Nationwide roll out of AI tool that predicts falls and viruses

A new AI tool is being rolled out across the NHS that can predict a patient's risk of falling with 97% accuracy, preventing as many as 2,000 falls and hospital admissions each day. 

The predictive tool, developed by health tech provider Cera, is now being used in more than 2 million patient home care visits a month, monitoring vital health signs to predict worrying signs of deterioration in advance. It can then alert healthcare staff so they can step in and reduce the risk of hospitalisation. 

The software is in use across more than two thirds of NHS Integrated Care Systems across the country and helps to provide care at home by flagging as many as 5,000 high-risk alerts a day, reducing hospitalisations by up to 70%. 

Falls are the largest cause of emergency hospital admissions for older people with estimates that around 30% of people aged 65 and above - 2.5 million people - and around half of those aged 80 and above will experience a fall at least once a year. These falls and fractures account for over 4 million bed days a year at an estimated cost of £2 billion. 

Cera's AI software will also be used to detect the symptoms of winter illnesses like Covid, flu, RSV, and norovirus, allowing NHS and care teams to intervene before hospital care is needed. 

The technology works by allowing carers, family members and health care staff to record patient updates on an app which then monitors and reacts to a range of vital health signs in real time, such as blood pressure, heart rate and temperature.  

It predicts future risks of falls and health risks, and alerts healthcare professionals of those at risk so they can step in and provide patients with the care in the community necessary to prevent future emergencies. 

Cera's software can also automate paperwork like visit schedules and creating care plans, giving staff more time to focus on caring for patients.

Since its successful trial July 2023, the measure is keeping thousands of elderly and vulnerable people safe at home, leading to a reduction of A&E attendances and freeing up hospital beds, which research shows is saving the NHS over £1 million a day. 

This innovation is just one example of a range of new technology-led models being harnessed by the NHS to provide patients with better care from home, and later this year, the NHS and government will launch a 10-year Health Plan, setting out longer-term measures to shift from analogue to digital and from hospital to community care.  

Dr Vin Diwakar, national director of transformation at NHS England, said: “This new tool now being used across the country shows how the NHS is harnessing the latest technology, including AI, to not only improve the care patients receive but also to boost efficiency across the NHS by cutting unnecessary admissions and freeing up beds ahead of next winter, helping hospitals to mitigate typical seasonal pressures. 

“We know falls are the leading cause of hospital admissions in older people, causing untold suffering, affecting millions each year and costing the NHS around £2 billion, so this new software has the potential to be a real game-changer in the way we can predict, prevent and treat people in the community. 

“This AI tool is a perfect example of how the NHS can use the latest tech to keep more patients safe at home and out of hospital, two cornerstones of the upcoming 10-year Health Plan that will see shifts from analogue to digital, and from hospital to community care.” 

Minister of State for Care Stephen Kinnock said: “Around a third of adults over 65 will experience a fall each year, which can be devastating not just physically, but also for their confidence and independence.

“I am determined that we harness cutting-edge technology to help our most vulnerable citizens receive expert care at home.

"This is smart, preventative healthcare in action, and exactly the kind of transformation we're championing in our 10 Year Health Plan – shifting from treating sickness to preventing it, from hospital to community care, and from analogue to digital solutions.”

Christine, 82 from Essex, receives care from Cera after a previous fall which left her with a broken femur and subsequent shock fracture. She said: “There is no question that Cera's preventative approach has helped me avoid injuries and falls ever since. They have kept me out of hospital, flagging up potential risks and helping me to avoid them. After I broke my leg, they also enabled me to return home from hospital much faster than I otherwise would have done.” 

Mary, whose father Peter received end-of-life care through Cera before passing away last year aged 93, said: "I will never be able to properly express my gratitude for everything Cera did for my dad - they supported him with their preventative care to spend the rest of his days in the comfort of his bungalow. 

"We need to keep the elderly and vulnerable out of hospital, and safe, well and happy at home with their loved ones. We need to change mentalities, to make sure that we embrace innovation and facilitate better preventative care at home." 

Designed by Dr Ben Maruthappu, a former NHS doctor and founder and chief executive of Cera, the AI technology was created to minimise avoidable or unnecessary hospitalisations and is now used by almost 10,000 home healthcare professionals across the country every single day, helping to increase staff efficiency and improve patient outcomes.  

Dr Ben Maruthappu, founder and chief executive of Cera, said: “AI in home care is a game-changer; by enabling better care delivery, it has the power to save countless lives while also saving the taxpayer billions.

“At Cera, we've seen first-hand how AI can transform health outcomes for high-risk and vulnerable individuals: preventing illness and injury, radically reducing avoidable hospitalisations, and empowering people to live longer, healthier lives, in their own homes.

“We're delighted to partner with the NHS to roll out our technology – keeping older and vulnerable people across the country out of hospital and safe at home.”