TY - JOUR
AU - Eradat Oskoui, Solmaz
AU - Retford, Matthew
AU - Forde, Eoghan
AU - Barnes, Rodrigo
AU - Hunter, Karen
AU - Wozencraft, Anne
AU - Thompson, Simon
AU - Orton, Chris
AU - Ford, David V.
AU - Heys, Sharon
AU - Kennedy, Julie
AU - McNerney, Cynthia
AU - Peng, Jeffrey
AU - Ghanbariadolat, Hamed
AU - Rees, Sarah
AU - Mulholland, Rachel
AU - Sheikh, Aziz
AU - Burgner, David
AU - Brockway, Meredith
AU - Azad, Meghan B.
AU - Rodriguez, Natalie
AU - Zoega, Helga
AU - Calvert, Clara
AU - Miller, Jessica E.
AU - Fiorentino, Nicole
AU - Racine-Poon, Amy
AU - Haggstrom, Jonas
AU - Postlethwaite, Neil
AU - Stock, Sarah J.
PY - 2024
DA - November
TI - Developing a Prototype for Federated Analysis to Enhance Privacy and Enable Trustworthy Access to COVID-19 Research Data
JO - International Journal of Medical Informatics
VL - 195
DO - https://doi.org/10.1016/j.ijmedinf.2024.105708
AB - Background: The use of federated networks can reduce the risk of disclosure for sensitive datasets by removing the requirement to physically transfer data. Federated networks support federated analytics, a type of privacy-enhancing technology, enabling trustworthy data analysis without the movement of source data.  Objectives: To set out the methodology used by the International COVID-19 Data Alliance (ICODA) and its partners, the Secure Anonymised Information Linkage (SAIL) Databank and Aridhia Informatics in piloting a federated network infrastructure and consequently testing federated analytics using test data provided from an ICODA project, the International Perinatal Outcome in the Pandemic (iPOP) Study. To share the challenges and benefits of using a federated network infrastructure to enable trustworthy analysis of health-related data from multiple countries and sources. Results: This project successfully developed a federated network between the SAIL Databank and the ICODA Workbench and piloted the use of federated analysis using aggregate-level model outputs as test data from the iPOP Study, a one-year, multi-country COVID-19 research project. This integration is a first step in implementing the necessary technical, governance and user experiences for future research studies to build upon, including those using individual-level datasets from multiple data nodes.  Conclusions: Creating federated networks requires extensive investment from a data governance, technology, training, resources, timing and funding perspective. For future initiatives, the establishment of a federated network should be built into medium to long term plans to provide researchers with a secure and robust data analysis platform to perform joint multi-site collaboration. Federated networks can unlock the enormous potential of national and international health datasets through enabling collaborative research that addresses critical public health challenges, whilst maintaining privacy and trustworthiness by preventing direct access to the source data.
PB - Elsevier
UR - https://www.research.ed.ac.uk/en/publications/617e8be6-5611-4f8a-933f-00aa9e30b045
KW - Coronavirus (COVID-19)
ER