{"title":"人口老龄化趋势下医院床位配置优化模型","authors":"Yuze Gu, Qi Luo","doi":"10.2991/aebmr.k.191217.053","DOIUrl":null,"url":null,"abstract":"Currently, there is an increasing trend for the demand of hospital beds. Due to the increasing cost of healthcare services and the aging of population, the hospitals need to pay more attention to integration of the resource management and hospital bed allocation. In this study, Gini coefficients and Lorenz Curve are used to predict the aging of population, which helps to build up the supply and demand curve of the hospital beds in the long time run. The Erlang Loss Formula is used to analyze the patient flow in the hospitals of the region with the different situations of area and the need for medical care. The Logistic model is used to predict the future outcome of allocation of hospital beds. In the next step, the optimization model is proceeded to get the optimal arrangement of hospital bed allocation.","PeriodicalId":369606,"journal":{"name":"European journal of economics and management sciences","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"OPTIMIZATION MODEL FOR ALLOCATION OF HOSPITAL BEDS UNDER THE TREND OF AGING POPULATION\",\"authors\":\"Yuze Gu, Qi Luo\",\"doi\":\"10.2991/aebmr.k.191217.053\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Currently, there is an increasing trend for the demand of hospital beds. Due to the increasing cost of healthcare services and the aging of population, the hospitals need to pay more attention to integration of the resource management and hospital bed allocation. In this study, Gini coefficients and Lorenz Curve are used to predict the aging of population, which helps to build up the supply and demand curve of the hospital beds in the long time run. The Erlang Loss Formula is used to analyze the patient flow in the hospitals of the region with the different situations of area and the need for medical care. The Logistic model is used to predict the future outcome of allocation of hospital beds. In the next step, the optimization model is proceeded to get the optimal arrangement of hospital bed allocation.\",\"PeriodicalId\":369606,\"journal\":{\"name\":\"European journal of economics and management sciences\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-12-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European journal of economics and management sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2991/aebmr.k.191217.053\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European journal of economics and management sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2991/aebmr.k.191217.053","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
OPTIMIZATION MODEL FOR ALLOCATION OF HOSPITAL BEDS UNDER THE TREND OF AGING POPULATION
Currently, there is an increasing trend for the demand of hospital beds. Due to the increasing cost of healthcare services and the aging of population, the hospitals need to pay more attention to integration of the resource management and hospital bed allocation. In this study, Gini coefficients and Lorenz Curve are used to predict the aging of population, which helps to build up the supply and demand curve of the hospital beds in the long time run. The Erlang Loss Formula is used to analyze the patient flow in the hospitals of the region with the different situations of area and the need for medical care. The Logistic model is used to predict the future outcome of allocation of hospital beds. In the next step, the optimization model is proceeded to get the optimal arrangement of hospital bed allocation.