Effective Coverage

IHME has developed a systematic approach to identifying the priority interventions in different world regions, developing measurement strategies for these interventions, and compiling publicly available datasets.

Major activities in Effective Coverage:

Conduct a systematic review and analysis of datasets for selected interventions:

IHME researchers are systematically reviewing and analyzing all available data that are relevant to this area of work. This includes data gathered from surveys (both interview and examination surveys) and administrative data (hospital admissions data and provider registries). In addition to identifying all available data, we are assessing datasets by comparing questions and results and by creating methods that allow researchers to produce comparable analyses using different types of data. To date, we have focused on the following interventions: oral rehydration therapy; vitamin A provision; contraception coverage; diabetes treatment; skilled birth attendance, in-facility birth, and antenatal care; vaccines for polio, measles, and hepatitis B; insecticide-treated bed nets and indoor residual spraying for malaria; and medications to lower blood pressure and cholesterol.

Develop and apply innovative analytical methods:

IHME is working to develop improved methods to better compare data from diverse sources and time periods. The Effective Coverage Work Group strives to measure the quality of health interventions and to develop a framework to identify the determinants and limits of intervention coverage and deliverability. IHME researchers are developing methods for estimating trends at the national level in crude and effective coverage from heterogeneous data sources. Updated methods will use both survey and administrative data and generate plausible uncertainty intervals, a significant improvement on existing methods.

For example, researchers have developed the bidirectional distance-dependent regression (BDDR) method. BDDR measures survey coverage for each time point by assessing the association among survey data for a particular country-year, survey data at some time in the past, survey data at some time in the future, and administrative data from the country-year in question.

The group also has been implementing and assessing methods such as covariate matching and instrumental variables regression to estimate the effectiveness of interventions using cross-sectional survey data. These approaches have been used to estimate the effectiveness of insecticide-treated bed nets in reducing severe anemia and parasitemia, as well as the effect of skilled birth care on neonatal mortality.

We will publish all results and methods and aspire to incorporate them into easy-to-use, publicly available software packages.

Develop methods for assessing malaria interventions:

We have measured the impact of selected malaria interventions such as insecticide-treated bed nets using data from cross-sectional surveys and analytical approaches that allow us to estimate the effectiveness of these interventions in preventing childhood mortality.

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