Regional Differences in Intervention Coverage and Health System Strength in Tanzania
Identifieur interne : 003420 ( Ncbi/Curation ); précédent : 003419; suivant : 003421Regional Differences in Intervention Coverage and Health System Strength in Tanzania
Auteurs : Claud J. Kumalija ; Sriyanjit Perera ; Honorati Masanja ; Josibert Rubona ; Yahya Ipuge ; Leonard Mboera ; Ahmad R. Hosseinpoor [Suisse] ; Ties Boerma [Suisse]Source :
- PLoS ONE [ 1932-6203 ] ; 2015.
Abstract
Assessments of subnational progress and performance coverage within countries should be an integral part of health sector reviews, using recent data from multiple sources on health system strength and coverage.
As part of the midterm review of the national health sector strategic plan of Tanzania mainland, summary measures of health system strength and coverage of interventions were developed for all 21 regions, focusing on the priority indicators of the national plan. Household surveys, health facility data and administrative databases were used to compute the regional scores.
Regional Millennium Development Goal (MDG) intervention coverage, based on 19 indicators, ranged from 47% in Shinyanga in the northwest to 71% in Dar es Salaam region. Regions in the eastern half of the country have higher coverage than in the western half of mainland. The MDG coverage score is strongly positively correlated with health systems strength (r = 0.84). Controlling for socioeconomic status in a multivariate analysis has no impact on the association between the MDG coverage score and health system strength. During 1991–2010 intervention coverage improved considerably in all regions, but the absolute gap between the regions did not change during the past two decades, with a gap of 22% between the top and bottom three regions.
The assessment of regional progress and performance in 21 regions of mainland Tanzania showed considerable inequalities in coverage and health system strength and allowed the identification of high and low-performing regions. Using summary measures derived from administrative, health facility and survey data, a subnational picture of progress and performance can be obtained for use in regular health sector reviews.
Url:
DOI: 10.1371/journal.pone.0142066
PubMed: 26536351
PubMed Central: 4633273
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Claud J. Kumalija<affiliation><nlm:aff id="aff001"><addr-line>Policy and Planning Department, Ministry of Health and Social Welfare, Dar es Salaam, United Republic of Tanzania</addr-line>
</nlm:aff>
<wicri:noCountry code="subfield">United Republic of Tanzania</wicri:noCountry>
</affiliation>
<affiliation><nlm:aff id="aff002"><addr-line>CTS Global, assigned to Centers for Disease Control and Prevention, Dar es Salaam, United Republic of Tanzania</addr-line>
</nlm:aff>
<wicri:noCountry code="subfield">United Republic of Tanzania</wicri:noCountry>
</affiliation>
<affiliation><nlm:aff id="aff003"><addr-line>Ifakara Health Institute, Dar es Salaam, United Republic of Tanzania</addr-line>
</nlm:aff>
<wicri:noCountry code="subfield">United Republic of Tanzania</wicri:noCountry>
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<affiliation><nlm:aff id="aff001"><addr-line>Policy and Planning Department, Ministry of Health and Social Welfare, Dar es Salaam, United Republic of Tanzania</addr-line>
</nlm:aff>
<wicri:noCountry code="subfield">United Republic of Tanzania</wicri:noCountry>
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<affiliation><nlm:aff id="aff004"><addr-line>World Bank, Dar es Salaam, United Republic of Tanzania</addr-line>
</nlm:aff>
<wicri:noCountry code="subfield">United Republic of Tanzania</wicri:noCountry>
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<affiliation><nlm:aff id="aff005"><addr-line>National Institute for Medical Research, Dar es Salaam, United Republic of Tanzania</addr-line>
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<wicri:noCountry code="subfield">United Republic of Tanzania</wicri:noCountry>
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<author><name sortKey="Perera, Sriyanjit" sort="Perera, Sriyanjit" uniqKey="Perera S" first="Sriyanjit" last="Perera">Sriyanjit Perera</name>
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<author><name sortKey="Masanja, Honorati" sort="Masanja, Honorati" uniqKey="Masanja H" first="Honorati" last="Masanja">Honorati Masanja</name>
<affiliation><nlm:aff id="aff003"><addr-line>Ifakara Health Institute, Dar es Salaam, United Republic of Tanzania</addr-line>
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<author><name sortKey="Ipuge, Yahya" sort="Ipuge, Yahya" uniqKey="Ipuge Y" first="Yahya" last="Ipuge">Yahya Ipuge</name>
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<wicri:noCountry code="subfield">United Republic of Tanzania</wicri:noCountry>
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<front><div type="abstract" xml:lang="en"><sec id="sec001"><title>Background</title>
<p>Assessments of subnational progress and performance coverage within countries should be an integral part of health sector reviews, using recent data from multiple sources on health system strength and coverage.</p>
</sec>
<sec id="sec002"><title>Method</title>
<p>As part of the midterm review of the national health sector strategic plan of Tanzania mainland, summary measures of health system strength and coverage of interventions were developed for all 21 regions, focusing on the priority indicators of the national plan. Household surveys, health facility data and administrative databases were used to compute the regional scores.</p>
</sec>
<sec id="sec003"><title>Findings</title>
<p>Regional Millennium Development Goal (MDG) intervention coverage, based on 19 indicators, ranged from 47% in Shinyanga in the northwest to 71% in Dar es Salaam region. Regions in the eastern half of the country have higher coverage than in the western half of mainland. The MDG coverage score is strongly positively correlated with health systems strength (r = 0.84). Controlling for socioeconomic status in a multivariate analysis has no impact on the association between the MDG coverage score and health system strength. During 1991–2010 intervention coverage improved considerably in all regions, but the absolute gap between the regions did not change during the past two decades, with a gap of 22% between the top and bottom three regions.</p>
</sec>
<sec id="sec004"><title>Interpretation</title>
<p>The assessment of regional progress and performance in 21 regions of mainland Tanzania showed considerable inequalities in coverage and health system strength and allowed the identification of high and low-performing regions. Using summary measures derived from administrative, health facility and survey data, a subnational picture of progress and performance can be obtained for use in regular health sector reviews.</p>
</sec>
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