Stories of our impact
Our data scientists are giving critical time back to doctors
Unprecedented patient demand. Hospital admissions on the rise. Funding struggling to catch up. Challenges with recruitment and staff retention.
It’s a tough landscape for the NHS and it doesn’t help that highly trained consultants spend hours on admin. So, since autumn 2017, we’ve been exploring whether artificial intelligence (AI) and robotics could put doctors back on the front line.
Colleagues from across the UK and the Netherlands with expertise in data science, AI and robotics, plus clinicians with extensive hospital knowledge, have created three proof-of-concept solutions to tackle major NHS challenges. And, so far, the prognosis is excellent.
The gastroenterology department of Edinburgh’s Western General Hospital receives up to 40 electronic GP referrals a day. Each one must be assessed by a consultant – a task that’s crying out for automation.
To speed up the triage process, we built a model that uses natural language processing to read referrals and categorise patients’ symptoms and urgency level. This involved taking almost 22,000 letters sent over a five-year period and creating a dictionary of the most frequently used words and phrases. When these terms appeared regularly in referrals, it pointed to a patient needing a specific type of care.
The model has been able to identify with 96 per cent accuracy, for instance, when the referral was classified as suspected cancer, suggesting a huge future for AI in the NHS. The team is also looking at whether it could be used to reduce long waits for routine appointments and match, more closely, resource with patient need.
Dr Ronen Gordon, our Clinical Lead for AI, says: “We believe this is just the start of an exciting journey. AI is growing and people are doing fantastic things, but this is addressing what’s really going on in a classic NHS hospital. It shows we are able to blend technical skills with real-world experience.”
“Developing intelligent automation techniques will help hospitals in the UK and across the globe to devote more time to patients.”
Western General isn’t the only success story – two other models have shown how machines can ease the burden on the NHS.
At a major teaching hospital in London we used technology to assess clinical letters and determine, with more than 90 per cent accuracy, a patient’s status, from referral to treatment. This has the potential to clear a massive paperwork backlog.
Another model, created for a Yorkshire-based group of hospitals, can automate the coding process that takes place when patients are discharged.
Typically, large teams use electronic data and paper-based medical notes to assess the type of care the patient received and generate a code, which is then used to calculate hospital payments. AI could transform this labour-intensive system and, to date, our technology has proved more than 99 per cent accurate.
There is still a long way to go but Ronen is excited. “The numbers are unbelievable – we’re really thrilled,” he says. “Developing intelligent automation techniques will help hospitals in the UK and across the globe to devote more time to patients.”