title: Factors associated with hospitalization of adult psychiatric patients: cluster analysis.
abstract: OBJECTIVE
  Factors associated with acute admission to inpatient psychiatric wards have been difficult to replicate, possibly reflecting methodological limitations of analyzing individual variables. The objective of this analysis was to identify factors associated with hospitalization at an inpatient psychiatric unit using cluster analytic methods.
  
  
  METHODS
  Demographic, admission and treatment data for all admissions to a single inpatient unit in 2010 were collected retrospectively. Cluster analysis was performed using Ward's method.
  
  
  RESULTS
  The initial clustering identified a high suicidality/crisis group, which then gave two further subclusters, an internalizing one characterized by affective symptoms and an externalizing one characterized by intoxication at admission, and a population with poor medication compliance that included most cases of psychosis. These subclusters had different clinical and demographic characteristics, different rates of hospital readmission and different durations of stay.
  
  
  CONCLUSIONS
  Cluster analysis may be a useful exploratory technique to assist in planning and developing services for adult patients needing admission to a psychiatric hospital.
authors: Department of Psychological Medicine, Dunedin School of Medicine, University of Otago, Dunedin, New Zealand.
authors: Yun Kern
authors: YK
authors: Chai
authors: Zuzana
authors: Z
authors: Wheeler
authors: Peter
authors: P
authors: Herbison
authors: Chris
authors: C
authors: Gale
authors: Paul
authors: P
authors: Glue
mesh_terms: D000328:Adult; D016000:Cluster Analysis; D005260:Female; D006760:Hospitalization / Q000706:statistics & numerical data*; D006778:Hospitals, Psychiatric / Q000706:statistics & numerical data*; D006801:Humans; D007902:Length of Stay / Q000706:statistics & numerical data; D008297:Male; D001523:Mental Disorders / Q000175:diagnosis*; D010359:Patient Readmission / Q000706:statistics & numerical data; D012189:Retrospective Studies; D012307:Risk Factors