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.
Professor Richard Dobson, Deputy Director of the NIHR Maudsley BRC and co-lead researcher at King’s IoPPN and UCL
07 May 2025
Groundbreaking AI trained on de-identified patient data to predict healthcare needs
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. The pilot study is being run by researchers at the Institute of Psychiatry, Psychology & Neuroscience (IoPPN) at King’s College London and University College London (UCL). The model could transform patient care, identifying opportunities where early interventions might significantly improve or save lives.
Foresight, a generative AI model developed at King's out of the CogStack platform, learns to predict what happens next based on past medical events. It is similar to models like ChatGPT, which predicts sequences based on what it’s seen previously in data.
In this pilot study, 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. These 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 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.
An earlier version of Foresight was previously trialled within two NHS Foundation Trusts (King’s College Hospital and South London and Maudsley) as part of a collaboration between King’s, UCL, the National Institute for Health and Care Research (NIHR) Maudsley Biomedical Research Centre (BRC) and NIHR UCLH BRC. The research, published in The Lancet Digital Health, demonstrated its potential for predicting the health trajectory of patients by forecasting future disorders, symptoms, medications and procedures.
By including data covering England’s entire population in the pilot study, the model can be used to make predictions about health outcomes across all demographics and for rare conditions.
The development of the model was supported by the NIHR Maudsley BRC and the NIHR UCLH BRC.
Addressing health inequalities
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.
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.
Dr Chris Tomlinson, co-lead researcher from UCL
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 made available for COVID-19 research.
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 centre of any guidance developed around the model’s use and predictions, to make sure this research and its applications are in their best interests.
The researchers underwent rigorous approval processes with the British Heart Foundation Data Science Centre at Health Data Research UK 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.
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.”
Professor Angela Wood, Associate Director at the BHF Data Science Centre at Health Data Research UK, said, “The Foresight model has the potential to support healthcare professionals to make timely and effective medical decisions for high-risk patients, and to help address health inequalities by ensuring everyone is represented in predictive healthcare.”
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.”
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.
Lucy Chappell, Chief Scientific Advisor for the Department of Health and Social Care
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, King’s College London, UCL NIHR Maudsley BRC, NIHR UCLH BRC, King’s College Hospital NHS Foundation Trust, South London and Maudsley NHS Foundation Trust, British Heart Foundation Data Science Centre’s CVD-COVID-UK/COVID-IMPACT Consortium, AWS, Databricks and CogStack. It is funded by NHS AI Lab, UK Research and Innovation, Medical Research Council, NIHR and Health Data Research UK.
CogStack was developed by researchers at King’s College London, King’s College Hospital NHS Foundation Trust, Guy’s and St Thomas’ NHS Foundation Trust, South London and Maudsley NHS Foundation Trust, UCL and UCLH.
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Professor of Medical Bioinformatics