RT Journal Article
SR Electronic
T1 EULAR points to consider for the use of big data in rheumatic and musculoskeletal diseases
JF Annals of the Rheumatic Diseases
JO Ann Rheum Dis
FD BMJ Publishing Group Ltd and European League Against Rheumatism
SP annrheumdis-2019-215694
DO 10.1136/annrheumdis-2019-215694
A1 Laure Gossec
A1 Joanna Kedra
A1 Hervé Servy
A1 Aridaman Pandit
A1 Simon Stones
A1 Francis Berenbaum
A1 Axel Finckh
A1 Xenofon Baraliakos
A1 Tanja A Stamm
A1 David Gomez-Cabrero
A1 Christian Pristipino
A1 Remy Choquet
A1 Gerd R Burmester
A1 Timothy R D J Radstake
YR 2019
UL http://ard.bmj.com/content/early/2019/07/07/annrheumdis-2019-215694.abstract
AB Background Tremendous 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).Methods A 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.Results Three 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.Conclusion These EULAR points to consider discuss essential issues and provide a framework for the use of big data in RMDs.