The project, run by Holly Health with Loughborough University and Modality Partnership, found that over a three-month period more than 180 users improved their engagement in self-managing their conditions by 21%.
Additionally, healthy habits amongst users rose by 10%, which has the potential to significantly improve public health at a large scale.
By combining behavioural science with machine learning technology within the Holly Health app, this project developed a just-in-time adaptive intervention (JITAI) system using machine learning to increase these healthy habits (e.g. regular physical activity, getting sufficient sleep) in patients with multimorbidity.
JITAI is a pioneering approach that provides timely, personalised coaching based on each person’s unique health patterns and behaviours. It uses real-time data and machine learning models to identify moments throughout the day when an individual is most likely to benefit from support and then provides that support.
The JITAI system works in a simple daily cycle, known as a ‘feedback loop’. It uses a type of artificial intelligence called Reinforcement Learning (RL), which means it learns from each person’s behaviour over time. Based on what it learns each day, the system becomes better at understanding what support works and uses this to plan more helpful coaching messages for the following day.
Around one in three adults in the UK live with multimorbidity, with 34 per cent of adults recording both physical and mental issues, a combination that can significantly impact people's ability to self-manage their conditions.
As the number of conditions increases, care becomes more complex and costly, placing sustained pressure on healthcare services. Multimorbidity now accounts for around 70 per cent of total NHS health and social care expenditure, contributing to an estimated £72 billion spent each year on preventable conditions.
The Innovate UK–funded 18-month project focused on advancing digital self-management for people living with or at risk of multimorbidity.
These findings demonstrate the potential for large-scale, personalised digital self-management support, helping to address critical NHS capacity and cost challenges while enabling patients to take greater control of their health. Following these promising early results, the project team are now hoping to trial the app with a larger group of patients.
Dr James Sanders, academic lead for the project at Loughborough University and part of the Centre for Lifestyle Medicine and Behaviour (CLiMB), commented: “Our collaboration demonstrates the potential of personalised, data-driven support to help people manage multiple long-term conditions. By integrating behaviour change research with adaptive machine learning, we can provide the right support at the right time, empowering people to take meaningful action towards better health.”
Dr James Fleming, Senior Lecturer in Intelligent Control Systems at Loughborough University, added: “This project takes advanced AI techniques out of the lab and puts them to work in real everyday life. The JITAI system can learn what support each person responds to and deliver coaching that feels personal and timely, helping people build healthier habits that last.”
Grace Gimson, CEO and Co-Founder at Holly Health, said: “This is one of our most exciting advancements to date. At a time when a huge amount of focus is on Large Language Model AI developments in healthcare, this project has enabled us to innovate in a unique direction, by hyper personalising the coaching nudges we deliver. We can’t wait to deploy this with wider NHS patient cohorts, to provide the compassionate and tailored lifestyle health support that people need more of.”
Professor Vincent Sai, Group CEO and Partner at Modality Partnership, commented: “By blending AI with behavioural science, we’re making personalised self-management a reality for patients with complex needs.”
Following the project’s success, the partners plan to expand access to the enhanced Holly Health service across NHS and community settings, aiming to support thousands more patients in managing long-term conditions and preventing new ones.