• Laure Gossec, Joanna Kedra, Hervé Servy, Aridaman Pandit, Simon Stones, Francis Berenbaum, Axel Finckh, Xenofon Baraliakos, Tanja A Stamm, David Gomez-Cabrero, Christian Pristipino, Remy Choquet, Gerd R Burmester, and RadstakeTimothy R D JTRDJDept of Rheumatology, Clinical Immunology and Laboratory of Translational Immunology, Universitair Medisch Centrum Utrecht, Utrecht, The Netherlands..
• Institut Pierre Louis d'Epidémiologie et de Santé Publique, INSERM, Sorbonne Universite, Paris, France laure.gossec@gmail.com.
• Ann. Rheum. Dis. 2020 Jan 1; 79 (1): 69-76.

BackgroundTremendous opportunities for health research have been unlocked by the recent expansion of big data and artificial intelligence. However, this is an emergent area where recommendations for optimal use and implementation are needed. The objective of these European League Against Rheumatism (EULAR) points to consider is to guide the collection, analysis and use of big data in rheumatic and musculoskeletal disorders (RMDs).MethodsA multidisciplinary task force of 14 international experts was assembled with expertise from a range of disciplines including computer science and artificial intelligence. Based on a literature review of the current status of big data in RMDs and in other fields of medicine, points to consider were formulated. Levels of evidence and strengths of recommendations were allocated and mean levels of agreement of the task force members were calculated.ResultsThree overarching principles and 10 points to consider were formulated. The overarching principles address ethical and general principles for dealing with big data in RMDs. The points to consider cover aspects of data sources and data collection, privacy by design, data platforms, data sharing and data analyses, in particular through artificial intelligence and machine learning. Furthermore, the points to consider state that big data is a moving field in need of adequate reporting of methods and benchmarking, careful data interpretation and implementation in clinical practice.ConclusionThese EULAR points to consider discuss essential issues and provide a framework for the use of big data in RMDs.© Author(s) (or their employer(s)) 2020. No commercial re-use. See rights and permissions. Published by BMJ.

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