Clinical Workflow Optimization Using Artificial Intelligence for Dermatological Conditions

Artificial intelligence (AI) based on images presents enormous potential for improving visual diagnostic accuracy in the medical field. During the COVID-19 pandemic, limited access to in-person healthcare services drove changes in medical care, accelerating the adoption of telemedicine. In this context, the use of AI for triage and decision support can 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 a dermatological center. Both triage of these patients, clinical evaluation, and their follow-up require in-person resources and the dedication of the specialist and staff. The use of tools like AI can benefit these professionals in reducing these processes and optimizing the workload. Advances in image recognition and interpretation, as well as in artificial intelligence, have driven innovations in diagnosing various pathologies, including skin conditions. Computer-Aided Diagnosis (CAD) systems and other algorithm-based technologies have demonstrated their 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 uses artificial intelligence to optimize clinical flow and the care process of patients with skin conditions, will be evaluated. The purpose of this tool is the automatic prioritization of patients with greater urgency, assigning them the type of consultation (dermatological or aesthetic), improving the diagnostic capacity and detection of malignant pigmented lesions in auxiliary staff, as well as providing a visual record (photograph) of the condition for later review by external experts. Thus, the main objective of this study is to validate that the Legit.Health tool, based on Artificial Intelligence, improves efficiency in clinical flow and the care process of patients, reducing the time and cost of care per patient through enhanced diagnostic accuracy and determination of the degree of malignancy or severity. The secondary objectives focus on measuring the diagnostic performance of Legit.Health: Demonstrate that Legit.Health improves the ability of healthcare professionals to detect malignant or suspicious pigmented lesions. Demonstrate that Legit.Health improves the ability and precision of healthcare professionals in measuring the degree of involvement in patients with female androgenetic alopecia. Demonstrate that Legit.Health improves the ability and precision of healthcare professionals 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 consulting for pigmented lesions. Evaluate the reduction in healthcare resource usage by the center by reducing the number of triage consultations and directly referring the patient 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 resource usage by reducing the number of triage consultations and directly referring the patient 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.