10002616 J Clin Psychiatry / Document Archive

Psychiatrist.com Home    Keyword Search

Close [X]

Search Our Sites

Enter search terms below (keywords, titles, authors, or subjects). Then select a category to search and press the Search button. All words are assumed to be required. To search for an exact phrase, put it in quotes. To exclude a term, precede it with a minus sign (-).

Keyword search:

Choose a category:

Choosing the appropriate category will greatly improve your chances of finding the best match.

All files at our sites: J Clin Psychiatry, Primary Care Companion, CME Institute, and MedFair

Search materials from our journals:

Abstracts from The Journal of Clinical Psychiatry, 1996–present, both regular issues and supplements

PDFs of the full text of The Journal of Clinical Psychiatry, 1996–present, both regular issues and supplements (Net Society Platinum [paid subscribers])

PDFs of the full text of The Primary Care Companion to The Journal of Clinical Psychiatry, 1999–present

Search CME offerings:

CME Institute, including CME from journals , supplements, and Web activities for instant CME credit (Net Society Gold [registered users]); also includes information about our CME program

CME activities from regular issues of The Journal of Clinical Psychiatry (Net Society Gold [registered users])

CME Supplements from The Journal of Clinical Psychiatry (Net Society Gold [registered users])


The article you requested is

Using Data Mining to Explore Complex Clinical Decisions: A Study of Hospitalization After a Suicide Attempt.

J Clin Psychiatry 2006;67:1124-1132
Copyright 2006 Physicians Postgraduate Press, Inc.

To view this item, select one of the options below.

    1. Purchase this PDF for $40
      If you are not a paid subscriber, you may purchase the PDF.
      (You'll need the free Adobe Acrobat Reader.)
    2. Subscribe
      Receive immediate full-text access to JCP. You can subscribe to JCP print + online for $166 individual.
      JCP's 75th AnniversaryCelebrate!
      Celebrate JCP's 75th Anniversary with a special online-only subscription price of $75.
    1. Activate
      If you are a paid subscriber to JCP and do not yet have a username and password, activate your subscription now.
    2. Sign in
      As a paid subscriber who has activated your subscription, you have access to the HTML and PDF versions of this item.
  1. Did you forget your password?

Still can't log in? Contact the Circulation Department at 1-800-489-1001 x4 or send an email


Background: Medical education is moving toward developing guidelines using the evidence-based approach; however, controlled data are missing for answering complex treatment decisions such as those made during suicide attempts. A new set of statistical techniques called data mining (or machine learning) is being used by different industries to explore complex databases and can be used to explore large clinical databases.

Method: The study goal was to reanalyze, using data mining techniques, a published study of which variables predicted psychiatrists' decisions to hospitalize in 509 suicide attempters over the age of 18 years who were assessed in the emergency department. Patients were recruited for the study between 1996 and 1998. Traditional multivariate statistics were compared with data mining techniques to determine variables predicting hospitalization.

Results: Five analyses done by psychiatric researchers using traditional statistical techniques classified 72% to 88% of patients correctly. The model developed by researchers with no psychiatric knowledge and employing data mining techniques used 5 variables (drug consumption during the attempt, relief that the attempt was not effective, lack of family support, being a housewife, and family history of suicide attempts) and classified 99% of patients correctly (99% sensitivity and 100% specificity).

Conclusions: This reanalysis of a published study fundamentally tries to make the point that these new multivariate techniques, called data mining, can be used to study large clinical databases in psychiatry. Data mining techniques may be used to explore important treatment questions and outcomes in large clinical databases and to help develop guidelines for problems where controlled data are difficult to obtain. New opportunities for good clinical research may be developed by using data mining analyses.