Research
Groundbreaking AI trained on de-identified patient data to predict healthcare needs
In a world-first study, an artificial intelligence (AI) model is being trained on a set of NHS data for 57 million people in England, from which personal information has been stripped away. Researchers say the model could transform patient care, identifying opportunities where early interventions might significantly improve or save lives.
Foresight, a generative AI model, learns to predict what happens next based on previous medical events. The pilot study is being run by researchers at University College London (UCL) and King’s College London (KCL).
A window of opportunity
Foresight is being trained on routinely collected, de-identified NHS data such as hospital admissions, to predict potential health outcomes for patient groups across England. This could be events such as hospitalisation, heart attacks or a new diagnosis.
The researchers believe the model's predictive power could pinpoint high-risk patient groups, opening up a window of opportunity to intervene to improve and save lives. Due to the diversity and completeness of the training data, the model could also help to highlight and address healthcare inequalities.
Professor Bryan Williams, our Chief Scientific and Medical Officer, said: “Artificial intelligence has the potential to revolutionise the diagnosis, treatment and care of people living with cardiovascular disease.
“The vital insights the Foresight model provide could transform our understanding of population and individual risk of developing heart disease, enabling us to better prevent heart attacks and stroke before they happen.
“To develop this lifesaving technology, researchers will access and analyse anonymous patient data securely and safely, ensuring public confidence, while placing the UK at the cutting edge of data science for health.”
Keeping data safe
The pilot study operates entirely within the NHS England Secure Data Environment (SDE), a secure data and research analysis platform, that uniquely enables this groundbreaking work by providing controlled access to de-identified health data from the 57 million people living in England.
Access to data at this scale is only made possible through the NHS England SDE, where both the AI model and all patient data remain under strict NHS control.
By including data covering England’s entire population, the model can make unbiased predictions about health outcomes across all demographics and for rare conditions.
Through rigorous approval processes, the British Heart Foundation Data Science Centre at Health Data Research UK made it possible for the researchers to access and work in the SDE. The Centre also involved members of the public, who continue to contribute to approving and shaping the research.
Going further with the data
In the future the researchers would like to train the model further on deeper data sources, going back further in time. They’re also exploring how to responsibly expand the scope of the model, which is currently restricted to COVID-related research.
However, the researchers are clear, patients and the public also must be at the heart of any guidance developed around the model’s use and predictions, to make sure this research and its applications are in their best interests.
A public contributor, involved in reviewing and approving this project, said: "As a patient, I’m interested in how this research could help identify linked health conditions, reduce the risk of developing new ones, and support those who face challenges accessing healthcare.
“It’s important that people know how their health data is being used, so it’s encouraging to see a focus on transparency and making sure AI is used in the NHS in a safe, ethical way with public benefit at its heart.”