IDEAS home Printed from https://ideas.repec.org/a/eee/socmed/v37y1993i4p549-554.html
   My bibliography  Save this article

Organizational predictors of outcomes of long-stay nursing home residents

Author

Listed:
  • Rohrer, James E.
  • Momany, Elizabeth T.
  • Chang, Wei

Abstract

Analysis of physical function as a measure of nursing home resident outcomes in 10 nursing homes revealed that organizational design variables were important. Results were consistent with contingency theory, which posits that to maximize performance organizational structure should be adjusted to variations in task difficulty and variability. This study revealed that better resident outcomes sometimes are achieved in faster-paced nursing homes when employees are less closely supervised and when the basis for job assignment is clear and consistent. A more hierarchical structure may be effective when workload is heavy. However, when workload and pace are held constant, better outcomes are associated with smaller hierarchies and non-specific job assignment. Implications for management and future research are discussed.

Suggested Citation

  • Rohrer, James E. & Momany, Elizabeth T. & Chang, Wei, 1993. "Organizational predictors of outcomes of long-stay nursing home residents," Social Science & Medicine, Elsevier, vol. 37(4), pages 549-554, August.
    • Handle: RePEc:eee:socmed:v:37:y:1993:i:4:p:549-554
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/0277-9536(93)90290-K
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

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

    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:eee:socmed:v:37:y:1993:i:4:p:549-554. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/315/description#description .

    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.