OHDSIThe OHDSI suite is an open-source, modular solution that enables organizations to explore 360° patient journeys and turn data into evidence. The ecosystem provides a broad range of tools that cover all aspects of real world data and evidence − from data characterization to a standardized data model (OMOP CDM). This enables large scale cross-database analytics with OHDSI.
Our workshops have trained 80+ participants from 12 European and US-based life science organizations that had decided to adopt the OMOP CDM and the OHDSI tool suite. We help bring various stakeholders within an organization to the same level of expertise and understanding of the multi-faceted OHDSI ecosystem.
The Hyve can help you verify the quality of data after each instance of data conversion into the OMOP common data model (CDM) because of our extensive knowledge of and experience with the OHDSI data quality assessment tools. By following this approach, we can guarantee the highest quality of analysis-ready CDM-harmonised data.
Our data engineers and semantic experts help identify relevant analysis use cases for your data and enable integration of real-world data with other data sources. Our expertise lies in using and integrating healthcare data for a wide range of purposes, from clinical and observational research to virtual trials and value-based healthcare.
From a fully outsourced approach to ETL to hands-on training aimed at self-service transformations, our experts can provide support with mapping electronic health records, registry and commercial claims data.
We can help with deployment of the OHDSI stack in your existing infrastructure – in the Cloud or on-premise – under the Apache 2 license.
Our data engineers can develop custom functionalities on top of an existing stack and integration with existing technologies and software.
We contribute to European flagship projects such as IMI EHDEN, a public-private partnership that leverages and further improves the OMOP/OHDSI ecosystem. The aim of the project is to build a federated network for analysis of longitudinal observational real-world data from hundreds of millions of European patients.
