New research calls for all health and care staff to be trained in AI

All health and care staff should receive training in artificial intelligence (AI) with additional specialist training for those who use AI tools in clinical practice, according to new research published this week.

AI technologies are already helping clinicians in trials across the NHS to care for patients and could further support the health and care service to detect and manage diseases like cancer.

With the possibility of further spread of AI, a new report published by the NHS AI Lab and Health Education England (HEE), has set out recommendations for education and training providers in England so they can plan, resource, develop and deliver new training packages on AI for health and care staff.

The report says more advanced specialist training is required for other health and care staff depending on their roles and responsibilities whether in procurement, implementation or if they may be using AI in clinical practice.

A previous report, by the same team, found the vast majority of clinicians were unfamiliar with AI technologies and there was a risk that without appropriate training and support, patients would not equally share in the benefits offered by AI as it is deployed across the NHS over the coming years.

This new report is intended to directly support all education and training providers in England to plan, resource, develop and deliver educational offerings to equip the workforce with the necessary knowledge, skills and capabilities they will need in AI.

Dr Eric Topol, whose independent report for the SofS outlined recommendations to ensure the NHS is the world leader in using digital technologies to benefit patients, said: "This collaborative research from HEE and the NHS AI Lab represents a significant step forward in developing confidence in AI in the healthcare workforce.

"It is a model for other countries to adopt as we move forward with implementing AI in medical practice." 

Patrick Mitchell Director Innovation, Digital and Transformation at HEE, commented: "This latest report builds on the previous one to highlight the need for targeted training across the professions to truly unlock the potential of AI in workforce and service transformation going on today."

Alan Davies, Innovative Programs & Partnerships Director at HEE, went on to add: "We have been delighted that this groundbreaking work has been welcomed by colleagues in NICE and MHRA as complementary and timely, and that colleagues across the devolved nations share our interest and determination to build on this further with related learning and educational materials."

Brhmie Balaram, Head of AI Research and Ethics at the NHS AI Lab, said: "For the NHS to wholly embrace new AI technologies so they are adopted equitably across the country it is vital that we ensure all our staff receive appropriate training in AI.

"This important new research will support those organisations that train our health and care workers to develop their curriculums to ensure staff of the future receive the training in AI they will need.

"This project is only one in a series at the NHS AI Lab to help ensure the workforce and local NHS organisations are ready for the further spread of AI technologies that have been found to be safe, ethical and effective."

The report breaks down the training requirements for AI into five groupings, referred to as archetypes, each of which encompasses a number of varied roles currently undertaken in the NHS. The five archetypes are Shapers, Drivers, Creators, Embedders and Users.

Individuals acting as each archetype will have different knowledge and skills requirements and require an education package tailored to their roles. For instance a Driver (champion and lead AI development and deployment at a regional/local level) would have different educational needs to a Creator (create AI technologies for use in healthcare settings).

The report and partnership with Health Education England is part of the NHS AI Labs' AI Ethics Initiative, which was introduced to support research and practical interventions that can strengthen the ethical adoption of AI in health and care.