Predicting Emergency Severity Index (ESI) level, hospital admission, and admitting ward in an emergency department using data-driven machine learning.
Journal:
BMC medical informatics and decision making
Published Date:
Jul 28, 2025
Abstract
INTRODUCTION: Emergency departments (EDs) are critical for ensuring timely patient care, especially in triage, where accurate prioritisation is essential for patient safety and resource utilisation. Building on previous research, this study leverages a comprehensive dataset of 653,546 ED visits spanning six years from Mater Dei Hospital, Malta. This dataset enables detailed trend analysis, demographic variation exploration, and predictive modelling of patient prioritisation, admission likelihood, and admitting ward.