Seminar: Using Hospital Admission Predictions at Triage for Improving Patient Length-of-Stay in Emergency Departments by Serhan Ziya
Department of Industrial Engineering
Using Hospital Admission Predictions at Triage for Improving Patient
Length-of-Stay in Emergency Departments
University of North Carolina
Long boarding times has long been recognized as one of the main reasons behind emergency department (ED) crowding. One of the suggestions made in the literature to reduce boarding times was to predict, at the time of triage, whether or not a patient will eventually be admitted to the hospital, and if the prediction turns out to be "admit," start preparations for the patient's transfer to the main hospital early in the ED visit. In this talk, we develop a methodology, using logistic regression, Markov decision processes, and queueing theory, that can be utilized for deciding when to request beds early for the patients and investigate the potential benefits of this methodology via a simulation model of an actual ED.
Serhan Ziya is a professor in the Department of Statistics and Operations Research at the University of North Carolina. He holds a BS degree in Industrial Engineering from Bogazici University and MS and Ph.D. degrees in Industrial and Systems Engineering from Georgia Institute of Technology. His research interests are in service operations, with a focus on healthcare operations, queueing systems, revenue management, and pricing. More information can be found from his website at http://ziya.web.unc.edu/.
Date: Friday, May 13, 2022
Online Seminar Link:
Meeting ID: 914 9694 2452