NHS Waiting Lists: Why Artificial Intelligence Offers Hope for Reducing Long Delays

Huge waiting lists are becoming a fact of life for the NHS, with total backlogs rising from 4.4 million at the start of 2020 to 7.21 million today, with tens of thousands waiting for at least 18 months.

But pioneering work with artificial intelligence (AI) is now holding out hope for reducing the health risks that such a long wait can come with.

NHS Cheshire & Merseyside Integrated Care Board (ICB) clinical leaders have used machine learning to help surgeons prioritize waiting lists, reduce bureaucracy when reviewing records, and buy consultants time to more quickly identify work in progress in an envisaged 25 system to cut costs for healthcare around the world. England.

And a related project is using AI’s ability to identify previously hidden at-risk patients to provide targeted “pre-rehab” to keep them healthy, understand why they’re waiting, and improve surgeries.

Those who have been identified can receive a “health drill” that includes tips that can help prevent the condition from worsening before surgery.

The first 100 patients completed the Waiting Well program of St Helens and Knowsley Teaching Hospitals NHS Trust, which pioneered the project. Others in the region are expected to follow suit due to early success.

Of 100 high-risk respiratory patients, surgeons expected about 12 percent to develop a chest infection at some point during or after surgery, but there was no confidence.

Professor Rowan Pritchard-Jones, senior medical director at ICB, also said that heart complications have been reduced and the program has helped reduce hospitalizations and readmissions of patients.

“We’re going to be very precise with our medications and support, but without creating additional clinical burden for busy people who have to spend their time clearing waiting lists instead of digging through mountains of notes every day,” he said. “If we can allocate our resources more efficiently and deliver better outcomes for patients, everyone will benefit.”

Cheshire and Merseyside’s artificial intelligence circuits are based on codes that doctors use to identify any disease or condition a patient may have. The AI ​​machine learning tool then scans the large dataset and creates a risk factor and expected outcome for each patient on the ICH waiting list.

This includes identifying patients who deteriorate disproportionately while waiting, such as B. those with breast disease or some form of COPD or asthma, even those who may be slightly overweight.

“We had a fantastic system that always allowed us to see the results of our work,” said Professor Pritchard-Jones. I.

“Like any surgeon, I get a report every month detailing the complications we had and what we expected based on the patient’s medical history. I saw the waiting lists grow during the pandemic, so I went back to my colleagues at C2-Ai, a technology company we’ve worked with for many years, and asked if we could get a forward-looking report that would meet the needs Patients were predicted to be treated like retrospective outcomes. And they could.

“It was like having your daughter by your side”

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

After doctors using C2-Ai technology determined that he was at high risk of worsening his condition, Mr. Dutton was invited to a targeted health workout. It included diet and exercise recommendations in preparation for surgery, which will take place in August 2022.

“I came in at 3:00 pm and left by 9:00 am the next day, making a bed for someone else,” he said. “Everything went well and the pain immediately disappeared. Six weeks after the operation, I spoke to a specialist who told me that I was very lucky because my gallbladder was full of stones, inflamed and about to burst.

“Everything I did before the surgery reduced the inflammation of the liver, which allowed them to remove the gallbladder surgically, so my recovery was much faster.

“This recovery was due to the health training I received. The hospital contacted me about five weeks before the operation and asked if I would like to speak to the trainers.

“My trainer explained my surgery to me and gave me a diet program why I should follow it. In the hospital, you only have 10 minutes with a specialist, and you return with questions you would like to ask. But the health coach gave me time to ask these questions. I went through the program, did the exercises, breathing (to help with my emphysema), whatever I needed to do.

“After the surgery, I spoke with a health coach for a month to help me recover. It was a great help, as if you had a daughter next to you who was easy to talk to. I like it. Two other gentlemen operated on by the same surgeon were still there when I went home. They didn’t have coaching.”

Dr Mark Ratnaraja, NHS pediatrician and chief executive of C2-Ai in the UK, said the pandemic poses a challenge that health care providers have never faced before.

“Yes, waiting lists were getting longer, but the scale of that length and waiting time was truly unprecedented,” he said. “If you operate on patients quickly, there are really no postoperative problems.

“But if you have to wait a very long time, there is a lot of evidence that the health of patients is deteriorating, which means that they are actually much worse during the operation than before the operation.

“That was the challenge we faced: how can we use this data to understand this dynamic change in risk over time, and since we have a constant stream of data from the hospitals we work with, we can use it on a simple for processing and presentation for the clinical team to understand, to identify and treat patients with the highest clinical need. We have reused the technology we have been using with the NHS for the last 10 years to solve this new problem.

The number of people waiting to start treatment for more than a year and a half is 45,631. NHS England data released last week showed it was down 17 percent from the previous month, a sign that progress is finally being made in clearing the backlog of treatment. the maximum waiting time is reached. Waiting times of over 52 weeks have dropped from 406,035 in December to 379,245 in January.

NHS England is closely monitoring how well the ICB is reducing waiting lists and improving patient outcomes. Professor Pritchard-Jones believes that the AI ​​tools at his disposal could revolutionize the healthcare industry needed to meet the government’s goal of eliminating full yearly expectations by March 2025.

The AI ​​used in both projects very accurately determines the risks of mortality and complications. BMJ A study involving over 11,000 patients, co-authored with Professor Pritchard-Jones, also found.

“We are looking at how we can scale this up and revolutionize the way we treat surgical patients across the country,” he said. “There is huge potential to change the way we think about patients awaiting surgery and think much more nuanced.”