Thousands of patients and NHS staff will benefit from dozens of new pioneering projects awarded a share of £36 million to test state-of-the-art AI technology. The projects will help the NHS to transform the quality of care and the speed of diagnoses for conditions such as lung cancer.
At CogX Festival today (Wednesday 16 June 2021), the Health and Social Care Secretary Matt Hancock announced the winners of the second wave of the NHS AI Lab’s AI in Health and Care Award. The 38 trailblazing projects backed by NHSX and Accelerated Access Collaborative (AAC) include:
- an AI-guided tool to help doctors and nurses to diagnose heart attacks more accurately
- an algorithm to fast-track the detection of lung cancer
- an AI-powered mental health app to help tackle symptoms of anxiety and depression while also identifying people experiencing severe mental health difficulties
- tech to help spot undiagnosed spinal fractures
Already, over 17,000 stroke patients and over 25,000 patients with diabetes or high blood pressure have benefited from the first round of the AI in Health and Care Award since September, where £50 million was given to 42 AI technologies.
Health and Social Care Secretary, Matt Hancock said:
“AI has the potential to completely revolutionise every part of how we approach healthcare, from how we diagnose diseases and the speed at which our doctors and nurses deliver treatments to how we support people’s mental health.
“The 38 projects we are backing reflect the UK’s trailblazing approach to innovation in the healthcare sector, and could help us take a leap forward in the quality of care and the speed of disease diagnoses and treatment in the NHS.
“Confronted with this global pandemic, our tech sector has risen to the challenge and upended how we do things through innovations to support people to test from home, complete remote consultations and diagnose issues safely.”
Sir Simon Stevens, chief executive of NHS England, said:
“Through our NHS AI Lab we're now backing a new generation of ground-breaking but practical solutions to some of the biggest challenges in healthcare.
“Precision cancer diagnosis, accurate surgery, and new ways of offering mental health support are just a few of the promising real world patient benefits. Because as the NHS comes through the pandemic, rather than a return to old ways, we're supercharging a more innovative future.
“So today our message to developers worldwide is clear - the NHS is ready to help you test your innovations and ensure our patients are among the first in the world to benefit from new AI technologies.”
The AI in Health and Care Award aims to accelerate the testing and evaluation of AI in the NHS so patients can benefit from faster and more personalised diagnosis and greater efficiency in screening services.
For example, use of Paige Prostate will be able to give more information about prostate cancer, including detecting a tumour, its size and how severe it is, enabling clinicians to make treatment more specific and more targeted. As well as this, Mia by Kheiron Medical, a winner from the first round of the AI Awards, aims to replace the need for two radiologists to review breast cancer scans by instead using one radiologist and the AI, making the process faster and more efficient.
38 winners of Round 2
The 38 projects are being supported by the second wave of the AI Awards include:
an algorithm from BeholdAI that can identify suspected lung cancer in chest X-rays to increase the numbers of cancers diagnosed and reduce the time patients wait for scans
the Paige Prostate cancer detection tool to help pathologists identify cancers and their spread in digital images to improve diagnostic accuracy and help tackle rising caseloads
Zebra Medical’s Bone Health Solutions tool to analyse existing CT scans to look for previously undiagnosed spinal fractures that could be a sign of osteoporosis to find more patients living with this undiagnosed disease, ensuring they receive appropriate advice or medication
mental health app Wysa, an AI powered chatbot and series of self-care exercises which will provide mental health support, helping people manage their mental health - patients will be given access to the app during the referral process for mental health services, to explore whether the app can ease symptoms of anxiety and depression before patients receive assessment and treatment
Matthew Gould, chief executive of NHSX, said:
“These trials are making the AI revolution a reality for patients.
“Thousands are already benefiting, from faster stroke treatment to ground-breaking home kidney testing.
“Today’s award winners will push NHS AI into new areas like mental health. The possibilities are immense. This work will help ensure the NHS is a world leader in safe use of AI in health and care.”
Matt Whitty, chief executive, Accelerated Access Collaborative and Innovation Research and Life Sciences director NHS England and NHS Improvement said:
‘Today's announcement of the Artificial Intelligence in Health and Care Award winners demonstrates our backing for a broad range of innovations, including those to improve cancer care and support for our first mental health project. The NHS has the tools in place to become a world leader in testing and deploying new Artificial Intelligence technologies that can improve patients' lives and showcase the breadth of talent and ingenuity present throughout the UK across academia, industry and the NHS.’
The AI award package also includes funding to support the research, development and testing of early phase, promising ideas which could be used in the NHS in future:
Diagnosing heart attacks - an AI-guided tool used that could diagnose heart attacks more accurately and quickly through better interpretation of blood analysis.
Monitoring cystic fibrosis - using AI with home monitoring equipment to predict sudden dips in the health of cystic fibrosis patients, aiming to prevent them occurring.
Monitoring brain tumours - developing AI to measure the volume of brain tumours from scans to assess which are at risk of growth to ensure those patients are monitored more frequently.
Improving kidney transplant outcomes – using data from 20 years of previous kidney transplants to improve the decision-making process for a patient to receive less-than-perfectly-matched donor kidneys or wait for the next available one.
Detecting bowel cancer - using AI to analyse video recordings of the gastrointestinal tract, taken from a swallowable camera, to target bowel cancer and other gastrointestinal diseases.
The NHS AI Lab will fund programmes to support the UK to become a world-leading, safe and ethically robust setting for the development and deployment of AI technologies. The Lab has also launched an AI Ethics Initiative to ensure AI products will not exacerbate health inequalities, including working with the Ada Lovelace Institute to design and trial algorithmic impact assessments.
The AI in Health and Care Award will distribute £140 million over three years, with the next round of applications set to open in late June.
366 applications were received which were reviewed through a series of stages including long-listing, due diligence checks, clinical and peer reviews, and interviews.
Four categories of AI products are being supported:
Phase 1 - to support the demonstration of the technical and clinical feasibility of the proposed concept, product or service.
Phase 2 - to support the development and evaluation of prototypes and generate early clinical safety/efficacy data.
Phase 3 - to support the first real-world tests in health and social care settings of AI products or tools to develop evidence of efficacy and preliminary proof of effectiveness, including evidence for routes to implementation to enable rapid adoption.
Phase 4 - to support the spread of AI products or tools that have market authorisation but insufficient evidence to merit large-scale commissioning or deployment. Successful products will be adopted in a number of NHS sites to stress test and evaluate the AI technology within routine clinical or operational pathways to determine efficacy or accuracy, and clinical and economic impact.