Abstract
Efficient staff rostering and patient scheduling to meet outpatient demand is a very complex and dynamic task. Due to fluctuations in demand and specialist availability, specialist allocation must be very flexible and non-myopic. Medical specialists are typically restricted in sub-specialization, serve several patient groups and are the key resource in a chain of patient visits to the clinic and operating room (OR). To overcome a myopic view of once-off appointment scheduling, we address the patient flow through a chain of patient appointments when allocating key resources to different patient groups. We present a new, data-driven algorithmic approach to automatic allocation of specialists to roster activities and patient groups. By their very nature, simplified mathematical models cannot capture the complexity that is characteristic to the system being modeled. In our approach, the allocation of specialists to their day-to-day activities is flexible and responsive to past and present key resource availability, as well as to past resource allocation. Variability in roster activities is actively minimized, in order to enhance the supply chain flow. With discrete-event simulation of the application case using empirical data, we illustrate how our approach improves patient Service Level (SL, percentage of patients served on-time) as well as Wait Time (days), without change in resource capacity.
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Monique Bakker is a Ph.D. candidate in the Department of Systems Engineering and Engineering Management at City University of Hong Kong. She has a Bachelor degree in business administration, and an M.Phil. in healthcare operations management from the University of Groningen.
Kwok-Leung Tsui is Head of the Department of Systems Engineering and Engineering Management, and Chair professor of Industrial Engineering at City University of Hong Kong. He received his Ph.D. in statistics from the University of Wisconsin at Madison. Dr. Tsui was a recipient of the NSF Young Investigator Award in 1992. He was the (elected) President and Vice President of the American Statistical Association Atlanta Chapter in 1992-1993; Chair of the INFORMS Section in Quality, Statistics, and Reliability in 2000; and the Founding Chair of the INFORMS Section in Data Mining in 2004. He is a fellow of the American Statistical Association, and U.S. representative in the ISO Technical Committee on Statistical Methods. His current research interests include data mining and surveillance in healthcare and public health, calibration and validation of computer models, bioinformatics, process control and monitoring, and robust design and Taguchi methods.
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Bakker, M., Tsui, KL. Dynamic resource allocation for efficient patient scheduling: A data-driven approach. J. Syst. Sci. Syst. Eng. 26, 448–462 (2017). https://doi.org/10.1007/s11518-017-5347-3
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DOI: https://doi.org/10.1007/s11518-017-5347-3