IDEAS home Printed from https://ideas.repec.org/h/spr/isochp/978-1-4614-5885-2_2.html
   My bibliography  Save this book chapter

Queueing Models for Healthcare Operations

In: Handbook of Healthcare Operations Management

Author

Listed:
  • Diwakar Gupta

    (University of Minnesota)

Abstract

Patients seeking healthcare often need to wait before they can receive needed services. Excessive waiting can cause prolonged discomfort, economic loss, and long-run health complications. This motivates us to look closely at the theory of queues in order to understand the reasons why queues form and the principles underlying good system design. Queueing models help explain the interaction between resource utilization and variability. Higher resource utilization lowers the per-patient cost of making resources available, but in the presence of variability in either the service requirements or the number of service requests or both, higher utilization increases patient waiting times. In fact, for a fixed level of variability, the effect of resource utilization is highly nonlinear—waiting times increase at an increasing rate in utilization. This implies that in healthcare settings where significant variability is naturally present and difficult to eliminate, capacity planning must trade-off the cost of providing resources and the cost of patient waiting. In this chapter, we review basic queueing models that help quantify the above-mentioned tradeoff and discuss the usefulness of such models to healthcare operations managers. Specifically, we summarize some known results for queueing systems with single and multiple servers, limited and unlimited waiting room, service priority, and networks of service stations.

Suggested Citation

  • Diwakar Gupta, 2013. "Queueing Models for Healthcare Operations," International Series in Operations Research & Management Science, in: Brian T. Denton (ed.), Handbook of Healthcare Operations Management, edition 127, chapter 0, pages 19-44, Springer.
  • Handle: RePEc:spr:isochp:978-1-4614-5885-2_2
    DOI: 10.1007/978-1-4614-5885-2_2
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

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


    Cited by:

    1. Hideaki Takagi & Yuta Kanai & Kazuo Misue, 2017. "Queueing network model for obstetric patient flow in a hospital," Health Care Management Science, Springer, vol. 20(3), pages 433-451, September.
    2. Yuta Kanai & Hideaki Takagi, 2021. "Markov chain analysis for the neonatal inpatient flow in a hospital," Health Care Management Science, Springer, vol. 24(1), pages 92-116, March.
    3. Saied Samiedaluie & Beste Kucukyazici & Vedat Verter & Dan Zhang, 2017. "Managing Patient Admissions in a Neurology Ward," Operations Research, INFORMS, vol. 65(3), pages 635-656, June.

    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:spr:isochp:978-1-4614-5885-2_2. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.