How it works | Open Health

We create opportunities

With Open Health, organisations can:

Explore new questions together before committing to data sharing or models
Combine clinical, genomic, behavioural, social, and environmental insights
Build AI-powered solutions grounded in real-world context
Collaborate across sectors while keeping data local, secure, and governed

This enables the creation of unique knowledge at the intersection of disciplines—supporting population health, prevention, precision decision-making, and system-level innovation.

A real use case: personalised AI for diabetes management

Imagine three organisations working together to support people living with diabetes:

A university hospital brings clinical expertise, outcomes data, and understanding of disease progression
A retailer or pharmacy sees real-world patterns in food choices, purchasing behaviour, and medication use
An employer understands daily routines, workplace environments, and wellbeing initiatives that influence long-term behaviour

Individually, each organisation holds part of the picture.

Together, they could build a far more personalised, context-aware AI solution for diabetes management.

But regulatory, ethical, and commercial constraints mean their data cannot be shared.

This is where Open Health changes what’s possible.

Using Open Health:

Partners define a shared goal: developing a personalised AI solution to support diabetes management—without sharing raw data
Each organisation declares what insights it can contribute, under its own governance and compliance rules
Open Health enables permissioned discovery, helping partners understand what can be learned and what is feasible before any model is built
Federated analytics and AI models are then run locally at each organisation, with computation brought to the data
Only approved, aggregated outputs are shared—ensuring transparency, auditability, and trust

The result is a collaborative, AI-powered solution that combines clinical insight, lifestyle context, and real-world environments—while keeping data secure and under local control.

More specific use case example

From one use case to many

The diabetes use case illustrates just one way Open Health can be applied. It is not the destination, but an example of a much broader capability.

Open Health is designed to support many partners, many priorities, and many contexts — across clinical care, public health, life sciences, research, policy, and industry. Whether organisations are working on chronic disease management, precision medicine, population health, drug development, or prevention, the same federated foundation applies.