The “Who, What, Where, When, How and How Much” of International Health Aid – But Not the “Why”

A study by Nirmala Ravishankar and colleagues at Chris Murray’s Institute for Health Metrics and Evaluation (IHME) published today in the Lancet and reported at Forbes and MSNBC gives the most comprehensive estimates yet available of the total amount that people in higher income countries have been spending to try to improve the health of those living in low and middle income countries. For you data junkies, that number was $19 billion in 2006 and $22 billion in 2007.The many reasons why improved information on resource flows would contribute to better health assistance policy are laid out in the 2007 CGD study entitled Following the Money: Toward Better Tracking of Global Health Resources. The new IHME study is valuable for providing the first comprehensive point of reference for the amount actually disbursed on health assistance worldwide. The figures are higher than those previously available from the OECD, which recently estimated that health assistance by bilaterals and multilaterals totaled only $12.6 billion in 2006. The total is also substantially smaller than the $45 billion that was recently suggested by the Council on Foreign Relations for that same year.Do we have reason to believe that the new estimates are more accurate than previous efforts? The starting point for IHME work was the OECD-DAC database. But unlike the OECD’s own statisticians, who confined themselves to analysis of aid commitments, the IHME team attempted to estimate total disbursements for health by all of the donors. While we would prefer to know disbursements than commitments, the task is challenging, because donors under-report aid disbursements to the DAC database. To compensate for this underreporting, and sometimes to fill in other gaps in the data, the IHME team were forced to fall back on data imputation, an approach which requires heroic assumptions. (We at the CGD have poked some fun at IHME’s penchant for data imputation before here and here, but we also practice a bit of this arcane art ourselves, e.g. here and here.) Although neither the published paper not the web appendix provides full details on how the authors imputed the missing numbers, on balance I prefer their imputed disbursement numbers to raw commitment numbers. I just wish the authors had told us what percentage of their totals depends upon imputed numbers.The authors go beyond their imputed inflation of the DAC database to add estimates of flows from philanthropic organizations and from US-based NGOs. This is a valuable contribution to our understanding of total health assistance flows, since by 2007 they account for more than 20% of all estimated disbursements. One wishes they had been able to include major international NGOs based outside the US, like Medecins sans Frontier and Oxfam, but hopefully they will issue updates of this data every year and will succeed in soliciting input from the missing organizations for those updates.The authors provide a large number of colorful and informative bar charts to track assistance funding over time, from the various sources to the various destinations. However, causal analysis based on these numbers is fraught with peril. Unfortunately, the authors themselves engage in some problematic causal analysis when they point with some unstated emotion (surprise? alarm? ) to the positive but imperfect correlation between the total disease burden in a country and the total amount of health assistance it receives. If we believe that health assistance should reduce disease burden then we might expect this correlation to be negative. If we believe that health assistance should be directed to places with higher burdens, then the correlation should be positive. If we think the main criterion for allocating foreign assistance should be the cost-effectiveness of spending opportunities, not the size of the burden, and that many other factors influence health beside health assistance from abroad, then we should expect that the correlation will be weak. If we believe all of these things at once, as most of us do, then we have no prior belief whatsoever about the correlation between burden and assistance and will find it to be uninteresting. So why the focus on this correlation at the end of the paper?Which brings me to the biggest gap in the paper – one that the authors would not have been able to fill because of the way this data is reported. The DAC breaks down health assistance in many ways, including a distinction between budget support and project support. But there is no distinction between results-based health assistance like GAVI and the rest of health assistance that one way or another only funds inputs without reference to outputs. Since the use of performance based incentives is becoming more popular, I expect that when this study is replicated ten years from now, the future authors will be able to show that an increasing proportion of total assistance is extended in the context of some kind of results framework. And over time, I would expect that countries which receive a larger share of their assistance in this way will experience more rapidly falling disease burdens. Now that will be interesting.