A Novel Deep Learning-Based System for Triage in the Emergency Department Using Electronic Medical Records: Retrospective Cohort Study
Journal
Journal of Medical Internet Research
Journal Volume
23
Journal Issue
12
Date Issued
2021
Author(s)
Abstract
Emergency department (ED) crowding has resulted in delayed patient treatment and has become a universal health care problem. Although a triage system, such as the 5-level emergency severity index, somewhat improves the process of ED treatment, it still heavily relies on the nurse's subjective judgment and triages too many patients to emergency severity index level 3 in current practice. Hence, a system that can help clinicians accurately triage a patient's condition is imperative.
Subjects
data to text; deep learning; electronic health record; emergency department; hospital admission; triage system
Other Subjects
adult; article; clinical outcome; cohort analysis; controlled study; convolutional neural network; deep learning; electronic health record; electronic medical record; emergency health service; emergency ward; female; hospital admission; hospitalization; human; intensive care unit; major clinical study; male; medical care; mortality; outcome assessment; prediction; prospective study; receiver operating characteristic; recurrent neural network; resource allocation; retrospective study; Taiwan; university hospital; electronic health record; hospital emergency service; retrospective study; Deep Learning; Electronic Health Records; Emergency Service, Hospital; Hospitalization; Humans; Prospective Studies; Retrospective Studies; Triage
Publisher
JMIR PUBLICATIONS, INC
Type
journal article