UCLH develops AI to identify patients likely to skip appointments
15 April 2019
UCLH has developed artificial intelligence to predict which patients are most likely to miss appointments.
A team from UCLH and UCL created an algorithm using records from 22,000 appointments for MRI scans, allowing it to identify 90% of those patients who would not attend.
“On average we estimate this could save £2-3 per appointment,” NHNN consultant Parashkev Nachev told The Guardian. “Given that a big hospital could have nearly a million scheduled events per year, that could potentially be a lot of resource.”
The project is part of a broader programme that aims to bring the benefits of the machine-learning revolution to the NHS, led by the NIHR University College London Hospitals Biomedical Research Centre (NIHR UCLH BRC), a £114m translational research centre that transforms scientific breakthroughs into life-saving treatments for patients.
The health secretary, Matt Hancock, called for AI-based approaches to be rolled out more widely. “Missed hospital appointments waste patient and staff time, prevent sick people from being seen at the earliest opportunity and cost our amazing NHS an unjustifiable amount of money,” he said.
“Artificial intelligence has enormous potential to revolutionise healthcare and this is exactly the type of innovation our NHS needs to embrace to ensure every penny goes further as part of the Long Term Plan.”
- Read more in the Guardian
- More about the programme
- NIHR University College London Hospitals Biomedical Research Centre