Dynamic appointment scheduling with patient preferences and choices
Abstract
Purpose
The purpose of this paper is to maximize the expected revenue of the outpatient department considering patient preferences and choices.
Design/methodology/approach
Patient preference refers to the preferred physician and time slot that patients hold before asking for appointments. Patient choice is the appointment decision the patient made after receiving a set of options from the scheduler. The relationship between patient choices and preferences is explored. A dynamic programming (DP) model is formulated to optimize appointment scheduling with patient preferences and choices. The DP model is transformed to an equivalent linear programming (LP) model. A decomposition method is proposed to eliminate the number of variables. A column generation algorithm is used to resolve computation problem of the resulting LP model.
Findings
Numerical studies show the benefit of multiple options provided, and that the proposed algorithm is efficient and accurate. The effects of the booking horizon and arrival rates are studies. A policy about how to make use of the information of patient preferences is compared to other naive polices. Experiments show that more revenue can be expected if patient preferences and choices are considered.
Originality/value
This paper proposes a framework for appointment scheduling problem in outpatient departments. It is concluded that more revenue can be achieved if more choices are provided for patients to choose from and patient preferences are considered. Additionally, an appointment decision can be made timely after receiving patient preference information. Therefore, the proposed model and policies are convenient tools applicable to an outpatient department.
Keywords
Acknowledgements
The research is partially supported by Research Grant Council (RGC) of Hong Kong by the Grant No. T32-102/14-N.
Citation
Wang, J. and Fung, R.Y.K. (2015), "Dynamic appointment scheduling with patient preferences and choices", Industrial Management & Data Systems, Vol. 115 No. 4, pp. 700-717. https://doi.org/10.1108/IMDS-12-2014-0372
Publisher
:Emerald Group Publishing Limited
Copyright © 2015, Emerald Group Publishing Limited