Migrating longitudinal African mental health data from staging to the OMOP common data model within the INSPIRE...

The standardization and integration of longitudinal mental health data from African cohort studies are critical in advancing research and informing policy. There are several challenges posed by diverse sources, instruments adapted for locals, and the absence of an interoperable framework to allow for meaningful analysis and cross-study comparisons.

We designed and executed a metadata-driven pipeline using the OMOP Common Data Model within the INSPIRE Network Datahub to harmonise multi-country African mental health datasets. Data extracted previously from longitudinal studies, standardised via a snowflake schema staging database, is now mapped to OMOP vocabularies with local extensions, and validated through quality assurance protocols using OHDSI tools.

A total of 202,013 person records and over 7 million observations across fourteen cohort studies were successfully migrated. Mapping completeness exceeded 99.9%, with high conformance, completeness, and plausibility across all OMOP domains. Custom vocabularies ensured the coverage of context-specific exposures and outcomes, thereby supporting robust cohort construction, event characterization, and longitudinal analyses.

This framework demonstrates scalable harmonisation and integration of African mental health data, bridging the gap between local datasets with global standards. This then enables the performance of federated analysis and reproducible research, increasing the utility and impact of mental health data in informing evidence-based policies and future collaborative studies across Africa.