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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AIMS Press
2015
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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. |
format | Online Article Text |
id | pubmed-5690440 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | AIMS Press |
record_format | MEDLINE/PubMed |
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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