IDEAS home Printed from https://ideas.repec.org/a/taf/tjorxx/v71y2020i8p1145-1160.html
   My bibliography  Save this article

Infinite-server queueing models of demand in healthcare: A review of applications and ideas for further work

Author

Listed:
  • David Worthington
  • Martin Utley
  • Dan Suen

Abstract

Despite the apparently unrealistic assumption of infinite resources, infinite-server queueing models have played a central role in the development of queueing theory and its applications. Healthcare modelling applications have certainly benefited from these models, where arguably their greatest importance has been to provide the basis for the analysis of “offered load” in systems with single or multiple nodes with multiple servers and time-varying arrivals. In this paper, we provide a review of major healthcare applications to date, identifying and consolidating the underpinning theoretical results and commenting on the nature of the applications. We conclude by identifying potential further healthcare applications, their relationships to existing theory and methods, and the need for new theory and methods, including the use of infinite-server models alongside other modelling methodologies.

Suggested Citation

  • David Worthington & Martin Utley & Dan Suen, 2020. "Infinite-server queueing models of demand in healthcare: A review of applications and ideas for further work," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 71(8), pages 1145-1160, August.
  • Handle: RePEc:taf:tjorxx:v:71:y:2020:i:8:p:1145-1160
    DOI: 10.1080/01605682.2019.1609878
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/01605682.2019.1609878
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/01605682.2019.1609878?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Bekker, René & uit het Broek, Michiel & Koole, Ger, 2023. "Modeling COVID-19 hospital admissions and occupancy in the Netherlands," European Journal of Operational Research, Elsevier, vol. 304(1), pages 207-218.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:tjorxx:v:71:y:2020:i:8:p:1145-1160. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/tjor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.