Evaluation of a hospital admission prediction model adding coded chief complaint data using neural network methodology.

Journal: European journal of emergency medicine : official journal of the European Society for Emergency Medicine

Published Date: Apr 1, 2015

Abstract

OBJECTIVE: Our objective was to apply neural network methodology to determine whether adding coded chief complaint (CCC) data to triage information would result in an improved hospital admission prediction model than one without CCC data.

Authors

Neal Handly

aDepartment of Emergency Medicine, Drexel University College of Medicine, Philadelphia, Pennsylvania bCollege of Computing and Informatics, Drexel University, Philadelphia, Pennsylvania cDepartment of Emergency Medicine, Allegheny Health Network, Pittsburgh, Pennsylvania dECI Health Partners, Chicago, Illinois, USA.
David A Thompson
Jiexun Li
David M Chuirazzi
Arvind Venkat

Keywords

Aged Aged, 80 and over Algorithms Area Under Curve Cohort Studies Confidence Intervals Emergency Medicine Emergency Service, Hospital Emergency Treatment Female Hospitalization Humans Male Neural Networks, Computer Patient Admission Pennsylvania Predictive Value of Tests Reproducibility of Results Retrospective Studies Risk Assessment Triage

External Resources

View on PubMed Access via DOI PubMed (24509606)

Evaluation of a hospital admission prediction model adding coded chief complaint data using neural network methodology.

Abstract

Authors

Keywords

External Resources

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