Data4Life releases open-source health data research platform built on OMOP CDM

Data4Life, a nonprofit digital health organization, has announced the release of its research platform, Data2Evidence (D2E), as open source. Built on the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM), D2E is designed to support the integration, standardization, and analysis of diverse health data for research purposes.

Now freely available to researchers and developers worldwide, D2E aims to support a range of use cases including epidemiology, public health, real-world evidence (RWE), medical informatics, and digital health research.

“The open-source release of Data2Evidence is a significant step toward making health data research more transparent, efficient, and collaborative,” said Christian Weiss, CEO of Data4Life. “We look forward to advancing evidence-based digital health together with a global community.”

D2E supports the ingestion, standardization, and analysis of diverse health data through built-in pipelines, cohort-building tools, and integrated quality control functions. The platform allows for integration with external machine learning tools to enable advanced data analysis.

It includes a customizable dashboard designed to provide anonymized, aggregated data summaries and visual comparisons for exploratory research. According to Data4Life, the open-source release allows for independent assessment of the platform’s privacy and security features.

Data4Life’s decision to open-source the platform allows for independent review of its privacy and security features, supporting transparency in research infrastructure.

D2E is designed to meet the needs of a wide research audience, including those already using the OMOP CDM through the Observational Health Data Sciences and Informatics (OHDSI) network, which includes more than 4,200 researchers. By aligning with OMOP standards and supporting open formats, D2E facilitates data reuse and helps address common barriers to interoperability.

Its modular architecture makes it suitable for use in longitudinal studies, pharmacovigilance, and digital health research. The platform also supports the secondary use of health data by helping standardize complex and diverse data sources.

“Open access to source code allows for independent review of security and privacy standards,” the organization stated. “Global collaboration and community-driven development speed up the creation of new features and applications.”