Resumen

Objectives: To present a transformative paradigm—the “EHR in Motion”—that overcomes fundamental mismatches between traditional electronic health records and dermatology’s visual, dynamic practice by integrating multimodal AI and mobile-first design, thereby enhancing diagnostic accuracy, workflow efficiency, and patient-clinician collaboration. Introduction: Contemporary dermatology is constrained by static, text-centric EHRs that fail to capture the specialty's visual and longitudinal nature, creating workflow inefficiencies, data fragmentation, and clinician burnout. This presentation introduces a reimagined platform designed for kinetic clinical practice. Materials / method: We conducted an analysis of peer-reviewed literature (2018-2025), evaluated FDA-cleared AI tools and commercial EHR platforms, and integrated findings with real-world implementation data. Development involved creating a proprietary mobile platform (DVL Archive) with image-native architecture, multimodal AI fusion (vision-language models), and ambient clinical intelligence, tested in clinical scenarios across dermatology subspecialties. Results: The EHR in Motion platform demonstrated a 10-16% increase in diagnostic accuracy via AI augmentation, reduced documentation time by over 50% through ambient scribing, and enabled scalable teledermatology access. The DVL Archive mobile solution successfully restored a collaborative, shoulder-to-shoulder consultation dynamic and facilitated seamless data flow across previously siloed systems (pharmacy, lab, telehealth). Conclusion: The integration of multimodal AI into a mobile, visually-native EHR represents a necessary evolution from passive documentation to active clinical intelligence. This paradigm restores the clinician-patient connection, bridges access gaps, and transforms the EHR into a dynamic partner in care delivery, defining the future of data-driven dermatology.