Power of big data to improve patient care in gastroenterology

There has been an explosion in the availability and accessibility of ‘big data’ and with it comes the obligation to maximise its potential to improve healthcare. This is across multiple domains including diagnostic algorithms, treatment efficacy, disease prevention and healthcare delivery. In a comprehensive review in this issue Catlow and colleagues discuss the key issues – big data analysis complements traditional research methodology; collection, curation and linking of datasets is challenging; artificial intelligence and machine learning algorithms can improve diagnostics, treatment stratification and thereby outcome. The authors consider these different themes in detail including summarising the definitions. The multiple sources of data are discussed including the strengths and weaknesses of different datasets. This includes discussion of the risks of bias – a larger sample can improve precision although doesn’t automatically reduce bias or sampling error (figure two). The potential to impact on healthcare is massive – the authors highlight the fact that real-world data need good data curation and an understanding of the clinical context and that we need to engage with our patients, so they understand how we are using …