ORAHS2024
Abstract Submission

284. A hybrid simulation and optimization approach to manage Emergency Department overcrowding and patient boarding

Contributed abstract in session MD-5: Emergency Department /1, stream Regular talks.

Monday, 13:50-15:00
Room: Room S6

Authors (first author is the speaker)

1. Elena Tanfani
Department of Economics and Business Studies, University of Genova
2. Paolo Landa
Département d’opérations et systèmes de décision, Université Laval
3. Luca Murazzano
Département d'Opérations et systèmes de décision, Université Laval
4. Marina Resta
Department of Business Studies and Economics, University of Genova
5. Angela Testi
Department of Economics and Quantitative Methods (DIEM), University of Genova

Abstract

Overcrowding in the Emergency Department (ED) and long waiting lists for
elective surgeries are the main areas of unmet need in public health systems
and an evidence of poor management. Patient boarding, i.e. the practice
of holding patients in the ED due to a lack of inpatient beds, has been proved to be a significant determinant of ED overcrowding. Bed management enables an improved organization of the flow of patients, thus reducing patient boarding. A hybrid simulation approach is proposed to model the interrelated dynamics of emergent and elective patient flows and evaluate the impact of alternative bed management strategies. Further, an optimization model is developed to determine the best set of decision parameters used by the bed manager to facilitate the admission of emergent patients in hospital wards. The hybrid simulation and optimization approach is applied to a real case study of a medium sized public hospital. An extensive scenarios analysis is presented to compare alternative strategies using a set of indicators able to evaluate the performance from different stakeholder viewpoints. The results highlight that improving the bed management strategy can reduce the number of boarding patients and the boarding waiting time without increasing the number of hospital beds and not affecting the elective patient flows.

Keywords

Status: accepted

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