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Acomprehensive computer database for medical physics on-call program

Published online by Cambridge University Press:  14 May 2019

Mohamed Mohamed  and
James C. L. Chow Open the ORCID record for James C. L. Chow [Opens in a new window]
Mohamed Mohamed
Affiliation:
Department of Physics, Ryerson University, Toronto, Ontario, Canada
James C. L. Chow*
Affiliation:
Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada
*
Author for correspondence: Dr James Chow, Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario M5G 2M9, Canada; Department of Radiation Oncology, University of Toronto, Toronto, Ontario M5G 2M9, Canada. Tel: 416 946 4501. Fax: 416 946 6566. E-mail: [email protected]
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Abstract

Purpose: A comprehensive and robust computer database was built to record and analyse the medical physics on-call data in emergency radiotherapy. The probability distributions of the on-call events varying with day and week were studied.

Materials and methods: Variables of medical physics on-call events such as date and time of the event, number of event per day/week/month, treatment site of the event and identity of the on-call physicist were input to a programmed Excel file. The Excel file was linked to the MATLAB platform for data transfer and analysis. The total number of on-call events per day in a week and per month in a year were calculated based on the physics on-call data in 2010–18. In addition, probability distributions of on-call events varying with days in a week (Monday–Sunday) and months (January–December) in a year were determined.

Results: For the total number of medical physics on-call events per week in 2010–18, it was found that the number was similar from Sundays to Thursdays but increased significantly on Fridays before the weekend. The total number of events in a year showed that the physics on-call events increased gradually from January up to March, then decreased in April and slowly increased until another peak in September. The number of events decreased in October from September, and increased again to reach another peak in December. It should be noted that March, September and December are months close to Easter, Labour Day and Christmas, when radiation staff usually take long holidays.

Conclusions: A database to record and analyse the medical physics on-call data was created. Different variables such as the number of events per week and per year could be plotted. This roster could consider the statistical results to prepare a schedule with better balance of workload compared with scheduling it randomly. Moreover, the emergency radiotherapy team could use the analysed results to enhance their budget/resource allocation and strategic planning.

Keywords

Databaseemergency radiotherapyhealth care managementmedical staff schedulingphysics on-call
Type
Original Article
Information
Journal of Radiotherapy in Practice , Volume 19 , Issue 1 , March 2020 , pp. 10 - 14
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Copyright
© Cambridge University Press 2019 

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