DERM in a routine pathway: finding cancer and significantly decreasing backlog

After seeing success in their partnership with Skin Analytics to deliver an AI-driven teledermatology pathway for suspected skin cancer, the dermatology team at Ashford & St. Peter’s Hospitals NHS Foundation Trust (ASPH) returned to Skin Analytics for further support with their routine pathway.

Our impact

patients seen
0
patient(s) waiting 18+ weeks
71
of patients upgraded to an urgent F2F appointment
0 %

ASPH needed Skin Analytics‘ help to set up an AI driven routine skin lesion pathway to address their backlog of 396 patients and pick up any premalignant or malignant lesions whilst discharging those lesions that had resolved.

ASPH and Skin Analytics initially partnered together in July 2022. Using Skin Analytics’ AI as a medical device, DERM, ASPH have seen more than 2,400 patients on their Urgent Suspected Cancer (USSC) pathway, of which, 21% have been discharged by Skin Analytics, 14% were redirected to an onward speciality and 14% were downgraded to a routine appointment.

With these benefits, nearly 50% of ASPH’s patients experienced a quicker next step in the post-referral pathway; so ASPH were confident in Skin Analytics’ ability to optimise their routine skin lesion pathway too.

The challenge

ASPH’s routine skin lesion pathway was facing some key challenges:

  • Up to 1 year wait times for some patients
  • With such a long wait, GPs were reluctant to use the standard routine pathway, resulting in an understandable misuse of the urgent suspected skin cancer pathway in some cases
  • Limited Dermatologist capacity offered no opportunity to clear the backlog and reset the pre-Covid 6-8 week wait for routine skin lesions

The solution

In July 2023, ASPH launched Skin Analytics’ AI teledermatology into their routine skin lesion pathway.

Prior to attending an imaging hub in the patient’s locality, the patient receives an SMS containing a link to a medical questionnaire and information about their appointment. At the hub, the patient’s medical and lesion history is confirmed and images of their mole or skin lesion are captured by a Healthcare Assistant using an iPhone and dermatoscope. These images are uploaded to the Skin Analytics platform to be assessed by DERM. Cases can then be reviewed by ASPH dermatologists where they are triaged to the most appropriate next step in their management or discharged.

Nationally, more than 1 in 3 melanoma are found on non-urgent referral pathways. Implementing AI teledermatology allowed ASPH to rapidly screen their routine waitlist backlog for premalignant or malignant lesions and ensure that face-to-face appointments were used for patients who needed treatment.

ASPH’s 18+ week Referral to Treatment (RTT) Waiting Times breach on the routine pathway reduced from 71 to 1 patients, and the overall routine waitlist reduced from 396 to 33 patients.

ASPH logo
NIHR
AAC
NHS

This report is independent research funded by the NHSX (AI In Health and Care Award, AI_AWARD02451: DERM: Best practice and health economic benefits of AI triage in innovative skin cancer pathways. (Skin Analytics)). The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, NHSX or the Department of Health and Social Care.

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