Table 3

Research agenda

ThemeResearch point
Data sourcesLeverage EULAR legacy initiatives around core datasets that should be collected in research (and usual care) as foundations for successful big data projects in the field of RMDs
Determine the optimal use of eHealth data through digital traces and patient-generated/patient-reported data
Determine the potential use of database linkages, such as healthcare system claims databases
Data accessIdentify the mechanisms supporting and implications following open access to, and sharing of, big data
Assess positive and negative aspects of data sharing in terms of article impact (academic/social) and translational success
Identify the challenges, opportunities and solutions for international data sharing
Develop a repository of privacy rules in different European countries
Identify public platforms for data and how the public can access their own data within big data sets for knowledge/education/self-management purposes
AnalysesEvaluate and compare statistical methods and benchmarking of big data
Develop methods of assessment and minimisation of bias and of generalisation/reproducibility
Determine the most appropriate open source tools to improve reproducibility of the results
Perform a critical assessment of statistical significance vs clinical relevance of the results obtained from medical big data
ReportingStimulate consistent reporting of big data studies using validated reporting guidelines
Stimulate and facilitate open sharing of codes/scripts
ImplementationDetermine the value of algorithms and big data findings in terms of quality of care and cost effectiveness
Assess levels of evidence in evidence-based medicine when based on big-data studies
Manage the potential rapid and frequent changes of outcomes when implementing big data findings
TrainingIdentify opportunities for training via the EULAR School of Rheumatology and other relevant organisations
Assess the importance of inter and cross-disciplinarity
Assess the place of multidisciplinary training at specific stages of individual careers and/or at specific stages of specific projects
Consider introducing a basic big data/systems biology/bioinformatic course at bachelors’ levels for healthcare professionals
CollaborationsStimulate national and international interest among the data scientist community in relation to RMDs
Promote the integration of RMD fluent ‘ethical experts’ in collaborative teams working on big data
Ethics and rolesStimulate ethical and moral discussions with patients and ‘data donors’ specifically in the context of big data, addressing topics such as informed consent/assent, confidentiality, anonymity and privacy concerns, particularly with regards to the re-use of the data
Discuss the roles and responsibilities of healthcare professionals, scientists/researchers and patients in relation to big data
Assess issues pertaining to commercial use of big data, particularly involving public–private consortiums and the use of multiple datasets
Assess the effects of big data results on use of drugs including in unauthorised/compassionate use cases
Define the role, modalities and rules of patient engagement in the generation and exploitation of big data
  • RMD, rheumatic and musculoskeletal disorder.