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the hospital. It is a crucial function within an
organization based on process activities. Improving
patient flow is a way of improving health services.
The model herein developed could be used as a
decision support tool for a priori verifying the
effects of different bed management rules both by a
patient and hospital point of view.
Of course the model could include other patient
characteristics and patient flows also versus other
hospital facilities and can easily be adapted to
simulate other case studies, changing the system
constraints and the organizational models of the ED
and hospital wards.
Future work will be directed to perform an
extensive scenario analysis and compare the results
with a larger amount of real data and performance
indexes.
Moreover, future research are going to explore
the potentiality of applying the optimization module
integrated in the simulation software environment, in
order to determine the optimal decision pertaining
the number of beds to be assigned to each ward
group, able to optimize ad hoc chosen objective
functions, such as maximizing the bed utilization
rate, minimizing the number of postponed patients
or the overall misallocation index.
ACKNOWLEDGEMENTS
The authors acknowledge support from the Italian
Ministry of Education, University and Research
(MIUR), under the grand FIRB n. RBFR081KSB.
Data have been made available thanks to a
collaboration between ARS Liguria (Dr. Francesco
Quaglia and Domenico Gallo) and the Department
of Economics and Business, University of Genova.
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ADiscreteEventSimulationModeltoSupportBedManagement
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