AI dermatology company Skin Analytics has received regulatory clearance in the UK to drive clinical management.
Using AI, the company’s medical device DERM is designed to accelerate patient diagnosis by ensuring urgent cases are identified early and moved into care quicker. The organisation works with NHS Partners to design new patient pathways that leverage DERM to assess more patients faster. This can support in reducing wait times for urgent cases and ease pressure on the NHS, which currently faces a shortage of dermatologists.
Rapid diagnostics has been identified in the NHS Long Term Plan as the biggest factor in cancer survival rates, which lays out a target to increase the proportion of cancers diagnosed at Stages 1 and 2 from half to three quarters by 2028. For skin cancer specifically, research has suggested that early identification in dangerous skin cancers such as melanoma can significantly impact survival rates.
DERM uses machine learning to support clinicians in recognising the most common malignant, pre-malignant and benign skin lesions including melanoma, the most dangerous of the common skin cancers and the fifth most common cancer in the UK.
The AI technology is currently supporting clinicians with a decision support service in five NHS sites across the country and with their partners, have assessed more than 23,000 NHS patients, found 1,473 skin cancers, and avoided 4,713 dermatology appointments.
The certification is the first step in enabling the company to unlock new pathways with NHS Trusts, aiming to further support the NHS with outpatient demand in dermatology.
The UKCA mark validates Skin Analytics’ 10-year history of research and development on skin lesions. DERM is being used across the NHS and the classification is expected to unlock alternative pathways to diagnosis. As AI continues to play a larger role in skin cancer diagnosis, the organisation will be expected to meet further quality standards and is also working with regulatory bodies such as the FDA to help shape standards for AI supported care.
James Hamlyn, quality assurance and regulatory director of Skin Analytics said: “Skin cancer rates are doubling in the UK every 10-15 years and about 30% of dermatology posts in the NHS are unfilled. Healthcare systems are not equipped to deal with the volume of patients they need to see, especially in the light of the backlog created by COVID. AI can bridge this gap.
“Achieving Class IIA UKCA certification is therefore a significant milestone for our field and is a tribute to our organisation’s rigorous quality and evidence standards. We know that the vast majority of patients on the skin cancer pathway last year were not urgent and DERM is able to support the NHS in their outpatient recovery work for dermatology. Working with our partners, we have the potential to drastically reduce patient wait times, unlock new access pathways for patients and reduce healthcare inequalities across the board.”
DERM is currently deployed in five NHS sites, including University Hospitals Birmingham NHS Foundation Trust, Mid and South Essex Health and Care Partnership, West Suffolk NHS Foundation Trust, University Hospitals of Leicester NHS Trust and Chelsea and Westminster Hospital NHS Foundation Trust. It has assessed almost 23,000 NHS patients, caught 1,473 cases of skin cancer on pathway and discharged 4,713 patients which has enabled clinicians to put patients onto the right pathway of care sooner.
Tom Wilson, interim Rapid Diagnostic Centre programme director, Mid and South Essex Joint Commissioning Team said: “Mid and South Essex Health & Care Partnership started deploying Skin Analytics as a two-year initial pilot across its primary care providers. The Trust was looking for a tool that could support GPs with decision-making, specifically, whether to refer a patient to the urgent two week wait referral, meaning that healthy patients can be identified as early as possible, freeing up capacity to focus on urgent cases.
“The strength of Skin Analytics' technology is its ease of use with most practices only needing minimal training and the speed with which a GP receives feedback from the AI powered system. We have been impressed with the support shown by the whole Skin Analytics team to deploy the service across a large number of providers, particularly in regards to the team's rigorous safety and risk management.”
