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Global health radiology planning using Geographic Information Systems to identify populations with decreased access to care.
Sachdev, Rahul; Sivanushanthan, Shan; Ring, Natalie; Lugossy, Anne-Marie; England, Ryan W.
Afiliação
  • Sachdev R; The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
  • Sivanushanthan S; Georgetown University School of Medicine, Washington, D.C., USA.
  • Ring N; Russel H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins Hospital, Baltimore, Maryland, USA.
  • Lugossy AM; RAD-AID International, Chevy Chase, Maryland, USA.
  • England RW; Russel H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins Hospital, Baltimore, Maryland, USA.
J Glob Health ; 11: 04073, 2021.
Article em En | MEDLINE | ID: mdl-34956638
BACKGROUND: Communities throughout northern Canada face significant health care disparities including decreased access to radiology. A medical hybrid airship is under development which aims to serve remote populations, requiring strategic outreach planning. This study aims to use geographic information systems (GIS) to identify (1) high risk and medically underserved patient populations in northern Canada and (2) potential landing sites for a medical airship to allow for mobile delivery of radiology services. METHODS: The northern region of Canada extending from the Rocky Mountains to the Atlantic Ocean was analyzed using multi-variable, multi-weighted GIS modeling. Based on population distance from hospitals (50% weight), health centers (eg, clinic; 30% weight), remote communities (not connected to electric grid; 10% weight), and roads (10% weight), individuals were stratified into one of five health care accessibility index (HAI) categories (ranging from very low to very high severity). HAI (80% weight) was combined with population density (20%) to create a health care access severity index (HASI). Topographic and land cover data were used to identify suitable landing sites for the medical airship. A coordinate data set was made from georeferenced health care facilities, and infrastructure data was obtained from OpenStreetMap. RESULTS: GIS analyzed 815 772 Canadians. Of this population, 522 094 (64%) were found to live ≥60 km from a hospital, 326 309 (40%) were ≥45 km from the nearest health center, 65 262 (8%) were within 30 km of a remote community, and 57 104 (7%) lived ≥1 km from the nearest road. Combined, the HASI identified 44% of the population as having decreased access to care (high or very high severity). Lastly, 27.5% of land analyzed was found to be suitable for airship operations. CONCLUSIONS: GIS identified medically underserved populations in northern Canada who may benefit from mobile radiology services. These techniques may help to guide future global health outreach efforts.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Radiologia / Sistemas de Informação Geográfica Tipo de estudo: Prognostic_studies Limite: Humans País/Região como assunto: America do norte Idioma: En Revista: J Glob Health Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Radiologia / Sistemas de Informação Geográfica Tipo de estudo: Prognostic_studies Limite: Humans País/Região como assunto: America do norte Idioma: En Revista: J Glob Health Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos