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General Information
    • ISSN: 2010-3751 (Print)
    • Frequency: Semi-annual
    • DOI: 10.18178/IJFCC
    • Editor-in-Chief: Prof. Pascal Lorenz
    • Executive Editor: Ms. Tina Yuen
    • Abstracting/ Indexing: Crossref, Electronic Journals LibraryGoogle Scholar, EBSCO, etc.
    • E-mail:  editor@ijfcc.org
    • Article Processing Charge: 500 USD
Editor-in-chief

Prof. Pascal Lorenz
University of Haute Alsace, France
 
It is my honor to be the Editor-in-Chief of IJFCC. The journal publishes good papers in the field of future computer and communication. Hopefully, IJFCC will become a recognized journal among the readers in the filed of future computer and communication.

IJFCC 2026 Vol.15(1): 37-43
DOI: 10.18178/ijfcc.2026.15.1.630

Using AI to Improve Operations in the Emergency Department

Taghreed A. Alahmadi*, Marwah J. Aljohani, Shrooq M. Alattas, Salma M. Elhag
Department of Information Systems, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia
TALAHMADI0052@stu.kau.edu.sa (T.A.A.); MALJOHANI0422@stu.kau.edu.sa (M.J.A.); salattas0059@stu.kau.edu.sa (S.M.A.); smomar@kau.edu.sa (S.M.E.)
*Corresponding author

Manuscript received March 2, 2026; revised April 17, 2026; accepted May 12, 2026; published May 28, 2026

Abstract—Overcrowding in Emergency Departments (EDs) is a major problem in most hospitals, and long waiting times are one of its main causes. This problem is due to the complete reliance on manual processes, from registering the patient in the system to the triage and prioritization of examination. Thus, this paper proposes an electronic system as an alternative to manual procedures to mitigate the effects of overcrowding. The proposed system automates patient registration using an identity verification scanner and introduces an AI-based triage concept to support patient classification based on vital data entered by nurses. This approach assists in the classification of cases as emergency or non-emergency, and directly determines the course of action, either by immediately referring the patient to a doctor or waiting for the patient’s turn to be examined. A Business Process Analysis (BPA) methodology was used to document and analyze both the current (“as-is”) and proposed (“to-be”) processes in the ED. A simulation was performed using the Bizagi Modeler to evaluate the performance of the proposed system. The results show that the redesigned process reduces the average patient waiting time in the ED by improving case periodization and workflow efficiency.

Keywords—emergency department, automated AI triage, registration, ID scanning, vital signs, patient flow

[PDF]

Cite:Taghreed A. Alahmadi, Marwah J. Aljohani, Shrooq M. Alattas, and Salma M. Elhag, "Using AI to Improve Operations in the Emergency Department ," International Journal of Future Computer and Communication, vol. 15, no. 1, pp. 37-43, 2026.


Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0)

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