Enormous waiting lists are becoming an NHS fact of life, with the total backlog growing from 4.4 million in early 2020 to 7.21 million today, and tens of thousands waiting at least 18 months.

But pioneering work with artificial intelligence (AI) is now offering hope in reducing the health risk that can be associated with such long waits.

Clinical leaders at NHS Cheshire & Merseyside integrated care board (ICB) have been using machine learning to help surgeons prioritise waiting lists, taking away the bureaucratic burden of sifting through paperwork and freeing up consultants’ time to clear their backlogs more quickly, in a scheme adopted by 25 health trusts around England.

And a linked project has been using AI’s ability to identify previously hidden at-risk patients, to allow targeted “pre-rehabilitation” to keep them well why they wait and to improve surgery outcomes.

Those identified can receive “health coaching”, offering advice that can help prevent them from deteriorating before they receive surgery.

The first 100 patients have now gone through the “Waiting Well” scheme at St Helens and Knowsley Teaching Hospitals NHS Trust, the first to implement the project. Others in the region are expected to follow suit, because of the early success it has had.

Of 100 high-risk respiratory patients, surgeons would expect around 12 per cent to develop a chest infection at some point during or post-op, but the trust did not see any.

Professor Rowan Pritchard-Jones, the executive medical director at the ICB, also said that cardiac complications had been reduced, and the scheme had helped to cut lengths of hospital stay and readmissions among patients.

“We are getting really precise with our medicine and our support, but without bringing additional clinical burdens onto busy people who should be spending their time clearing waiting lists, not sitting through a mountain of notes every day,” he said. “If we can be more effective with our resources and provide better outcomes for patients, then everybody wins.”

The basis of the Cheshire & Merseyside AI schemes are the codes that medics use to identify all the diseases or medical conditions in a patient. The AI machine learning tool then sifts through the large dataset and produces a risk factor and expected outcome for each patient on the ICB’s waiting list.

That includes finding patients who disproportionately deteriorate while they wait, such as those who have chest disease, or some COPD, or asthma, even those who are possibly a bit overweight.

“We’ve had a fantastic system that has always allowed us to look at our outcomes of surgery,” Professor Pritchard-Jones, told i.

“I, like every surgeon, get a report every month detailing the complications we had and what we would have expected, based on the patient’s background. I saw waiting lists balloon through the pandemic, so went back to colleagues at C2-Ai, the technology firm we have worked with for many years now, and asked if we could get a forward-looking report predicting patient need, rather than looking at retrospective outcomes. And they could.”

‘It was like having a daughter at your side’

Wilf Dutton, 65, had to wait nearly three years for gallbladder surgery due to the pandemic and personal family commitments, during which time his condition worsened.

Having been identified as being at high risk of deterioration by doctors with the help of the C2-Ai technology, Mr Dutton was invited to receive targeted “health coaching”, from a company called Surgery Hero. It included advice on diet and exercise in preparation for the operation which was carried out in August 2022.

“I went in at 3pm and was out the following day at 9am, freeing up the bed for someone else,” he said. “Everything went well and the pain disappeared immediately. I spoke to the specialist six weeks after the operation, who told me I was very lucky as the gallbladder was full of stones, was inflamed and ready to burst.

“Whatever I had done prior to the operation had reduced liver inflammation, which allowed them to take the gallbladder out with keyhole surgery, so my recovery was a lot quicker.

“That recovery was due to health coaching I received. The hospital contacted me about five weeks before my operation and asked me if I would like to speak to coaches.

“My coach explained my operation to me and gave me a dietary programme, explaining why I needed to be on that. In the hospital you only get 10 minutes with the specialist – and you come away with questions you wish you had asked. But the health coach gave me the time to ask those questions. I went through the programme, did the exercises, the breathing (to help with my emphysema), everything I needed to do.

“After the operation, I continued talking to the health coach for a month to help with my recovery. It was a great help, it was like having a daughter at your side who you could just talk to. I thought it was fantastic. Two other gentlemen operated on by the same surgeon were still in when I went home. They hadn’t had the coaching.”

Dr Mark Ratnarajah, an NHS paediatrician and UK managing director for C2-Ai, said the pandemic introduced a problem medics had not seen before.

“Yes, waiting lists were getting longer, but the extent of that length and wait really was unprecedented,” he said. “If you’re operating on patients quickly, post-surgical problems, as result of a deterioration in the patient’s underlying condition and or worsening comorbidities, do not really manifest.

“But if you’re waiting for very long periods of time, there’s a lot of evidence that patients’ health worsens, which means that by the time they’re operated on, they’re actually much sicker than they were previously.

“That was the challenge we were given: how to use that data to understand that dynamic shift in risk over time, and because we’re getting a constant data feed from the hospitals we’re working with, we can assimilate it and present it in an easy to understand way for the clinical team, so that the patients with the highest clinical need are identified and elevated. We were repurposing technologies we have used with the NHS over the last 10 years to solve this new problem.”

The number waiting more than a year and a half to start treatment is 45,631, NHS England figures released last week revealed, a 17 per cent fall on the previous month, in a sign that progress is finally being made on clearing the backlog of longest waits. Waits of more than 52 weeks are down from 406,035 in December to 379,245 in January.

NHS England is keeping a close eye on how well the ICB does in reducing its waiting list and improving patient outcomes. Professor Pritchard-Jones believes the AI tools at his disposal could provide a revolution the health service needs to meet the Government’s target of eliminating year-long waits completely by March 2025.

The AI used in both projects is highly accurate in identifying mortality and complication risk, a recent BMJ study involving more than 11,000 patients and co-authored by Professor Pritchard-Jones, also found.

“We have one eye on how we can scale this and have a revolution in the way surgical patients are managed across the nation,” he said. “There is enormous potential to change the way we think about patients waiting for an operation and be far more sophisticated in our thinking.”