LinXmart data matching software
The Centre for Data Linkage at Curtin University has developed innovative data matching software – LinXmart – which connects (links) data from different sources, both within or across organisational boundaries, allowing businesses to maximise insights about their customers and clients.
Background and overview
LinXmart makes it easy for organisations to match up and share data about their clients without ever revealing the identity of those clients. LinXmart converts personally identifiable information (PII) into a privacy-preserved state (through cryptographic processes) before it is shared with others. LinXmart matches this anonymised data to a very high standard; records do not have to match exactly, as the software can handle spelling/typing errors, changes in addresses, and when there is missing information in some of the records.
The technology was initially developed to deliver national data matching services to the Australian health sector but has now attracted considerable interest nationally and internationally.
Examples of use
Data linkage has been a powerful tool for the health research community in Australia. LinXmart was used to link hospital and death records data across four Australian states: New South Wales, Western Australia, South Australia and Queensland. The matching of over 40 million records made it possible for researchers to explore cross border hospital use and hospital related deaths.
LinXmart is also being used to ‘connect up’ other sensitive government datasets to enable analytics on service use. In a pioneering initiative, the Western Australian Government has partnered with Curtin University and the Western Australian Department of Health to establish the Social Investment Data Resource (SIDR) – a linked, administrative database containing de-identified information on individuals who have had contact with key government agencies. The SIDR is helping government and researchers to better design, target and evaluate social policies, services and intervention programs across Western Australia.
Current state of development
The technology is being offered under a licensing model, installed on the clients’ servers, and with associated training and consultancy services if required. Intellectual property is owned by Curtin University.A SaaS delivery model under development and due for release within the next 12 months
Licenses have been signed with a number of Australian clients, primarily at State and Commonwealth government level where data linkage and integration services are provided to enable research and evidence-informed policy development.
LinXmart has also been sub-licenced to a strategic partner and is being used as part of the Secure eResearch (SeRP) platform in the UK, Canada and Australia.
The most compelling benefits of LinXmart are:
- Linkage Quality – Ability for LinXmart to connect person-based records across datasets at the highest quality is a major competitive advantage to customers. High accuracy maximises insights and enables identification of potential outliers in their data.
- Risk reduction through Privacy-preserving linkage – No other enterprise software package currently offers this solution. The software does not require Personally Identifiable Information to be disclosed –significantly reducing privacy and reputational risks.
- Efficiency savings – The software has a range of features that handle the management of on-going data linkage. Ongoing linkage is typically complex and can consume valuable (and rare) organisational resources. LinXmart saves on these costs.
Curtin is looking for additional licensees. These could be government and research organisations, but also health insurance, big pharma or med-tech companies who are trying to bring together client data from disparate sources to accelerate medical discoveries and improve health outcomes.
Curtin is also looking to form partnerships with data platform providers who are interested in developing or improving upon their current data integration capabilities. Our software offers opportunities to customise data matching, improve the accuracy of matching and reduce risks associated with matching person-based records.