IDEAS home Printed from https://ideas.repec.org/a/taf/thssxx/v11y2022i2p109-125.html
   My bibliography  Save this article

Modelling changes in healthcare demand through geographic data extrapolation

Author

Listed:
  • Geraint Ian Palmer
  • Paul Harper
  • Vincent Knight
  • Cathy Brooks

Abstract

Stay Well Plans are a new programme of care offered to frail and elderly people in Newport. In 2016 a roll out the programme to be offered in all five counties serviced by Aneurin Bevan University Health Board was planned. This paper presents the data analysis and modelling used to determine the programme's effects on the demand of the wider system, and the effects of a Gwent-wide roll out. We extrapolate information from data from a geographical subset of the model domain to a larger geographical area, adjusting for population sizes, deprivation, and distances to healthcare facilities. These parametrise a Markov model and Monte Carlo simulation to predict changes in demand due to different levels of roll out. We conclude that a programme roll out may result in a large reduction on demand at residential care, however at the expense of an increase in demand at community care services.

Suggested Citation

  • Geraint Ian Palmer & Paul Harper & Vincent Knight & Cathy Brooks, 2022. "Modelling changes in healthcare demand through geographic data extrapolation," Health Systems, Taylor & Francis Journals, vol. 11(2), pages 109-125, April.
    • Handle: RePEc:taf:thssxx:v:11:y:2022:i:2:p:109-125
    DOI: 10.1080/20476965.2021.1906764
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/20476965.2021.1906764
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/20476965.2021.1906764?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.

    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:thssxx:v:11:y:2022:i:2:p:109-125. 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/thss .

    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.