New Predictive Health Tool Aims to Reduce Avoidable Deaths Among People with Learning Disabilities

A new digital healthcare tool, developed by Loughborough University alongside the Leicestershire Partnership NHS Trust, could help clinicians glimpse the health futures of people with learning disabilities before those futures arrive. As the researchers behind the DECODE project explain, this kind of predictive clarity may finally shift a stubborn imbalance: avoidable deaths among this population remain more than double the rate seen in the wider public.

A model trained on the people it aims to serve

The tool is funded by the National Institute for Health and Care Research and built on anonymised health data from more than 33,000 adults with learning disabilities across England and Wales. It takes the basics already gathered during an annual GP health check—age, sex, existing conditions—and projects which illnesses a person is most likely to develop, and roughly when.

What distinguishes it is specificity. The DECODE team found that 86 percent of those studied were living with multiple long-term conditions—sometimes as many as a dozen at once—often in combinations rarely seen outside this group. "Some of these combinations are different from what is seen in the general population, and this has never been known before," says Dr. Satheesh Gangadharan, consultant psychiatrist at Leicestershire Partnership NHS Trust and co-lead of DECODE.

A gap we now have a way to narrow

On average, people with learning disabilities die twenty years earlier than the wider population, and thirty-nine percent of those deaths are classified as avoidable. For Professor Thomas Jun, co-lead of DECODE and an expert in sociotechnical systems design at Loughborough, the promise is both clinical and deeply human. "I 100% believe this work will save lives, empower healthcare professionals, and improve the quality of life for people with learning disabilities and their carers," he says.

The researchers envision the tool woven directly into the routine annual health check that people with learning disabilities already receive from their GP. A clinician would see not only today's diagnoses but tomorrow's likely ones, rendered as visual maps of how conditions unfold and interact. That earlier window, the team argues, opens space for interventions that might, over time, bend the curve back toward something like fairness.

What to watch in the years ahead

The team estimates the tool could be ready to trial in real healthcare settings within four years, once it has been refined against larger datasets. They are now seeking further funding to move from proof of concept to bedside. "We feel we are halfway towards creating real change," Jun adds.

We should also remember who would actually use a tool like this. Many of the clinicians arriving in the NHS come through routes such as the Health and Care visa, which sits apart from the broader Skilled Worker framework. If this work can turn prediction into prevention, the quiet annual check at the GP may finally become the turning point it was always meant to be.