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Global health radiology planning using Geographic Information Systems to identify populations with decreased access to care

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 informat...

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Autores principales: Sachdev, Rahul, Sivanushanthan, Shan, Ring, Natalie, Lugossy, Anne-Marie, England, Ryan W
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Society of Global Health 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8684794/
https://www.ncbi.nlm.nih.gov/pubmed/34956638
http://dx.doi.org/10.7189/jogh.11.04073
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author Sachdev, Rahul
Sivanushanthan, Shan
Ring, Natalie
Lugossy, Anne-Marie
England, Ryan W
author_facet Sachdev, Rahul
Sivanushanthan, Shan
Ring, Natalie
Lugossy, Anne-Marie
England, Ryan W
author_sort Sachdev, Rahul
collection PubMed
description 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.
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spelling pubmed-86847942021-12-23 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 J Glob Health Articles 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. International Society of Global Health 2021-12-11 /pmc/articles/PMC8684794/ /pubmed/34956638 http://dx.doi.org/10.7189/jogh.11.04073 Text en Copyright © 2021 by the Journal of Global Health. All rights reserved. https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License.
spellingShingle Articles
Sachdev, Rahul
Sivanushanthan, Shan
Ring, Natalie
Lugossy, Anne-Marie
England, Ryan W
Global health radiology planning using Geographic Information Systems to identify populations with decreased access to care
title Global health radiology planning using Geographic Information Systems to identify populations with decreased access to care
title_full Global health radiology planning using Geographic Information Systems to identify populations with decreased access to care
title_fullStr Global health radiology planning using Geographic Information Systems to identify populations with decreased access to care
title_full_unstemmed Global health radiology planning using Geographic Information Systems to identify populations with decreased access to care
title_short Global health radiology planning using Geographic Information Systems to identify populations with decreased access to care
title_sort global health radiology planning using geographic information systems to identify populations with decreased access to care
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8684794/
https://www.ncbi.nlm.nih.gov/pubmed/34956638
http://dx.doi.org/10.7189/jogh.11.04073
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