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- Presentation
DataDerm 2.0 - a new era of leveraging technology to add value to patients and practices
Description
Dr. Joseph Sabinski from OM One presented on the advancements in dermatology data analysis through the DataDerm initiative, emphasizing the power of leveraging extensive datasets to enhance patient care and practice. He highlighted the scale of DataDerm, which includes over 65 million clinical visits from more than 16 million patients, providing a robust resource for understanding dermatological conditions. The presentation focused on how OM One integrates diverse data sources, including electronic health records and claims data, to create comprehensive patient journeys. Sabinski discussed the extraction of valuable insights from unstructured clinical narratives, which are often more informative than structured data. He introduced innovative approaches like digital phenotyping, utilizing AI to identify hidden patterns in patient histories that may signal undiagnosed conditions. The Patient Finder initiative, which aims to identify undiagnosed patients by analyzing fingerprints of disease patterns in known cases, demonstrated significant enrichment in patient discovery rates. The collaboration between OM One and dermatological experts aims not only to enhance research and clinical understanding but also to provide actionable insights that improve patient outcomes. The potential for future advancements and even deeper insights into patient journeys was underscored, indicating ongoing excitement and innovation in utilizing technology for better healthcare.
View moreConclusions
- The collaboration between OM1 and the AAD has led to the creation of the DataDerm registry, enabling the collection of vast amounts of dermatological data.
- DataDerm has aggregated over 65 million clinical visits, offering valuable insights into patient journeys with skin diseases.
- Advanced analytics and AI tools like PhenOM are being utilized to extract meaningful patterns and enhance patient care.
- Linking DataDerm with OM1's Real-World Data Cloud allows for comprehensive patient insights and research opportunities.
- The use of natural language processing and AI drastically improves the ability to analyze unstructured clinical notes to derive valuable treatment information.
- Data sets can be enriched to improve visibility into disease management and outcomes for specific conditions such as psoriasis and hidradenitis suppurativa.
- Patient Finder technology helps identify undiagnosed patients by learning from known patient data to spot similar patterns in others.
- The research has shown substantial improvements in identifying patients at risk for conditions like generalized pustular psoriasis through data-driven methods.
- Ongoing research and collaboration efforts aim to deepen the understanding of key skin conditions and improve clinical outcomes.