Predicting length of stay for Medicare patients at a teaching hospital.
This research examines how the patients' characteristics and clinical indicators affect length of stay for the top five Diagnosis-Related-Groups (DRGs) for Medicare patients at a teaching hospital in the United States. The top DRGs were selected on the basis of volume per year. Teaching hospitals in the United States devote a significant amount of their resources to research and teaching, while providing treatment for patients. The ability to predict length of stay can substantially improve a teaching hospital's capacity utilization, while ensuring that resources are available to meet the health care needs of the Medicare population. Multiple regression models are developed to predict the length of stay using the patients' characteristics and clinical indicators as independent variables. The results indicate that approximately 60 percent (R(2)) of the variance in the length of stay is explained by the patients' characteristics and clinical indicators for these DRGs. The Mortality and Severity indices are found to be the strongest predictors for length of stay in all DRGs. Other patients' characteristics and clinical indicators such as age, gender, race/ethnicity, marital status, admission type and admission source are also significant predictors for some DRGs. In addition, most of these variables affect the length of stay in the same manner as shown in previous studies, even though the previous studies do not have the DRG specificity of this study.
Department of Industrial Engineering, University of Miami, Florida 33124-0623, USA. comachon@eng.miami.edu
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Omachonu
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Suthummanon
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Akcin
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Asfour
D000368:Aged; D003953:Diagnosis-Related Groups; D004194:Disease / Q000145:classification; D005260:Female; D006291:Health Policy; D006302:Health Services Research; D006784:Hospitals, Teaching; D006801:Humans; D007902:Length of Stay; D008297:Male; D006278:Medicare; D014481:United States