|
|
Digital
Library of the European Council for Modelling
and Simulation |
|
Title: |
Healthcare Demand
Simulation Model |
|
Authors: |
Bozena
Mielczarek, Jacek Zabawa |
|
Published in:
|
(2018). ECMS 2018
Proceedings Edited by: Lars Nolle, Alexandra Burger, Christoph Tholen, Jens
Werner, Jens Wellhausen European Council for Modeling and Simulation. doi: 10.7148/2018-0005 ISSN:
2522-2422 (ONLINE) ISSN:
2522-2414 (PRINT) ISSN:
2522-2430 (CD-ROM) 32nd European Conference on Modelling and
Simulation, Wilhelmshaven, Germany, May 22nd
– May 265h, 2018 |
|
Citation
format: |
Bozena
Mielczarek, Jacek Zabawa (2018). Healthcare Demand Simulation Model, ECMS 2018 Proceedings Edited by: Lars Nolle,
Alexandra Burger, Christoph Tholen, Jens Werner, Jens Wellhausen European
Council for Modeling and Simulation. doi:
10.7148/2018-0053 |
|
DOI: |
https://doi.org/10.7148/2018-0053 |
|
Abstract: |
The aim of this paper is to study the
influence of demography on the demand for healthcare services. The research
is carried on in Wrocław Region (WR), Poland. We apply the system dynamic
method and aging chain approach to simulate the number of individuals
belonging to the respective age-gender cohorts. We consider such demographic
descriptive parameters as birth and death rates, life expectancy and
migration factors. Then, the discrete event simulation model is used to
predict the annual demand for emergency hospital care, as registered at the
hospitals located in the WR. The historical data on hospital admissions are
drawn from National Health Fund regional branch. The input parameters
describing the population are calculated based on historical and forecasted
rates of primary demographic parameters, retrieved from various databases and
official projections published by the Polish Central Statistical Office
(CSO). The simulation predicts
that between 2011 and 2020 the WR population will grow by 4.5% and the
population aged 60+ will increase by 16.2%. Over the same period the number
of arriving patients, compared to 2011, will be higher by 1.52%. Furthermore,
the noticeable differences will be observed in the number of arrivals between
particular hospitals. |
|
Full
text: |
|
