Seamless, low-cost access to research data

OUH needed to ensure that data within the SDE was structured in a way that could be readily consumed by researchers using standard clinical research tools.

The goal was to implement the Observational Medical Outcomes Partnership (OMOP) Common Data Model, the leading model for clinical data analytics, to provide seamless, low-cost access to research data.

This involved developing a scalable mapping process from current data formats to the OMOP model and recommending an architecture to support this transformation.

Transforming the use of data

By collaborating with OUH, we conducted an options appraisal, evaluating off-the-shelf and bespoke solutions based on OUH's requirements.

A custom solution was chosen to tightly integrate documentation, adding more value despite the higher costs.

We simultaneously built and improved the bespoke solution, conducting mappings from four source datasets to the OMOP Common Data Model v5.4.

Additionally, we developed a GitHub site to promote adoption and gather feedback from the research community. A robust process for analysing, mapping, and transforming data was established, including defining the scope, conducting analysis, transforming the data, and validating the outputs.