{"title":"基于人员流动和卫生资源,在地理信息系统中自动划定合理服务区和卫生专业人员短缺区","authors":"Yunlei Liang, Song Gao","doi":"10.1111/tgis.13207","DOIUrl":null,"url":null,"abstract":"How people travel to receive health services is essential for understanding healthcare shortages. The rational service areas (RSAs) are defined to represent local healthcare markets and used as the basic units to evaluate whether people have access to health resources. Therefore, finding an appropriate way to develop RSAs is important for understanding the utilization of health resources and supporting accurate resource allocation to the health professional shortage areas (HPSAs). Existing RSAs are usually developed based on the local knowledge of public health needs and are created through time‐intensive manual work by health service officials. In this research, a travel data‐driven and spatially constrained community detection method based on human mobility flow is proposed to automate the process of establishing the statewide RSAs and further identifying HPSAs based on healthcare criteria in a geographic information system (GIS) software. The proposed method considers the difference between rural and urban populations by assigning different parameters and delineates RSAs with the goal of reducing health resource inequalities faced by rural areas. Using the data in the State of Wisconsin, our experiment shows that the proposed RSA delineation method outperforms other baselines including the traditional Dartmouth method in the aspects of RSA compactness, region size balances, and health shortage scores. Furthermore, the whole process of delineating RSAs and identifying HPSAs is automated using Python toolboxes in ArcGIS to support future analyses and practices in a timely and repeatable manner.","PeriodicalId":47842,"journal":{"name":"Transactions in GIS","volume":"109 1","pages":""},"PeriodicalIF":2.1000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Automatic delineation of rational service areas and health professional shortage areas in GIS based on human movements and health resources\",\"authors\":\"Yunlei Liang, Song Gao\",\"doi\":\"10.1111/tgis.13207\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"How people travel to receive health services is essential for understanding healthcare shortages. The rational service areas (RSAs) are defined to represent local healthcare markets and used as the basic units to evaluate whether people have access to health resources. Therefore, finding an appropriate way to develop RSAs is important for understanding the utilization of health resources and supporting accurate resource allocation to the health professional shortage areas (HPSAs). Existing RSAs are usually developed based on the local knowledge of public health needs and are created through time‐intensive manual work by health service officials. In this research, a travel data‐driven and spatially constrained community detection method based on human mobility flow is proposed to automate the process of establishing the statewide RSAs and further identifying HPSAs based on healthcare criteria in a geographic information system (GIS) software. The proposed method considers the difference between rural and urban populations by assigning different parameters and delineates RSAs with the goal of reducing health resource inequalities faced by rural areas. Using the data in the State of Wisconsin, our experiment shows that the proposed RSA delineation method outperforms other baselines including the traditional Dartmouth method in the aspects of RSA compactness, region size balances, and health shortage scores. Furthermore, the whole process of delineating RSAs and identifying HPSAs is automated using Python toolboxes in ArcGIS to support future analyses and practices in a timely and repeatable manner.\",\"PeriodicalId\":47842,\"journal\":{\"name\":\"Transactions in GIS\",\"volume\":\"109 1\",\"pages\":\"\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2024-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transactions in GIS\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1111/tgis.13207\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"GEOGRAPHY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transactions in GIS","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1111/tgis.13207","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GEOGRAPHY","Score":null,"Total":0}
Automatic delineation of rational service areas and health professional shortage areas in GIS based on human movements and health resources
How people travel to receive health services is essential for understanding healthcare shortages. The rational service areas (RSAs) are defined to represent local healthcare markets and used as the basic units to evaluate whether people have access to health resources. Therefore, finding an appropriate way to develop RSAs is important for understanding the utilization of health resources and supporting accurate resource allocation to the health professional shortage areas (HPSAs). Existing RSAs are usually developed based on the local knowledge of public health needs and are created through time‐intensive manual work by health service officials. In this research, a travel data‐driven and spatially constrained community detection method based on human mobility flow is proposed to automate the process of establishing the statewide RSAs and further identifying HPSAs based on healthcare criteria in a geographic information system (GIS) software. The proposed method considers the difference between rural and urban populations by assigning different parameters and delineates RSAs with the goal of reducing health resource inequalities faced by rural areas. Using the data in the State of Wisconsin, our experiment shows that the proposed RSA delineation method outperforms other baselines including the traditional Dartmouth method in the aspects of RSA compactness, region size balances, and health shortage scores. Furthermore, the whole process of delineating RSAs and identifying HPSAs is automated using Python toolboxes in ArcGIS to support future analyses and practices in a timely and repeatable manner.
期刊介绍:
Transactions in GIS is an international journal which provides a forum for high quality, original research articles, review articles, short notes and book reviews that focus on: - practical and theoretical issues influencing the development of GIS - the collection, analysis, modelling, interpretation and display of spatial data within GIS - the connections between GIS and related technologies - new GIS applications which help to solve problems affecting the natural or built environments, or business