Synthetic Health Data Education and Training Masterclass Series

Opportunity 

Access to sensitive health data remains a major barrier to research, workforce education and digital-health innovation. Synthetic health data can help organisations explore datasets, test analytical pipelines and build capability without directly exposing patient information. But realising this opportunity requires more than technical tools: organisations also need fit-for-purpose governance, validation methods, ethical oversight and public trust.  

Led by La Trobe University with support from the DHCRC Synthetic Data (SynD) Community of Practice and international experts from Swansea University and the Secure Anonymised Information Linkage (SAIL) Databank, this masterclass series aimed to address critical barriers in health data access, privacy, and interoperability by supporting participants to explore federated AI models for multi-site analysis, understand ethical, regulatory, and governance considerations, and get hands-on experience with AI-enhanced low- and high-fidelity synthetic data.  

Project Objectives  

Led by La Trobe University, the project set out to help build Australia’s capability to generate, assess and use synthetic health data responsibly with a targeted education, training, and masterclass series on synthetic health data and AI-driven analytics. The training was designed to equip participants with the skills, knowledge, and confidence to generate, manipulate, and analyse synthetic datasets responsibly and effectively in healthcare research, education, and innovation, connecting technical methods with practical questions about privacy, utility, social licence and organisational adoption.