The role of psychometric data in predicting inpatient mental health service utilization

Inpatient mental health readmission rates have increased dramatically in re cent years, with a subset of consumers referred to as revolving-door patien ts. In an effort to reduce the financial burden associated with these patie nts and increase treatment efficacy, researchers have begun to explore fact ors associated with increased service utilization. To date, predictors of i ncreased service usage are remarkably discrepant across studies. Further ex ploration, therefore, is needed to better explicate the relevance of "tradi tional" predictors and also to identify alternate strategies that may assis t in predicting rehospitalization. One method that may be helpful in identi fying patients at high risk is the development of a psychometric screening procedure. As a means to this end, the present study was designed to assess the potential usefulness of psychometric data in predicting mental health service utilization. The sample consisted of 131 patients hospitalized duri ng an index period of 8 months at an acute-care psychiatric hospital. Numbe r of readmissions was recorded in a 9 month post-index period. Measures com pleted during the index admission included the Brief Psychiatric Rating Sca le-Anchored (BPRS-A), Symptom Checklist-90-Revised (SGL-90-R), Kaufman Brie f Intelligence Test CK-BIT), and the Beck Depression Inventory (BDI). Resul ts indicated that psychometric data accounted for significant variance in p redicting past, present and future mental health service utilization. The B PRS-A, SCL-90-R, and BDI show particular promise as time efficient psychome tric screening instruments that may better enable practitioners to identify patients proactively who are at increased risk for rehospitalization. Impl ications are discussed with regard to patient-treatment matching and discha rge planning.