Metrics of the Sustainable Developments Goals: Can we trust our data?

This article was exclusively written for the Sting by Ms Laura Jung, a medical student from Leipzig, Germany. She is affiliated to the International Federation of Medical Students Associations (IFMSA). However, the opinions expressed in this piece belong strictly to the writer and do not necessarily reflect IFMSA’s view on the topic, nor The European Sting’s one. From a public health perspective, metrics of the sustainable development goals (SDGs) are seen as the main instrument telling us if set goals have been achieved. They are also an unquestionable driver which enables and encourages efforts to produce better health. We use large, quantitative data sets to compare health improvements in different regions and try to make sense of the complexities around sustainable development. However, the benefits of these quantitative metrics are not indisputable and several difficulties might arise. Firstly, while the numbers might be presented as facts, they are often rather loose estimates of the situation than actual counts. This is certainly the case for measures of maternal mortality, which are especially hard to obtain in countries where most deliveries are taking place outside of Health Care Facilities. Reasons for inaccurate numbers include lack of diagnostic methods or alternative explanations for causes of death as well as deliberate data manipulation in order to improve hospital performances (Adams 2016). The methods used to create big data sets seem useful to produce a “snapshot”, but might be inappropriate to capture a more holistic picture of local situations. No matter what exactly the reasons for imprecise data might be, they are often not acknowledged in the later process of data handling. Once collected, the numbers travel to data management centres in the Western World, where they are analysed in the most careful way but without taking their origin into account. The lack of interaction with the local can be seen critical. As all too often, once the data is published with apparently objective tables and informative graphs, it is uncritically accepted as a fact. If we don´t want to base decisions about health policies and funding on loose estimates, we should start to more careful with these numbers and stop to systematically disentangle them from their context, just because it gives as the feeling of making complex health issues more manageable. A second, and perhaps even more important issue around metrics in development, is our tendency to perceive quantitative data as apolitical and value-free. An unbiased starting point for evidence-based decision-making, leaving out personal preferences and politics. We should be aware that metrics are never actually neutral. When we look closely, we can see how historical inequalities are reproduced through measurement of development. What is measured and which methods are used, is decided in powerful headquarters in the Western World.  Local perspectives are often not included in the agenda setting and methods of data collection are more adapted to the needs of donor organisations than that they are reflecting local realities. That doesn’t mean metrics cannot be useful for the evaluation of the SDGs. But when we use them, we should be aware that we might simplify complex health issues to statistical problems and that our data might not always be as precise and as neutral as we would like it to be. References Adams, Vincanne, ed. 2016  Metrics. What counts in global health. Critical global health About the author

Laura is a medical student from Leipzig, Germany. Currently she is taking a break from her medical studies and intercalates in a one-year MSc programme in Public Health at the London School of Hygiene and Tropical Medicine.