Accident and emergency departments (A&E) are the first place of contact for urgent and complex patients. These departments are subject to uncertainties due to the unplanned patient arrivals. After arrival to an A&E, patients are categorized by a triage nurse based on the urgency. The performance of an A&E is measured based on the number of patients waiting for more than a certain time to be treated. Due to the uncertainties affecting the patient flow, finding the optimum staff capacities while ensuring the performance targets is a complex problem. This paper proposes a robust-optimization based approximation for the patient waiting times in an A&E. We also develop a simulation optimization heuristic to solve this capacity planning problem. The performance of the approximation approach is then compared with that of the simulation optimization heuristic. Finally, the impact of model parameters on the performances of two approaches is investigated. The experiments show that the proposed approximation results in good enough solutions.
Mots-clés : Health-care modelling, capacity planning, accident and emergency services, queuing theory, simulation optimization, robust optimization
@article{RO_2020__54_6_1757_0,
author = {G\"okalp, Elvan},
title = {Robust capacity planning for accident and emergency services},
journal = {RAIRO - Operations Research - Recherche Op\'erationnelle},
pages = {1757--1773},
publisher = {EDP-Sciences},
volume = {54},
number = {6},
year = {2020},
doi = {10.1051/ro/2019112},
mrnumber = {4150246},
language = {en},
url = {http://www.numdam.org/articles/10.1051/ro/2019112/}
}
TY - JOUR AU - Gökalp, Elvan TI - Robust capacity planning for accident and emergency services JO - RAIRO - Operations Research - Recherche Opérationnelle PY - 2020 SP - 1757 EP - 1773 VL - 54 IS - 6 PB - EDP-Sciences UR - http://www.numdam.org/articles/10.1051/ro/2019112/ DO - 10.1051/ro/2019112 LA - en ID - RO_2020__54_6_1757_0 ER -
%0 Journal Article %A Gökalp, Elvan %T Robust capacity planning for accident and emergency services %J RAIRO - Operations Research - Recherche Opérationnelle %D 2020 %P 1757-1773 %V 54 %N 6 %I EDP-Sciences %U http://www.numdam.org/articles/10.1051/ro/2019112/ %R 10.1051/ro/2019112 %G en %F RO_2020__54_6_1757_0
Gökalp, Elvan. Robust capacity planning for accident and emergency services. RAIRO - Operations Research - Recherche Opérationnelle, Tome 54 (2020) no. 6, pp. 1757-1773. doi : 10.1051/ro/2019112. http://www.numdam.org/articles/10.1051/ro/2019112/
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