About 1 in 100 people are identified as having a learning disability. Of this population, over 65% have two or more long-term health problems, known as multiple long-term conditions (MLTCs), and a life expectancy that is 20 years lower than the UK average.
Often the physical ill-health symptoms experienced by those with a learning disability are mistakenly attributed to a mental health/behavioural problem, or as being inherent to their disability. This means they do not always receive the same level of care as those without a learning disability.
And as there is no easy way to understand and predict the complex interactions between MLTCs and the care needs of individuals, it is difficult to provide effective joined-up care between health and social services.
For the DECODE (Data-driven machinE-learning aided stratification and management of multiple long-term COnditions in adults with intellectual disabilitiEs) project, the team will use machine learning to better understand MLTCs in people with learning disabilities.
The researchers will analyse healthcare data on people with learning disabilities from England and Wales to find out what MLTCs are more likely to occur together, what happens to some of these MLTCs over time, and the role other factors, such as lifestyle choices, financial position, and social situations, play in their MLTCs.
The team will also work directly with people with learning disabilities, their carers, and the professionals who support them. This will help them to identify the most important MLTCs affecting the lives of people with learning disabilities, make informed recommendations about the care of people with MLTCs, and produce visual information such as graphs and infographics that can be easily understood.
The end goal is to create a new joined-up model of care for people with learning disabilities, that brings together the multiple clinical guidelines relevant to the dominant MLTCs in this population, in a format that is accessible for all users. Ultimately this will enable the better management of MLTCs by health and social care providers, and in some cases prevent them from developing.
Loughborough’s Dr Thomas Jun, a Reader in Socio-technical System Design, is co-lead for the project. Speaking about DECODE he said: “We are very excited about this collaboration opportunity, working with clinicians and experts in data science, AI, medical informatics, human factors, design, ethics and qualitative research, as well as those with lived experience of learning disabilities. We will be able to demonstrate how AI can create safe, ethical and cost-effective improvement to the quality of life for thousands of people with learning disabilities.”
Co-lead Dr Satheesh Gangadharan, a Consultant Psychiatrist with the Leicestershire Partnership NHS Trust, added: “Moving forward we hope our research will shape how people with a learning disability and long-term conditions are supported in the UK and beyond. The links we have with the National Learning Disability Professional Senate, Royal Colleges, Health Education England, Public Health Wales, NHS England and NHS Wales will enable us to make a real impact and improve the care.”
Dr Georgina Cosma, Senior Lecturer and Associate Professor from Loughborough's Department of Computer Science, is also among the project partners.
The DECODE project is being funded by the National Institute for Health Research (NIHR), the research partner of the NHS, public health and social care, and is due to start in April. The other academic project partners include the University of Leicester, Swansea University, King’s College London, University of Plymouth, the University of Nottingham, and De Montfort University.