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Quantifying the Error Associated with Alternative GIS-based Techniques to Measure Access to Health Care Services

The aim of this study was to quantify the error associated with different accessibility methods commonly used by public health researchers. Network distances were calculated from each household to the nearest GP our study area in the UK. Household level network distances were assigned as the gold st...

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Detalles Bibliográficos
Autores principales: Mizen, Amy, Fry, Richard, Grinnell, Daniel, Rodgers, Sarah E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AIMS Press 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5690440/
https://www.ncbi.nlm.nih.gov/pubmed/29546134
http://dx.doi.org/10.3934/publichealth.2015.4.746
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author Mizen, Amy
Fry, Richard
Grinnell, Daniel
Rodgers, Sarah E.
author_facet Mizen, Amy
Fry, Richard
Grinnell, Daniel
Rodgers, Sarah E.
author_sort Mizen, Amy
collection PubMed
description The aim of this study was to quantify the error associated with different accessibility methods commonly used by public health researchers. Network distances were calculated from each household to the nearest GP our study area in the UK. Household level network distances were assigned as the gold standard and compared to alternate widely used accessibility methods. Four spatial aggregation units, two centroid types and two distance calculation methods represent commonly used accessibility calculation methods. Spearman's rank coefficients were calculated to show the extent which distance measurements were correlated with the gold standard. We assessed the proportion of households that were incorrectly assigned to GP for each method. The distance method, level of spatial aggregation and centroid type were compared between urban and rural regions. Urban distances were less varied from the gold standard, with smaller errors, compared to rural regions. For urban regions, Euclidean distances are significantly related to network distances. Network distances assigned a larger proportion of households to the correct GP compared to Euclidean distances, for both urban and rural morphologies. Our results, stratified by urban and rural populations, explain why contradicting results have been reported in the literature. The results we present are intended to be used aide-memoire by public health researchers using geographical aggregated data in accessibility research.
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spelling pubmed-56904402018-03-15 Quantifying the Error Associated with Alternative GIS-based Techniques to Measure Access to Health Care Services Mizen, Amy Fry, Richard Grinnell, Daniel Rodgers, Sarah E. AIMS Public Health Research Article The aim of this study was to quantify the error associated with different accessibility methods commonly used by public health researchers. Network distances were calculated from each household to the nearest GP our study area in the UK. Household level network distances were assigned as the gold standard and compared to alternate widely used accessibility methods. Four spatial aggregation units, two centroid types and two distance calculation methods represent commonly used accessibility calculation methods. Spearman's rank coefficients were calculated to show the extent which distance measurements were correlated with the gold standard. We assessed the proportion of households that were incorrectly assigned to GP for each method. The distance method, level of spatial aggregation and centroid type were compared between urban and rural regions. Urban distances were less varied from the gold standard, with smaller errors, compared to rural regions. For urban regions, Euclidean distances are significantly related to network distances. Network distances assigned a larger proportion of households to the correct GP compared to Euclidean distances, for both urban and rural morphologies. Our results, stratified by urban and rural populations, explain why contradicting results have been reported in the literature. The results we present are intended to be used aide-memoire by public health researchers using geographical aggregated data in accessibility research. AIMS Press 2015-11-18 /pmc/articles/PMC5690440/ /pubmed/29546134 http://dx.doi.org/10.3934/publichealth.2015.4.746 Text en © 2015 Richard Fry et al., licensee AIMS Press This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
spellingShingle Research Article
Mizen, Amy
Fry, Richard
Grinnell, Daniel
Rodgers, Sarah E.
Quantifying the Error Associated with Alternative GIS-based Techniques to Measure Access to Health Care Services
title Quantifying the Error Associated with Alternative GIS-based Techniques to Measure Access to Health Care Services
title_full Quantifying the Error Associated with Alternative GIS-based Techniques to Measure Access to Health Care Services
title_fullStr Quantifying the Error Associated with Alternative GIS-based Techniques to Measure Access to Health Care Services
title_full_unstemmed Quantifying the Error Associated with Alternative GIS-based Techniques to Measure Access to Health Care Services
title_short Quantifying the Error Associated with Alternative GIS-based Techniques to Measure Access to Health Care Services
title_sort quantifying the error associated with alternative gis-based techniques to measure access to health care services
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5690440/
https://www.ncbi.nlm.nih.gov/pubmed/29546134
http://dx.doi.org/10.3934/publichealth.2015.4.746
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