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A spatial national health facility database for public health sector planning in Kenya in 2008.

Noor AM, Alegana VA, Gething PW, Snow RW - Int J Health Geogr (2009)

Bottom Line: Efforts to tackle the enormous burden of ill-health in low-income countries are hampered by weak health information infrastructures that do not support appropriate planning and resource allocation.This represented an overall increase of 1,862 facilities compared to 2003.This information is key to future planning and with this paper we have released the digital spatial database in the public domain to assist the Kenyan Government and its partners in the health sector.

View Article: PubMed Central - HTML - PubMed

Affiliation: Malaria Public Health and Epidemiology Group, Centre for Geographic Medicine, KEMRI, University of Oxford, Wellcome Trust Collaborative Programme, Kenyatta National Hospital Grounds (behind NASCOP), Nairobi, Kenya. anoor@nairobi.kemri-wellcome.org

ABSTRACT

Background: Efforts to tackle the enormous burden of ill-health in low-income countries are hampered by weak health information infrastructures that do not support appropriate planning and resource allocation. For health information systems to function well, a reliable inventory of health service providers is critical. The spatial referencing of service providers to allow their representation in a geographic information system is vital if the full planning potential of such data is to be realized.

Methods: A disparate series of contemporary lists of health service providers were used to update a public health facility database of Kenya last compiled in 2003. These new lists were derived primarily through the national distribution of antimalarial and antiretroviral commodities since 2006. A combination of methods, including global positioning systems, was used to map service providers. These spatially-referenced data were combined with high-resolution population maps to analyze disparity in geographic access to public health care.

Findings: The updated 2008 database contained 5,334 public health facilities (67% ministry of health; 28% mission and nongovernmental organizations; 2% local authorities; and 3% employers and other ministries). This represented an overall increase of 1,862 facilities compared to 2003. Most of the additional facilities belonged to the ministry of health (79%) and the majority were dispensaries (91%). 93% of the health facilities were spatially referenced, 38% using global positioning systems compared to 21% in 2003. 89% of the population was within 5 km Euclidean distance to a public health facility in 2008 compared to 71% in 2003. Over 80% of the population outside 5 km of public health service providers was in the sparsely settled pastoralist areas of the country.

Conclusion: We have shown that, with concerted effort, a relatively complete inventory of mapped health services is possible with enormous potential for improving planning. Expansion in public health care in Kenya has resulted in significant increases in geographic access although several areas of the country need further improvements. This information is key to future planning and with this paper we have released the digital spatial database in the public domain to assist the Kenyan Government and its partners in the health sector.

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Province maps of Kenya showing: A) areas in 2003 that were within the 5 km benchmark of geographic access to public health services recommended by the ministry of health*; B) areas in 2008 that were within the 5 km benchmark of geographic access to public health services recommended by the ministry of health*; C) percentage increase in population within 5 km of a public health facility from 2003 to 2008**; and D) number of people in 2008 that were outside the 5 km benchmark to public health services***. Geographic access is represented as Euclidean (straightline) distance to public health facilities. 390 service providers that were not spatially positioned and all specialist facilities that do not provide services to ambulatory patients (72 in 2003 and 67 in 2008) were not included in the computation of distances to health facilities. *11% of the population was outside 5 km of a public health facility in 2008 compared to 29% in 2003. **The highest percentage increase in public health facilities in 2003–2008 occurred in areas in North Eastern province (Table 2). Most areas in this province, however, also registered the lowest proportional increase in population within 5 km of a public health facility in the same period. ***Several of the large, sparsely populated areas of northern part of the country had 100,000 or more people of the population outside of a 5 km of a public health facility accounting for 80% of the population in some of these areas. Areas within provinces in 2B and 2C represent the districts as at December 2007 (n = 69). Since then the number of districts have increased to 149 but the digital boundaries these new districts were not available at the time of the study.
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Figure 2: Province maps of Kenya showing: A) areas in 2003 that were within the 5 km benchmark of geographic access to public health services recommended by the ministry of health*; B) areas in 2008 that were within the 5 km benchmark of geographic access to public health services recommended by the ministry of health*; C) percentage increase in population within 5 km of a public health facility from 2003 to 2008**; and D) number of people in 2008 that were outside the 5 km benchmark to public health services***. Geographic access is represented as Euclidean (straightline) distance to public health facilities. 390 service providers that were not spatially positioned and all specialist facilities that do not provide services to ambulatory patients (72 in 2003 and 67 in 2008) were not included in the computation of distances to health facilities. *11% of the population was outside 5 km of a public health facility in 2008 compared to 29% in 2003. **The highest percentage increase in public health facilities in 2003–2008 occurred in areas in North Eastern province (Table 2). Most areas in this province, however, also registered the lowest proportional increase in population within 5 km of a public health facility in the same period. ***Several of the large, sparsely populated areas of northern part of the country had 100,000 or more people of the population outside of a 5 km of a public health facility accounting for 80% of the population in some of these areas. Areas within provinces in 2B and 2C represent the districts as at December 2007 (n = 69). Since then the number of districts have increased to 149 but the digital boundaries these new districts were not available at the time of the study.

Mentions: The highest percentage increase between 2003 and 2008 in public health facilities occurred in North Eastern province (70%), followed by Nyanza (40%) and Eastern (39%) with Nairobi showing the lowest increase of less than a quarter (22%) (Table 2). Overall, 89% of the population was within the national target of 5 km distance to a public health facility in 2008 compared to 71% in 2003. This improvement, however, varied widely across the country (Figure 2). Although North Eastern province registered the highest growth in public health facilities (68%), it remained the least well served with only 29% of the population within 5 km of a public health service provider in 2008, an increase of about 10% from 2003 (Table 2 & Figure 2B &2C). Of the 4 million people who were outside the 5 km benchmark in 2008, approximately 3.3 million (83%) were from the northern, predominantly pastoralist, areas of the Rift Valley, North Eastern and Eastern provinces (Table 2 & Figure 2D).


A spatial national health facility database for public health sector planning in Kenya in 2008.

Noor AM, Alegana VA, Gething PW, Snow RW - Int J Health Geogr (2009)

Province maps of Kenya showing: A) areas in 2003 that were within the 5 km benchmark of geographic access to public health services recommended by the ministry of health*; B) areas in 2008 that were within the 5 km benchmark of geographic access to public health services recommended by the ministry of health*; C) percentage increase in population within 5 km of a public health facility from 2003 to 2008**; and D) number of people in 2008 that were outside the 5 km benchmark to public health services***. Geographic access is represented as Euclidean (straightline) distance to public health facilities. 390 service providers that were not spatially positioned and all specialist facilities that do not provide services to ambulatory patients (72 in 2003 and 67 in 2008) were not included in the computation of distances to health facilities. *11% of the population was outside 5 km of a public health facility in 2008 compared to 29% in 2003. **The highest percentage increase in public health facilities in 2003–2008 occurred in areas in North Eastern province (Table 2). Most areas in this province, however, also registered the lowest proportional increase in population within 5 km of a public health facility in the same period. ***Several of the large, sparsely populated areas of northern part of the country had 100,000 or more people of the population outside of a 5 km of a public health facility accounting for 80% of the population in some of these areas. Areas within provinces in 2B and 2C represent the districts as at December 2007 (n = 69). Since then the number of districts have increased to 149 but the digital boundaries these new districts were not available at the time of the study.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
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Figure 2: Province maps of Kenya showing: A) areas in 2003 that were within the 5 km benchmark of geographic access to public health services recommended by the ministry of health*; B) areas in 2008 that were within the 5 km benchmark of geographic access to public health services recommended by the ministry of health*; C) percentage increase in population within 5 km of a public health facility from 2003 to 2008**; and D) number of people in 2008 that were outside the 5 km benchmark to public health services***. Geographic access is represented as Euclidean (straightline) distance to public health facilities. 390 service providers that were not spatially positioned and all specialist facilities that do not provide services to ambulatory patients (72 in 2003 and 67 in 2008) were not included in the computation of distances to health facilities. *11% of the population was outside 5 km of a public health facility in 2008 compared to 29% in 2003. **The highest percentage increase in public health facilities in 2003–2008 occurred in areas in North Eastern province (Table 2). Most areas in this province, however, also registered the lowest proportional increase in population within 5 km of a public health facility in the same period. ***Several of the large, sparsely populated areas of northern part of the country had 100,000 or more people of the population outside of a 5 km of a public health facility accounting for 80% of the population in some of these areas. Areas within provinces in 2B and 2C represent the districts as at December 2007 (n = 69). Since then the number of districts have increased to 149 but the digital boundaries these new districts were not available at the time of the study.
Mentions: The highest percentage increase between 2003 and 2008 in public health facilities occurred in North Eastern province (70%), followed by Nyanza (40%) and Eastern (39%) with Nairobi showing the lowest increase of less than a quarter (22%) (Table 2). Overall, 89% of the population was within the national target of 5 km distance to a public health facility in 2008 compared to 71% in 2003. This improvement, however, varied widely across the country (Figure 2). Although North Eastern province registered the highest growth in public health facilities (68%), it remained the least well served with only 29% of the population within 5 km of a public health service provider in 2008, an increase of about 10% from 2003 (Table 2 & Figure 2B &2C). Of the 4 million people who were outside the 5 km benchmark in 2008, approximately 3.3 million (83%) were from the northern, predominantly pastoralist, areas of the Rift Valley, North Eastern and Eastern provinces (Table 2 & Figure 2D).

Bottom Line: Efforts to tackle the enormous burden of ill-health in low-income countries are hampered by weak health information infrastructures that do not support appropriate planning and resource allocation.This represented an overall increase of 1,862 facilities compared to 2003.This information is key to future planning and with this paper we have released the digital spatial database in the public domain to assist the Kenyan Government and its partners in the health sector.

View Article: PubMed Central - HTML - PubMed

Affiliation: Malaria Public Health and Epidemiology Group, Centre for Geographic Medicine, KEMRI, University of Oxford, Wellcome Trust Collaborative Programme, Kenyatta National Hospital Grounds (behind NASCOP), Nairobi, Kenya. anoor@nairobi.kemri-wellcome.org

ABSTRACT

Background: Efforts to tackle the enormous burden of ill-health in low-income countries are hampered by weak health information infrastructures that do not support appropriate planning and resource allocation. For health information systems to function well, a reliable inventory of health service providers is critical. The spatial referencing of service providers to allow their representation in a geographic information system is vital if the full planning potential of such data is to be realized.

Methods: A disparate series of contemporary lists of health service providers were used to update a public health facility database of Kenya last compiled in 2003. These new lists were derived primarily through the national distribution of antimalarial and antiretroviral commodities since 2006. A combination of methods, including global positioning systems, was used to map service providers. These spatially-referenced data were combined with high-resolution population maps to analyze disparity in geographic access to public health care.

Findings: The updated 2008 database contained 5,334 public health facilities (67% ministry of health; 28% mission and nongovernmental organizations; 2% local authorities; and 3% employers and other ministries). This represented an overall increase of 1,862 facilities compared to 2003. Most of the additional facilities belonged to the ministry of health (79%) and the majority were dispensaries (91%). 93% of the health facilities were spatially referenced, 38% using global positioning systems compared to 21% in 2003. 89% of the population was within 5 km Euclidean distance to a public health facility in 2008 compared to 71% in 2003. Over 80% of the population outside 5 km of public health service providers was in the sparsely settled pastoralist areas of the country.

Conclusion: We have shown that, with concerted effort, a relatively complete inventory of mapped health services is possible with enormous potential for improving planning. Expansion in public health care in Kenya has resulted in significant increases in geographic access although several areas of the country need further improvements. This information is key to future planning and with this paper we have released the digital spatial database in the public domain to assist the Kenyan Government and its partners in the health sector.

Show MeSH