Validity of an artificial neural network in predicting discharge destination from a postacute geriatric rehabilitation unit.
To develop an artificial neural network (ANN) designed to predict discharge destination from postacute geriatric rehabilitation units. Nonconcurrent prospective study. Postacute geriatric rehabilitation units: a 20-bed unit in a nonproprietary skilled nursing facility and a 40-bed unit in a suburban private facility. Consecutive sample of 661 patients admitted between January 1995 and February 1999, including a derivation group of 452 patients and a validation group of 209 patients. A feed-forward, back-propagation neural network to predict discharge destination. Discharge destination from postacute geriatric rehabilitation. An ANN was trained on clinical pattern set derived from 452 patients and validated prospectively on 209 consecutive patients admitted to postacute geriatric rehabilitation units. The neural network achieved a sensitivity of 85.7% (95% confidence interval [CI], 83.7-89.4) and specificity of 94.1% (95% CI, 84.4-99.1) in identifying discharge destination with a corresponding area under the curve of 95.7% (95% CI, 92.1-98.3). An ANN can predict discharge to the community postacute rehabilitation with a high degree of accuracy. It could have particular value to predict return to the community for older adults with multiple comorbidities after an acute hospitalization.