This paper is in the following e-collection/theme issue:

Bioinformatics, genomics, tools and databases (23) Clinical Information and Decision Making (1603) Decision Support for Health Professionals (1323)

Published on in Vol 3, No 1 (2022): Jan-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/38845, first published .
Reducing Crowding in Emergency Departments With Early Prediction of Hospital Admission of Adult Patients Using Biomarkers Collected at Triage: Retrospective Cohort Study

Reducing Crowding in Emergency Departments With Early Prediction of Hospital Admission of Adult Patients Using Biomarkers Collected at Triage: Retrospective Cohort Study

Reducing Crowding in Emergency Departments With Early Prediction of Hospital Admission of Adult Patients Using Biomarkers Collected at Triage: Retrospective Cohort Study

Authors of this article:

Ann Corneille Monahan1 Author Orcid Image ;   Sue S Feldman2 Author Orcid Image ;   Tony P Fitzgerald3, 4 Author Orcid Image
Article Authors Cited by (4) Tweetations (2) Metrics

Journals

  1. Monahan A, Feldman S. The Utility of Predictive Modeling and a Systems Process Approach to Reduce Emergency Department Crowding: A Position Paper. Interactive Journal of Medical Research 2023;12:e42016 View
  2. Williams E, Huynh D, Estai M, Sinha T, Summerscales M, Kanagasingam Y. Predicting Inpatient Admissions From Emergency Department Triage Using Machine Learning: A Systematic Review. Mayo Clinic Proceedings: Digital Health 2025;3(1):100197 View
  3. Abugroun A, Awadalla S, Singh S, Fang M. Development of an emergency department triage tool to predict admission or discharge for older adults. International Journal of Emergency Medicine 2025;18(1) View
  4. Aloini D, Benevento E, Berdini M, Stefanini A. Predicting Radiology Service Times for Enhancing Emergency Department Management. Socio-Economic Planning Sciences 2025:102208 View