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D4L Integrate

Effortlessly extract and combine siloed clinical data into one ready-to-use interoperable dataset.

Health Data Management Solution
Get your clinical data ready for research with D4L Integrate. With our OMOP-based Common Data Model, data from siloed systems can be integrated into one dataset. Extraction, transformation, and loading of data are facilitated by user-friendly built-in tools, streamlining the process.
Together, D4L Integrate and D4L Analyze form the Data2Evidence Platform, an end-to-end solution for effectively managing medical research data. Sign up here for a publicly available Data2Evidence demo.

Benefits of D4L Integrate at a glance

Unlock the value of your data through an interoperable dataset

Integrate data modalities beyond EHR data (e.g., genomics and imaging data) with customized extensions of the OMOP Common Data Model.

Ensure the quality of your data

Monitor the quality of your data with integrated tooling for quality checks and data characterization.

Optimize data access processes

Increase efficiency through streamlined data access request management and integration with existing identity governance solutions.

Tailor access exactly to researchers’ needs

Flexibly define user roles and their access rights to limit exposure beyond the data necessary for a specific analysis.

Tailor D4L Integrate to your needs

Choose between on-premises or cloud-based deployment, a centralized or federated setup, and pick your preferred database management system.

Comply with the highest security standards

Ensure compliance with our solution designed to meet GDPR and HIPAA regulations. It offers flexible deployment options in your private data center or in the cloud to meet your security requirements.

D4L Integrate in action

Improving patient care by advancing biomedical research in digital health and artificial intelligence.

Data4Life contributes to the AI ready platform at Mount Sinai (AIR·MS), giving researchers access to vast datasets across the Mount Sinai Health System

More about AIR·MS

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