Clinical trial · Observational
DERM Health Economics Study
Impact of an Artificial Intelligence Platform (DERM) on the Healthcare Resource Utilisation (HRU) Needed to Diagnose Skin Cancer When Used as Part of a United Kingdom-based Teledermatology Service
NCT04123678CI-TRIAL-00053253completedClinicalTrials.gov clinicaltrialsProvenance
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
This study aims to provide an initial assessment of the potential impact DERM could have on the number of onward referrals for a face to face dermatologist review and/or biopsy from a teledermatology-based service, and to improve the understanding of the patient pathways that exist.
Conditions
Conditions (2)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Melanoma | Melanoma | ONTOLOGY_EXACT | 0.98 |
| Non-melanoma Skin Cancer | Skin Carcinoma | ALIAS | 0.90 |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| Deep Ensemble for the Recognition of Malignancy (DERM) | Device | — | UNRESOLVED |
Design
Arms and outcomes
Arms (1)
- label
- All
- description
- Patients attending a Medical Photography facility with at least 1 suspicious skin lesion will be approached to participate in the study. Participants will have an additional macro and dermoscopic image of each suspicious skin lesions suitable for photography. Photographs will be taken by a healthcare professional using an iPhone XR smart phone camera with a DL1 dermoscopic lens attachment. The images will be encrypted and electronically transmitted to Skin Analytics' cloud servers for analysis by DERM. The suspected diagnosis determined by DERM will be compared with dermatologist review and histologically confirmed diagnosis, where obtained. Healthcare resource utilization information and patient satisfaction data will also be collected
- interventionNames
- Device: Deep Ensemble for the Recognition of Malignancy (DERM)
Primary outcomes (1)
- measure
- Referral rate
- timeFrame
- Study completion, on average 5 days
- description
- The rate of unnecessary referrals for a face to face dermatologist review for the same detection rate between standard of care and DERM of lesions reviewed by teledermatology or DERM
Secondary outcomes (26)
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
Show eligibility criteria text
Inclusion Criteria: * Participant is willing and able to give informed consent for participation in the study, * Male or Female, aged 18 years or above, * Has at least one suspicious skin lesion which is being photographed as part of Standard of Care (SoC), * In the Investigators opinion, able and willing to comply with all study requirements. Exclusion Criteria: * Any other significant disease or disorder which, in the opinion of the Investigator, may either put the participants at risk because of participation in the study, or may influence the result of the study, or the participant's ability to participate in the study.
References
Publications (1)
- DERIVEDMarsden H, Kemos P, Venzi M, Noy M, Maheswaran S, Francis N, Hyde C, Mullarkey D, Kalsi D, Thomas L. Accuracy of an artificial intelligence as a medical device as part of a UK-based skin cancer teledermatology service. Front Med (Lausanne). 2024 Mar 22;11:1302363. doi: 10.3389/fmed.2024.1302363. eCollection 2024. PMID 38585154