5 papers
Do Machine Learning-Guided Proactive Full Capacity Protocols Mitigate Emergency Department Overcrowding? A Simulation-Based Evaluation
Khalid Aram, Orhun Vural, Bunyamin Ozaydin +2
Objective: Emergency department (ED) overcrowding threatens care quality, yet Full Capacity Protocols (FCPs) are typically activated only after crowding thresholds have been exceed…
An Integrated Forecasting Prototype for Emergency Department Boarding Time to Support Proactive Operational Decision Making
Orhun Vural, Abdulaziz Ahmed, Ferhat Zengul +2
Overcrowding in emergency departments (ED) remains a persistent operational challenge worldwide, causing delays in care delivery and downstream congestion. ED boarding time, define…
Deep Learning-Based Forecasting of Boarding Patient Counts to Address ED Overcrowding
Orhun Vural, Bunyamin Ozaydin, James Booth +2
This study presents a deep learning-based framework for predicting emergency department (ED) boarding counts six hours in advance using only operational and contextual data, withou…
Assessing the Impact of External and Internal Factors on Emergency Department Overcrowding
Abdulaziz Ahmed, Khalid Y Aram, Mohammed Alzeen +4
Study Objective: To analyze the factors influencing Emergency Department (ED) overcrowding by examining the impacts of operational, environmental, and external variables, including…
An Artificial Intelligence-Based Framework for Predicting Emergency Department Overcrowding: Development and Evaluation Study
Orhun Vural, Bunyamin Ozaydin, Khalid Y. Aram +3
Background: Emergency department (ED) overcrowding remains a major challenge, causing delays in care and increased operational strain. Hospital management often reacts to congestio…