Co-occurring Psychiatric and Substance Use Disorders: A Multistate Feasibility Study of the Quadrant Model

Abstract

The quadrant model was developed to organize the heterogeneous group of persons with co-occurring psychiatric and substance use disorders and to anticipate differential use of systems of care. The purpose of the study presented here was to test the feasibility of applying the model to classify persons with co-occurring disorders, examine the reliability of quadrant prevalence and distribution, and test the validity of differential service use by quadrant. Medicaid claims data from 1999 from six states were analyzed, and 22,912 individuals with co-occurring disorders were classified into quadrants, by severity of substance use and psychiatric disorders. Distribution by quadrant and the utilization of emergency and inpatient services were analyzed. A majority of cases were classified in quadrant IV (52.5%) (high severity of psychiatric and substance use disorders), and fewest were classified in quadrant I (8.2%) (low severity of psychiatric and substance use disorders). There was equivalence in distribution for quadrant III (19.8%) (high severity of substance use disorders and low severity of psychiatric disorders) and quadrant II (19.4%) (high severity of psychiatric disorders and low severity of substance use disorders). Distribution was consistent across states, and service utilization was most associated with quadrant IV. Persons with the more severe psychiatric problems (quadrants II and IV) were more likely to be female, to be older, and to have been hospitalized or to have visited an emergency department. Another important finding is the high rate of persons with substance dependence disorders (quadrants III and IV). The feasibility of applying the quadrant model was supported. The quadrant model has been well adopted conceptually by community providers and policy makers. The consistency of the findings across six state Medicaid systems supports the potential utility of the model to articulate patient characteristics and service use patterns. Further application and research with this model is proposed.