Data linkage infrastructure for cross-jurisdictional health-related research in Australia

Abstract

BackgroundThe Centre for Data Linkage (CDL) has been established to enable national and cross-jurisdictional health-related research in Australia. It has been funded through the Population Health Research Network (PHRN), a national initiative established under the National Collaborative Research Infrastructure Strategy (NCRIS). This paper describes the development of the processes and methodology required to create cross-jurisdictional research infrastructure and enable aggregation of State and Territory linkages into a single linkage “map”.MethodsThe CDL has implemented a linkage model which incorporates best practice in data linkage and adheres to data integration principles set down by the Australian Government. Working closely with data custodians and State-based data linkage facilities, the CDL has designed and implemented a linkage system to enable research at national or cross-jurisdictional level. A secure operational environment has also been established with strong governance arrangements to maximise privacy and the confidentiality of data.ResultsThe development and implementation of a cross-jurisdictional linkage model overcomes a number of challenges associated with the federated nature of health data collections in Australia. The infrastructure expands Australia’s data linkage capability and provides opportunities for population-level research. The CDL linkage model, infrastructure architecture and governance arrangements are presented. The quality and capability of the new infrastructure is demonstrated through the conduct of data linkage for the first PHRN Proof of Concept Collaboration project, where more than 25 million records were successfully linked to a very high quality.ConclusionsThis infrastructure provides researchers and policy-makers with the ability to undertake linkage-based research that extends across jurisdictional boundaries. It represents an advance in Australia’s national data linkage capabilities and sets the scene for stronger government-research collaboration.

Hospital admissions in children with cerebral palsy: a data linkage study

“…[23][24][25] Limitations associated with this methodology include a lack of data on CP severity and complexity as well as the potential to miss CP admissions where CP is not listed as a discharge diagnosis. 26 Linkage of multiple data sets is most straightforward when the various data sets use a common unique identifier. 23,25 On the other hand, linking a CP register to an administrative health services data set to investigate service use in this population offers a number of advantages.…”

The effect of data cleaning on record linkage quality

“…In Australia, research carried out using linked health data has led to numerous health policy changes [1,2], and the success of previous linkage efforts has led to the development of national linkage infrastructure [3]. …”

Accuracy and predictive value of incarcerated adults' accounts of their self-harm histories: findings froman Australian prospective data linkage study

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