AI in healthcare: Using algorithms to predict your risk of ending up in hospital

Imagine being able to check your health score like you might check you credit rating – that’s the aim of a pioneering AI trial that wants to work out the likelihood of a patient being admitted to hospital.

The pilot project is being run by Bering Research and GPs at Axbridge Surgery in Somerset. The project uses an algorithm in Bering’s Brave AI system to analyse the complexity of patient health, to predict which patients might be at risk of needing to be admitted to hospital, and to help GPs to work to get that risk reduced.

The AI tool presents its analysis in the form of a complexity score that is based on a percentage scale. The score is related to underlying health conditions and a range of contributory factors, such as high blood pressure or a history of smoking. A patient with a complexity score of 80%, for example, would be at high risk of needing to be admitted to hospital.

Allison Nation, associate director of digital strategy at NHS Somerset Clinical Commissioning Group, is leading the governance around the project and is focused on how the pilot project might lead to big benefits in the future. She believes the AI tool could help to transform healthcare provision.

“As a patient, I would love it if I knew what my complexity score was and that I knew I could support my family with understanding their health conditions,” she says to ZDNet at the recent HETT conference in London. “As a digital lead, I have an ambition that all practices and patients have equitable access to this service. It could be a game-changing innovation.”

Evidence suggests other experts agree with Nation’s assertion. Earlier this year, the prime minister announced £250m funding for a new national AI lab to help improve the health and lives of patients. Private business is getting involved, too. Babylon announced a £450m R&D investment, partly for AI technology to manage chronic conditions.

In the case of Somerset, the AI tool is currently being used by about 100 patients in discussions with members of the GP team at Axbridge. Nation describes the pilot as patient-centric: she says the project involves an enthusiastic practice helping its patients understand how their health condition and lifestyle choices might have an impact on hospital admissions.

Nation says one of the key learnings from the trial is an understanding of what it means for a patient to have a complexity score of around 50%, and to then think about the concerns raised and the actions required. She says the trial has shown the public is not necessarily averse to the idea of having AI analyse and then present a health complexity score.

“Patients aren’t as nervous as they were a number of years ago – this is not a scared entity. Digital literacy has improved. People understand that they can check their credit score online, they’re booking travel online, and they’re using a range of digital tools,” says Nation.

“We can’t assume every patient wants it and some will be more progressive than others. But we shouldn’t stand back from exploring what AI could bring to us.”

However, introducing technology isn’t without its risks. Some experts believe AIs can be overly cautiously in diagnosis.