The Journal of Behavioral Health Services & Research

, Volume 30, Issue 3, pp 342–351

Predicting rehospitalization and outpatient services from administration and clinical databases

Authors

    • Washington Institute for Mental Illness Research and TrainingWashington State University
  • Joan E. Russo
    • Department of Psychiatry and Behavioral SciencesUniversity of Washington School of Medicine
    • Outcomes Assessment and Quality AssuranceHarborview Medical Center
  • Bruce Stegner
    • Washington Institute for Mental Illness Research and TrainingWashington State University
    • Mental Health Division in Department of Social and Health Services
  • Dennis G. Dyck
    • Washington Institute for Mental Illness Research and TrainingWashington State University
  • Richard K. Ries
    • Department of Psychiatry and Behavioral SciencesUniversity of Washington School of Medicine
    • Outpatient Psychiatry and Addiction ServicesHarborview Medical Center
  • Peter Roy-Byrne
    • Department of Psychiatry and Behavioral SciencesUniversity of Washington School of Medicine
    • Outcomes Assessment and Quality AssuranceHarborview Medical Center
Brief Reports

DOI: 10.1007/BF02287322

Cite this article as:
Hendryx, M.S., Russo, J.E., Stegner, B. et al. The Journal of Behavioral Health Services & Research (2003) 30: 342. doi:10.1007/BF02287322

Abstract

The study tests whether psychiatric services utilization may be predicted from administrative databases without clinical variables equally as well as from databases with clinical variables. Persons with a psychiatric hospitalization at an urban medical center were followed for 1 year postdischarge (N=1384.) Dependent variables included statewide rehospitalization and the number of hours of outpatient services received. Three linear and logistic regression models were developed and cross-validated: a basic model with limited administrative independent variables, an intermediate model with diagnostic and limited clinical indicators, and a full model containing additional clinical predictors. For rehospitalization, the clinical cross-validated model accounted for twice the variance accounted by the basic model (adjusted R2=.13 and .06, respectively). For outpatient hours, the basic cross-validated model performed as well as the clinical model (adjusted R2=.36 and .34, respectively.) Clinical indicators such as assessment of functioning and co-occurring substance use disorder should be considered for inclusion in predicting rehospitalization.

Copyright information

© National Council for Community Behavioral Healthcare 2003