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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

Outputs of the analysis of the existing network of health facilities. The extents of catchment areas are based on four travelling scenarios and a maximum travelling time of 90 minutes. (A) Only walking; (B) car + walking; (C) bus + walking; (D) bicycle + walking. Parameters of each scenario are defined in Table 2.
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Figure 6: Outputs of the analysis of the existing network of health facilities. The extents of catchment areas are based on four travelling scenarios and a maximum travelling time of 90 minutes. (A) Only walking; (B) car + walking; (C) bus + walking; (D) bicycle + walking. Parameters of each scenario are defined in Table 2.

Mentions: We show in Figure 6 the results of the analysis of the health facility network using each transportation scenario and a maximum travelling time of 90 minutes. For scenario 2 and 3, the catchments extend much further than for scenarios 1 and 4. This is due to the use of motor vehicle on roads that lengthen the travelling distance within the set maximum travelling time. Most of the catchments in scenario 1 are approximately circular, which reflects the uniformity of the landcover around the considered health facilities. However, some of these catchments have a truncated surface that is due to the intervening river network treated here as complete barrier to movement. This illustrates two important points regarding spatial data quality in AccessMod. First, the geographic coordinates of health facilities must be sufficiently accurate. A substantial shift in these coordinates can lead to a very different catchment area if, for example, this would place the health facility on the other side of a river or within a different type of landcover. This of course also applies to the other layers that are used in AccessMod (e.g. road and river networks, barriers to movements, extent of exclusion area).


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)

Outputs of the analysis of the existing network of health facilities. The extents of catchment areas are based on four travelling scenarios and a maximum travelling time of 90 minutes. (A) Only walking; (B) car + walking; (C) bus + walking; (D) bicycle + walking. Parameters of each scenario are defined in Table 2.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 6: Outputs of the analysis of the existing network of health facilities. The extents of catchment areas are based on four travelling scenarios and a maximum travelling time of 90 minutes. (A) Only walking; (B) car + walking; (C) bus + walking; (D) bicycle + walking. Parameters of each scenario are defined in Table 2.
Mentions: We show in Figure 6 the results of the analysis of the health facility network using each transportation scenario and a maximum travelling time of 90 minutes. For scenario 2 and 3, the catchments extend much further than for scenarios 1 and 4. This is due to the use of motor vehicle on roads that lengthen the travelling distance within the set maximum travelling time. Most of the catchments in scenario 1 are approximately circular, which reflects the uniformity of the landcover around the considered health facilities. However, some of these catchments have a truncated surface that is due to the intervening river network treated here as complete barrier to movement. This illustrates two important points regarding spatial data quality in AccessMod. First, the geographic coordinates of health facilities must be sufficiently accurate. A substantial shift in these coordinates can lead to a very different catchment area if, for example, this would place the health facility on the other side of a river or within a different type of landcover. This of course also applies to the other layers that are used in AccessMod (e.g. road and river networks, barriers to movements, extent of exclusion area).

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