AI which could help prevent bone fractures being missed is given go-ahead

Platforms powered by artificial intelligence have been recommended for use on the NHS to help prevent medics from missing bone fractures on X-rays.

The technologies could help speed up diagnosis and reduce the need for follow-up appointments, experts said.

Urgent care centres in England can use four platforms following the publication of draft guidance by the National Institute for Health and Care Excellence (Nice).

Nice said clinical evidence suggests AI could “improve fracture detection on X-rays in urgent care without increasing the risk of incorrect diagnoses”.

It added that the technology “could help reduce the number of fractures that are missed in urgent care, which would reduce the risk of further injury or harm to people during the time between the initial interpretation and treatment decision in urgent care and the radiology review”.

Improving the accuracy of diagnosis could also reduce the number of people being recalled to hospital after a radiology review, as well as unnecessary referrals to fracture clinics, according to the guidance.

People with a suspected fracture are typically assessed by an urgent care nurse or doctor, who will request an X-ray to be carried out by a radiographer.

Nice recommends these X-rays should be reviewed by a radiologist, radiographer or other trained professional, who should provide a detailed report before the patient is discharged.

However, the watchdog’s committee heard that this is not always possible in practice, with reporting delays lasting days or weeks.

Mark Chapman, director of healthtech at Nice, said: “Every day across the NHS, thousands of images are interpreted by expert radiologists and radiographers, but there is a high vacancy rate within these departments across the country and more support is needed to manage their workload.

“These AI technologies are safe to use and could spot fractures which humans might miss given the pressure and demands these professional groups work under.”

The four platforms recommended for NHS use are: TechCare Alert, which can be used on patients of any age; Rayvolve for adults only; and BoneView and RBfracture, which for adults and children aged two and up.

Mr Chapman added: “Using AI technology to help highly skilled professionals in urgent care centres to identify which of their patients has a fracture could potentially speed up diagnosis and reduce follow-up appointments needed because of a fracture missed during an initial assessment.”

According to Nice, the “true cost of implementing and using AI technologies for fracture detection is uncertain” as data was from retrospective studies.

During modelling, the cost per scan was estimated at £1, with centres using the technology advised to ensure the cost per scan is similar to the estimate in the draft guidance.

The draft guidance said “further evidence” is needed on the cost of implementation, adding: “These costs are important for understanding the financial investment that is needed and also the feasibility and sustainability of integrating AI technologies into routine healthcare.”

A consultation on the draft recommendations will run until November 5 2024.

Charlotte Beardmore, executive director of professional policy at the Society and College of Radiographers, said: “The Society of Radiographers supports Nice’s draft guidance on using AI to help detect fractures in urgent care when used to complement the expertise of reporting radiographers and radiologists and where the evidence base demonstrates efficacy.

“These AI tools can potentially improve accuracy but will not replace the expertise of radiographers and radiologists.

“With the current pressures on diagnostic services and high vacancy rates, AI can assist professionals by reducing the potential for missed fractures and enhancing patient care.

“All results will continue to be reviewed by registered and entitled professionals, as this is a requirement of the Ionising Radiation (Medical Exposure) (Amendment) Regulations 2024. The society remains committed to ensuring the safe and effective use of AI in radiography, alongside appropriate training and support for radiographers.”