From cause to care: Can a triple approach to better population data improve the global outlook of congenital heart disease?

Abstract

Congenital heart disease (CHD) is common, costly, and critical. Approximately half of all infant deaths due to congenital anomalies are associated with CHD or neural tube defects. As infant mortality improves due to better infection control and peripartum care, congenital anomalies are becoming a key driver of pediatric survival and health. Improving CHD prevention and care globally will play a significant role toward key goals such as United Nation's sustainable development goals (SDGs) of good health and well-being (SDG 3) and reduced inequalities (SDG 10). This review addresses two questions: how can we reinterpret and reframe available data on CHD to spur action in prevention and care? How can we re-engineer how we currently track CHD in populations to efficiently generate new data to assess successes and detect gaps in prevention and care? Answering these questions requires understanding the causal chain of disease, from cause to CHD occurrence to health outcomes. This perspective provides a logical basis for two innovations. First, develop a data-driven message that reframes epidemiologic and clinical data in terms of incentives for action, evidence for change, and strategies for population-wide impact. Second, through partnerships between clinical and public health systems, implement an integrated "triple surveillance," which, in the same population, concurrently tracks the three elements of the causal chain-causes, disease occurrence, health outcomes. By streamlining activities and minimizing operational waste, such systems can have a vital role in improving prevention and care on a population level, including in many low and middle-income countries.