AI in Dermatology: a White Paper by Edge Health for NHSE

The Context

The NHS is currently grappling with a growing demand for Dermatology. Waiting lists have grown by 82% since 2021, and the rate of GP referrals for skin cancer having nearly doubled in the last decade. This is compounded by a national shortfall in dermatologists as vacancies in 2021 amounted to 159 WTE.  Our report, published in July 2024, has shown that AI holds considerable promise for skin cancer pathways including improving effectiveness and reducing wait times. 

AI is currently in use for diagnosis within NHS skin cancer pathways with all lesions second-read by a clinician. Greater efficiency, speed of diagnosis and clinician time could be released if AI as a Medical Device (AIaMD) functioned autonomously. NHS England commissioned Edge health to conduct an independent review of the safety and effectiveness of AI in Dermatology and assessment of its performance against accepted standards of accuracy.

Methods and Key Findings

We examined real-world data from over 33,000 lesions assessed by DERM – an AIaMD developed by Skin Analytics, the only product that currently meets regulatory standards for autonomous use. We conducted a semi-systematic meta-analysis reviewing 153 studies and interviewed eight members of staff across three providers currently adopting the AIaMD. This enabled a grounded perspective on its application in skin cancer detection.

Our findings indicate that DERM’s diagnostic accuracy in ruling out melanomas is at least as good as in-person consultations with dermatologists. This suggests that AI could play a crucial role in distinguishing benign from concerning lesions, streamlining referrals, and ensuring those in need of urgent care are seen promptly. We also identified potential system-level efficiencies, finding that each pound spent could return up to £2.3 in savings. In this context, our report highlights AIaMD’s potential to refine the triage process, thereby addressing the rising demand for services and reducing waiting times for assessments.

While our economic analysis suggests potential savings, the primary focus of the report is on the clinical and operational implications of AIaMD, and what steps should be taken to monitor its use in Dermatology through post-market surveillance (PMS). Clear PMS plans and agreements need to be in place, with responsibilities lying with both deployment sites and manufacturers. Our report condenses PMS recommendations from several literature sources and offers an example of how PMS could be implemented in practice.

In commenting our analysis, NHS England said:

The report makes clear that the use of AI holds considerable promise for improving the efficiency and effectiveness of skin cancer pathways. Evidence of its deployment in the NHS has demonstrated that whilst the tool could be used autonomously to exclude benign skin, adequate safeguards, will need to be in place. This provides the potential to free up specialists to focus their expertise on the most urgent and complex cases.

Julia Schofield, Clinical Lead for Dermatology for the National Outpatient Recovery and Transformation programme

Read Our Report

The report concludes that thoughtful deployment of AI in Dermatology has the potential to enhance patient pathways and alleviate system pressures. With appropriate safeguards and continuous evaluation, AI can support the NHS in upholding its commitment to innovative, high-quality patient care.

Read the full report below.