The award was split into phases based on the readiness of the AI technology.

• Phases 1 – 2 accelerate promising ideas and products that are pre-commercialisation and have yet to receive market authorisation.
• Phase 3 develops first real-world testing in health and social care settings to establish evidence of effectiveness and efficacy.
• Phase 4 will identify promising products which are ready for robust evaluation across multiple real-world test sites. These evaluations help build an evidence base to inform recommendations for national roll-out and, where relevant, National Institute for Health and Care Excellence (NICE) guidance.

Phase 4 evaluations

Independent evaluations were commissioned for all our Phase 4 award winners. These evaluations filled key evidence gaps for relevant published evidence standards frameworks and aimed to accelerate local and national adoption. Evaluations focussed on:

• accuracy
• safety
• effectiveness
• value
• fit with site
• implementation
• feasibility of scale up
• sustainability of scale up

Thirteen independent evaluations were commissioned. The quality of the evaluation designs and delivery was overseen by an Evaluation Advisory Group. The terms of reference and membership list can be viewed on our FutureNHS platform (this platform requires a log in).

Insights on the practical ‘how to’ of designing and implementing real-world evaluations of AI were collated into a lessons learned report that can be found here: Planning and implementing real-world artificial intelligence (AI) evaluations: lessons from the AI in Health and Care Award

This report sits alongside theoretical frameworks for evaluation and will be useful to teams implementing and evaluating AI in health and care, as well as to national teams working to support innovation.