ED waiting time predictions in real-time: development of data acquisition system and performance evaluation of advanced statistical models. (Old ID 27255)
Role
Principal Investigator
Description
Emergency department (ED) waiting times are a significant predictor of the patient experience. This project aims to use advanced statistical models and machine-learning algorithms to capture dynamic fluctuations in waiting time, to implement and validate the prediction performance of these models. A solution that is capable of sourcing data from ED information systems and feed it into prediction models to generate waiting time forecasts would bring practical benefits for staff and patients. There is also potential to assist clinicians and nurses to estimate demand for care and calibrate workflow.
Date
19 May 2021 - 30 Apr 2022
Project Type
GRANT
Keywords
Waiting time prediction;Data acquisition system;Machine learning;Emergency department
Funding Body
Emergency Medicine Foundation
Amount
36733
Project Team
Kelly Trinh