Lessons learned from big data (APRICOT, NECTARINE, PeDI)

Abstract

Big data in paediatric anaesthesia allows the evaluation of morbidity and mortality of anaesthesia in a large population, but also the identification of rare critical events and of their causes. This is a major step to focus education and design clinical guidelines. Moreover, they can help trying to determine normative data in a population with a wide range of ages and body weights. The example of blood pressure under anaesthesia will be detailed. Big data studies should encourage every department of anaesthesia to collect its own data and to benchmark its performance by comparison with published data. The data collection processes are also an opportunity to build collaborative research networks and help researchers to complete multicentric studies. Up to recently, big data studies were only performed in well developed countries. Fortunately, big data collections have started in some low and middle income countries and truly international studies are ongoing.