Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
8-2013
Abstract
In this work, we consider the problem of allocating doctors in the ambulatory area of a hospital's emergency department (ED) based on a set of policies. Traditional staffing methods are static, hence do not react well to surges in patient demands. We study strategies that intelligently adjust the number of doctors based on current and historical information about the patient arrival. Our main contribution is our proposed data-driven online approach that performs adaptive allocation by utilizing historical as well as current arrivals by running symbiotic simulation in real-time. We build a simulation prototype that models ED process that is close to real-world with time-varying demand and re-entrant patients. The experimental results show that our approach allows the ED to better cope with demand surges and to meet a service level desired by the hospital.
Discipline
Artificial Intelligence and Robotics | Business | Operations Research, Systems Engineering and Industrial Engineering
Publication
IEEE International Conference on Automation Science and Engineering (CASE)
First Page
984
Last Page
989
ISSN
2161-8070
Identifier
10.1109/CoASE.2013.6653988
Publisher
IEEE
City or Country
Madison, WI, USA
Citation
TAN, Kar Way; TAN, Wei Hao; and LAU, Hoong Chuin.
Improving Patient Length-of-Stay in Emergency Department Through Dynamic Resource Allocation Policies. (2013). IEEE International Conference on Automation Science and Engineering (CASE). 984-989.
Available at: https://ink.library.smu.edu.sg/sis_research/1934
Copyright Owner and License
LARC
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
http://dx.doi.org/10.1109/CoASE.2013.6653988
Included in
Artificial Intelligence and Robotics Commons, Business Commons, Operations Research, Systems Engineering and Industrial Engineering Commons