Predicting Resource Utilization by Children with Serious Emotional Disturbance and Their Families

Our study represents a rural case management agency's use of its data to aid in its transition from being funded by federal grant funds to self-sustainment. We wanted to learn if some characteristics of those children served could predict the resources needed to serve them. We analyzed data on 90 children and adolescents living in a rural community. Using multiple regression analysis we found that CAFAS total and CBCL total problem scores predicted Medicaid reimbursements but not flexible funds spending or case management hours. History of psychiatric hospitalization, however, predicted flexible funds spending and case management hours. Using one-way ANOVA and post hoc analysis we found that the staff members' assessments of each child and family's level of service needs were reflected in differences in mean CAFAS total scores, Medicaid reimbursements and case management hours, but not CBCL total problem scores or flexible funds spending.