edenceHealth NV

edenceHealth NV
Post Code
Business Phone Number
+32 (0)3 450 80 30
Business Email
Business Website Address
Year of Certification
Work Languages
English, Dutch, French, Norwegian, Hebrew, Spanish
OHDSI Software and Tools, OMOP CDM ETL, Technical infrastructure services, OHDSI Training, OMOP Standardized Vocabularies
Experience with health data translation
  • edenceHealth has successfully completed multiple EHDEN data harmonization projects, covering over 40 million patient records, a wide range of data source sizes and complexities, ETL programming languages and deployment technologies
  • edenceHealth has experience doing data harmonization towards OMOP CDM for other projects. For example, we are currently working on several data harmonization projects for HONEUR data partners. HONEUR is a Janssen-led federated network of Haematology centers which, like EHDEN, uses OMOP CDM and OHDSI as the technical foundation.
  • edenceHealth team members have several years of previous experience performing OMOP CDM data harmonization for other data sources and projects, such as for participating centers/data sources in the EMIF project
  • edenceHealth is the technical partner on a federated data network initiative in Rwanda (LAISDAR), where we are responsible for designing and implementing the federated data network, as well as harmonizing different data sources to OMOP CDM
  • edenceHealth has the capability to develop web-based applications. For example, we are currently developing a data entry platform for a clinical registry to replace a legacy system
  • For relevant posters/abstracts, see https://edence.health/publications/
Other expertise
  • Implementing ETL pipelines in Python, SQL and other technologies
  • In-house developed tools for terminology mappings and review
  • Infrastructure/containerization (AWS, Docker, Kubernetes, Podman)
  • Setting up/containerizing/configuring/working with a range of OHDSI tools such as Atlas/WebAPI, Achilles, WhiteRabbit, Usagi, DataQualityDashboard (DQD), CdmInspection, Arachne
  • Patient level prediction/modeling using EHR and claims data
  • Technology stack:
  • Programming languages (Python, R, Java, JavaScript)
  • SQL databases (PostgreSQL, MySQL, MS SQL Server, Redshift, SQLite, Oracle)
  • NoSQL databases (CouchDB, Redis, MongoDB)
  • Web development (Django, Flask, Shiny)
  • Statistical programming and data visualizations (Python and R, using a range of libraries/packages)
  • Notebooks (Jupyter and Zeppelin notebook servers)