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Making Medicaid Data More Accessible Through Common Data Models and FHIR APIs

Making Medicaid Data More Accessible Through Common Data Models and FHIR APIs
  • Food and Drug Administration (FDA) and National Institutes of Health/National Library of Medicine (NIH/NLM)
Start Date
  • 03/01/2021
  • Standardized Collection of Standardized Clinical Data
  • Collection of Participant-Provided Information
  • Linking of Clinical and Other Data for Research


STATUS: Active Project


This is a joint agency project involving the Food and Drug Administration (FDA) and National Institutes of Health/ National Library of Medicine (NIH/NLM)that addresses the PCOR priority to expand data capacity or data infrastructure for conducting research that informs decisions about the effectiveness of health interventions used in the Medicaid and Children's Health Insurance Programs.

Common data models (CDMs) can improve data access, accelerate analyses, and enable multi-database studies. By standardizing both the data structure and analytics layer, evidence generation platforms can be developed with greater efficiency, versatility, consistency and scalability. The Transformed Medicaid Statistical Information System (T-MSIS) Analytic Files (TAF) and Research Identifiable Files (RIFs) are a new research-optimized national Medicaid dataset. These files include data on Medicaid and Children’s Health Insurance Program (CHIP) enrollment, demographics, service utilization and payments.

This project seeks to standardize T-MSIS data into one of two CDM formats to enable researchers to improve data quality characterization and leverage an array of versatile open source analysis tools.


The purpose of this project is to address the following objectives:

  • Create open source code to format Transformed Medicaid Statistical Information System (T-MSIS) data into the Sentinel and Observational Medical Outcomes Partnership (OMOP) Common Data Models (CDMs)
  • Develop data quality metrics to characterize each CDM formatted version
  • Create a mother-infant linkage to support several Sentinel analyses on maternal health
  • Evaluate the feasibility of implementing Fast Healthcare Interoperability Resources (FHIR) APIs (Application Programming Interfaces) to link T-MSIS data with electronic health record (EHR) data
  • Develop a webinar series to train Medicaid researchers on the new data transformation tools and disseminate major findings