“I’m a huge believer in AI and machine learning,” says Monica Jones, chief data officer at the University of Leeds and deputy director of HDR (Health Data Research) UK North. “It’s been talked about for a long time, but it’s here and it’s here to stay. But AI technologies rely on high-quality, well-managed data, and to harness the transformative potential of AI, we need to strengthen our data base: bad data – bad AI; good data – good AI.”
Simon Noel, head of nursing informatics at Oxford University Hospitals NHS Foundation Trust, says “the sky is the limit” when it comes to AI’s potential.
“Healthcare, by its very nature, is data-intensive and generates a huge amount of information about a huge number of people in a huge number of areas – not just around diagnostics, but also around operational performance, people, trends, population health,” says Noel, who sits on the CNIO Digital Health advisory board, which is drafting a position statement on the use of AI in clinical note production. “It’s a rich and dynamic environment that’s a natural place for AI to take hold.”
There is a huge opportunity to predict what will happen to people and populations.
Simon Noel
He is particularly excited about initiatives emerging in the area of complex data management, such as using MRI to predict whether patients will eventually develop heart disease. “There are a multitude of opportunities to predict what is going to happen to people and populations, and if we are able to apply that information appropriately, it can be a huge help in targeting what we need to do in health care, but also in preventing people from getting sick.”
Dan Midgley, UK and Ireland sales director at Orion Health, says there are misunderstandings about what AI does and means, but the promise is actually huge. “In the coming months and years, it’s really going to be about how AI can help clinicians make decisions, plan and prioritise, rather than taking over,” he says. “I think some people worry about replacing the clinician-patient relationship, but we don’t see it that way. It’s more about whether we embrace the promise of AI, how can clinicians make better decisions, how can patients take ownership of their own care, and how can we augment capabilities and get people to the right place at the right time?”
Longer term, he adds, it’s about increasing productivity and reducing administrative burdens for staff. “It’s also about making sure that care is more personalized and patient-centered, and ideally more proactive as well — starting to identify when intervention is needed before a patient is really sick, rather than waiting for them to show up in the emergency room.”
