MEASURE Evaluation’s activities in Burundi included helping to strengthen the HMIS, enhancing data quality, training on data use in order to improve policy and program decision making, and filling in information gaps on key populations at risk of HIV infection.

With one of the world’s lowest per capita incomes, and a risk of HIV transmission among key populations, Burundi faces many challenges to economic growth and tremendous stress on its healthcare system. Life expectancy is less than 60 years, infant mortality is 54 deaths per 1,000 live births, maternal mortality is high at 712 deaths per 100,000 live births,[1] and malnutrition stands at 67.3 percent.[2] The country’s health management information system (HMIS) is relatively weak and strengthening that critical component is a key priority for the government.

Specifically, accurate malaria and HIV data are vital to be included in the HMIS, as they generate the majority of the cases received by health facilities. The data—if available—would help facilities and the national health program to identify trends for good or ill and to allocate scarce human and financial resources to best effect.    

MEASURE Evaluation worked to strengthen performance of the Burundi National Health Information System (SNIS), to strengthen the capacity of the National AIDS Control Program and the Burundi Ministère de la Santé Publique (MSP) in the expansion of the use of the DHIS 2 software platform for data collection and analysis at all levels of the health system.

MEASURE Evaluation’s work addressed key recommendations from a 2013 Performance of Routine Information System Management (PRISM) assessment. MEASURE Evaluation’s activities in Burundi included improving facility-based information systems; building a harmonized community-based information system, and improving the M&E system for the National AIDS Control Program. Specific tools include guidelines for supervision and management of health information, and a rapid assessment of sentinel surveillance and community-based health information systems.

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Related Content

[1] http://data.worldbank.org/indicator/SH.STA.MMRT

[2] https://borgenproject.org/malnutrition-in-burundi/

Filed under: Data Quality , Africa , HIV/AIDS , Data Demand and Use , At-Risk Populations , Health Information Systems , Burundi
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