What You Should Know:
– Datma, a leader in federated real-world data access announced the launch of advanced patient journey mapping capabilities within its flagship platform, datma.FED.
– The new functionality is designed to provide pharmaceutical companies with a clearer, privacy-preserving view of how therapies are adopted in real-world care by enabling structured analysis of patient timelines across diverse clinical, genomic, and diagnostic data sources.
Unveiling Real-World Insights into Therapy Adoption
Patient journey mapping offers crucial real-world insights into how individuals navigate the healthcare system, from initial diagnosis through therapy initiation and ongoing care. Understanding these pathways helps pharmaceutical teams identify critical barriers that can prevent timely treatment, recognize existing care gaps, and evaluate variations in provider decision-making. By supporting privacy-preserved queries across different health systems and laboratories, datma.FED now provides a scalable method for understanding therapy adoption patterns directly at the point of care.
“This launch is an important step toward helping pharma teams understand what’s happening between diagnosis and treatment, where patients drop off, how providers make decisions, and why variation exists across care settings,” said Robin Edison, VP of Product at datma. “This functionality gives organizations visibility without requiring raw patient-level data to be centralized or transferred.”
Turning Complex Data Into Actionable Journeys with AI
The new capability leverages large language models (LLMs) to extract structured timelines from a variety of unstructured and structured data sources. This includes clinical notes, molecular panels, medication records, and other event data. These events are then categorized, timestamped, and converted into structured sequences that accurately represent an individual patient’s journey. Advanced clustering methods are subsequently applied to these representations to identify shared treatment patterns and facilitate comparisons across different clinical sites or patient populations.
A core tenet of this feature is its operation within datma.FED’s robust federated architecture. All patient journey analysis is conducted locally, meaning sensitive data remains securely within each participating institution’s own infrastructure. Journeys are computed on-site, anonymized as numerical embeddings, and then analyzed in aggregate. This innovative approach enables valuable cross-site insights without the need for data transfers, thereby maintaining compliance and protecting patient privacy.
