Abstract

BackgroundCommercial 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.MethodsTo 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.ResultsInternationally, 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.ConclusionsTo 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.

Highlights

  • Commercial geospatial data resources are frequently used to understand healthcare utilisation

  • There is considerable international variation in each indicator’s availability, with for example both predictive and live traffic data underpinning Environmental Systems Research Institute (ESRI)’s drive-time calculations in 11 countries, but only partial coverage of the major road network being available in 24 countries

  • Levels of inequality were lower for resources for computing patient travel times than for resources for geocoding patient addresses or characterising patients’ areas of residence

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Summary

Introduction

Commercial geospatial data resources are frequently used to understand healthcare utilisation. 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. GIS has been proposed as an integrative information and communication technology tool for accelerating progress towards universal health coverage (UHC) [2]. To realise the potential of GIS, it has been argued that the health sector has to ‘geoenable’ its health information systems [2]. A management structure that provides sufficient funding to underpin GIS adoption, resources for creating and maintaining health information systems, and an underlying national spatial data infrastructure are all prerequisites for GIS uptake in the health sector. Awareness of GIS use in healthcare planning remains low even in developed countries [4], where within the UK National Health Service its use remains largely restricted to mapping

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