Spatial and temporal variations of spatial population accessibility to public hospitals: a case study of rural-urban comparison
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Song, Yongze | - |
dc.contributor.author | Tan, Yi | - |
dc.contributor.author | Song, Yimeng | - |
dc.contributor.author | Wu, Peng | - |
dc.contributor.author | Cheng, Jack C. P. | - |
dc.contributor.author | Kim, Mi Jeong | - |
dc.contributor.author | Wang, Xiangyu | - |
dc.date.accessioned | 2022-07-11T15:46:10Z | - |
dc.date.available | 2022-07-11T15:46:10Z | - |
dc.date.created | 2021-05-14 | - |
dc.date.issued | 2018-07 | - |
dc.identifier.issn | 1548-1603 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/149679 | - |
dc.description.abstract | Quantification and assessment of nationwide population access to health-care services is a critical undertaking for improving population health and optimizing the performance of national health systems. Rural–urban unbalance of population access to health-care services is widely involved in most of the nations. This unbalance is also potentially affected by varied weather and road conditions. This study investigates the rural and urban performances of public health system by quantifying the spatiotemporal variations of accessibility and assessing the impacts of potential factors. Australian health-care system is used as a case study for the rural–urban comparison of population accessibility. A nationwide travel time-based modified kernel density two-step floating catchment area (MKD2SFCA) model is utilized to compute accessibility of travel time within 30, 60, 120, and 240 min to all public hospitals, hospitals that provide emergency care, and hospitals that provide surgery service, respectively. Results show that accessibility is varied both temporally and spatially, and the rural–urban unbalance is distinct for different types of hospitals. In Australia, from the perspective of spatial distributions of health-care resources, spatial accessibility to all public hospitals in remote and very remote areas is not lower (and may even higher) than that in major cities, but the accessibility to hospitals that provide emergency and surgery services is much higher in major cities than other areas. From the angle of temporal variation of accessibility to public hospitals, reduction of traffic speed is 1.00–3.57% due to precipitation and heavy rain, but it leads to 18–23% and 31–50% of reduction of accessibility in hot-spot and cold-spot regions, respectively, and the impact is severe in New South Wales, Queensland, and Northern Territory during wet seasons. Spatiotemporal analysis for the variations of accessibility can provide quantitative and accurate evidence for geographically local and dynamic strategies of allocation decision-making of medical resources and optimizing health-care systems both locally and nationally. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | V.H. Winston and Sons, Inc. | - |
dc.title | Spatial and temporal variations of spatial population accessibility to public hospitals: a case study of rural-urban comparison | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kim, Mi Jeong | - |
dc.identifier.doi | 10.1080/15481603.2018.1446713 | - |
dc.identifier.scopusid | 2-s2.0-85044022961 | - |
dc.identifier.wosid | 000439884200005 | - |
dc.identifier.bibliographicCitation | GIScience and Remote Sensing, v.55, no.5, pp.718 - 744 | - |
dc.relation.isPartOf | GIScience and Remote Sensing | - |
dc.citation.title | GIScience and Remote Sensing | - |
dc.citation.volume | 55 | - |
dc.citation.number | 5 | - |
dc.citation.startPage | 718 | - |
dc.citation.endPage | 744 | - |
dc.type.rims | ART | - |
dc.type.docType | 정기학술지(Article(Perspective Article포함)) | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | Y | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Physical Geography | - |
dc.relation.journalResearchArea | Remote Sensing | - |
dc.relation.journalWebOfScienceCategory | Geography, Physical | - |
dc.relation.journalWebOfScienceCategory | Remote Sensing | - |
dc.subject.keywordPlus | CATCHMENT-AREA METHOD | - |
dc.subject.keywordPlus | PRIMARY-HEALTH-CARE | - |
dc.subject.keywordPlus | GEOGRAPHICAL ACCESSIBILITY | - |
dc.subject.keywordPlus | ACCESS | - |
dc.subject.keywordPlus | SYSTEMS | - |
dc.subject.keywordPlus | TIME | - |
dc.subject.keywordAuthor | accessibility | - |
dc.subject.keywordAuthor | spatial and temporal variations | - |
dc.subject.keywordAuthor | public hospitals | - |
dc.subject.keywordAuthor | emergency and surgery service | - |
dc.subject.keywordAuthor | MKD2SFCA model | - |
dc.identifier.url | https://www.tandfonline.com/doi/full/10.1080/15481603.2018.1446713 | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
222, Wangsimni-ro, Seongdong-gu, Seoul, 04763, Korea+82-2-2220-1365
COPYRIGHT © 2021 HANYANG UNIVERSITY.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.