Clinical Workflow Optimization Using Artificial Intelligence for Dermatological Conditions

Summary

Artificial intelligence (AI) based on imaging holds tremendous potential to enhance visual diagnostic accuracy in the medical field. Amid the COVID-19 pandemic, limited access to in-person healthcare services drove shifts in medical care, hastening the adoption of telemedicine. In this context, AI usage for triage and decision support may be crucial for professionals to manage workload and improve performance. In dermatology, pigmented lesions, acne, and alopecia are three recurring pathology groups with high demand in dermatological centers. Both triage, clinical evaluation, and patient follow-up require in-person resources and specialist dedication. Employing tools like AI can benefit these professionals in reducing such processes and optimizing workload.

Advancements in image recognition and interpretation, as well as in artificial intelligence, have spurred innovations in diagnosing various pathologies, including skin conditions. Computer-Aided Diagnosis (CAD) systems and other algorithm-based technologies have demonstrated the ability to classify lesion images with a competency comparable to that of an expert physician.

In this study, the Legit.Health tool, developed by AI LABS GROUP S.L., which utilizes artificial intelligence to optimize clinical flow and patient care processes for skin conditions, will be evaluated. The purpose of this tool is to automatically prioritize patients with greater urgency, assign the type of consultation (dermatological or aesthetic), enhance diagnostic capability and detection of malignant pigmented lesions in auxiliary staff, and provide a visual record (photograph) of the condition for later review by external experts.

Thus, the main objective of this study is to validate that Legit.Health, based on Artificial Intelligence, improves efficiency in clinical flow and patient care processes, thereby reducing time and cost of patient care through enhanced diagnostic accuracy and severity determination.

The secondary objectives focus on measuring the diagnostic performance of Legit.Health:

Demonstrate that Legit.Health enhances healthcare professionals\' ability to detect malignant or suspicious pigmented lesions.

Demonstrate that Legit.Health improves healthcare professionals\' ability and precision in measuring the degree of involvement in patients with female androgenetic alopecia.

Demonstrate that Legit.Health improves healthcare professionals\' ability and precision in measuring the degree of involvement in patients with acne.

Additionally, the study aims to assess the utility of this tool:

Automate the triage/initial assessment process in patients presenting with pigmented lesions.

Evaluate the reduction in healthcare resources usage by the center by reducing the number of triage consultations and directing the patient directly to the appropriate consultation (esthetic or dermatological).

Evaluate Legit.Health\'s usability by the patient. Demonstrate that Legit.Health increases specialist satisfaction. Evaluate the reduction in healthcare resources usage by reducing the number of triage consultations and directing the patient directly to the appropriate consultation, whether in aesthetic or dermatological settings.

Methodology Study Design Type This is an observational study, both prospective with a longitudinal character and retrospective case series.

Study Period This study estimates a recruitment period of 3 months. The total study duration is estimated at 6 months, including the previous time for retrospective analysis and the necessary time after recruiting the last subject for database closure and editing, data analysis, and preparation of the final study report.

The total study duration for each participant with pigmented lesions will be 1-3 months. The duration for patients with acne and alopecia will be 1 day.

Study Population Adult patients (≥ 18 years) with skin pathologies treated at the Dermatology Unit of IDEI.

Conditions

• Acne
• Acne Vulgaris
• Alopecia, Androgenetic
• Pigmented Lesions
• Pigmented Skin Lesion

Sponsors & Collaborators

• Instituto de Dermatología Integral (IDEI)

  collaborator UNKNOWN

• AI Labs Group S.L

  lead INDUSTRY

Principal Investigators

• Miguel Sánchez-Viera, PhD · IDEI Hospital

Eligibility

Min Age

16 Years

Sex

ALL

Healthy Volunteers

No

Timeline & Regulatory

Start

2024-01-15

Primary Completion

2024-06-30

Completion

2024-09-30

Countries

• Spain

Study Locations