Real-World Evidence BRIDGE: A Tool to Connect Protocol With Code Programming.

Objective: To enhance documentation on programming decisions in Real World Evidence (RWE) studies.

Materials And Methods: We analyzed several statistical analysis plans (SAP) within the Vaccine Monitoring Collaboration for Europe (VAC4EU) to identify study design sections and specifications for programming RWE studies. We designed a machine-readable metadata schema containing study sections, codelists, and time anchoring definitions specified in the SAPs with adaptability and user-friendliness.

Results: We developed the RWE-BRIDGE, a metadata schema in form of relational database divided into four study design sections with 12 tables: Study Variable Definition (two tables), Cohort Definition (two tables), Post-Exposure Outcome Analysis (one table), and Data Retrieval (seven tables). We provide a guide to populate this metadata schema and a Shiny app that checks the tables. RWE-BRIDGE is available on GitHub (github.com/UMC-Utrecht-RWE/RWE-BRIDGE).

Discussion: The RWE-BRIDGE has been designed to support the translation of study design sections from statistical analysis plans into analytical pipelines and to adhere to the FAIR principles, facilitating collaboration and transparency between researcher and programmers. This metadata schema strategy is flexible as it can support different common data models and programming languages, and it is adaptable to the specific needs of each SAP by adding further tables or fields, if necessary. Modified versions of the RWE-BRIGE have been applied in several RWE studies within VAC4EU.

Conclusion: RWE-BRIDGE offers a systematic approach to detailing variables, time anchoring, and algorithms for RWE studies. This metadata schema facilitates communication between researcher and programmers.