Objectives: This effort used Databricks to create an Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) for Transformed MSIS Analytic File (TAF) Medicaid records.
Materials and methods: Our process included data volume and content assessment of TAF, translation mapping of TAF concepts to OMOP concepts and the creation of Extract Transform and Load (ETL) code.
Results: The final CDM contained 119,048,562 individuals and 24,806,828,121 clinical observations from 2014 through 2018.
Discussion: The transformation of TAF into OMOP can support the generation of evidence with special attention to low-income patients on public insurance. Such patients are perhaps underrepresented in academic medical center patient populations.
Conclusion: Our effort successfully used Databricks to transform TAF records into OMOP CDM. Our CDM can be used to generate evidence for OMOP network studies.
Keywords: Centers for Medicare and Medicaid Services; Common Data Model; Medicaid; Observational Health Data Sciences and Informatics; Observational Medical Outcomes Partnership.