Data4Life Data2Evidence 2 research platform using OMOP common data model

Описание: Data2Evidence – Deep Dive into the Research Platform That Turns Raw Data into Real-World Evidence

Behind every medical breakthrough lies a massive challenge: turning complex, siloed healthcare data into actionable insights. In this in-depth explainer, we show how Data2Evidence bridges that gap — supporting researchers and IT teams alike with a secure, standardized, and collaborative environment.

Data2Evidence is an open-source platform that helps institutions transform fragmented health data into research-ready datasets using the internationally recognized OMOP common data model. It streamlines every step — from ETL (extract, transform, load) to analysis and collaboration — in full compliance with GDPR and HIPAA.

Step 1: Data Preparation & Integration with D4L Integrate

D4L Integrate is the data engineering core of the platform. It enables IT teams and data administrators to:

Extract data from electronic health records (EHRs), lab systems, genomics pipelines, imaging platforms, and more

Map and harmonize different data types into a single, interoperable dataset using customizable tools

Use flexible ETL pipelines tailored for OMOP CDM, with the option to extend to other data modalities (e.g., genomics, imaging, sensor data)

Validate data quality before loading with integrated Data Quality Dashboards (DQD) to detect and fix errors (e.g., missing fields, data type mismatches, logic inconsistencies)

Create custom data workflows without having to load full datasets, allowing near real-time testing and refinement

Version datasets to allow parallel workstreams: researchers can work with stable data slices while administrators update the master set

Manage metadata (e.g., data source, collection location, consent status) to improve transparency and reusability

Control access with role-based permissions to ensure researchers get precisely the data they need – and nothing more

Step 2: Data Exploration & Cohort Building with D4L Analyze

Once the data is integrated and ready, D4L Analyze gives research teams the tools to work directly with the data — no advanced technical background required.

Researchers can:

Explore available datasets through intuitive dashboards and metadata views

Define concept sets (e.g., diabetes, specific drug classes) to structure queries around diagnoses, medications, procedures, and other clinical criteria

Build cohorts through easy-to-use inclusion and exclusion filters, including binary and temporal logic (e.g., “X must happen within 30 days after Y”)

Get real-time feedback via dynamic graphs and visualizations during cohort creation

Run cohort quality checks to verify completeness, consistency, and clinical relevance

Save and share cohorts and filters for reusability and reproducibility

Step 3: Collaboration, Notebooks & Advanced Analytics

D4L Analyze also supports modern research workflows through advanced tools:

Interactive notebooks (e.g., Jupyter) allow researchers to run statistical analyses or machine learning pipelines directly within the platform

Integrate external tools or export data in standard formats (CSV, JSON, etc.) for use with R, Python, or other analytics environments

Connect to high-performance computing clusters for larger-scale analyses

Securely collaborate with team members or external partners by sharing datasets, cohorts, and notebooks – with full traceability

Monitor access and activity via integrated logs to meet compliance and audit requirements

Compliance & Deployment

Data2Evidence is designed for flexible, secure deployment:

Deploy on-premises in your institution’s data center or in a secure cloud environment

Built to meet GDPR and HIPAA data protection requirements

Enables data governance best practices while fostering transparency and participant trust

With Data2Evidence, institutions can:
Break down data silos
Save months of manual data wrangling
Accelerate cohort creation
Empower clinicians and researchers to drive insights
Reuse validated datasets for future studies
Make real-world clinical data ready for high-impact research

Data2Evidence.
Empowering health research to turn patient data into evidence.
From siloed systems to scalable science — with Data4Life.