Data linkage infrastructure for cross-jurisdictional health-related research in Australia
Open accessAbstract
BACKGROUND: The 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". METHODS: The 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. RESULTS: The 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. CONCLUSIONS: This 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.
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Recent investments in infrastructure to link data across policy sectors for research purposes should increase opportunities to evaluate natural experiments.
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- Authors
- Boyd, J. H., Ferrante, A. M., O’Keefe, C. M., Bass, A. J., Randall, S. M., & Semmens, J. B.
- Affiliations
- Curtin University (AU)
- Commonwealth Scientific and Industrial Research Organisation (AU)
- Menzies Institute for Medical Research (AU)
- Corresponding author
- Boyd, James H
- Venue
- BMC Health Services Research
- Published
- 2012-12
- Volume
- 12
- Issue
- 1
- Pages
- 480-480
- ISSN
- 1472-6963 (ISSN-L)
- PMC
- PMC3579698
- OpenAlex
- W2049856698
- Cited by
- 79
- References
- 14
- Citations by year
- 2026: 3 · 2025: 4 · 2024: 5 · 2023: 6 · 2022: 4 · 2021: 7 · 2020: 3 · 2019: 6 · 2018: 7 · 2017: 8 · 2016: 5 · 2015: 11 · 2014: 5 · 2013: 5
- FWCI
- 8.91
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- BMC Health Services Research (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- UWA Profiles and Research Repository (UWA) (publishedVersion, other-oa)
- PubMed (publishedVersion)
- eCite Digital Repository (University of Tasmania) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- eSpace (Curtin University) (submittedVersion, cc-by)
- Figshare (submittedVersion, cc-by)
- Funders
- Australian Government
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Data Quality and Management
- Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Keywords
- data linkage, health data infrastructure, data integration, data governance, data privacy and confidentiality, linkage quality, Australia
- MeSH terms
- Australia, Confidentiality, Health Services Research, Humans, Medical Record Linkage, Policy Making, Software, State Medicine, Computer Security, Benchmarking
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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