NHS Shared Business Services (NHS SBS) has published a “comprehensive” framework agreement intended to bring together the “wealth of experience” produced from current AI offerings to help “take the NHS above the foothills of digital transformation”.
The framework agreement, to be used by NHS SBS approved organisations, is set out to cover the provision of health AI solutions and “related goods and services”, covering six lots: radiology and diagnostic imaging; pathological diagnosis and early detection; predictive analytics; research and development; operational efficiency; and specialist support.
On radiology and diagnostic imaging, the framework agreement looks to support the delivery of “a compliant route to market for the analysis of medical imaging for rapid diagnosis”, with nine areas of focus outlined including AI to detect neurological disorders; AI in detection for obstetrics and gynaecology; and AI in the diagnosis and treatment of cardiological disorders.
Lot 2 is designed to support the delivery of “a compliant route to market for the analysis of samples for rapid diagnosis”, including in haematology AI tools to assist in diagnosing blood disorders; virology AI to detect, identify, and monitor viral infections; and dermatology AI to analyse skin samples and “improve the diagnosis and management of skin conditions”.
The next lot is designed to help in delivering a compliant route to market for solutions which focus on transforming patient care, including AI algorithms to predict patients at high risk of hospital admission to allow for early intervention; and AI algorithms that predict the likelihood of missed appointments, “helping to reduce no-show rates”.
Research and development is the focus of Lot 4, which looks to deliver a compliant route to market for solutions which focus on transforming drug discovery and clinical trials. This includes two “sublots”: AI for the acceleration of drug discovery by analysing large datasets to identify potential drug candidates; and AI for the design and management of clinical trials to improve the efficiency and accuracy of research.
Lot 5 focuses on AI in operational efficiency, including AI in helping manage hospital resources, bed availability and staff allocation, “to optimise operations and reduce waiting times”; and AI in optimising the supply chain for medical supplies and medications, “ensuring timely availability and reducing waste”.
And finally, Lot 6 covers AI consultancy, implementation and training services, with three “sublots” including “consultancy specialised advisory services for the adoption and implementation of AI in healthcare”; specialised services to support the integration of AI technologies; and training programmes designed to “help educate healthcare professionals about the use and application of AI technologies”.
The framework agreement states that market engagement sessions are planned for March and April 2025, with an estimated date for the publication of the contract notice given as the 22 August 2025. To find out more, please click here.
AI in supporting NHS reform
A HTN Now panel discussion from last year looked at whether the reality of AI will live up to the current hype, and how to manage bias in healthcare data. Expert panellists included Puja Myles, director at MHRA Clinical Practice Research Datalink; Shanker Vijayadeva, GP lead and digital transformation for the London region at NHS England; and Ricardo Baptista Leite, M.D., CEO at HealthAI, the global agency for responsible AI in health. The session explored topics including what is needed to manage bias; what “responsible AI” really looks like; how to ensure AI is inclusive and equitable; how AI can help support underserved populations; the deployment of AI in the NHS; and the potential to harness AI in supporting the shift from reactive to proactive care.
We asked our LinkedIn followers for their thoughts on the biggest concern for AI in healthcare: equitability, bias, transparency or regulation? 52 percent of over 100 voters highlighted regulation as their main concern, with 21 percent voting for bias.
Somerset NHS Foundation Trust’s AI policy was recently shared by the trust’s chief scientist for data, operational research & artificial intelligence, focusing on the need for safe integration and an approach balancing innovation with ethical and legal responsibilities.
HTN’s panel discussion from November last year brought together a panel of experts from across the NHS to dissect the findings from Lord Darzi’s report, reflecting on what is holding the NHS back from innovation; the challenges and missed opportunities; and the role of digital and tech in driving change, supporting a focus on prevention and promoting integrated care. Panellists considered challenges including getting training in place to support the NHS workforce with the integration of AI technologies, and creating the headroom required to enable organisations to effectively consider the value of AI solutions.
And the plan for reforming NHS elective care focused on a vision of future NHS care which is “increasingly personalised and digital”, focusing on improved experience, convenience, choice, and control. “Different models of care will be more widely and consistently adopted,” it states, with the “more widespread” use of AI and other technologies helping to support productivity across the health sector.
