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AccessMod 3.0: computing geographic coverage and accessibility to health care services using anisotropic movement of patients.

Ray N, Ebener S - Int J Health Geogr (2008)

Bottom Line: Four major types of analysis are available in AccessMod: (1) modeling the coverage of catchment areas linked to an existing health facility network based on travel time, to provide a measure of physical accessibility to health care; (2) modeling geographic coverage according to the availability of services; (3) projecting the coverage of a scaling-up of an existing network; (4) providing information for cost effectiveness analysis when little information about the existing network is available.By incorporating the demand (population) and the supply (capacities of heath care centers), AccessMod provides a unifying tool to efficiently assess the geographic coverage of a network of health care facilities.This tool should be of particular interest to developing countries that have a relatively good geographic information on population distribution, terrain, and health facility locations.

View Article: PubMed Central - HTML - PubMed

Affiliation: Information, Evidence and Research, World Health Organization, 20 av, Appia, 1211 Geneva 27, Switzerland. nicolas.ray@zoo.unibe.ch

ABSTRACT

Background: Access to health care can be described along four dimensions: geographic accessibility, availability, financial accessibility and acceptability. Geographic accessibility measures how physically accessible resources are for the population, while availability reflects what resources are available and in what amount. Combining these two types of measure into a single index provides a measure of geographic (or spatial) coverage, which is an important measure for assessing the degree of accessibility of a health care network.

Results: This paper describes the latest version of AccessMod, an extension to the Geographical Information System ArcView 3.x, and provides an example of application of this tool. AccessMod 3 allows one to compute geographic coverage to health care using terrain information and population distribution. Four major types of analysis are available in AccessMod: (1) modeling the coverage of catchment areas linked to an existing health facility network based on travel time, to provide a measure of physical accessibility to health care; (2) modeling geographic coverage according to the availability of services; (3) projecting the coverage of a scaling-up of an existing network; (4) providing information for cost effectiveness analysis when little information about the existing network is available. In addition to integrating travelling time, population distribution and the population coverage capacity specific to each health facility in the network, AccessMod can incorporate the influence of landscape components (e.g. topography, river and road networks, vegetation) that impact travelling time to and from facilities. Topographical constraints can be taken into account through an anisotropic analysis that considers the direction of movement. We provide an example of the application of AccessMod in the southern part of Malawi that shows the influences of the landscape constraints and of the modes of transportation on geographic coverage.

Conclusion: By incorporating the demand (population) and the supply (capacities of heath care centers), AccessMod provides a unifying tool to efficiently assess the geographic coverage of a network of health care facilities. This tool should be of particular interest to developing countries that have a relatively good geographic information on population distribution, terrain, and health facility locations.

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Related in: MedlinePlus

Data sets used for the example analysis. (A) Inset showing the location of Malawi and the area of interest in the southern part of the country; (B) Digital Elevation Model (DEM); (C) landcover grid with the river and road network, and the subset of 10 health facilities used in the analysis; (D) population grid with the river network. The southern wetland area (white polygon) is not considered in the analysis, and is treated as 'no data'.
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Figure 5: Data sets used for the example analysis. (A) Inset showing the location of Malawi and the area of interest in the southern part of the country; (B) Digital Elevation Model (DEM); (C) landcover grid with the river and road network, and the subset of 10 health facilities used in the analysis; (D) population grid with the river network. The southern wetland area (white polygon) is not considered in the analysis, and is treated as 'no data'.

Mentions: To show the capacities of AccessMod under different realistic settings, we used data from the Southern part of Malawi (see Figure 5a). This area has been selected because it represents a mix of rural and urban areas, has different vegetation density levels, and several rivers form barriers to movements. The data sets used here are those that have been prepared for the AccessMod tutorial that is included in the download package:


AccessMod 3.0: computing geographic coverage and accessibility to health care services using anisotropic movement of patients.

Ray N, Ebener S - Int J Health Geogr (2008)

Data sets used for the example analysis. (A) Inset showing the location of Malawi and the area of interest in the southern part of the country; (B) Digital Elevation Model (DEM); (C) landcover grid with the river and road network, and the subset of 10 health facilities used in the analysis; (D) population grid with the river network. The southern wetland area (white polygon) is not considered in the analysis, and is treated as 'no data'.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2651127&req=5

Figure 5: Data sets used for the example analysis. (A) Inset showing the location of Malawi and the area of interest in the southern part of the country; (B) Digital Elevation Model (DEM); (C) landcover grid with the river and road network, and the subset of 10 health facilities used in the analysis; (D) population grid with the river network. The southern wetland area (white polygon) is not considered in the analysis, and is treated as 'no data'.
Mentions: To show the capacities of AccessMod under different realistic settings, we used data from the Southern part of Malawi (see Figure 5a). This area has been selected because it represents a mix of rural and urban areas, has different vegetation density levels, and several rivers form barriers to movements. The data sets used here are those that have been prepared for the AccessMod tutorial that is included in the download package:

Bottom Line: Four major types of analysis are available in AccessMod: (1) modeling the coverage of catchment areas linked to an existing health facility network based on travel time, to provide a measure of physical accessibility to health care; (2) modeling geographic coverage according to the availability of services; (3) projecting the coverage of a scaling-up of an existing network; (4) providing information for cost effectiveness analysis when little information about the existing network is available.By incorporating the demand (population) and the supply (capacities of heath care centers), AccessMod provides a unifying tool to efficiently assess the geographic coverage of a network of health care facilities.This tool should be of particular interest to developing countries that have a relatively good geographic information on population distribution, terrain, and health facility locations.

View Article: PubMed Central - HTML - PubMed

Affiliation: Information, Evidence and Research, World Health Organization, 20 av, Appia, 1211 Geneva 27, Switzerland. nicolas.ray@zoo.unibe.ch

ABSTRACT

Background: Access to health care can be described along four dimensions: geographic accessibility, availability, financial accessibility and acceptability. Geographic accessibility measures how physically accessible resources are for the population, while availability reflects what resources are available and in what amount. Combining these two types of measure into a single index provides a measure of geographic (or spatial) coverage, which is an important measure for assessing the degree of accessibility of a health care network.

Results: This paper describes the latest version of AccessMod, an extension to the Geographical Information System ArcView 3.x, and provides an example of application of this tool. AccessMod 3 allows one to compute geographic coverage to health care using terrain information and population distribution. Four major types of analysis are available in AccessMod: (1) modeling the coverage of catchment areas linked to an existing health facility network based on travel time, to provide a measure of physical accessibility to health care; (2) modeling geographic coverage according to the availability of services; (3) projecting the coverage of a scaling-up of an existing network; (4) providing information for cost effectiveness analysis when little information about the existing network is available. In addition to integrating travelling time, population distribution and the population coverage capacity specific to each health facility in the network, AccessMod can incorporate the influence of landscape components (e.g. topography, river and road networks, vegetation) that impact travelling time to and from facilities. Topographical constraints can be taken into account through an anisotropic analysis that considers the direction of movement. We provide an example of the application of AccessMod in the southern part of Malawi that shows the influences of the landscape constraints and of the modes of transportation on geographic coverage.

Conclusion: By incorporating the demand (population) and the supply (capacities of heath care centers), AccessMod provides a unifying tool to efficiently assess the geographic coverage of a network of health care facilities. This tool should be of particular interest to developing countries that have a relatively good geographic information on population distribution, terrain, and health facility locations.

Show MeSH
Related in: MedlinePlus