The National Institute for Health and Care Research (NIHR) has awarded £8 million to six innovations using AI and digital to speed up diagnosis and improve patient care.
Innovations granted a share of the funding include SAMURAI-CT, an AI tool designed to detect “serious findings” from head CT scans with aims of reducing discharge times by more than 20 percent. It is currently being tested across Oxford University Hospitals, Royal Berkshire, University Hospitals of Derby and Burton, and NHS Greater Glasgow and Clyde.
Intelligent Heart Evaluation Framework is an AI heart failure screening tool which works by analysing ECGs and identifying patients who do not need scans to free-up capacity. The project is based at Barts Health, with ambitions to carry out testing for regulatory approval.
Another of the innovations is SWIFT LUNG, testing the Optellum AI tool to predict lung cancer and speed up scan assessments, with trials taking place at NHS Highlands, NHS Greater Glasgow and Clyde, and Oxford University Hospitals.
Intelligent Navigation using AI, using AI and a text-based app accessed via the NHS App to help prioritise patients based on symptoms and medical history, is being rolled out across the NHS Wealden Ridge Partnership.
SMART-XR is testing which scans AI can handle autonomously to reduce radiologist workload and cut reporting delays, comparing AI reviews of 12 months’ worth of X-rays to test for accuracy at Oxford University Hospitals and Manchester University NHS FT.
Leicestershire Partnership, North East London, Norfolk and Suffolk, and West Suffolk trusts, along with Lincolnshire ICB and Nottinghamshire ICB, are involved in the testing of ORBIT – a digital therapy programme designed to help manage tics, hoping to reduce waiting times and improve access to treatment. Ambitions are to test the programme in real-world settings to gain NICE approval.
NIHR CEO Lucy Chappell remarked: “By backing these 6 digital research projects, the NIHR is helping to drive the fundamental shift from an analogue to a digital health service and deliver the government’s 10-year health plan. This important investment in AI and innovation will cut NHS waiting times, fast-tracking diagnoses and ensuring patients receive more accessible, efficient, and high-quality care.”
Wider trend: Health tech innovation
NIHR’s Invention for Innovation Funding At the Speed of Translation (FAST) programme is offering funding between £50,000 and £100,000 over a period of six-to-twelve months for preventative technologies in the community care space. The programme is designed to support the real-world integration of tech aligned with the prevention agenda into community care settings such as neighbourhood health hubs, community diagnostic centres, and community pharmacies.
Barts Health NHS Trust has highlighted efficiencies achieved through the use of AI in handling patient complaints, sharing outcomes from a six month project at Newham Hospital. AI tools in use form part of the Microsoft Copilot system, and are approved for NHS use, the trust explains. All responses are reviewed and approved by staff members, and conversations, investigations, and clinical decisions are “always led by people”. Over a period of six months, the project resulted in increased efficiency in the complaints process, Barts Health shares. Key outcomes included a reduction of more than half in the amount of time spent drafting response letters, a “significant” reduction in the number of cases needing to be reopened, and an increased ability to respond to patients more quickly.
A “smart” t-shirt is being piloted in Leicester to evaluate its usefulness in helping clinicians to diagnose breathing pattern disorders more accurately, with support from the NIHR Invention for Innovation (i4i) programme. The Anasa® system Smart Shirt, developed by wearable tech company Atride, is currently being trialled with patients at the NIHR Leicester Biomedical Research Centre, hosted at University Hospitals of Leicester NHS Trust. According to UHL, it combines nanotechnology and electronics woven into its fabric to enable continuous respiratory monitoring.
