IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0051365.html
   My bibliography  Save this article

Weekday Affects Attendance Rate for Medical Appointments: Large-Scale Data Analysis and Implications

Author

Listed:
  • David A Ellis
  • Rob Jenkins

Abstract

The financial cost of missed appointments is so great that even a small percentage reduction in Did Not Attend (DNA) rate could save significant sums of money. Previous studies have identified many factors that predict DNA rate, including patient age, gender, and transport options. However, it is not obvious how healthcare providers can use this information to improve attendance, as such factors are not under their control. One factor that is under administrative control is appointment scheduling. Here we asked whether DNA rate could be reduced by altering scheduling policy. In Study 1, we examined attendance records for 4,538,294 outpatient hospital appointments across Scotland between January 1st 2008 and December 31st 2010. DNA rate was highest for Mondays (11%), lowest for Fridays (9.7%), and decreased monotonically over the week (Monday-Friday comparison [χ2(1, N = 1,585,545) = 722.33, p

Suggested Citation

  • David A Ellis & Rob Jenkins, 2012. "Weekday Affects Attendance Rate for Medical Appointments: Large-Scale Data Analysis and Implications," PLOS ONE, Public Library of Science, vol. 7(12), pages 1-4, December.
  • Handle: RePEc:plo:pone00:0051365
    DOI: 10.1371/journal.pone.0051365
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0051365
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0051365&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0051365?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
    ---><---

    Citations

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


    Cited by:

    1. David A Ellis & Richard Wiseman & Rob Jenkins, 2015. "Mental Representations of Weekdays," PLOS ONE, Public Library of Science, vol. 10(8), pages 1-17, August.
    2. Jet G Sanders & Rob Jenkins, 2016. "Weekly Fluctuations in Risk Tolerance and Voting Behaviour," PLOS ONE, Public Library of Science, vol. 11(7), pages 1-12, July.
    3. Henry Lenzi & Ângela Jornada Ben & Airton Tetelbom Stein, 2019. "Development and validation of a patient no-show predictive model at a primary care setting in Southern Brazil," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-14, April.

    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:plo:pone00:0051365. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.