{"title":"Modeling Spatial Accessibility of Healthcare Services for the Elderly Population with a SAM-G2SFCA Method: A Resource-Sharing Perspective","authors":"Zheng Gong, Chengzhi Zhang, Zhihui Song, Keying Peng, Feng Gao, Shaoli Li, Shaoying Li","doi":"10.1007/s12061-025-09677-z","DOIUrl":null,"url":null,"abstract":"<div><p>Accessibility of healthcare services is a paramount determinant of elderly health outcomes. However, existing research often neglects the effects of resource-sharing pressures among different demographic groups for healthcare resources when measuring the accessibility for elderly population. To bridge this gap, this study developed a Supply Allocation Model (SAM) that considers the interactions between the elderly and non-elderly populations, as well as the distribution of healthcare resources. The model was subsequently integrated with the G2SFCA method, utilizing demographic, mobile phone, and point of interest (POI) datasets to assess the spatial accessibility of healthcare services for the elderly population in Guangzhou, China. The model’s accuracy and reliability were tested through calibration and validation processes, utilizing real-world healthcare treatment datasets. The effectiveness of the SAM was measured through the computation of the healthcare accessibility index and the Gini coefficient, utilizing both the SAM-G2SFCA and G2SFCA models. The results show that the SAM achieves the highest prediction accuracy at a 15-minute threshold. As the time threshold decreases, the role of supply factors in predicting the proportion of healthcare utilization strengthens. Moreover, the SAM-G2SFCA leads to a reduction in the equity of accessibility across all time thresholds when compared to the G2SFCA method, particularly in peripheral urban areas where elderly populations face greater resource-sharing pressures and healthcare accessibility is often overestimated. These findings provide valuable insights for policy formulation and theoretical advancement, informing the design of more equitable and efficient healthcare resource allocation strategies.</p></div>","PeriodicalId":46392,"journal":{"name":"Applied Spatial Analysis and Policy","volume":"18 2","pages":""},"PeriodicalIF":1.9000,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Spatial Analysis and Policy","FirstCategoryId":"90","ListUrlMain":"https://link.springer.com/article/10.1007/s12061-025-09677-z","RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENVIRONMENTAL STUDIES","Score":null,"Total":0}
引用次数: 0
Abstract
Accessibility of healthcare services is a paramount determinant of elderly health outcomes. However, existing research often neglects the effects of resource-sharing pressures among different demographic groups for healthcare resources when measuring the accessibility for elderly population. To bridge this gap, this study developed a Supply Allocation Model (SAM) that considers the interactions between the elderly and non-elderly populations, as well as the distribution of healthcare resources. The model was subsequently integrated with the G2SFCA method, utilizing demographic, mobile phone, and point of interest (POI) datasets to assess the spatial accessibility of healthcare services for the elderly population in Guangzhou, China. The model’s accuracy and reliability were tested through calibration and validation processes, utilizing real-world healthcare treatment datasets. The effectiveness of the SAM was measured through the computation of the healthcare accessibility index and the Gini coefficient, utilizing both the SAM-G2SFCA and G2SFCA models. The results show that the SAM achieves the highest prediction accuracy at a 15-minute threshold. As the time threshold decreases, the role of supply factors in predicting the proportion of healthcare utilization strengthens. Moreover, the SAM-G2SFCA leads to a reduction in the equity of accessibility across all time thresholds when compared to the G2SFCA method, particularly in peripheral urban areas where elderly populations face greater resource-sharing pressures and healthcare accessibility is often overestimated. These findings provide valuable insights for policy formulation and theoretical advancement, informing the design of more equitable and efficient healthcare resource allocation strategies.
期刊介绍：
Description
The journal has an applied focus: it actively promotes the importance of geographical research in real world settings
It is policy-relevant: it seeks both a readership and contributions from practitioners as well as academics
The substantive foundation is spatial analysis: the use of quantitative techniques to identify patterns and processes within geographic environments
The combination of these points, which are fully reflected in the naming of the journal, establishes a unique position in the marketplace.
RationaleA geographical perspective has always been crucial to the understanding of the social and physical organisation of the world around us. The techniques of spatial analysis provide a powerful means for the assembly and interpretation of evidence, and thus to address critical questions about issues such as crime and deprivation, immigration and demographic restructuring, retailing activity and employment change, resource management and environmental improvement. Many of these issues are equally important to academic research as they are to policy makers and Applied Spatial Analysis and Policy aims to close the gap between these two perspectives by providing a forum for discussion of applied research in a range of different contexts
Topical and interdisciplinaryIncreasingly government organisations, administrative agencies and private businesses are requiring research to support their ‘evidence-based’ strategies or policies. Geographical location is critical in much of this work which extends across a wide range of disciplines including demography, actuarial sciences, statistics, public sector planning, business planning, economics, epidemiology, sociology, social policy, health research, environmental management.
FocusApplied Spatial Analysis and Policy will draw on applied research from diverse problem domains, such as transport, policing, education, health, environment and leisure, in different international contexts. The journal will therefore provide insights into the variations in phenomena that exist across space, it will provide evidence for comparative policy analysis between domains and between locations, and stimulate ideas about the translation of spatial analysis methods and techniques across varied policy contexts. It is essential to know how to measure, monitor and understand spatial distributions, many of which have implications for those with responsibility to plan and enhance the society and the environment in which we all exist.
Readership and Editorial BoardAs a journal focused on applications of methods of spatial analysis, Applied Spatial Analysis and Policy will be of interest to scholars and students in a wide range of academic fields, to practitioners in government and administrative agencies and to consultants in private sector organisations. The Editorial Board reflects the international and multidisciplinary nature of the journal.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
