David Fone, Sandra Hollinghurst, Mark Temple, Alison Round, Nathan Lester, Alison Weightman, Katherine Roberts, Edward Coyle, Gwyn Bevan, Stephen Palmer
{"title":"系统回顾计算机模拟建模在人口健康和卫生保健服务中的应用和价值。","authors":"David Fone, Sandra Hollinghurst, Mark Temple, Alison Round, Nathan Lester, Alison Weightman, Katherine Roberts, Edward Coyle, Gwyn Bevan, Stephen Palmer","doi":"10.1093/pubmed/fdg075","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The objective of the review was to evaluate the extent, quality and value of computer simulation modelling in population health and health care delivery.</p><p><strong>Methods: </strong>A narrative systematic review was carried out of world literature from 1980 to 1999, searching Medline, INSPEC, Embase, HealthSTAR, Science Citation Index, CINAHL, MathSci, INFORMS Online and SIGLE databases, and researchers in the field were contacted. Papers were included if they contained a computer simulation model of individuals in a stochastic system and the topic or setting related to population health or health service delivery.</p><p><strong>Results: </strong>A total of 182 papers met the inclusion criteria. Simulation modelling has been undertaken in a wide range of health care topic areas, including hospital scheduling and organization, communicable disease, screening, costs of illness and economic evaluation. However, the quality of published papers was variable and few reported on the outcomes of implementation of models, so that the value of modelling could not be assessed.</p><p><strong>Conclusion: </strong>Simulation modelling is a powerful method for modelling both small and large populations to inform policy makers in the provision of health care. It has been applied to a wide variety of health care problems. Although the number of modelling papers has grown substantially over recent years, further research is required to assess the value of modelling.</p>","PeriodicalId":77224,"journal":{"name":"Journal of public health medicine","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2003-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/pubmed/fdg075","citationCount":"565","resultStr":"{\"title\":\"Systematic review of the use and value of computer simulation modelling in population health and health care delivery.\",\"authors\":\"David Fone, Sandra Hollinghurst, Mark Temple, Alison Round, Nathan Lester, Alison Weightman, Katherine Roberts, Edward Coyle, Gwyn Bevan, Stephen Palmer\",\"doi\":\"10.1093/pubmed/fdg075\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>The objective of the review was to evaluate the extent, quality and value of computer simulation modelling in population health and health care delivery.</p><p><strong>Methods: </strong>A narrative systematic review was carried out of world literature from 1980 to 1999, searching Medline, INSPEC, Embase, HealthSTAR, Science Citation Index, CINAHL, MathSci, INFORMS Online and SIGLE databases, and researchers in the field were contacted. Papers were included if they contained a computer simulation model of individuals in a stochastic system and the topic or setting related to population health or health service delivery.</p><p><strong>Results: </strong>A total of 182 papers met the inclusion criteria. Simulation modelling has been undertaken in a wide range of health care topic areas, including hospital scheduling and organization, communicable disease, screening, costs of illness and economic evaluation. However, the quality of published papers was variable and few reported on the outcomes of implementation of models, so that the value of modelling could not be assessed.</p><p><strong>Conclusion: </strong>Simulation modelling is a powerful method for modelling both small and large populations to inform policy makers in the provision of health care. It has been applied to a wide variety of health care problems. Although the number of modelling papers has grown substantially over recent years, further research is required to assess the value of modelling.</p>\",\"PeriodicalId\":77224,\"journal\":{\"name\":\"Journal of public health medicine\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1093/pubmed/fdg075\",\"citationCount\":\"565\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of public health medicine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1093/pubmed/fdg075\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of public health medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/pubmed/fdg075","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Systematic review of the use and value of computer simulation modelling in population health and health care delivery.
Background: The objective of the review was to evaluate the extent, quality and value of computer simulation modelling in population health and health care delivery.
Methods: A narrative systematic review was carried out of world literature from 1980 to 1999, searching Medline, INSPEC, Embase, HealthSTAR, Science Citation Index, CINAHL, MathSci, INFORMS Online and SIGLE databases, and researchers in the field were contacted. Papers were included if they contained a computer simulation model of individuals in a stochastic system and the topic or setting related to population health or health service delivery.
Results: A total of 182 papers met the inclusion criteria. Simulation modelling has been undertaken in a wide range of health care topic areas, including hospital scheduling and organization, communicable disease, screening, costs of illness and economic evaluation. However, the quality of published papers was variable and few reported on the outcomes of implementation of models, so that the value of modelling could not be assessed.
Conclusion: Simulation modelling is a powerful method for modelling both small and large populations to inform policy makers in the provision of health care. It has been applied to a wide variety of health care problems. Although the number of modelling papers has grown substantially over recent years, further research is required to assess the value of modelling.
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