Psychiatric status, quality of life, and level of care as predictors of outcomes of acute inpatient treatment.

Abstract

The study examined the role of five types of variables--demographic characteristics, psychiatric status, functional quality of life, satisfaction with quality of life, and level of care--in predicting key outcomes of inpatient treatment. Multivariate canonical regression and univariate multiple regression models were constructed using data from 1,053 inpatients at a public hospital in Washington State. The models were used to predict length of stay, change in symptom severity during hospitalization, psychiatrists' ratings of patients' insight into their illness at discharge, patients' global satisfaction with life, and rehospitalization within 18 months. Hierarchical stepwise procedures were used to select variables that were significant predictors of outcomes. All five classes of predictors were related to the outcomes. The roles of demographic characteristics and diagnoses were minimal. Previous hospitalization and severity of symptoms at admission were strong predictors of psychiatric status. Indicators of functional quality of life and satisfaction with quality of life explained significant variance in all models after accounting for the other classes of predictors. Frequency of family visits was the strongest functional quality-of-life predictor, relating to positive outcomes. Pretreatment satisfaction with life was a significant predictor of most outcomes, and increased satisfaction was associated with positive outcomes. Patients' quality of life before psychiatric inpatient treatment predicted treatment outcomes independently of psychiatric status, demographic characteristics, and level-of-care variables. Prospective studies are needed to predict outcomes using multidimensional constructs.