title: Predicting length of children's psychiatric hospitalizations: an "ecologic" approach.
abstract: This article describes the development and validation of a simple and modestly successful model for predicting inpatient length of stay (LOS) at a state-funded facility providing acute to long term care for children and adolescents in Ohio. Six variables--diagnostic group, legal status at time of admission, attending physician, age, sex, and county of residence--explained 30% of the variation in log10LOS in the subgroup used to create the model, and 26% of log10LOS variation in the cross-validation subgroup. The model also identified LOS outliers with moderate accuracy (ROC area = .68-0.76). The authors attribute the model's success to inclusion of variables that are correlated to idiosyncratic "ecologic" factors as well as variables related to severity of illness. Future attempts to construct LOS models may adopt similar approaches.
authors.affiliation: Department of Veterans Affairs Medical Center, Cincinnati, OH.
authors.forename: D
authors.initials: D
authors.lastname: Mossman
authors.forename: D A
authors.initials: DA
authors.lastname: Songer
authors.forename: D G
authors.initials: DG
authors.lastname: Baker
mesh_terms: D000293:Adolescent; D000367:Age Factors; D002675:Child, Preschool; D003953:Diagnosis-Related Groups; D005069:Evaluation Studies as Topic; D005260:Female; D005544:Forecasting; D006776:Hospitals, Pediatric / Q000706:statistics & numerical data*; D006778:Hospitals, Psychiatric / Q000706:statistics & numerical data*; D006779:Hospitals, Public / Q000706:statistics & numerical data*; D006801:Humans; D007902:Length of Stay / Q000706:statistics & numerical data*; D008297:Male; D015233:Models, Statistical; D009820:Ohio; D016311:Outliers, DRG; D012372:ROC Curve; D012044:Regression Analysis; D012111:Residence Characteristics; D012720:Severity of Illness Index; D012737:Sex Factors