• AMIA Annu Symp Proc · Jan 2007

    Predicting hospital admission at triage in an emergency department.

    • Judith W Dexheimer, Jeffrey Leegon, and Dominik Aronsky.
    • Department of Biomedical Informatics,Vanderbilt University Medical Center, Nashville, TN, USA.
    • AMIA Annu Symp Proc. 2007 Jan 1: 937.

    AbstractPredicting hospital admission for Emergency Department (ED) patients at the time of triage may improve throughput. To predict admission we created and validated a Bayesian Network from 47,993 encounters (training: n=23,996, validation: n=9,599, test: n=14,398). The area under the receiver operator characteristic curve was 0.833 (0.8260.840) for the network and 0.790 (0.7810.799) for the control variable (acuity only). Predicting hospital admission early during an encounter may help anticipate ED workload and potential overcrowding.

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