Using an Artificial Intelligence Medical Device to Help Primary Care Practitioners Identify and Manage Skin Conditions (Tumor, Inflammatory, and Infectious Diseases) in Adult Patients at Pozuelo and Majadahonda Health Centers

NCT07429123 | Completed

• 1 other identifier: LEGIT.HEALTH_DAO_Derivación_PH
• Study Type: observational
• Target: 131
• Locations: 1 country
• Sites: 1

Brief Summary

The goal of this observational study is to learn if an artificial intelligence (AI) tool helps primary care practitioners better identify skin conditions. The study focuses on adults with suspected skin pathologies, including tumor, inflammatory, and infectious diseases. The main questions it aims to answer are:

• Does using the AI tool help doctors make more accurate diagnoses for multiple skin conditions?
• Does the tool help doctors better decide which patients need a referral to a dermatologist and which can be managed in primary care?
• Are doctors satisfied with how well the tool works and how easy it is to use in their daily work?
• Can the tool help doctors more accurately differentiate between benign lesions and skin cancer? Participants will:
• Visit their primary care doctor for a regular skin checkup.
• Have photos taken of their skin condition using a smartphone or a dermatoscope.
• Provide informed consent for their photos and basic health information (such as age and sex) to be analyzed by the AI tool.
• Receive standard care from their doctor, with the tool providing a second opinion to assist in the clinical decision-making process.

Conditions

Skin Abnormalities; Malignancy; Melanoma (Skin Cancer); Skin Cancer; Skin Condition

Keywords

Dermatolgy; Primary care; Skin cancer; Melanoma; Triage; Diagnostic accuracy

Outcome Measures

Primary Outcomes (1)

• Referral appropriateness

  This metric evaluates the appropriateness of patient referrals from primary care to specialized dermatology services. A referral is classified as "avoidable" or "unnecessary" when both the primary care practitioner and the expert dermatologist agree that the case can be effectively managed within primary care without a specialist consultation. The study's primary target for this metric was a minimum increase in referral adequacy of 15%. This threshold represents the minimum clinically important difference required to demonstrate the device's utility in optimizing clinical workflows and reducing healthcare costs.

  Baseline

Secondary Outcomes (2)

• Area Under the ROC Curve (AUC) for Malignancy Detection

  Baseline

• Healthcare Professional Satisfaction (CUS Score)

  4 months (practitioners completed the questionnaire twice: once at 2 months and again at 4 months after starting the study).

Study Arms (1)

Patiens with skin conditions treated in Primary care

This single-group cohort comprises adult patients presenting with diverse skin pathologies who were evaluated by healthcare professionals (HCPs) using an AI-based clinical decision support tool. The cohort includes individuals suspected of having tumoral (benign or malignant), inflammatory, or infectious conditions.

Device: Primary care practitioners aided by Legit.Health Plus

Interventions

Primary care practitioners aided by Legit.Health Plus DEVICE

The device is a computer vision software designed to assist healthcare practitioners in assessing skin structures through the analysis of digital images. Primary care practitioners utilize the device by capturing photographs of affected skin areas with a smartphone or mobile dermatoscope and uploading them to the platform. The software processes images of the epidermis and dermis to quantify visible clinical signs-including intensity, count, and extent-and provides an interpretive distribution of possible International Classification of Diseases (ICD) categories. Practitioners use the platform's results as a second medical opinion to guide diagnosis, triage, and referral decisions for pathologies including tumoral (benign and malignant), inflammatory, and infectious conditions. The intervention also provides clinicians with access to specific referral criteria, clinical questionnaires, and basic treatment

Patiens with skin conditions treated in Primary care

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

The study population is drawn from adult patients presenting with dermatological concerns at two primary care centers in the Madrid region: Centro de Salud de Majadahonda and Centro de Salud de Pozuelo. These participants are residents within the catchment areas of these clinics, with Hospital Universitario Puerta de Hierro Majadahonda serving as their reference hospital for specialized dermatology care. The source population consists of individuals in a real-world clinical setting undergoing preliminary assessment by primary care practitioners (PCPs) for potential referral to specialized dermatology services. This diverse cohort is intended to represent a typical population affected by various skin pathologies, specifically including tumoral (benign and malignant), inflammatory, and infectious conditions. Participants are identified and recruited during routine medical visits whenever a skin-related pathology is suspected.

You may qualify if:

• Tumor pathology:
• Benign:
• Histiocytoma
• Seborrheic keratosis
• Angiomas
• Precancerous:
• Actinic keratosis
• Suspected malignancy:
• Basal cell carcinoma
• Squamous cell carcinoma
• Pigmented lesions:
• Melanocytic nevus
• Malignant melanoma
• Inflammatory pathology:
• Psoriasis

You may not qualify if:

• Patients under 18 years of age.
• Pregnant patients.
• Patients who, in the opinion of the researcher, will not comply with the study procedures.

Sponsors & Collaborators

• AI Labs Group S.L: lead
• Fundación para la Investigación Biomédica, Hospital Universitario Puerta de Hierro: collaborator
• Puerta de Hierro University Hospital: collaborator

Study Sites (1)

Puerta de Hierro Majadahonda University Hospital

Majadahonda, Madrid, Spain

Location

MeSH Terms

Conditions

Skin Diseases; Skin Abnormalities; Neoplasms; Melanoma; Skin Neoplasms

Condition Hierarchy (Ancestors)

Skin and Connective Tissue Diseases; Congenital Abnormalities; Congenital, Hereditary, and Neonatal Diseases and Abnormalities; Neuroendocrine Tumors; Neuroectodermal Tumors; Neoplasms, Germ Cell and Embryonal; Neoplasms by Histologic Type; Neoplasms, Nerve Tissue; Nevi and Melanomas; Neoplasms by Site

Study Officials

• Gaston Roustan, PhD

  Puerta de Hierro Majadahonda University Hospital

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Target Duration: 1 Year
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: February 10, 2026
• First Posted: February 24, 2026
• Study Start: June 24, 2022
• Primary Completion: December 19, 2023
• Study Completion: January 10, 2024
• Last Updated: February 24, 2026

Record last verified: 2026-02

Locations

ES (1)