dsOMOP: Bridging OMOP CDM and DataSHIELD for Secure Federated Analysis of Standardized Clinical Data.

MOTIVATION

Collaborative clinical research projects face several challenges related to data sharing. The disparity between data standards and strict privacy regulations become more relevant as the number of involved institutions increases. To address these challenges, the scientific community has progressively adopted common data models like the OMOP CDM for multicenter data standardization and implemented federated data analysis platforms like DataSHIELD to perform remote analyses without transferring individual-level data between centers, thus mitigating disclosure risks. However, there is no native implementation that automatically combines both solutions, revealing the need for a tool that enables interoperability between these systems.

RESULTS

We present dsOMOP, a collection of DataSHIELD packages that facilitates automated extraction and transformation of OMOP CDM data into DataSHIELD-compatible datasets, enabling disclosure-controlled federated analyses of standardized clinical data. dsOMOP allows research institutions to provide access to their data for collaborative projects in a format that is interoperable with the project's available data, thus facilitating the analysis of large-scale, multicenter clinical data. It incorporates OMOP data directly into the DataSHIELD workflow, where all analyses occur entirely in a federated environment subject to rigorous disclosure controls, ensuring that only aggregated, non-disclosive results are ever returned to analysts.

AVAILABILITY

The general information page for the dsOMOP environment is available at https://isglobal-brge.github.io/dsOMOP, where the most recent installation instructions and usage guides for all dsOMOP packages and their extensions can be found in the 'Packages' section.The dsOMOP package and its complementary tools are fully available under the MIT license on GitHub: dsOMOP (https://github.com/isglobal-brge/dsOMOP), dsOMOPClient (https://github.com/isglobal-brge/dsOMOPClient), dsOMOPHelper (https://github.com/isglobal-brge/dsOMOPHelper), and dsOMOP.oracle (https://github.com/isglobal-brge/dsOMOP.oracle).Usage vignettes for the client-side packages are available at the websites of dsOMOPClient (https://isglobal-brge.github.io/dsOMOPClient) and dsOMOPHelper (https://isglobal-brge.github.io/dsOMOPHelper). A permanent archival snapshot of the exact code used in this manuscript is deposited at Figshare: https://doi.org/10.6084/m9.figshare.28607186.

CONCLUSION

dsOMOP allows automated, federated analyses of OMOP CDM-compliant data within the DataSHIELD environment, enabling federated analyses of standardized clinical data while safeguarding patient privacy through controlled, aggregated outputs. This tool supports large-scale, multicenter research by facilitating data interoperability and aligning with privacy regulations.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.