title: Forecasting length of stay in child residential treatment.
abstract: A sample of 126 consecutively admitted residential treatment children (mean age = 9.86, SD=1.84; 70.6% male; 42.1% African American; 50% Caucasian) were studied over a five-year period to identify predictors of length-of-stay. Cox regression was the primary statistical method used to analyze psychiatric and behavioral rating data for children assessed by teachers and treatment staff using the Devereux Scales of Mental Disorders (DSMD). Parental alcohol abuse, and children's age, medication status, race, initial DSMD total and critical pathology scores, were predictive of length-of-stay. Residential length-of-stay was strongly linked to initial levels of psychiatric symptomatology. Models that can help forecast length of stay are vital tools in helping to improve both clinical and utilization management strategies.
authors.affiliation: Department of Justice Studies, Institute for the Study and Prevention of Violence, Kent State University, Research and Evaluation, Beech Brook, Kent, Cleveland, OH 44242-0001, USA. dhussey@kent.edu
authors.forename: David L
authors.initials: DL
authors.lastname: Hussey
authors.forename: Shenyang
authors.initials: S
authors.lastname: Guo
mesh_terms: D002648:Child; D039721:Diagnostic and Statistical Manual of Mental Disorders; D005260:Female; D005544:Forecasting; D006801:Humans; D007902:Length of Stay / Q000706:statistics & numerical data*; D008297:Male; D001523:Mental Disorders / Q000175:diagnosis / Q000534:rehabilitation*; D011237:Predictive Value of Tests; D011446:Prospective Studies; D012114:Residential Treatment; D012720:Severity of Illness Index