PREDICTING LENGTH OF STAY IN AN ACUTE PSYCHIATRIC-HOSPITAL

Objective: Multivariate statistical methods were used to identify pati ent-related variables that predicted length of stay in a single psychi atric facility. The study investigated whether these variables remaine d stable over time and could be used to provide individual physicians with data on length of stay adjusted for differences in clinical casel oads and to detect trends in the physicians' practice patterns. Method s: Data on all patients discharged over two six-month periods were col lected at an acute psychiatric inpatient facility. Stepwise multiple r egression analyses were conducted on the two datasets. Results: The re sults from both analyses revealed that five variables significantly pr edicted length of stay and were stable over time. They were a primary diagnosis of schizophrenia, the number of previous admissions, a prima ry diagnosis of a mood disorder, age, and a secondary diagnosis of an alcohol- or other drug-related disorder. For some physicians, the mean length of stay of their patients differed significantly from the leng th predicted by the regression model-generally, it was shorter Conclus ions: The results demonstrate that patient-related predictors of lengt h of stay in a single psychiatric hospital can be identified using rel atively simple statistical procedures and can be consistent across a l arge dataset and over time.