Machine Learning-Based Prediction of Clinical Outcomes for Children During Emergency Department Triage.

ABSTRACT:

Importance

While machine learning approaches may enhance prediction ability, little is known about their utility in emergency department (ED) triage.

Objectives

To examine the performance of machine learning approaches to predict clinical outcomes and disposition in children in the ED and to compare their performance with conventional triage approaches.

Design, setting, and participants

Prognostic study of ED data from the National Hospital Ambulatory Medical Care Survey from January 1, 2007, through December 31, 2015. A nationally representative sample of 52 037 children aged 18 years or younger who presented to the ED were included. Data analysis was performed in August 2018.

Main outcomes and measures

The outcomes were critical care (admission to an intensiv

SUBMITTER: Goto T 

PROVIDER: S-EPMC6484561 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature