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Simulation modelling for contracting hospital emergency services at the regional level

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  • Mielczarek, Bożena

Abstract

Hospital emergency services are closely connected to demographic issues and population changes. The methodology presented here helps to assess the effects of the forecasted demand changes on the next-year emergency unit workloads. The objective of the study is to estimate the expected volume of emergency hospital services, as measured by the number and costs of medical procedures provided to patients, to be contracted by the Polish National Health Fund (NFZ) branch at the regional level to cover the forecasted demand. A discrete-event simulation model was developed to elaborate the credible forecasts of the function components, the fundamental elements of the contract values granted by the NFZ for emergency departments for the following year. Emergency department-level data were drawn from the NFZ regional branch registry to perform a statistical analysis of emergency services provided to patients in 17 admission units and emergency wards in 2010. The model results indicate that the predicted increase in two age groups, i.e., the youngest children and the older population, will have different effects on the number and value of hospital emergency services to be considered in the contracting policy. There is potential for a discrete-event simulation to support strategic health policy decision making at the regional level. The value of this approach lies in providing estimates for the what-if scenarios related to the prognosis of changing acute demand.

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  • Mielczarek, Bożena, 2014. "Simulation modelling for contracting hospital emergency services at the regional level," European Journal of Operational Research, Elsevier, vol. 235(1), pages 287-299.
  • Handle: RePEc:eee:ejores:v:235:y:2014:i:1:p:287-299
    DOI: 10.1016/j.ejor.2013.10.061
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    1. Boyle, Laura M. & Marshall, Adele H. & Mackay, Mark, 2022. "A framework for developing generalisable discrete event simulation models of hospital emergency departments," European Journal of Operational Research, Elsevier, vol. 302(1), pages 337-347.
    2. Niyirora, Jerome & Zhuang, Jun, 2017. "Fluid approximations and control of queues in emergency departments," European Journal of Operational Research, Elsevier, vol. 261(3), pages 1110-1124.
    3. Glasgow, Simon M. & Perkins, Zane B. & Tai, Nigel R.M. & Brohi, Karim & Vasilakis, Christos, 2018. "Development of a discrete event simulation model for evaluating strategies of red blood cell provision following mass casualty events," European Journal of Operational Research, Elsevier, vol. 270(1), pages 362-374.

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