People centred population based linked data research and analysis

Originally piloted as a multi-departmental project within the Government of South Australia, SA NT DataLink is now the key provider of data linkage services in South Australia, the Northern Territory of Australia and the Commonwealth of Australia, enabling academics and policy makers to undertake research, policy, planning and evaluation. Uniquely governed by a broad range of consortium partners, SA NT DataLink’s business model operates with flexibility to adapt to researcher priorities and government requirements. Its Data Linkage Unit (DLU) routinely links data from over 50 sources with more than 57 million records on approximately 2.9 million individuals. It arguably provides the broadest range of linked data sources in Australia, focussing on administrative datasets and clinical registries from various health and human services domains. Operating in strict adherence with the separation principal, SA NT DataLink’s Data Integration Unit (DIU) separately manages anonymised clinical and service use data in collaboration with the respective data custodians through the Custodian-Controlled Data Repository (CCDR), allowing approved analysts to efficiently access high quality linked anonymised data. To protect individual privacy throughout the process of data linkage and data provision, SA NT DataLink’s processes align with state, territory and federal privacy legislations. Operating consistently with National Health and Medical Research Council (NHMRC) guidelines, linkage projects are subject to approvals by the relevant data custodians and NHMRC approved Human Research Ethics Committees (HREC). SA NT DataLink has provided linkage services to more than 100 data linkage projects, informing nationally significant research and policy initiatives, including an intervention to improve indigenous children’s hearing and child development. To respond to the increasing demand for data linkage service, SA NT DataLink is improving its internal systems and linkage processes, ranging from easier access to research variable level metadata to more efficient storage of linkage mapping using a NoSQL graph daatabase.