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A cross-sectional ecological analysis of international and sub-national health inequalities in commercial geospatial resource availability

A cross-sectional ecological analysis of international and sub-national health inequalities in commercial geospatial resource availability
A cross-sectional ecological analysis of international and sub-national health inequalities in commercial geospatial resource availability
Background: commercial geospatial data resources are frequently used to understand healthcare utilisation. Although there is widespread evidence of a digital divide for other digital resources and infra-structure, it is unclear how commercial geospatial data resources are distributed relative to health need.

Methods: to examine the distribution of commercial geospatial data resources relative to health needs, we assembled coverage and quality metrics for commercial geocoding, neighbourhood characterisation, and travel time calculation resources for 183 countries. We developed a country-level, composite index of commercial geospatial data quality/availability and examined its distribution relative to age-standardised all-cause and cause specific (for three main causes of death) mortality using two inequality metrics, the slope index of inequality and relative concentration index. In two sub-national case studies, we also examined geocoding success rates versus area deprivation by district in Eastern Region, Ghana and Lagos State, Nigeria.

Results: internationally, commercial geospatial data resources were inversely related to all-cause mortality. This relationship was more pronounced when examining mortality due to communicable diseases. Commercial geospatial data resources for calculating patient travel times were more equitably distributed relative to health need than resources for characterising neighbourhoods or geocoding patient addresses. Countries such as South Africa have comparatively high commercial geospatial data availability despite high mortality, whilst countries such as South Korea have comparatively low data availability and low mortality. Sub-nationally, evidence was mixed as to whether geocoding success was lowest in more deprived districts.

Conclusions: to our knowledge, this is the first global analysis of commercial geospatial data resources in relation to health outcomes. In countries such as South Africa where there is high mortality but also comparatively rich commercial geospatial data, these data resources are a potential resource for examining healthcare utilisation that requires further evaluation. In countries such as Sierra Leone where there is high mortality but minimal commercial geospatial data, alternative approaches such as open data use are needed in quantifying patient travel times, geocoding patient addresses, and characterising patients’ neighbourhoods.
1476-072X
Dotse-Gborgbortsi, Winfred
8e7a4177-1620-4a2b-a860-baa1c5e29bb8
Wardrop, Nicola
8f3a8171-0727-4375-bc68-10e7d616e176
Adewole, Ademola
c120bc85-43a7-4ed3-ae8a-85bfa397ad61
Thomas, Mair
c43a2135-6dbc-4fc4-9c69-cd9ece0623b1
Wright, James
94990ecf-f8dd-4649-84f2-b28bf272e464
Dotse-Gborgbortsi, Winfred
8e7a4177-1620-4a2b-a860-baa1c5e29bb8
Wardrop, Nicola
8f3a8171-0727-4375-bc68-10e7d616e176
Adewole, Ademola
c120bc85-43a7-4ed3-ae8a-85bfa397ad61
Thomas, Mair
c43a2135-6dbc-4fc4-9c69-cd9ece0623b1
Wright, James
94990ecf-f8dd-4649-84f2-b28bf272e464

Dotse-Gborgbortsi, Winfred, Wardrop, Nicola, Adewole, Ademola, Thomas, Mair and Wright, James (2018) A cross-sectional ecological analysis of international and sub-national health inequalities in commercial geospatial resource availability. International Journal of Health Geographics, 17 (14). (doi:10.1186/s12942-018-0134-z).

Record type: Article

Abstract

Background: commercial geospatial data resources are frequently used to understand healthcare utilisation. Although there is widespread evidence of a digital divide for other digital resources and infra-structure, it is unclear how commercial geospatial data resources are distributed relative to health need.

Methods: to examine the distribution of commercial geospatial data resources relative to health needs, we assembled coverage and quality metrics for commercial geocoding, neighbourhood characterisation, and travel time calculation resources for 183 countries. We developed a country-level, composite index of commercial geospatial data quality/availability and examined its distribution relative to age-standardised all-cause and cause specific (for three main causes of death) mortality using two inequality metrics, the slope index of inequality and relative concentration index. In two sub-national case studies, we also examined geocoding success rates versus area deprivation by district in Eastern Region, Ghana and Lagos State, Nigeria.

Results: internationally, commercial geospatial data resources were inversely related to all-cause mortality. This relationship was more pronounced when examining mortality due to communicable diseases. Commercial geospatial data resources for calculating patient travel times were more equitably distributed relative to health need than resources for characterising neighbourhoods or geocoding patient addresses. Countries such as South Africa have comparatively high commercial geospatial data availability despite high mortality, whilst countries such as South Korea have comparatively low data availability and low mortality. Sub-nationally, evidence was mixed as to whether geocoding success was lowest in more deprived districts.

Conclusions: to our knowledge, this is the first global analysis of commercial geospatial data resources in relation to health outcomes. In countries such as South Africa where there is high mortality but also comparatively rich commercial geospatial data, these data resources are a potential resource for examining healthcare utilisation that requires further evaluation. In countries such as Sierra Leone where there is high mortality but minimal commercial geospatial data, alternative approaches such as open data use are needed in quantifying patient travel times, geocoding patient addresses, and characterising patients’ neighbourhoods.

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Accepted/In Press date: 16 May 2018
e-pub ahead of print date: 23 May 2018
Published date: 23 May 2018

Identifiers

Local EPrints ID: 421238
URI: https://eprints.soton.ac.uk/id/eprint/421238
ISSN: 1476-072X
PURE UUID: ee89c1f3-1588-4b07-bd26-c88b853ef9bd
ORCID for James Wright: ORCID iD orcid.org/0000-0002-8842-2181

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Date deposited: 25 May 2018 16:30
Last modified: 20 Jul 2019 00:57

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