Timo Latruwe , Marlies Van der Wee , Pieter Vanleenhove , Joke Devriese , Sofie Verbrugge , Didier Colle
{"title":"医院床位容量战略规划的长期预测与仿真模型","authors":"Timo Latruwe , Marlies Van der Wee , Pieter Vanleenhove , Joke Devriese , Sofie Verbrugge , Didier Colle","doi":"10.1016/j.orhc.2022.100375","DOIUrl":null,"url":null,"abstract":"<div><p>Growing healthcare needs leverage the potential savings of using resources efficiently. To that end, ProMoBed is a comprehensive model that supports strategic planning of bed capacity in inpatient hospitals. The model consists of an extrapolation and simulation component, the former supplying input for the latter. The extrapolation model forecasts admission rates and the average Length of Stay for pathology groups, and corrects for demographic changes. Subsequently, the simulation model emulates the demand for bed capacity, and makes service-level based bed capacity suggestions. Additionally, the model uses the Shapley value principle to disaggregate the effects on demand for inpatient days due to different causes. Results from the extrapolation model are applied to regions in Belgium, showing expected divergence in inpatient day demand evolution.</p></div>","PeriodicalId":46320,"journal":{"name":"Operations Research for Health Care","volume":"36 ","pages":"Article 100375"},"PeriodicalIF":1.5000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"A long-term forecasting and simulation model for strategic planning of hospital bed capacity\",\"authors\":\"Timo Latruwe , Marlies Van der Wee , Pieter Vanleenhove , Joke Devriese , Sofie Verbrugge , Didier Colle\",\"doi\":\"10.1016/j.orhc.2022.100375\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Growing healthcare needs leverage the potential savings of using resources efficiently. To that end, ProMoBed is a comprehensive model that supports strategic planning of bed capacity in inpatient hospitals. The model consists of an extrapolation and simulation component, the former supplying input for the latter. The extrapolation model forecasts admission rates and the average Length of Stay for pathology groups, and corrects for demographic changes. Subsequently, the simulation model emulates the demand for bed capacity, and makes service-level based bed capacity suggestions. Additionally, the model uses the Shapley value principle to disaggregate the effects on demand for inpatient days due to different causes. Results from the extrapolation model are applied to regions in Belgium, showing expected divergence in inpatient day demand evolution.</p></div>\",\"PeriodicalId\":46320,\"journal\":{\"name\":\"Operations Research for Health Care\",\"volume\":\"36 \",\"pages\":\"Article 100375\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2023-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Operations Research for Health Care\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2211692322000364\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"HEALTH CARE SCIENCES & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Operations Research for Health Care","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2211692322000364","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
A long-term forecasting and simulation model for strategic planning of hospital bed capacity
Growing healthcare needs leverage the potential savings of using resources efficiently. To that end, ProMoBed is a comprehensive model that supports strategic planning of bed capacity in inpatient hospitals. The model consists of an extrapolation and simulation component, the former supplying input for the latter. The extrapolation model forecasts admission rates and the average Length of Stay for pathology groups, and corrects for demographic changes. Subsequently, the simulation model emulates the demand for bed capacity, and makes service-level based bed capacity suggestions. Additionally, the model uses the Shapley value principle to disaggregate the effects on demand for inpatient days due to different causes. Results from the extrapolation model are applied to regions in Belgium, showing expected divergence in inpatient day demand evolution.