The NIHR has awarded more than £8 million to six pioneering projects designed to reduce NHS waiting lists and speed up access to care. The six projects are testing a range of AI and digital innovations - including using AI to speed up analysis of head CT scans and chest X-rays - to hasten diagnosis, improve patient care, and make services more accessible and efficient.
A total of £8,136,409 has been awarded through NIHR’s Invention for Innovation (i4i) programme, which sought bold, high-impact solutions capable of rapidly improving patient flow.
With around 1.3 million patients seen every day, timely access to care remains one of the NHS’s biggest challenges. While many factors influence whether patients are seen quickly, they typically focus on two critical points in the care pathway: time to diagnosis and time to treatment. Despite pressures across the health system, demand for services keeps rising, and this makes it harder to deliver timely diagnosis and treatment.
This funding aims to unlock capacity and cut delays by supporting disruptive technologies, digital tools, AI-driven platforms, and new models of care. By backing projects that could deliver rapid, system-wide benefits, NIHR hopes to help the NHS ease backlogs, free up capacity, and ensure patients receive faster, more effective treatment.
Professor Lucy Chappell, Chief Scientific Adviser to the Department of Health and Social Care and CEO of the NIHR, said: "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."
The 6 projects awarded funding are:
SAMURAI-CT - Systematic Assessment of Medical Utility of Radiology Artificial Intelligence - CT Head
Led by Oxford University Hospitals NHS Foundation Trust
This project is testing an AI tool that can detect serious findings on head CT scans. Proven in research settings, it now aims to help radiologists in 4 NHS emergency departments make faster, more accurate diagnoses and cut discharge times for normal scans by at least 20%. The testing is taking place at Oxford University Hospitals NHS Foundation Trust, Royal Berkshire NHS Foundation Trust, University Hospitals of Derby and Burton NHS Foundation Trust and Greater Glasgow and Clyde Health Board.
AI-enabled ECG to reduce demand for echocardiography and shorten diagnostic waiting lists
Led by Queen Mary University of London
This project is developing an AI heart failure screening tool that analyses ECGs. Known as iHeF (Intelligent Heart Evaluation Framework), iHEF could help the NHS run more efficiently by identifying patients who don’t need scans. This would free up hospital diagnostic capacity, cutting waiting times, and fast-tracking patients who need lifesaving treatment. The main goal is to refine the tool and carry out testing for regulatory approval. The project is taking place at Barts Health NHS Foundation Trust.
SWIFT LUNG - Streamlined Workflow for Investigation and Fast Tracking Lung Cancer Diagnosis
Led by NHS Greater Glasgow And Clyde
This project is testing the Optellum AI tool designed to improve care for people with lung nodules. It predicts lung cancer and provides a patient safety net. The study will see if it can speed up scan assessments, reduce waiting times, support consistent care decisions, improve patient follow-up, and cut healthcare costs. It is being trialled in 3 NHS sites across England and Scotland: NHS Highlands, NHS Greater Glasgow and Clyde and Oxford University Hospitals NHS Foundation Trust.
Intelligent Navigation using AI to bust waiting times for urgent healthcare (INA)
Led by University of Oxford
This project will evaluate a system called Intelligent Navigation. Instead of relying on patients, or receptionists/call handlers to run through a set list of questions, Intelligent Navigation uses AI and a text-based app accessed from the NHS app, to help prioritise patients based on their symptoms and medical history. This ensures the most urgent cases are seen first. The team will analyse whether Intelligent Navigation can reduce waiting times for urgent care and provide value for money. The project is being developed and rolled out across the NHS Wealden Ridge Partnership in East Sussex.
SMART-XR - Scalable Medical AI for Radiology Transformation – X-Ray
Led by Harrison-AI Medical UK Ltd
This project is testing whether AI can safely and practically report chest X-rays autonomously. Using a carefully set clinical threshold, it will identify which scans AI can handle, aiming to reduce radiologists’ workload and cut reporting delays across the NHS. The evaluation will compare AI reviews of 12 months of chest X-rays from Oxford University Hospitals NHS Foundation Trust and Manchester University NHS Foundation Trust and clinical review and test for accuracy. Research like this helps to determine how best to deploy AI screening alongside human expertise.
Transforming Treatment for Young People with Tic Disorders: Scalable, Evidence-Based Digital Therapy
Led by University of Nottingham
This project is testing ORBIT (a digital therapy program to help manage tics) in real-world settings to gain NICE approval. The team is refining their psychoeducation program, TIPS (Tic Information and Psychoeducation Support) and integrating it into an NHS-ready system alongside ORBIT. The approach could cut waiting times, help more people access treatment, and do so in a way that is affordable for the NHS. The project aims to implement the ORBIT service (TIPS and ORBIT ERP) in up to 5 NHS Trusts: Leicestershire Partnership NHS Trust, North East London Foundation Trust, Norfolk and Suffolk NHS Foundation Trust, West Suffolk NHS Foundation Trust, Lincolnshire ICB and Nottinghamshire ICB.
The announcement of these six projects was made alongside a wider DHSC announcement about government investment through which millions of patients will receive faster diagnoses, following a £28.1 million government investment in artificial intelligence (AI) tools across the NHS.
The funding will both scale up a proven AI technology to every NHS Trust in England and pilot the next wave of digital innovations. This is the latest step in the government's drive to shift the NHS from analogue to digital and cut waiting times.
