Veradigm integrates SDoH and mortality data to its EHR database

Veradigm’s integration of social determinants of health (SDoH) and mortality data into its electronic health record (EHR) database will provide researchers with enhanced insights into the socioeconomic and clinical factors influencing patient health, aiding more in-depth realworld data (RWD) research studies.

Veradigm, a healthcare data and technology solutions provider, has announced the expansion of its EHR database with the integration of social determinants of health (SDoH) and mortality data. These updates enhance Veradigm Network EHR (VNEHR) Data, one of the most comprehensive ambulatory EHR databases in the US, offering researchers deeper insights into the factors influencing patient health.

The addition of SDoH data offers a broader perspective on patient well-being by integrating key socioeconomic, environmental, and behavioral insights, such as income levels, education, housing stability, and social support. “With our NLP-derived SDoH and mortality data, life sciences organizations gain a competitive advantage by moving beyond traditional clinical measures to explore the full spectrum of factors influencing patient health,” said Stuart Green, Vice President and General Manager of Life Sciences Business for Veradigm. “This innovation unlocks new research opportunities and can position organizations as leaders in advancing health equity and improving patient outcomes.”

By employing advanced natural language processing (NLP) technology, Veradigm addresses a critical challenge in healthcare data: the vast amount of essential patient information trapped in unstructured clinical notes. With NLP, Veradigm can extract and de-identify this data, offering researchers actionable insights to study therapeutic decisions, disease progression, and patient outcomes across diverse populations and treatment areas.

The integration of mortality data into the ambulatory EHR database further enhances its utility for long-term studies, post-market surveillance, and identifying mortality trends associated with treatments or medical devices. This data is instrumental in advancing precision medicine, refining patient segmentation, and supporting evidence-based reimbursement strategies. Additionally, mortality insights can accelerate drug development by identifying at-risk populations and delivering targeted data for clinical research.