Steven Radelet1, Bilal Siddiqi2. 1. Center for Global Development, Washington DC, USA. Electronic address: sradelet@cgdev.org. 2. Center for Global Development, Washington DC, USA.
Abstract
BACKGROUND: The Global Fund to Fight AIDS, Tuberculosis and Malaria evaluates programme performance after 2 years to help decide whether to continue funding. We aimed to identify the correlation between programme evaluation scores and characteristics of the programme, the health sector, and the recipient country. METHODS: We obtained data on the first 140 Global Fund grants evaluated in 2006, and analysed 134 of these. We used an ordered probit multivariate analysis to link evaluation scores to different characteristics, allowing us to record the association between changes in those characteristics and the probability of a programme receiving a particular evaluation score. FINDINGS: Programmes that had government agencies as principal recipients, had a large amount of funding, were focused on malaria, had weak initial proposals, or were evaluated by the accounting firm KPMG, scored lowest. Countries with a high number of doctors per head, high measles immunisation rates, few health-sector donors, and high disease-prevalence rates had higher evaluation scores. Poor countries, those with small government budget deficits, and those that have or have had socialist governments also received higher scores. INTERPRETATION: Our results show associations, not causality, and they focus on evaluation scores rather than actual performance of the programmes. Yet they provide some early indications of characteristics that can help the Global Fund identify and monitor programmes that might be at risk. The results should not be used to influence the distribution of funding, but rather to allocate resources for oversight and risk management.
BACKGROUND: The Global Fund to Fight AIDS, Tuberculosis and Malaria evaluates programme performance after 2 years to help decide whether to continue funding. We aimed to identify the correlation between programme evaluation scores and characteristics of the programme, the health sector, and the recipient country. METHODS: We obtained data on the first 140 Global Fund grants evaluated in 2006, and analysed 134 of these. We used an ordered probit multivariate analysis to link evaluation scores to different characteristics, allowing us to record the association between changes in those characteristics and the probability of a programme receiving a particular evaluation score. FINDINGS: Programmes that had government agencies as principal recipients, had a large amount of funding, were focused on malaria, had weak initial proposals, or were evaluated by the accounting firm KPMG, scored lowest. Countries with a high number of doctors per head, high measles immunisation rates, few health-sector donors, and high disease-prevalence rates had higher evaluation scores. Poor countries, those with small government budget deficits, and those that have or have had socialist governments also received higher scores. INTERPRETATION: Our results show associations, not causality, and they focus on evaluation scores rather than actual performance of the programmes. Yet they provide some early indications of characteristics that can help the Global Fund identify and monitor programmes that might be at risk. The results should not be used to influence the distribution of funding, but rather to allocate resources for oversight and risk management.