Disparities in Geographical Access to Hospitals in Portugal

Geographical accessibility to health care services is widely accepted as relevant to improve population health. However, measuring it is very complex, mainly when applied at administrative levels that go beyond the small-area level. This is the case in Portugal, where the municipality is the administrative level that is most appropriate for implementing policies to improve the access to those services. The aim of this paper is to assess whether inequalities in terms of access to a hospital in Portugal have improved over the last 20 years. A population-weighted driving time was applied using the census tract population, the roads network, the reference hospitals’ catchment area and the municipality boundaries. The results show that municipalities are 25 min away from the hospital—3 min less than in 1991—and that there is an association with premature mortality, elderly population and population density. However, disparities between municipalities are still huge. Municipalities with higher rates of older populations, isolated communities or those located closer to the border with Spain face harder challenges and require greater attention from local administration. Since municipalities now have responsibilities for health, it is important they implement interventions at the local level to tackle disparities impacting access to healthcare.

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Framing the decision to contract out elderly care and primary health care services – perspectives of local level politicians and civil servants in Finland

BMC Health Services Research ◽

10.1186/1472-6963-12-201 ◽

2012 ◽

Vol 12 (1) ◽

Cited By ~ 19

Author(s):

Liina-Kaisa Tynkkynen ◽

Juhani Lehto ◽

Sari Miettinen

Keyword(s):

Health Care ◽

Primary Health Care ◽

Health Care Services ◽

Local Level ◽

Elderly Care ◽

Civil Servants ◽

Care Services ◽

Primary Health ◽

Primary Health Care Services

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Improving geographical accessibility modeling for operational use by local health actors

10.1101/2020.03.09.20033100 ◽

2020 ◽

Author(s):

Felana Angella Ihantamalala ◽

Vincent Herbreteau ◽

Christophe Révillion ◽

Mauricianot Randriamihaja ◽

Jérémy Commins ◽

...

Keyword(s):

Rural Areas ◽

Local Level ◽

Travel Speed ◽

Local Health ◽

Residential Areas ◽

Geographic Accessibility ◽

Geographical Access ◽

Shortest Route ◽

Context Specific ◽

Geographical Accessibility

AbstractBackgroundGeographical accessibility to health facilities remains one of the main barriers to access care in rural areas of the developing world. Although methods and tools exist to model geographic accessibility, the lack of basic geographic information prevents their widespread use at the local level for targeted program implementation. The aim of this study was to develop very precise, context-specific estimates of geographic accessibility to care in a rural district of Madagascar to help with the design and implementation of interventions that improve access for remote populations.MethodsWe used a participatory approach to map all the paths, residential areas, buildings and rice fields on OpenStreetMap (OSM). We estimated shortest route from every household in the District to the nearest primary health care center (PHC) and community health site (CHS) with the Open Source Routing Machine (OSMR) tool. Then, we used remote sensing methods to obtain a high resolution land cover map, a digital elevation model and rainfall data to model travel speed. Travel speed models were calibrated with field data obtained by GPS tracking in a sample of 168 walking routes. Model results were used to predict travel time to seek care at PHCs and CHSs for all the shortest route estimated earlier. Finally, we integrated geographical accessibility results into an e-health platform developed with R Shiny.ResultsWe mapped over 100,000 buildings, 23,000 km of footpaths, and 4,925 residential areas throughout Ifanadiana district; this data is freely available on OSM. We found that over three quarters of the population lived more than one hour away from a PHC, and 10-15% lived more than one hour away from a CHS. Moreover, we identified areas in the North and East of the district where the nearest PHC was further than 5 hours away, and vulnerable populations across the district with poor geographical access (>1 hour) to both PHCs and CHSs.ConclusionOur study demonstrates how to improve geographical accessibility modeling so that results can be context-specific and operationally actionable by local health actors. The importance of such approaches is paramount for achieving universal health coverage in rural areas throughout world.

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VARIATION OF COMORBIDITIES IN ROMANIA AT THE LAU2 LEVEL, A CROSS-SECTIONAL ANALYSIS

CBU International Conference Proceedings ◽

10.12955/cbup.v7.1456 ◽

2019 ◽

Vol 7 ◽

pp. 790-793

Author(s):

Adrian Pana ◽

Bogdan-Vasile Ileanu

Keyword(s):

Health Care ◽

Health Care Services ◽

Local Level ◽

Health Indicators ◽

Care Utilization ◽

Population Number ◽

Cross Sectional ◽

Care Services ◽

Diagnostic Coding ◽

Referral Hospitals

Introduction: Romania is still lagging behind in regard to main health indicators when compared to average values of European Union countries with a disproportionate share of disability due mainly to chronic diseases. There are tools available to quantify the negative health outcomes due to comorbidities, and among them the Elixhauser Index was found to be the best to predict health care utilization and expenditures. Objective: To measure the extent of comorbidities at the LAU2 level using the Elixhauser Index. Methods: All relevant comorbidities at the local level were summed-up using the Elixhauser index. This was followed with standardization by population number and then by 10-year age group. Due to large oscillation from one year to another during the 2014-2016 period, the geometrical mean was computed, then few measures of the variation such as decile ratio and variation coefficient were also computed. Results: High variability of comorbidities is observed at the local level (LAU2). Clusters of comorbidities concentration are found near medical university centers and localities in non-MUC districts located at the furthest distance from the county residential center. Conclusions: Several factors such as proximity to referral hospitals, increased accessibility to these hospitals due to low control at primary healthcare levels, availability of diagnostic technologies and different diagnostic coding patterns, as well as isolation and unavailability of primary health care services are listed as possible factors that can explain these results.

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Measuring geographical accessibility to rural and remote health care services: Challenges and considerations

Spatial and Spatio-temporal Epidemiology ◽

10.1016/j.sste.2017.04.002 ◽

2017 ◽

Vol 21 ◽

pp. 87-96 ◽

Cited By ~ 4

Author(s):

Tayyab Ikram Shah ◽

Stephan Milosavljevic ◽

Brenna Bath

Keyword(s):

Health Care ◽

Health Care Services ◽

Rural And Remote ◽

Care Services ◽

Geographical Accessibility ◽

Remote Health ◽

Rural And Remote Health

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Improving geographical accessibility modeling for operational use by local health actors

10.21203/rs.3.rs-17182/v1 ◽

2020 ◽

Cited By ~ 3

Author(s):

Felana Angella Ihantamalala ◽

Vincent Herbreteau ◽

Christophe Révillion ◽

Mauricianot Randriamihaja ◽

Jérémy Commins ◽

...

Keyword(s):

Rural Areas ◽

Local Level ◽

Travel Speed ◽

Local Health ◽

Residential Areas ◽

Geographic Accessibility ◽

Geographical Access ◽

Shortest Route ◽

Context Specific ◽

Geographical Accessibility

Abstract Background Geographical accessibility to health facilities remains one of the main barriers to access care in rural areas of the developing world. Although methods and tools exist to model geographic accessibility, the lack of basic geographic information prevents their widespread use at the local level for targeted program implementation. The aim of this study was to develop very precise, context-specific estimates of geographic accessibility to care in a rural district of Madagascar to help with the design and implementation of interventions that improve access for remote populations. Methods We used a participatory approach to map all the paths, residential areas, buildings and rice fields on OpenStreetMap (OSM). We estimated shortest route from every household in the District to the nearest primary health care center (PHC) and community health site (CHS) with the Open Source Routing Machine (OSMR) tool. Then, we used remote sensing methods to obtain a high resolution land cover map, a digital elevation model and rainfall data to model travel speed. Travel speed models were calibrated with field data obtained by GPS tracking in a sample of 168 walking routes. Model results were used to predict travel time to seek care at PHCs and CHSs for all the shortest route estimated earlier. Finally, we integrated geographical accessibility results into an e-health platform developed with R Shiny. Results We mapped over 100,000 buildings, 23,000 km of footpaths, and 4,925 residential areas throughout Ifanadiana district; this data is freely available on OSM. We found that over three quarters of the population lived more than one hour away from a PHC, and 10-15% lived more than one hour away from a CHS. Moreover, we identified areas in the North and East of the district where the nearest PHC was further than 5 hours away, and vulnerable populations across the district with poor geographical access (>1 hour) to both PHCs and CHSs. Conclusion Our study demonstrates how to improve geographical accessibility modeling so that results can be context-specific and operationally actionable by local health actors. The importance of such approaches is paramount for achieving universal health coverage in rural areas throughout world.

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