1. Dynamic scheduling of patients in emergency departments
- Author
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Thiago Alves de Queiroz, Manuel Iori, Arthur Kramer, Yong-Hong Kuo, Università degli Studi di Modena e Reggio Emilia = University of Modena and Reggio Emilia (UNIMORE), École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT), Institut Henri Fayol (FAYOL-ENSMSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Département Génie mathématique et industriel (FAYOL-ENSMSE), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Institut Henri Fayol, Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), Universidade Federal do Rio Grande do Norte [Natal] (UFRN), and The University of Hong Kong (HKU)
- Subjects
[SDV.EE.SANT]Life Sciences [q-bio]/Ecology, environment/Health ,Scheduling ,Healthcare ,Emergency department ,Variable neighborhood search ,Weighted tardiness ,Information Systems and Management ,General Computer Science ,Management Science and Operations Research ,Industrial and Manufacturing Engineering ,[SPI]Engineering Sciences [physics] ,Modeling and Simulation ,[SPI.GPROC]Engineering Sciences [physics]/Chemical and Process Engineering - Abstract
International audience; Emergency department overcrowding is a global issue that poses a great threat to patient health and safety. The timeliness of medical services provided to patients is crucial to emergency departments as it directly impacts the mortality and morbidity of urgent patients. However, critical resources (e.g., doctors and nurses) are typically constrained due to the limited financial budget. Thus, hospital administrators may need to investigate solutions to improve the efficiency of the emergency department. In this work, we study the dynamic problem of scheduling patients to doctors, aiming at minimizing the total weighted tardiness. We propose a simple reoptimization heuristic based on multiple queues of patients in accordance with their urgency levels, and then combine it with an effective variable neighborhood search. We also propose a scenario-based planning approach that uses sampled scenarios to anticipate future events and the variable neighborhood search to schedule patients. The methods are adapted to handle a problem variant where information on arrival time and urgency level of some patients can be received in advance by the emergency department. With a comprehensive computational study on two sets of realistic instances from Hong Kong SAR of China and Italy, we validate the performance of the proposed methods, evaluating the benefits of having more doctors and receiving early information.
- Published
- 2023