The role of suicide risk in the decision for psychiatric hospitalization after a suicide attempt

Crisis. 2011;32(2):65-73. doi: 10.1027/0227-5910/a000050.

Abstract

Background: Suicide prevention can be improved by knowing which variables physicians take into account when considering hospitalization or discharge of patients who have attempted suicide.

Aims: To test whether suicide risk is an adequate explanatory variable for predicting admission to a psychiatric unit after a suicide attempt.

Methods: Analyses of 840 clinical records of patients who had attempted suicide (66.3% women) at four public general hospitals in Madrid (Spain).

Results: 180 (21.4%) patients were admitted to psychiatric units. Logistic regression analyses showed that explanatory variables predicting admission were: male gender; previous psychiatric hospitalization; psychiatric disorder; not having a substance-related disorder; use of a lethal method; delay until discovery of more than one hour; previous attempts; suicidal ideation; high suicidal planning; and lack of verbalization of adequate criticism of the attempt.

Conclusions: Suicide risk appears to be an adequate explanatory variable for predicting the decision to admit a patient to a psychiatric ward after a suicide attempt, although the introduction of other variables improves the model. These results provide additional information regarding factors involved in everyday medical practice in emergency settings.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Checklist
  • Child
  • Female
  • Hospitalization*
  • Hospitals, General
  • Hospitals, Public
  • Humans
  • Male
  • Middle Aged
  • Probability
  • Psychiatric Department, Hospital*
  • Risk Assessment
  • Spain
  • Suicidal Ideation*
  • Suicide / psychology*
  • Suicide / statistics & numerical data
  • Suicide Prevention*
  • Suicide, Attempted / prevention & control
  • Suicide, Attempted / psychology*
  • Suicide, Attempted / statistics & numerical data
  • Young Adult