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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.
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]
Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: Appointment window scheduling with wait-dependent abandonment for elective inpatient admission.
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  Data: <searchLink fieldCode="AR" term="%22Lu%2C+Yuwei%22">Lu, Yuwei</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Jiang%2C+Zhibin%22">Jiang, Zhibin</searchLink><relatesTo>3,4</relatesTo> (AUTHOR)<i> zbjiang@sjtu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Geng%2C+Na%22">Geng, Na</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Jiang%2C+Shan%22">Jiang, Shan</searchLink><relatesTo>5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Xie%2C+Xiaolan%22">Xie, Xiaolan</searchLink><relatesTo>3,6</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Production+Research%22">International Journal of Production Research</searchLink>. Oct2022, Vol. 60 Issue 19, p5977-5993. 17p. 1 Diagram, 7 Charts, 4 Graphs.
– Name: Subject
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  Data: <searchLink fieldCode="DE" term="%22Queuing+theory%22">Queuing theory</searchLink><br /><searchLink fieldCode="DE" term="%22Customer+satisfaction%22">Customer satisfaction</searchLink><br /><searchLink fieldCode="DE" term="%22Consumers%22">Consumers</searchLink><br /><searchLink fieldCode="DE" term="%22Scheduling%22">Scheduling</searchLink><br /><searchLink fieldCode="DE" term="%22Operations+research%22">Operations research</searchLink><br /><searchLink fieldCode="DE" term="%22Hospital+admission+%26+discharge%22">Hospital admission & discharge</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: 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]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1080/00207543.2021.1977407
    Languages:
      – Code: eng
        Text: English
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        PageCount: 17
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    Subjects:
      – SubjectFull: Queuing theory
        Type: general
      – SubjectFull: Customer satisfaction
        Type: general
      – SubjectFull: Consumers
        Type: general
      – SubjectFull: Scheduling
        Type: general
      – SubjectFull: Operations research
        Type: general
      – SubjectFull: Hospital admission & discharge
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      – TitleFull: Appointment window scheduling with wait-dependent abandonment for elective inpatient admission.
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            NameFull: Lu, Yuwei
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            NameFull: Jiang, Zhibin
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            NameFull: Geng, Na
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            NameFull: Jiang, Shan
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            NameFull: Xie, Xiaolan
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              M: 10
              Text: Oct2022
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              Y: 2022
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