Invited Paper

Health evaluations in Africa – A review of the health strand held at the 7th Biennial Conference of the African Evaluation Association

Edna Berhane
African Evaluation Journal | Vol 3, No 2 | a170 | DOI: https://doi.org/10.4102/aej.v3i2.170 | © 2015 Edna Berhane | This work is licensed under CC Attribution 4.0
Submitted: 02 September 2015 | Published: 30 September 2015

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Edna Berhane, Khulisa Management Services, South Africa


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Abstract

Although Africa has made significant progress in public health over the past several decades, it still faces a very high burden of disease compared to the rest of the world. This overwhelming disease burden is further aggravated by a lack of adequate financial and human resources for health, inequitable distribution of health services, and other social, economic and political factors. Given these constraints, it has become critical for African countries to ensure that health interventions are selected based on evidence and implemented efficiently and effectively to ensure desired outcomes and impact. This has led to an increasing appreciation for monitoring and evaluation as an integral element of programme planning, implementation and scale-up. The importance of M&E within the health sector was recently reflected in the fact that the health evaluation strand was the largest at AfrEA’s 7th Biennial International Conference, held over 3 days in March 2014 in Yaoundé, Cameroon. The health strand, which had nine sub-themes, was sponsored, managed, and supported by the USAID-funded AfricanStrategies for Health (ASH) project. This review summarises the health strand presentations, and panel and roundtable discussions. The evaluations featured in the strand were diverse interms of health area focus, evaluation methodology, language and authors’ affiliation. More than 21 African countries from all regions of sub-Saharan Africa were represented. Among thekey recurrent messages highlighted during the conference were the importance of: data use for planning and improving health programmes, data quality, well-functioning M&E systems and identifying and sharing best/good practices.

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