The use of length of stay distributions to predict hospital discharges.
Many hospital admissions scheduling or admissions control systems reported in the literature rely on estimates of future discharges to help control the variance in daily patient census. One of the two most frequently reported methods of estimating discharges attempts to explain the variance in historical length of stay (LPS) data. This paper explores the relationship between LOS variance explanation and the ability to predict discharges and concludes that even a large improvement in the ability to explain LOS variance will only marginally reduce the errors in the associated discharge predictions. In drawing this conclusion, a general discharge prediction model is developed and a more relevant statistic than per cent variance explained is introduced.
D000289:Admitting Department, Hospital / Q000458:organization & administration*; D000704:Analysis of Variance; D001509:Bed Occupancy; D003955:Diagnostic Tests, Routine; D006748:Hospital Departments / Q000458:organization & administration*; D006801:Humans; D007902:Length of Stay; D010351:Patient Discharge; D011336:Probability; D014481:United States