Advanced Analytics in Healthcare

Creating cutting-edge national-scale analytics infrastructure for health research and research translation
Four medical researchers gathering around a computer in a lab
Who will benefit
Health researchers using contemporary analytical methods such as AI to derive insights from data for better diagnostics and clinical care

The Challenge

The sensitive nature of much health information results in silos of data in local or secure environments, but modern data science depends on data aggregations of considerable scale and integration. Applying techniques like machine learning to sensitive data across multiple secure data repositories for national-scale health insights creates challenges that require national coordination and capability.

The Approach

The ARDC is uniquely positioned to coordinate and deliver national infrastructure capability to support advanced analytics in health research through the People Research Data Commons (People RDC).

Framework Development Phase

The Framework Development Phase will take place in the first half of 2024. It will involve co-designing a national framework, the specification and reference architecture for national infrastructure to support AI and other analytics in health research.

Two activities will be carried out:

This project will methodically capture researchers’ perspectives to help prioritise the ARDC’s infrastructure support for advanced health analytics with infrastructure.

This is a partnership between the ARDC and the Australian Data Science Network, a national network of data science research groups.

Participation opportunities will be shared in due course. To be alerted, please register your interest.

As a companion to the Framework Project, this project will create a demonstrator implementation of federated learning. It will provide a test bed for constructing a federated learning infrastructure for healthcare data.

Key project partners include UNSW, hospitals and academic partners collaborating on the Australian Cancer Data Network, a project supported by an ARDC co-investment through the Platforms Program.

The project focuses on developing federated learning implementation, which includes: 

  • comparing existing federated learning tools
  • selecting best-of-breed federated modelling options for healthcare data
  • considering national infrastructure provision. 

To contribute a use case to this project, please contact the ARDC.

Infrastructure Deployment Phase

Using the framework developed in the previous phase, coordinated implementation projects and services will commence in 2024 and 2025, focusing on analytics of health data from:

  • health studies (academia)
  • the health system (government)
  • national facilities (NCRIS).

Once developed and implemented, the analytics infrastructure and the national capabilities built through our other streams of programs under the People RDC – namely, data strategy and discovery, secure data access, and data integration – will be brought together and applied to improve health services and address specific disease areas.


At the Framework Development Phase, we will work with selected national groups and conduct broad consultation. 

The Infrastructure Deployment Phase will offer further opportunities to participate for researchers, policymakers and innovators. There will also be more opportunities for partnerships with institutions, data custodians and technology service providers.

We invite you to register your interest in the People RDC and keep in touch with us through public consultations.

Target Outcomes

At the Framework Development Phase (the first half of 2024), a Framework Project and a Demonstrator Project will be carried out with the following outcomes in mind:

Framework Project

Through this project, the research community will be able to define requirements and shape national capability including:
  • underpinning compute and storage such as cloud GPU access
  • national reference datasets and synthetic data
  • national federation services and coordination for machine learning
  • shared tools and platforms
  • policy, skills, support materials, resources and education.

Demonstrator Project

As a companion to the Framework Project, this project will create a demonstrator implementation of federated learning. It will provide a test bed for constructing a federated learning infrastructure for healthcare data.

Together, the 2 projects will help develop a reference architecture/framework for advanced analytics, and facilitate meta-specifications for scheduled ARDC services, capabilities and co-investments. 

The Infrastructure Development Phase (2025 to 2028) will provide national coordination, capability, partnerships and services supporting national scale analytics of health data.