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The University of Southampton

Research project: AIM study - The development and validation of population clusters for integrating health and social care: A mixed-methods study on Multiple Long-Term Conditions (MLTC)

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This project will both develop and validate population clusters that consider health and social care determinants and subsequent need for people with MLTC using data-driven Artificial Intelligence (AI) methods, which will be compared with expert-driven approaches to validate efficacy of the machine learning methodology. This will be followed by evaluation of cluster trajectories and efficacy in relation to improved health outcomes and reduction in costs/resources.


An estimated 14 million people in England are living with multiple long-term health conditions (MLTC). Efforts to improve care mainly focus on biological markers or medical features of disease such as blood pressure or cholesterol, without adequately addressing other non-medical factors that contribute to good health. This may include social, economic and environmental factors such as mobility, housing conditions, finances or social isolation.

A shift towards integrated care that considers the ‘whole person’ and their environment is essential in addressing the complex individual needs of people living with MLTC. One approach to delivering more personalised care is to 'cluster' or group people based on similarities in their medical and non-medical needs. This approach has been adopted in other countries but not in the UK due to uncertainty about how to develop clusters, and a lack of evidence linking this approach to improved health or reduced costs.


  1. To generate evidence on how to cluster people by health and social need using machine learning, in other words, we will use a computer system to help us identify and group people with similar needs together.
  2. To use this information to develop tailored approaches for clusters that join up health and social care, and in doing so, improve the lives of people with MLTC.


  1. We will undertake interviews to ask patients, carers and professionals for their views on what is important in MLTC when considering both medical and social needs.
  2. We will bring together a panel of lay people, professionals and experts to ask for their views on what medical and non-medical factors are key to improving the care, and addressing the wider needs, of people with multiple long term conditions.
  3. We will use millions of anonymised patient records to test machine learning and generate clusters that will be compared to those developed through patient/professional opinions to see which are better at predicting outcomes.
  4. We will study clusters to learn what happens over time in terms of health/social costs, and to understand the profiles of people within each cluster.
  5. We will use this information to develop tailored care for each cluster for people with MLTC.

Our findings

We will make our findings available and accessible to people with MLTC, and those who work and make decisions in health and social care. We will co-host information events with a range of audiences to share the results and discuss the wider implications for improving the health and social care of people experiencing MLTC.

Local Investigators 

Dr Hajira Dambha-Miller (co-PI) – GP and NIHR Clinical Lecturer

Dr Beth Stuart – Associate Professor in Medical Statistics  

Professor Miriam Santer – Professor Primary Care

Professor Paul Roderick – Professor of Public Health

Dr Leanne Morrison – Lecturer in Health Psychology

Professor Hazel Everitt – Professor of Primary Care Research

Professor Paul Little CBE – Professor of Primary Care Research

Study team

Dr Ralph Akyea – Research Fellow – University of Nottingham/University of Southampton

Dr Marisza Hijryana - Research Fellow, University of Southampton

Dr Hilda Hounkpatin – Senior Research Fellow, University of Southampton

Dr Ikumi Okamoto - Research Fellow, University of Southampton

Dr Glenn Simpson - Lead Research Fellow, University of Southampton

Dr Jonathan Stokes – Research Fellow in Health Economics, University of Manchester

Dr Zlatko Zlatev – Senior Enterprise Fellow, University of Southampton


Professor Andrew Farmer (co-PI) – Professor and University Lecturer, Oxford University

Michael Boniface – Professorial Fellow in Information Systems

Professor Adriane Chapman – Human Centered AI

Dr Jon Gibson – Health Economist, University of Manchester

Dr Nazrul Islam – Epidemiologist and data scientist, Big data Institute, Oxford University

Dr Francesco Zaccardi – Clinical Epidemiologist & Assistant Director of the Real-World Evidence Unit

Professor Karen Jones – Director, Personal Social Services Research Unit; Associate Director of Dr

NIHR School for Social Care Research, University of Kent

Ms Firoza Davies - PPI representative

Funder: NIHR Ethics Number 67953

Duration: 1ST October 2021 - 1st October 2023


Contact: Dr Glenn Simpson

This study is being conducted by the Primary Care Research Centre.

Related Research Groups: Primary Care, Population Sciences and Medical Education.

Related research groups

Primary Care, Population Sciences and Medical Education
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