Appointment window scheduling with wait-dependent abandonment for elective inpatient admission.
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| Title: | Appointment window scheduling with wait-dependent abandonment for elective inpatient admission. |
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| Authors: | Lu, Yuwei1,2 (AUTHOR), Jiang, Zhibin3,4 (AUTHOR) zbjiang@sjtu.edu.cn, Geng, Na4 (AUTHOR), Jiang, Shan5 (AUTHOR), Xie, Xiaolan3,6 (AUTHOR) |
| Source: | International Journal of Production Research. Oct2022, Vol. 60 Issue 19, p5977-5993. 17p. 1 Diagram, 7 Charts, 4 Graphs. |
| Subjects: | Queuing theory, Customer satisfaction, Consumers, Scheduling, Operations research, Hospital admission & discharge |
| Abstract: | In this study, we propose a new appointment window scheduling (AWS) approach of informing customers of an admission window (AW) rather than the traditional appointment time. We provide a formal description of this AWS problem for only one kind of customer and propose a dedicated chance-constrained policy to assign AWs dynamically under the condition with fixed service capacity, different scales as well as status in different waiting stages, and wait-dependent abandonment. Numerical experiments show that customer satisfaction can be significantly improved (by reducing over 60% of wait-but-abandon events and by reducing 90% of departures caused by waiting beyond the AW), and server utilisation is slightly improved. And the improvements are more significant when systems are overloaded, and customers are more sensitive to online waiting than offline waiting. The AWS scenario can also be applied to other queueing systems as long as it is possible and profitable to let customers wait outside of the waiting area. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | In this study, we propose a new appointment window scheduling (AWS) approach of informing customers of an admission window (AW) rather than the traditional appointment time. We provide a formal description of this AWS problem for only one kind of customer and propose a dedicated chance-constrained policy to assign AWs dynamically under the condition with fixed service capacity, different scales as well as status in different waiting stages, and wait-dependent abandonment. Numerical experiments show that customer satisfaction can be significantly improved (by reducing over 60% of wait-but-abandon events and by reducing 90% of departures caused by waiting beyond the AW), and server utilisation is slightly improved. And the improvements are more significant when systems are overloaded, and customers are more sensitive to online waiting than offline waiting. The AWS scenario can also be applied to other queueing systems as long as it is possible and profitable to let customers wait outside of the waiting area. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 00207543 |
| DOI: | 10.1080/00207543.2021.1977407 |
