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Over 120,000 patients assessed across the UK

Since 2020, Skin Analytics has assessed over 120,000 NHS patients for suspicion of skin cancer, helping Secondary Care organisations remove the need for up to 95% of face-to-face NHS urgent suspected skin cancer appointments.

Clinical performance over time

We have pioneered a market leading approach to performance monitoring for our AI as a medical device, DERM.

We’re committed to providing the best technology and being completely transparent about our results.

This table is a summary of our performance since April 2022 up to Q2 2024 Post Market Surveillance Reports, with analysis based on

lesion outcomes
1000


How do we set our performance targets?

Our performance targets are based on clinical performance published in the literature and agreed by our Clinical Advisory Committee which is composed of leading UK and international dermatologists and health economics experts.

Target
Apr 2022 to
Apr 2024
DERM v4
Dec 2023 to
Apr 2024
Negative Predictive Value
Melanoma
99%
As set here
99.8%
N=44,299
100%
N=8,180
Sensitivity
All skin cancer
97%
N=6,224
98%
N=204
Melanoma
95%
95%
N=1,037
100%
N=43
Invasive melanoma
95%
97%
N=567
100%
N=24
SCC
95%
98%
N=1,571
96%
N=57
BCC
90%
97%
N=3,551
97%
N=104
Specificity
Benign (biopsy and clinically confirmed)
75%
N=32,442
84%
N=6,091
Benign (biopsy only)
29%
N=5,318
23%
N=223
Listen to a podcast on post-market surveillance

Publications and Clinical Evidence

Patient perspectives of artificial intelligence as a medical device in a skin cancer pathway

Kawsar A, Hussain K, Kalsi D, et al.
Full publication

Accuracy of an Artificial Intelligence as a medical device as part of a UK-based skin cancer teledermatology service

Helen Marsden, Chronis Kemos, Marcello Venzi, Mariana Noy, Shameera Maheswaran, Nicholas Francis, Christopher Hyde, Daniel Mullarkey, Dilraj Kalsi and Lucy Thomas
Full publication

Effectiveness of an image analyzing AI-based Digital Health Technology to identify Non-Melanoma Skin Cancer and other skin lesions: results of the DERM-003 study​

Marsden H, Morgan C, Austin S, Degiovanni C, Venzi M, Kemos C, Greenhalgh J, Mullarkey D, Palamaras I.
Full publication

Real-world post-deployment performance of a novel machine learning-based digital health technology for skin lesion assessment and suggestions for post-market surveillance

Dilraj Kalsi, Lucy Thomas, Chris Hyde, Dan Mullarkey, Jack Greenhalgh, Justin M Ko
Full publication

Assessment of Accuracy of an Artificial Intelligence Algorithm to Detect Melanoma in Images of Skin Lesions​

Phillips, M. et al.
Full publication

Detection of Malignant Melanoma Using Artificial Intelligence: An Observational Study of Diagnostic Accuracy​

Phillips, M., Greenhalgh, J., Marsden, H., Palamaras, I.
Full publication

Download an e-book of Skin Analytics' Frontiers publications

Download


Some research featured in this e-book is from other researchers.

Independent research

In addition to the data we publish, much of which has been externally audited, Skin Analytics is working with a number of external partners to evaluate and support the expansion of our services across the NHS, including a number of independent and health economics evaluations.

 

Edge Health

Evaluating Pathways for AI Dermatology in Skin Cancer Detection

NHSE’s Outpatient Recovery and Transformation Programme (OPRT) team commissioned Edge Health to write an independent report evaluating the use of AI in skin cancer pathways.

Edge Health were tasked with exploring all AI technologies with appropriate regulatory clearance to be deployed within autonomous pathways. DERM was the only technology that met the requirements, so much of the report focuses on our performance.

Findings:

  • AIaMD can be used autonomously in the NHS if certified under classes UKCA IIa or CE III. DERM is the only AIaMD with the necessary evidence base demonstrating its safety and effectiveness for regulatory approval at this level.
  • AIaMD can rapidly process initial assessments, which could reduce waiting times for secondary care reviews, thereby enhancing patient experience and service delivery.
  • AI-enabled pathways lower system costs by reducing the need for face-to-face reviews and biopsies. Illustrative budget impact modelling suggests up to £86 in savings per case in autonomous pathways.
  • DERM’s performance is at least as good as face-to-face dermatologist evaluations. The Negative Predictive Value (NPV) for correctly excluding melanoma in a matched-prevalence population were 99.8% for DERM and 98.9% for dermatologists.*

*Based upon:
1. An independent analysis of 33,693 real-world lesions assessed by DERM (including 835 melanoma), and
2. A systematic review and meta-analysis of all studies involving consultant dermatologists up to April 2024

Evaluation overview
Full evaluation
Unity Insights

AI in Health and Care Award: Skin Analytics evaluation

The Department of Health and Social Care (DHSC) funded deployment and a real-world evaluation of DERM as part of the AI in Health and Care Award.

Working with the University of Surrey, Unity Insights conducted an evaluation of DERM in four NHS sites, across 9,649 patients between February 2022 and April 2023.

Findings:

  • In secondary care, DERM demonstrated high pathway sensitivity for malignant melanoma (97%), achieving its target rates of 95%.
  • DERM effectively triages high risk lesions to the appropriate management outcome.
  • 85% of patients rated the AI-enabled teledermatology service as good or very good.
  • Staff reported the effect of the AI teledermatology service on capacity as “transformational”.
  • Health economics compared teledermatology both with and without DERM against face-to-face referrals - all instances highlighted savings for the NHS.
Full evaluation
Edge Health

Evaluating AI Implementation in the NHS: Skin Analytics AI-powered Teledermatology

Edge Health worked on behalf of the East Midlands Academic Health Science Network to evaluate our pathway at University Hospitals Leicester.

We recommend that you see a case study of the pathway previously conducted.

Findings:

  • Despite being in its pilot phase, the AI tool demonstrated its capability to enhance patient access to dermatology services.
  • Whilst the pathway alone saves more money than it costs, the initial benefit-cost ratio does not include nonquantified benefits such as reduced Waiting List Initiative clinics, reduced biopsies and reduced long-term care costs.
  • The pathway could offer considerable benefits to the wider Dermatology cohort, healthcare staff, and the health system if implemented at scale, with potential yearly savings across the Midlands ranging between £2.1M and £5.7M.
Full evaluation

Research coming soon

  • The University of Exeter are working to independently evaluate our recently granted project through the SBRI Cancer Programme that will focus on the use of DERM in populations who have not been referred by their GP.

  • Researchers at The University of Birmingham involved with the creation of the Medical Algorithmic Audit framework published in the Lancet and the BMJ journals have been applying this framework to a Skin Analytics deployment. An abstract has been presented, full publication to follow.

Health Economics

Since 2018, we have worked with teams from Health Enterprise East, the York Health Economics Consortium, Imperial Trust, as well as the Exeter Test Group to ensure that our services are truly sustainable for the NHS.

Today, we are uniquely well-placed to answer on the cost effectiveness of using DERM in secondary care, with over three years of comprehensive real-world evidence, derived from the assessment of more than 70,000 patients across 14 NHS sites (at the time of research).

Results from our health economic analysis show that Skin Analytics delivers robust NHS dermatology cost savings. We've added a useful summary of our Skin Analytics' Health Economics fact sheet for you to read.


Read the summary

Health Economics

Since 2018, we have worked with teams from Health Enterprise East, the York Health Economics Consortium, Imperial Trust, as well as the Exeter Test Group to ensure that our services are truly sustainable for the NHS.

Today, we are uniquely well-placed to answer on the cost effectiveness of using DERM in secondary care, with over three years of comprehensive real-world evidence, derived from the assessment of more than 70,000 patients across 14 NHS sites (at the time of research).

Results from our health economic analysis show that Skin Analytics delivers robust NHS dermatology cost savings

Summary of Skin Analytics' Health Economics

Learn more

For more details, please reach out to us directly.

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