The initial Observational Medical Dataset Simulator can construct many millions of hypothetical patients with drug exposure, background conditions, and known adverse events that can be used to benchmark methods performance. OSIM has provided access to large-scale data to methodologists, and facilitated the establishment of the OMOP Cup Competition. It also advanced the OMOP Research Team's learnings about the complex interdependencies between clinical observations in real data, and how those relationships may influence a method's behavior in identifying true associations and discerning from false positive findings.

Based on these learnings, there has been a continuation on the research and development into a second-generation simulated dataset procedure, known as OSIM2, which establishes a complementary model to the original OSIM program, applying an alternative design to accommodate additional complexities observed in real-world data, including advanced modeling of the correlations between drugs and conditions. OSIM2 allows for more direct comparisons between simulated data and real observational databases, and should enable greater methods evaluation by allowing assessment of how methods accommodate these complex interrelationships.

OSIM2 source code, documentation, and databases are available for download: