist were found decreasing from 16.5 and 25.6 to 11.8 and 19.7, when the old schedule was compared to the new one, respectively.
Conclusion: Since more balanced workload among physicists can be achieved using the new on-call scheduling method, it is concluded that our new method can produce an on-call schedule with better budget and resource allocation in emergency radiotherapy program.
Keywords
Quality Assurance, Monte Carlo, Data Acquisition
Taxonomy
TH- External beam- photons: Development (new technology and techniques)
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