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The figures are glaring: If you live with a severe mental illness such as a psychotic disorder, you will die on average than the rest of the population, largely because you are much more likely to suffer from life-limiting preventable physical conditions such as diabetes, obesity or heart disease.

A groundbreaking risk prediction tool, PsyMetRiC, aims to change that. Developed by Dr Ben Perry, an Associate Clinical Professor of Psychiatry at the University �鶹��ѡ, PsyMetRiC helps clinicians forecast the risk of young people with psychosis developing physical health problems in the future, supporting earlier intervention and preventative measures.

A host of risk factors

When it comes to physical health, the odds are stacked against people who live with psychosis. “As a medical student, I was quite shocked by the poor physical health of people with severe mental illness. It just seemed like a massive blind spot to me. That’s what motivated me to become a psychiatrist and drove me to get involved in research,” Dr Perry recalls.

Psychotic disorders such as schizophrenia, which often manifest in early adulthood, severely impact lifestyles, making them more likely to eat poorly or exercise infrequently. that people with psychosis are up to three times more likely to smoke than others.

But that is not the only contributor. Some antipsychotic medications come with side effects for physical health, often making patients feel hungry or more sedate, says Dr Perry. “There are also healthcare inequalities baked into the system, so people with severe mental illness generally receive worse physical healthcare than the rest of the population,” he adds.

There are also genetic risks. There is growing evidence that genetic influences that might increase our risk of developing severe mental illness may also play a part in physical health problems, Dr Perry explains. The same applies to environmental factors, such as early traumas. “Whether it’s genes or environment, the same sorts of influences that might increase our risk of a mental illness are also increasing our risk of physical health problems,” he says.

Levelling the field

Prediction tools are not new in medicine. Over the past decades they have been widely implemented in clinics around the world. Health professionals routinely use prediction tools to assess how likely a patient is to develop a poor health outcome, which helps to inform treatment discussions. Those tools are trained on real-world data, and work much like calculators: health professionals input key metrics on a patient’s health, age and background, and the tool predicts the risk of that patient developing a disease over time.

“The problem with the tools we have for cardiometabolic health is that they don’t work well for young people; and specifically, they really don’t work well for young people who might be at risk for other reasons, such as severe mental illness,” Dr Perry says. “They substantially underpredict risk in this group, and the result is that the young people who need interventions are not getting them.”

That is where PsyMetRiC comes in. It is trained on the real-world data from young people with severe mental illness, so is tailored to predict risks for that cohort. “By focusing on this group, we can create a tool that is appropriately weighted and can accurately predict their risk of future physical health outcomes,” he explains.

First developed in 2021 using data from three regions in the UK, PsyMetRiC has now been validated in 10 countries across four continents, demonstrating accuracy and reliability internationally. In 2024, Dr Perry secured almost £2 million in funding from the UK’s National Institute for Health and Care Research (NIHR), under a prestigious five-year Advanced Fellowship programme.

With that funding, Dr Perry is working to make the tool more accurate by accessing huge primary care datasets. PsyMetRiC’s sample size has increased from 1,100 health records at its launch, up to around 50,000 today, he explains. Ensuring that the tool is equitable, meaning that it works equally well no matter the person’s background, is another priority.

Healthcare inequalities are baked into the system, and therefore into the datasets used by researchers, Dr Perry explains: “We need to be really careful with how we use data, because we can end up reinforcing existing healthcare inequalities.” That is a problem with some of the prediction tools already in use, he warns: “Some of the general population-based tools developed years ago have been shown not to work as well in people from, say, ethnic minority groups. So we're likely to be propagating healthcare inequalities in those groups. That's not a mistake that I want to repeat.”

To avoid that, PsyMetRiC draws on a set of recommendations, called STANDING Together, published last year in . These aim to improve the way datasets are used in health technologies and reduce the risk of bias.

Maximising impact

Predicting risk is one thing, but altering health outcomes is another. That requires clinical practice and patient behaviour to change. To this end, Dr Perry is also using NIHR funding to assess how to maximise the impact of PsyMetRiC. “There is no point in trying to implement a prediction model that doesn't change anything in clinician or patient behaviour,” he says.

In this respect, too, he is learning from established risk prediction models. “The general population-based tools haven’t focused much on ensuring that they have impact. There's evidence that those tools are good at making clinicians reach for their prescription pads, but they don't do much else — they don't tend to change patient behaviours,” he explains.

That may partly be due to problems with risk communication, he adds: “So do clinicians feel able to have conversations with patients about their physical health risks? Are they having those conversations in a way that is sensitive and motivating but doesn't lead to distress? I wonder, if we focus more on risk communication, whether we might be able to change that picture.”

As well as exploring risk communication improvements, Dr Perry plans to study treatment pathways for psychosis patients at risk of developing physical health conditions. “There's no point implementing PsyMetRiC if we don't have treatments that are acceptable and feasible in routine practice — otherwise, we're just causing distress and worry in our patients,” he says. “So the next step is thinking about what treatments we offer and how much risk should be tolerated before an intervention should be offered.”

Drawing on lived experience

Dr Perry, who joined the University �鶹��ѡ in 2024, is supported by collaborators from several of its schools and colleges, bringing expertise in everything from health economics to biostatistics and qualitative research. That is much needed in such a trans-disciplinary area of research, he stresses.

“Data analytics is just a small piece of the puzzle. You need expertise in biostatistics and analysis, regulatory science, implementation science, patient involvement, qualitative research, commercialisation, and much more,” he explains. “I’ve been amazed by just how collaborative the University �鶹��ѡ is. My research is being transformed through the collaborations that I’ve developed across the whole university, because this is a very trans-disciplinary project.”

PsyMetRiC is also advised by a group of 10 young people with lived experience of psychosis, as well as two UK mental health charities: the McPin Foundation and the Centre for Mental Health. “Every aspect of the research and how it's communicated is being shaped by their involvement,” Dr Perry says of the young advisors. “They have shaped the outcomes we are predicting in the model, as well as how we communicate that information — visually, orally, and in written form. I’m really grateful for that involvement.”