IDEAS home Printed from https://ideas.repec.org/a/aph/ajpbhl/10.2105-ajph.2015.302737_9.html
   My bibliography  Save this article

Predictive modeling and concentration of the risk of suicide: Implications for preventive interventions in the us department of veterans affairs

Author

Listed:
  • McCarthy, J.F.
  • Bossarte, R.M.
  • Katz, I.R.
  • Thompson, C.
  • Kemp, J.
  • Hannemann, C.M.
  • Nielson, C.
  • Schoenbaum, M.

Abstract

Objectives. The Veterans Health Administration (VHA) evaluated the use of predictive modeling to identify patients at risk for suicide and to supplement ongoing care with risk-stratified interventions. Methods. Suicide data came from the National Death Index. Predictors were measures from VHA clinical records incorporating patient-months from October 1, 2008, to September 30, 2011, for all suicide decedents and 1% of living patients, divided randomly into development and validation samples. We used data on all patients alive on September 30, 2010, to evaluate predictions of suicide risk over 1 year. Results. Modeling demonstrated that suicide rates were 82 and 60 times greater than the rate in the overall sample in the highest 0.01% stratum for calculated risk for the development and validation samples, respectively; 39 and 30 times greater in the highest 0.10%; 14 and 12 times greater in the highest 1.00%; and 6.3 and 5.7 times greater in the highest 5.00%. Conclusions. Predictive modeling can identify high-risk patients who were not identified on clinical grounds. VHA is developing modeling to enhance clinical care and to guide the delivery of preventive interventions.

Suggested Citation

  • McCarthy, J.F. & Bossarte, R.M. & Katz, I.R. & Thompson, C. & Kemp, J. & Hannemann, C.M. & Nielson, C. & Schoenbaum, M., 2015. "Predictive modeling and concentration of the risk of suicide: Implications for preventive interventions in the us department of veterans affairs," American Journal of Public Health, American Public Health Association, vol. 105(9), pages 1935-1942.
    • Handle: RePEc:aph:ajpbhl:10.2105/ajph.2015.302737_9
    DOI: 10.2105/AJPH.2015.302737
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.2105/AJPH.2015.302737
    Download Restriction: no
    File URL: https://libkey.io/10.2105/AJPH.2015.302737?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
    ---><---

    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:aph:ajpbhl:10.2105/ajph.2015.302737_9. 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: Christopher F Baum (email available below). General contact details of provider: https://www.apha.org .

    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.