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Konferenzpaper | Open Access

Resource Planning for Hospitals Under Special Consideration of the COVID-19 Pandemic : (Optimization and Sensitivity Analysis)

Autor*innen
Bartz-Beielstein, Thomas ; Dröscher, Marcel ; Gür, Alpar ; Hinterleitner, Alexander ; Mersmann, Olaf ; Peeva, Dessislava Todorova ; Reese, Lennard ; Rehbach, Nicolas Alexander ; Rehbach, Frederik ; Sen, Amrita ; Subbotin, Aleksandr ; Zaefferer, Martin
DOI
10.1145/3449726.3459473
ISBN-13
#defaultkonferenzband 9781450383509

Weitere Details

Sprache
englisch
Darstellungsform
Text
Seitenbereich
293 - 294
Schlüsselwörter
COVID-19 , Capacity Planning , Hospital Resource Planning , Optimization-via-Simulation , Prediction Tool , Sensitivity Analysis , Surrogate-Model-Based Optimization , capacity planning , hospital resource planning , optimization , sensitivity analysis , simulation , surrogate models

Pandemics pose a serious challenge to health-care institutions. To support the resource planning of health authorities from the Cologne region, BaBSim.Hospital, a tool for capacity planning based on discrete event simulation, was created. The predictive quality of the simulation is determined by 29 parameters with reasonable default values obtained in discussions with medical professionals. We aim to investigate and optimize these parameters to improve BaBSim.Hospital using a surrogate-based optimization approach and an in-depth sensitivity analysis.

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