A new report commissioned by NHS England (NHSE): Evaluating Pathways for AI Dermatology in Skin Cancer Detection states Skin Analytics’ Artificial Intelligence as a Medical Device (AIaMD), DERM, can be used autonomously in the NHS.
The report showed Skin Analytics AIaMD demonstrated excellent performance with a Negative Predictive Value (NPV) of 99.8%, compared to human face-to-face dermatologist evaluations of 98.9%. It reviewed DERM’s performance on over 33,500 NHS patients, and confirms that AI can be used autonomously in the NHS if certified under classes UKCA IIa or CE III.
According to the report, preliminary analysis suggests that AI implementation could lead to significant savings, with a potential return of £2.30 for every £1 spent, and estimated savings of £86 per case. These savings mainly arise from a reduced need for face-to-face reviews and biopsies, leading to lower overall system costs.
It goes on to acknowledge a substantial increase in demand for dermatology services, with a 170% rise in urgent suspected cancer (USC) referrals over the past decade. It is noted that despite this, training positions for dermatologists remain insufficient and immediate short-term solutions like AI are needed to alleviate the current service burdens and reserve dermatology capacity for patients who need to be seen urgently.
AI for Skin Cancer Detection in the NHS: Skin Analytics’ DERM
DERM (Deep Ensemble for the Recognition of Malignancy) is a UKCA Class IIa AI as a Medical Device (AIaMD) that assesses images of skin lesions for skin cancer. It is the only UKCA Class IIa licenced AI medical device designed to assess skin lesions available in the UK market. It enables patients to be triaged earlier, accurately identifying benign lesions and detecting cancers in pursuit of driving better patient outcomes.
Currently DERM is mainly deployed in the patient pathway following an urgent suspected skin cancer referral by an NHS GP for suspicion of skin cancer. DERM is used for 1 in 10 of all urgent skin cancer referrals across 18 NHS sites in the UK, including University Hospitals Birmingham NHS Foundation Trust, Liverpool University Hospitals Foundation Trust, Dorset County Hospital Foundation Trust and Manchester University NHS Foundation Trust. These implementations are part of the NHS’s effort to improve skin cancer wait times, particularly in high-demand areas.
Neil Daly, CEO of Skin Analytics, said: “Skin cancer generates the most urgent referrals of any cancer in the UK, and this is growing every year. Despite sustained and considerable effort from dermatology departments, waitlists are growing significantly and the standard of care is not good enough. NHS data suggests that at the end of 2022 11% of urgent skin cancer referrals were waiting more than four weeks for a first assessment, amounting to 17,454 patients in Q3 FY 22/23. Since 2020, we have seen over 116,000 NHS patients for suspicion of cancer and the use of our technology, DERM, has helped NHS Secondary Care partners reduce the need for more than 63% of face-to-face urgent suspected skin cancer appointments.”
Julia Schofield, Consultant Dermatologist at United Lincolnshire Hospitals NHS Trust, said in her blog on the NHS England Report: “Of those people referred with suspected skin cancer, only around 1 in 10 have urgent skin cancer, according to NHS England cancer data, and the majority of referrals are people with benign skin lesions that don’t require any treatment. A neat solution would be to use AIaMD to diagnose the benign skin lesions referred in urgent suspected skin cancer pathways. This would free up capacity in dermatology services which would be welcomed by all.
“This is not simply an academic exercise. Some NHS Trusts are already using AIaMD to help diagnose benign skin lesions, thanks to investment by NHS England. The evidence from these Trusts which has been peer-reviewed and published in journals, has been used to inform the Edge Health report. What can’t be conveyed through data are the interviews with clinicians who have told us that they have been able to see more patients who would otherwise be waiting for the care of a specialist.”
Article as seen in:
Health Tech World
Medical Device Network
Digital Health