{"title":"Modeling healthcare demand using a hybrid simulation approach","authors":"B. Mielczarek, J. Zabawa","doi":"10.1109/WSC.2016.7822204","DOIUrl":null,"url":null,"abstract":"This paper describes a hybrid simulation model that uses a system dynamics and discrete event simulation to study the influence of long-term population changes on the demand for healthcare services. A dynamic simulation model implements an aging chain approach to forecast the number of individuals who belong to their respective age-sex cohorts. The demographic parameters that were calculated from a Central Statistical Office Local Data Base were applied to the Wroclaw Region population from 2002 to 2014, and the basic scenario for the projected trends was adopted for a time horizon from 2015 to 2035. The historical data on hospital admissions were obtained from the Regional Health Fund. A discrete event model generates batches of patients with cardiac diseases and modifies the demand according to the demographic changes that were forecasted by a population model. The results offer a well-defined starting point for future research in the health policy field.","PeriodicalId":367269,"journal":{"name":"2016 Winter Simulation Conference (WSC)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Winter Simulation Conference (WSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WSC.2016.7822204","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 18
Abstract
This paper describes a hybrid simulation model that uses a system dynamics and discrete event simulation to study the influence of long-term population changes on the demand for healthcare services. A dynamic simulation model implements an aging chain approach to forecast the number of individuals who belong to their respective age-sex cohorts. The demographic parameters that were calculated from a Central Statistical Office Local Data Base were applied to the Wroclaw Region population from 2002 to 2014, and the basic scenario for the projected trends was adopted for a time horizon from 2015 to 2035. The historical data on hospital admissions were obtained from the Regional Health Fund. A discrete event model generates batches of patients with cardiac diseases and modifies the demand according to the demographic changes that were forecasted by a population model. The results offer a well-defined starting point for future research in the health policy field.