5. Simplify and streamline access to existing health data - That the Australian Government lead a project to simplify and streamline safe access to Australia’s health data sets for researchers and other relevant stakeholders, so that existing health data may be more effectively utilised in research projects to improve the health outcomes of Australians. 6. Trial new approaches to understand metastatic breast cancer prevalence - That Cancer Australia fund the trialling of new approaches to understand the number of people diagnosed with metastatic breast cancer across the country. This could include federated learning systems and other innovative confidential data-sharing capabilities to draw analyses.† Medium to longer term recommendations 7. Establish dedicated funding for routine breast cancer stage and recurrence capture – That all state and territory governments are committed to provide dedicated and enduring funding to population-based cancer registries to enable the routine
collection, collation and reporting of breast cancer stage and recurrence data to form part of core business activities. Cost-effective, automated systems should also be funded for data retrieval and structured input into medical systems. 8. Establish a national cancer data framework – That the Australian Government, in collaboration with state and territory governments, the AIHW, Cancer Australia, the AACR, professional associations, cancer consumer organisations and other relevant cancer sector stakeholders, establish a national cancer data framework centralising leadership, accountability and minimum cancer data standards. Consideration may be given to commence this framework, as part of the Australian Cancer Plan, for breast cancer streams in the first instance. 9. Invest in and support electronic structured reporting – That the Australian Government and state and territory governments invest in electronic structured reporting for pathology data and imaging data, as well infrastructure to support the increased automation of cancer notification processes.
* Data linkages bring together information from different sources to create a new, richer dataset. Data linkages enable large-scale analysis of whole populations across the healthcare system. † Federated learning is a machine learning method that trains an algorithm via multiple independent sessions, each using its own dataset. Fundamentally, it does not require an exchange of data to centralised servers.
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