Building the observational medical outcomes partnership's T-MSIS Analytic File common data model.

Williams N

Inform Med Unlocked. 2023;39:101259. doi: 10.1016/j.imu.2023.101259. Epub 2023 May 5. PMID: 37305615; PMCID: PMC10249773.

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Abstract:

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.

Williams N. Building the observational medical outcomes partnership's T-MSIS Analytic File common data model. 
Inform Med Unlocked. 2023;39:101259. doi: 10.1016/j.imu.2023.101259. Epub 2023 May 5. PMID: 37305615; PMCID: PMC10249773.

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