Automated analysis of unstructured clinical assessments improves emergency department triage performance: A retrospective deep learning analysis
Abstract Objectives Efficient and accurate emergency department (ED) triage is critical to prioritize the sickest patients and manage department flow. We explored the use of electronic health record data and advanced predictive analytics to improve triage performance. Methods Using a data set of ove...
Saved in:
| Main Authors: | Dana R. Sax, E. Margaret Warton, Oleg Sofrygin, Dustin G. Mark, Dustin W. Ballard, Mamata V. Kene, David R. Vinson, Mary E. Reed |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-08-01
|
| Series: | Journal of the American College of Emergency Physicians Open |
| Online Access: | https://doi.org/10.1002/emp2.13003 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Clinical characteristics of COVID‐19 patients evaluated in the emergency department: A retrospective cohort study of 801 cases
by: Dale M. Cotton, et al.
Published: (2021-08-01) -
Stroke prophylaxis after US emergency department diagnosis and discharge of patients with atrial fibrillation and flutter from 21 hospitals
by: Bory Kea, et al.
Published: (2025-05-01) -
Risk adjusted 30‐day mortality and serious adverse event rates among a large, multi‐center cohort of emergency department patients with acute heart failure
by: Dana R. Sax, et al.
Published: (2022-06-01) -
Comparison between the Smart Triage model and the Emergency Triage Assessment and Treatment guidelines in triaging children presenting to the emergency departments of two public hospitals in Kenya.
by: Stephen Kamau, et al.
Published: (2024-08-01) -
Pilot trial of an electronic decision support to improve care for emergency department patients with acute heart failure
by: Dana R. Sax, et al.
Published: (2024-12-01)