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, in a world-first pilot project run by researchers at UCL and King's College London.
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. It's similar to models like ChatGPT, which predicts the next word in a sentence based on what it's seen previously from data across the internet.
Foresight is being trained on routinely collected, de-identified NHS data, like hospital admissions and rates of Covid-19 vaccination, to predict potential health outcomes for patient groups across England. This could be events such as hospitalisation, heart attacks or a new diagnosis. Predicting these events early could enable targeted intervention, shifting towards more preventative healthcare at scale.
The pilot study operates entirely within the NHS England Secure Data Environment (SDE), a secure data and research analysis platform, that uniquely enables this 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 predictions about health outcomes across all demographics and for rare conditions.
Lead researcher Dr Chris Tomlinson (UCL Institute of Health Informatics) said: "AI models are only as good as the data on which they're trained. So if we want a model that can benefit all patients, with all conditions, then the AI needs to have seen that during training.
"Using national-scale data allows us to represent the kaleidoscopic diversity of England's population, particularly for minority groups and rare diseases, which are often excluded from research."
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.
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. And the ability to analyse healthcare risks and outcomes on a population level could offer critical support to the NHS when it comes to planning.
Simon Ellershaw, a PhD researcher at UCL Institute of Health Informatics, said: "Combining the computing resources needed for AI with NHS data has always been challenging, but thanks to the support of our partners we've been able to safely and securely apply state-of-the-art AI methods to NHS data at unprecedented scale."
The pilot study is an opportunity to test the model in a secure and safe environment, protecting privacy, and all predictions are rigorously tested for accuracy against real-world outcomes. Currently the model is using recent data, from November 2018 to the end of 2023, for a limited number of datasets and is made available for Covid-19 research.
Lead researcher Professor Richard Dobson, based at UCL Institute of Health Informatics as well as King's College London, who is also Deputy Director of the NIHR Maudsley Biomedical Research Centre, said: "This pilot is building on previous research that demonstrated Foresight's ability to predict health trajectories from data from two NHS trusts. To be able to use it in a national setting is very exciting as it will potentially demonstrate more powerful predictions that can inform services nationally and locally.
"Currently the data in this pilot is broad but shallow, and ultimately we'd like to harness the expertise and AI platforms behind Foresight by including richer sources of information like clinicians' notes, or results of investigations such as blood tests and scans if they become available."
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 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 BHF Data Science Centre 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."
Dr Vin Diwakar, National Director of Transformation at NHS England, said: "AI has the potential to transform the way we prevent and treat disease, if trained on large datasets and safely tested. The NHS Secure Data Environment has been fundamental to this pioneering research, shaping a future where earlier treatments and interventions are targeted to those who will benefit, preventing future ill health. This will boost our ability to move quickly towards personalised, preventative care."
Health data, AI, and the NHS
The Government recently announced the development of a Health Data Research Service, designed to support secure access to data for health researchers. The service is designed to ensure that projects like Foresight, which securely and safely access data to drive innovation and improve patient lives, will be much easier to support.
Health and Social Care Secretary Wes Streeting said: "Our Plan for Change is harnessing trailblazing AI to radically transform our NHS - while also protecting patient data with strict security procedures. I'm determined that we use this kind of groundbreaking technology to cut down on unnecessary hospital trips, speed up diagnosis times, and free up staff time. AI will be central as we bring our analogue NHS into the digital age to deliver faster and smarter care across the country."
Chief Scientific Advisor for the Department of Health and Social Care Lucy Chappell said: "Using AI to drive innovation across the NHS is key in making strides for better care to patients. This study could allow earlier diagnosis and treatment, enabling people to better manage their health and care, whilst ensuring patient data is safeguarded. The NIHR is proud to be supporting this work through our world-leading infrastructure."
Science and Technology Secretary Peter Kyle said: "This ambitious research shows how AI, paired with the NHS's wealth of secure and anonymised data, is set to unlock a healthcare revolution. This technology is transforming what's possible in tackling a host of debilitating diseases, from diagnosis, to treatment, to prevention. This is work that that will be instrumental to this Government's missions to overhaul healthcare and grow the economy, which sit at the heart of our Plan for Change. And an unrelenting focus on privacy and security, means people can rest assured that their data is in safe hands."
Foresight is a collaboration between NHS England, UCL, King's College London, National Institute for Health and Care Research Biomedical Research Centres (University College London Hospital, Maudsley), NHS Foundation Trusts (King's College Hospital, South London and Maudsley), British Heart Foundation Data Science Centre's CVD-COVID-UK/COVID-IMPACT Consortium, and technology partners AWS, Databricks, and CogStack.
Funders and oversight bodies include NHS AI Lab, UK Research and Innovation, Medical Research Council, National Institute for Health and Care Research, and Health Data Research UK.
