We maintain unidentified records in an interconnectable form and provide analysis of selected data in an anonymous form after other security precautions. Authorized researchers are able to reach data remotely around the world, with analytical tools. As the data obtained for the research is anonymized, the work is carried out without the researchers knowing the identities of the people represented. We do this by working with data custodians, academics, regulators, public doctors, practitioners and policy makers from Wales, the UK and internationally. Organisation for Economic Co-operation and Development (2015) Health Data Governance: Privacy, Monitoring and Research. OECD Health Policy Studies, OECD Publishing, Paris. www.oecd.org/governance/health-data-governance-9789264244566-en.htm of budgetary constants and rapid and varied developments in data and social environments are ongoing challenges and require ongoing efforts and adaptations. These are embodied in issues such as . B, such as: effectively meeting the needs of several programs and funders; Ensure secure access to high-granular data to maximize research potential and meet the needs of different research communities.
We strive to adopt a “one-off” approach based on the flexible and multifunctional developments of the UK Serp and NRDA. It is a pattern that we follow in the other centres that we host not to work in silos, but to share learning and know-how to avoid duplication. We also appreciate the opportunities for cooperation and mutual learning offered by the International Population Data Linkage Network (IPDLN). The usefulness of the database is demonstrated by the growing commitment to high-quality research studies and we want to make this resource available to researchers in the best way possible. Initially, HIRU analysts played an active role in most studies and prepared data views for researchers, but more and more studies began with skills and resources for routine data analysis. There are now many studies in which data are used in different ways and three examples are cited here. 1) The data are used for cohort development in a Study funded by the Medical Research Council on Ankylosing Spondylitis (AS). This project combines the clinical data of rheumatologists (diagnosis, MRI/radiography) with routine datasets such as general practical records, hospital data (ambulatory clinical data, hospital data, accidents and emergencies, laboratory/pathology data) and social service databases, as well as data collected directly by patients themselves (disease activity, function, quality of life).