In many cases, the research question, design and methodology follow the availability of data. A prominent example is the emergence of genetic information after the completion of the Human Genome Project in 2003, which ultimately enabled the establishment of precision medicine as a health science discipline. Health economics analysis also relies upon data availability.
In the setting of global health economics research, available data often limits the scope of what is possible to study. Identifying the effect of a specific technology, innovation or a policy within a health system is one of the most important and most challenging research objectives in global health economics. Health systems in developing countries often have limited capability to monitor, track or verify inputs and outcomes. Even when information is recorded, it is sometimes not collected regularly or made available in accessible formats and may be subject to measurement error. Thus, evaluation and decision making is more difficult.
Improving the efficiency of resource allocation and utilisation, for instance through the design of health benefits packages, is a data hungry exercise. It comprises knowledge of the epidemiologic context, the health system characteristics, organisational and financial arrangements, and intervention specifications. Understanding what data is available is a priority during the early stages of Thanzi la Onse. We have scanned the research landscape for all available information to understand what is feasible to analyse and this has helped us to fine tune our potential research questions and designs.
Identifying the effect of a specific technology, innovation or a policy within a health system is one of the most important and most challenging research objectives in global health economics.
The three research themes; epidemiology, health economics and politics within Thanzi la Onse comprise researchers with different skillsets, knowledge, and perspectives. During the project’s and the Thanzi la Onse data meeting hosted by Imperial College London, we managed to inform each other about ongoing research or research plans, identify overlapping data sources and data needs, exchange information on where to look for additional information and discussed how to take forward the use of data in interdisciplinary collaborations. The data landscape consists of a multitude of survey information, national data repositories, administrative information, as well as qualitative information. Given that effective collaboration across our partner institutions is an important driver of research success, we have established regular opportunities to share information in regular Webinar series, biennial research meetings, and the annual conference in Malawi.
Available secondary data might be limited, but in Thanzi la Onse we’re determined to make best use of all resources and analyse data in ways that produce new, reliable and valuable insights for health policy.
By: Matthias Arnold, Wiktoria Tafesse and Dominic Nkhoma| October 10th 2018