DHS Methodological Report No. 20
This study used Service Provision Assessment (SPA) and Demographic and Health Survey (DHS) data from Haiti, Malawi, and Tanzania to compare traditionally used additive methods with a data reduction method—
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principal component analysis (PCA).
We scored the quality of health facilities with three approaches (simple additive, weighted additive, and PCA) for two constructs: quality of services, with only facilities-level data, and quality of care, which incorporates observation and client data. We ranked facilities as high, medium, or low quality based on their scores. Our results indicated that the rankings change with the scoring methodology. There was more consistency in the rankings of facilities by the simple additive and PCA methods than the weighted additive and PCA-based rankings. This may be due to the low factor loadings and little variance explained by the first component in the PCA. We aggregated facility scores to their respective DHS clusters (Haiti, Malawi) or regions (Tanzania) and geographically linked them to women interviewed in DHS surveys to test associations between the use of family planning services and the quality environment, as measured with each index.
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In 2014, the Ministry of Health (MOH) in Malawi conducted a nationwide assessment of emergency obstetric and newborn care (EmONC) services. This cr
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oss-sectional facility-based survey used 10 data collection modules. Data collection began on 23rd September 2014 and concluded on 17th October 2014, in all 28 districts. Facilities in both the public and private sector (for-profit and not-for-profit) were included. Since the focus of the assessment was obstetric and newborn care, health facilities that did not offer maternal and newborn health (MNH) services were not selected. In all districts, a census of all hospitals and a 60 percent random sample of health centres that ought to have performed deliveries in the previous year yielded a total of 365 facilities: 87 hospitals and 278 health centres. All these facilities were visited during the assessment. During analysis, weighting procedures were applied to extrapolate results to the district and national level, representing all 87 hospitals and 464 health centres. Such weighting was necessary as a stratified random sample of health centres was taken and weighting applied to all indicators and presentations that have health facility as a unit of measurement. Case reviews and provider’s interviews, on the other hand, are not weighted as their sampling strategy is based on convenience.
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The Road Map outlines various strategies which will guide policy makers, development partners, training institutions and service providers in supporting Government efforts towards the attainment of
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MDGs related to maternal and neonatal health.
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Moving towards equity and quality
Barriers to the prompt and effective diagnosis and treatment of malaria exist at both the community and health facility level. Household surveys measure malaria case management at the population level with standard indicators that assess treatment-s
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eeking behavior, access to diagnostic testing, and access to appropriate treatment. Performance on these indicators varies widely from country to country. Among countries with Demographic and Health Surveys (DHS) or Malaria Indicator Surveys (MIS) completed between 2014 and 2016, advice and treatment was sought for a median of 47% of children under age 5 with fever.
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As our world changes, so too does the burden of disease. Globalisation, evolving trade and consumption patterns, and increased access to life-saving medical care are just some of the factors that ha
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ve transformed the global health landscape.
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From Exclusion to Inclusion
DHS Analytical Studies No. 60