(041) Chronic Itch, Chronic Silence: An App to Bridge Diagnostic Gaps in Vulvar Conditions

Abstract Introduction Currently, there are challenges in diagnosing vulvar dermatologic conditions with universally accepted ontologies, including limited resources that underrepresent diverse skin tones. This has led to the development of an app to address this health concern. Our team created a comprehensive, detailed database that serves as a pilot, foundational resource for developing clinical decision support tools in vulvar dermatology. This database includes condition-specific attributes, differential diagnoses, chronological timelines, and treatment options. Various resources were utilized to address conditions affecting the vulva across diverse patient populations. Objective The development of a structured database and algorithmic application that cross-references clinical signs, distribution, and condition-specific attributes to enhance clinicians’ ability to accurately diagnose vulvar conditions. Methods We conducted a structured review of reputable dermatological databases and peer-reviewed publications for 26 vulvar dermatologic conditions that are commonly misdiagnosed in pigmented skin. A standardized data abstraction spreadsheet was developed to capture key diagnostic variables for each condition. Extracted features included morphology, symptom profile, chronicity, hormonal or age associations, exacerbating factors, and defining distinguishing characteristics. Data was manually curated for clinical precision, and discrepancies across sources were resolved based on concordance of distinguishing features and relevance to point-of-care decision-making. Representative images were manually curated from validated sources (ie, In Plain Sight, VisualDx, UpToDate). Search criteria combined condition names with “vulvar,” “genital,” and “skin of color,” and images were screened for diagnostic clarity, accurate labeling, and de-identification. Only images vetted by board-certified dermatologists, gynecologists, or peer-reviewed authors were used, and non-diagnostic or low-quality images were excluded. Images were selected for diversity and assessed across skin tone (Fitzpatrick skin type filters or visual review), disease severity (mild to extensive), and anatomic distribution (vulvar to perineal/inguinal) to reflect the range of clinical presentations observed in practice. Results The final tool incorporates the structured review of 26 conditions into six major diagnostic pathways, beginning with the patient’s primary symptom or clinical finding. Based on the image database constructed from validated resources, this includes erythematous/inflammatory lesions, cystic or nodular lesions, infectious conditions, premalignant/malignant lesions, atrophic disorders, and pain or functional disorders. Each pathway begins with a primary presenting symptom and guides clinicians through key distinguishing features, including lesion morphology, chronicity, associated discharge, and pain. Recommended first-line treatments are provided in alignment with evidence-based guidelines. The finalized entries reflect consistent terminology, clarified diagnostic distinctions, and unified attribute fields for morphology, symptom pattern, chronicity, and management approaches. This harmonized dataset establishes the foundation for the next development phase, which will focus on variable mapping and interface integration within the Eval-health platform. Conclusions The proposed development of this database app, based on a review of vulvar dermatologic conditions, will provide a standardized, accessible resource for clinicians and providers to support the diagnosis of various vulvar dermatologic conditions. By leveraging the app’s key features and evidence-based management guidelines, it can enhance the precision of treatment and improve patient care. Disclosure No.