AI to help NHS tackle super flu and A&E delays
Hospitals across England are increasingly using artificial intelligence (AI) to reduce waiting times for patients.
The tool, part of the government’s AI exemplars programme, is already in use by 50 NHS organisations.
The forecasting system analyses hospital admissions, historical data, weekly trends, and Met Office temperature forecasts to identify likely peak periods.
This allows hospitals to adjust staffing and bed allocation in advance, rather than responding to last-minute pressures.
Health innovation minister Dr Zubir Ahmed said: “The AI revolution is here and we are arming our NHS staff with the latest technology to help slash A&E waits for patients this busy winter period. Innovations like these will help hospitals manage winter pressure and prioritise resources over the coming months as we continue to battle a tidal wave of flu.”
Winter has already brought record flu cases, alongside the usual seasonal challenges.
With over 18 million flu vaccines delivered this autumn, the AI tool is designed to spot surges in demand before they happen, giving hospitals time to plan staffing and beds efficiently.
Boosting NHS efficiency
Tech secretary Liz Kendall said: “By helping to predict demand, this AI forecasting tool is getting patients the care they need faster while supporting our incredible NHS staff.”
“That means easing pressure by ensuring the NHS is at the forefront of the latest technology during the busiest time of year.”
The A&E forecasting tool is one part of a broader AI strategy within the NHS.
Other projects include AI Diagnostics, which supports clinicians in detecting conditions such as lung cancer, and AI-assisted discharge summaries, which allow patients to leave hospital sooner while ensuring professionals retain final approval.
AI-powered chat services, like GOV.UK chat, are also being trialled to improve public access to information.
AI is also being applied in preventative care.
Home care provider Cera, which delivers around 2.5 million visits a month, has used AI to predict high-risk patients and prevent avoidable hospital admissions.
Dr Ben Maruthappu, Cera’s chief executive, said: “Investing more in AI-driven care can also help to accelerate hospital discharges – freeing up beds by arranging faster, safer care at home, where patient recovery can be carefully monitored and reported back to the local authority.”
Meanwhile, trials of the AI scribe system, Tortus, across nine NHS sites in London have shown that the technology can increase clinician-patient interaction by 23.5 per cent, and reduce appointment times by 8.2 per cent.
In A&E, the tool allowed staff to see 13.4 per cent more patients per shift and halved the time taken to complete initial patient notes, according to Dr Ahmed Mahdi, consultant in emergency medicine at St George’s University Hospital.