Data sharing across osteoarthritis research groups and disciplines: Opportunities and challenges. Issue 1 (March 2022) - Evans, Jill; Hamilton, Rebecca I.; Biggs, Paul; Holt, Cathy; Elliott, Mark T.
Abstract: Background: Osteoarthritis is a heterogeneous condition characterised by a wide variety of factors and represents a worldwide healthcare challenge. There are multiple clinical and research specialisms involved in the diagnosis, prognosis and treatment of osteoarthritis, and there may be opportunities to share or pool data which are currently not being utilised. However, there are challenges to doing so which require carefully structured solutions and partnership working. Methods: Interviews were conducted with nine experts from various fields within osteoarthritis research. A semi-structured approach was used, and thematic analysis applied to the results. Results: Generally, osteoarthritis researchers were supportive of data sharing, provided it is done responsibly and without impacting data integrity. Benefits identified included increasing typically low-powered data, the potential for machine learning opportunities, and the potential for improved patient outcomes. However, a number of challenges were identified, relating to: data security, data harmonisation, storage costs, ethical considerations and governance. Conclusions: There is clear support for increased data sharing and partnership working in osteoarthritis research. Further investigation will be required to navigate the complex issues identified; however, it is clear that collaborative opportunities should be better facilitated and there may be innovative ways to do this. It is also clear that nomenclature within different disciplines could be better streamlined, to improve existing opportunities to harmonise data.