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How to shorten the healthcare waiting list? The next challenge of AI to reshape healthcare

Posted on: November 26, 2021

November 20, 2021

Rolling out artificial intelligence in healthcare still faces barriers. But even small-scale solutions are helping the NHS face its biggest problem

Artificial intelligence is already being used to read medical imagery, help patients manage conditions such as diabetes, and even suggest new cancer-drug regimens.

But with the world still reeling from the pandemic, AI is now needed to help an even more pressing problem. “The biggest pressure is trying to marshal our resources against the waiting list,” said Catherine Pollard, director of tech policy at NHS, speaking at a recent Microsoft Health breakfast at WIRED Health: Tech. “We have really significant staffing challenges. That needs solutions – ones that are really practical.”

5.6 million people in the UK are currently on hospital waiting lists.

Digitization is helping: remote appointments, for example, soared in popularity during the pandemic and can cut down time spent on non-urgent cases.

“We’ve got 55% of our adult population registered on our app. 600,000 patients total, over a million consultations,” explained Omar Din, managing director of primary care at AT Medics & Operose Health. “63% of those consultations are purely administrative. We spend time looking at that and then triage it to the right person in the team. When someone requests a sick note, I don’t want that going to my GP, I want it to go to someone else who can deal with it.”

However, not all patients can attend appointments remotely, and many hospitals still lack the required digital tools and skills to manage patients’ electronic records, let alone deploy AI solutions.

Even when systems are digitized, poor implementation can mean they’re not used effectively. “When I worked in a hospital, we had 100 different forms on the EHR [electronic healthcare record,” said Emma Stratful, transforming digital health at OX.DH. “Clinicians do not have time to navigate 100 forms – so everything went into progress notes.”

That’s where practical AI can come in useful. Enabling doctors to use voice assistant technology can save time that would previously have been used typing up notes.

Natural Language Processing (NLP) can then help clinicians and researchers access those notes more effectively. “Primary care data is the richest data in the NHS because of the way in which it is populated by clinicians – but it’s the unstructured data that’s got value to it,” Din said. Guy’s & St Thomas’ hospital trust, for example, are involved in a project using NLP to identify social factors associated with mental health problems.

“For example, if the patient said they’re having housing issues, or they have had trouble at home, I can now get my social prescriber or my mental health practitioner involved, and it’s not hitting the GP,” Din explained.

Genomics England is using NLP to analyze patient notes in the National Cancer Registry, connecting that phenotypic data to imaging and genomic data in order to get a better understanding of cancer progression.

The main barrier for AI solutions in health is still data.

Even just within the NHS, there are 223 hospital trusts, often running siloed IT systems and reluctant to share. The challenge is around a meaningful data strategy. “They just don’t talk to each other,” Stratful explained. “Their data is there, but it’s how do you get access to it in a meaningful way?”

Part of that challenge is finding ways to manage data in a transparent and secure way, while maintaining patient privacy. Genomics England has taken a novel approach: “Put the patients in charge,” said Genomics England CEO Chris Wigley. Participants in its 100,000 Genomes Project elect representatives to sit on an access review committee; any researchers or companies that want to access GE’s 50 petabyte database must first receive the committee’s approval.

“We’ve had 139 companies work on the data, and no whisper of complaint from anyone.” Wigley said.

Another way is to circumvent the traditional healthcare system altogether.

In early 2020, Tim Spector, professor of genetic epidemiology at King’s College London and co-founder of the ZOE diet study app, decided to pivot to study COVID symptoms. Four million people have now taken part, opting in and logging their data on the Zoe app.

“What we’re trying to do is to change the culture of healthcare research,” Spector said. “We did a mental health survey of a million people, a diet survey of a million people, and we had results in a week. Before, it would have cost us five years of writing grants and at least £5 million to do that.”

Jacob West, director of healthcare at Microsoft UK, explained how Microsoft is supporting healthcare providers through its Cloud for Healthcare, NLP tools, as well as technology including HoloLens.

“The pandemic has actually crystallized our approach to healthcare, as a first responder to the first responders,” West said. “We’re really interested in how we can help create what I would call intelligent health systems, so we can unlock unstructured data, curate it, analyze it and then feed it back in real time to people who need it.”

For example in the US, Ochsner Health has trialled an AI system which monitors deteriorating vital signs, and has helped to reduce patient codes by 44%.

Microsoft is also supporting AI projects to detect cancer, detect cardiovascular disease, and prevent blindness. In each case, the solutions combine reliable, widely available technologies that together can make a measurable impact – in a single hospital, or at scale. “We must also invest in enabling and upskilling our healthcare workforce and future leaders so that they can understand, embrace, and scale trusted, reliable, human centered AI” said Junaid Bajwa, chief medical scientist at Microsoft Research. Done right, even small-scale AI solutions can help cut the waiting list – and let doctors spend more time with their patients.

Read more about Microsoft’s AI for Health program here.

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