Tech giants are seemingly launching an AI platform every other day, but does the UK health system have the capabilities necessary to help these advancements live up to the hype, with a large chunk of its organisations still running on paper or using fax machines and pagers?

A recent HIMSS UK Executive Leadership Summit (ELS) saw patients, entrepreneurs, clinicians, researchers and scientists discuss during a panel debate whether the NHS is ready for an AI-enabled future.

Matteo Berlucchi, CEO of Your.MD, argued that by using the ‘AI label’, the public might get ‘sidetracked’ into conversations that could deflect from truly understanding the potential of new approaches to data collection and the use of advanced algorithms that could ‘bring to the market a level of efficiency, scalability and consistency’ not seen before.   

“The pre-condition for these solutions to flourish is access to quality data,” Berlucchi explained, with panelists arguing that the current state of the fundamental NHS architecture is not able to support large-scale AI deployment.

During an evidence session for a Science and Technology committee inquiry in January, Dominic King, DeepMind Health Clinical Lead, who was also part of the ELS AI debate, explained that ‘a lot of work’ would need to be done to get NHS datasets into a ‘machine readable AI-ready format’.

“We have found with our work at Moorfields Eye Hospital, for example, that, once the partnership is signed and data are transferred from the controller to the processor, our research does not start the next day.

“It took many months of cleaning and labelling the data (…).

“The NHS does not have datasets that have been meticulously labelled, pixel by pixel, for training material for artificial intelligence companies. That is what we have created in partnership with Moorfields Eye Hospital. It now has, unarguably, the leading retinal scan dataset in the world,” King said. 

However, it is unclear what role the government should play in improving the quality of NHS data, and if it should lobby the Treasury for extra funding to help release its value. 

"As with all new tech, we think #AI can sort out all our problems, but we've got to get the fundamental architecture sorted first." Dominic King, Clinical Lead at @DeepMind_Health #ELSLondon pic.twitter.com/F8gqtQ7h4R

— HIMSS UK (@HIMSS_UK) March 22, 2018

Public trust, ethics and bias

Ensuring data is fit for purpose is not the only challenge.

Panelists argued that the NHS would have to secure public trust and buy-in, with Eleonora Harwich, Reform’s Head of Digital and Tech Innovation, explaining that this is an ‘essential’ element that will support sensible AI adoption.

Founder of 11Health and patient leader Michael Seres argued that patients, doctors and researchers would have to be involved in conversations around design and deployment, while Berlucchi explained:

“It is of paramount importance that any organisation that can gather quality data, the NHS in the first place, does so in a transparent and structured way with a focus on data protection and interoperability.

“This is a fine balance as people will want to be in control of what happens to their data but at the same time companies will have to cooperate with each other in order to create valuable solutions to help the population as a whole.”

Regardless, Seres urged delegates to not get ‘hung up’ on misleading headlines, but focus on whether the technology could empower patients and their carers:

“There’s nothing that I wouldn’t do to share my data, no one I wouldn’t share my data with if it gives me another day (…), or another opportunity to engage or see my daughter at a concert,” Seres, who was diagnosed aged 12 with Crohn's Disease, explained.

The UK's new centre for data ethics and innovation, announced last autumn, is expected to provide assurance that ethical standards are at the forefront of AI and data-driven technology development and address the issue of bias in the design of AI systems.

Earlier this year, Information Commissioner Elizabeth Denham told the Science and Technology committee that the centre could play a ‘really good role’ in fostering public discussion around the use and application of new technologies to NHS data, promoting the UK as a ‘place of innovation and as a leading country in AI technologies’.

“The challenges facing the NHS exist in every healthcare system in the world. We need to deliver cost effective care, improve quality and safety making unexplained variation a thing of the past, and we need to democratise healthcare for all.

“Let’s take advantage of the dramatic increase in available data, and the sophisticated tools out there to process it, so no one gets left behind,” said Mark Davies, Chair of the panel debate at the HIMSS UK summit.

Today (16 April), the House of Lords Select Committee on AI published a report assessing the social, economic and ethical ramifications of AI adoption, calling on the NHS to digitise 'current practices and records' consistently by 2022 to ensure the data it holds does not remain 'inaccessible'. 

Discussions around the potential and challenges of AI in healthcare will continue at the HIMSS UK e-Health Week conference, taking place at Olympia in London on 15 and 16 May.