Artificial intelligence (AI) that predicts likely missed appointments and offers back-up bookings will be piloted by the NHS in a bid to maximise resources and potentially save billions.
Through algorithms and anonymised data, the technology breaks down the reasons why someone may not attend an appointment – using a range of external insights including the weather, traffic and jobs.
The appointments are then arranged for the most convenient time for patients – for example, it will give evening and weekend slots to those less able to take time off during the day. The system also implements intelligent back-up bookings to ensure no clinical time is lost, maximising efficiency.
It is currently being piloted in Mid and South Essex NHS Foundation Trust, which supports a population of 1.2 million people, with an average did not attend (DNA) rate of 8%. When used at full scale, it is predicted it will allow an additional 80-100,000 patients to be seen each year at the Trust.
The software, created by Deep Medical and co-designed by a frontline worker and NHS clinical fellow, is set to be tested at five additional trusts from this year.
The NHS recently launched a renewed drive to reduce hundreds of thousands of missed hospital appointments every month, to help boost the recovery of elective services. It is estimated that there are eight million missed hospital appointments each year with an estimated annual cost to the NHS of £1.2 billion pounds.
NHS chief executive Amanda Pritchard said: “The NHS has been at the forefront of innovation for almost 75 years, adopting the latest technologies and treatments to ensure patients have the best possible experience.
“This new pilot is no different – it shows the NHS testing the latest technological advancements to address the real world challenges we face. The system will help ensure patients receive ‘smart’ appointments, that are convenient and fit into people’s increasingly busy lives.
“It is a win-win for patients and the NHS alike – it will help us to free up doctors’ time to treat more patients, save taxpayers’ money as well as helping to reduce waiting times.”