Creating spatially defined databases for equitable health service planning in low-income countries: the example of Kenya
Introduction
There has been a resurgence of interest in the geographic inequalities in health among countries of Western Europe and North America linked to atlases of risk and analyses of the economic, social, service and environmental causes for disparities in health outcomes (Macintyre, 1986, Kunst and Mackenbach, 1994, Bartley et al., 1997, Kennedy et al., 1998, Gilson, 1998, Braveman and Tarimo, 2002). By contrast, our understanding of spatial determinants of risk, health and access to services in the low-income tropics is limited.
While high-income countries are able to fund and integrate new information tools to guide national health policy, low-income countries who bear the majority of the global burden of disease have inadequate and poorly performing health management information systems (HMIS). Many countries in sub-Saharan Africa (SSA) have embraced the need to develop broad health sector reforms linked to poverty reduction strategies (Owino, 1997, Bossert, 1998, Agyepong, 1999). Targets are established by national governments to reach specific goals of mortality reduction through equitable access to services. The strategies adopted to achieve these goals should be based upon knowledge of existing services, disease burden and equity. In practice, the extent to which the evidence base for these decisions can be developed is often limited (Murray, 1995, Owino and Munga, 1997, WHO, 2000, Niessen et al., 2000).
Geographical information systems (GIS), with their capacity for spatial data input, data storage, multi-factor analysis and output have been identified as an important tool in setting public health agendas and understanding the levels of inequalities in access to health care (Twigg, 1990, Scholten and de Lepper, 1991, Fotheringham and Rogerson, 1994, Loslier, 1994, Snow et al., 1998, Hay, 2000, Higgs and Gould, 2001). In this paper, we describe efforts to reconstruct the national map of health service providers in Kenya using all available information. We use this to highlight the current HMIS problems facing Kenya and similar countries in the region. We also explore how these might be resolved through coordinated efforts using GIS applications. We demonstrate the simple use of GIS data to highlight disparity in physical access to health service.
Section snippets
The Kenya context
Since independence in Kenya (1963) continuous attempts have been made to create an equitable health care system. It was clear that access to formal health services was a major problem to the bulk of the population, 95% of who were listed as rural in the 1962 census (Mburu, 1980). Despite declining economic growth, high population growth rates and an increasingly overwhelmed and under-resourced health system, Kenya was able to realise precipitous and sustained declines in infant and child
Results
Following two years of compiling various facility lists and checking on completeness, duplications and positions, the final database contained a total of 6674 health service providers (Table 1). We did not include mobile clinics, community pharmacies or village health posts, which represent a dynamic and transient grouping of lowest level providers subject to NGO or DHMT resources and support. The list did attempt to include private sector providers, a large grouping of health facilities widely
Discussion
The last available map of health service providers in Kenya was developed in 1959 (Butler, 1959; Fig. 1). Forty years on we have attempted to reconstruct the national health facility map. We have identified 3319 general health service providers supported by the MoH or their mission, NGO or LA partners providing services to 29 million people in 1999. Since 1959, the services–population ratio changed from 1:26,000 people to 1:9300 people in 1999. At an initial glance (Fig. 2, Fig. 3) the location
Acknowledgements
This study received financial support from The Wellcome Trust, UK (#058922), Roll Back Malaria Initiative, AFRO (AFRO/WHO/RBM # AF/ICP/CPC/400/XA/00) and the Kenya Medical Research Institute. SIH is currently supported by the Wellcome Trust as a Research Career Development Fellow (#069045) and RWS is supported by the Wellcome Trust as senior fellow (#058992). The authors are grateful to a large number of contributors to the location and checking of information used to create the National Health
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