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

    Basic Details
    Date Posted
    Friday, September 24, 2021
    Status
    In progress
    Description

    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 Patient-Centered Outcomes Research (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.

    This project aims to develop and publish open source code to format T-MSIS Research Identifiable File (RIFs) to the Sentinel CDM in tandem with NLM’s formatting of the T-MSIS RIFs to the OMOP CDM. Data quality will be characterized using a harmonized Data Quality Assessment Framework for electronic healthcare data that was developed in a previously funded OS-PCORTF project. To illustrate the benefits of CDM transformation, open source tools will be used to conduct several studies of public health importance, such as studies of maternal mortality and adherence to clinical guidelines for perinatal testing. Additionally, the project will assess the feasibility of using Fast Healthcare Interoperability Resources (FHIR) APIs (Application Programming Interfaces) to link Electronic Health Record (EHR) data to T-MSIS claims data. Lastly, the project will ensure stakeholder engagement and sustainability via a Technical Expert Panel (TEP) to provide guidance on the data quality metrics, the PCOR demonstration projects, and development of a series of training materials. The goal of the training materials is to ensure findings are optimally disseminated to the Medicaid research community to lead to greater utilization of the CDM translation code and use of T-MSIS for patient-centered outcomes research in Sentinel and OMOP ecosystems.

    This project covers several major tasks:

    Task 1: Develop open source code to format the T-MSIS data into the Sentinel and Observational Medical Outcomes Partnership (OMOP) Common Data Models (CDMs)

    Task 2: Leverage the ASPE funded data quality metrics model to characterize each CDM-formatted version

    Task 3: Develop open-source code to create a mother-infant linkage in the Sentinel CDM to support several Sentinel analyses on maternal health

    Task 4: Conduct one or more demonstration studies assessing the harms and benefits of an aspect of maternal health using the transformed T-MSIS dataset and Sentinel analytic tools. The FDA-led workgroup will include participation from CDC/NCHHSTP, CDC/NCBDDD, NIH/NICHD and HRSA

    Task 5: Evaluate the feasibility of implementing FHIR APIs to link T-MSIS data with EHR data

    Task 6: Engage stakeholders and create sustainability by:

    • Establishing a TEP with relevant expertise in the Medicaid program, T-MSIS data, or patient-centered outcomes research to provide non-binding guidance from an end-user’s perspective on the data quality metrics selected in Task 2,  potential PCOR demonstration projects using the new T-MSIS dataset in Task 4, and the structure of the training materials
    • Developing a webinar series to train Medicaid researchers on the new data transformation tools and disseminate major project findings

     

    Information
    Time Period
    August 1, 2021 – September 29, 2024
    Population / Cohort
    Low-income younger adults and children; mother-infant data
    Data Source(s)
    SCDM-formatted Transformed Medicaid Statistical Information System (T-MSIS) utilization and claims data from Medicaid and the Medicaid Children’s Health Insurance Program (CHIP).
    Workgroup Leader(s)

    Judith C. Maro, PhD; Department of Population Medicine, Harvard Pilgrim Health Care Institute and Harvard Medical School, Boston, MA

    David Money, RPh., PMH; Efe Eworuke, Ph.D., MSc; Division of Epidemiology II, Office of Pharmacovigilance and Epidemiology, Office of Surveillance and Epidemiology, Center for Drug and Evaluation Research, US Food and Drug Administration, Silver Spring, MD;

    Sarah Dutcher, PhD, Office of Surveillance and Epidemiology, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland

    Workgroup Member(s)

    Patricia Bright, MSPH, PhD; Jamila Mwidau, RN, BSN, MPH; Sanae Cherkaoui, MS, MPH, CPH; Office of Surveillance and Epidemiology, Center for Drug and Evaluation Research, US Food and Drug Administration, Silver Spring, MD

    Brad Hammill, DrPh; Steven J. Lippmann, PhD; Michael Stagner; Jessica E. Pritchard, PhD Department of Population Health Sciences, Duke University School of Medicine, Durham, NC

    Christine Halbig, MPH; Laura Shockro, Katie Shapiro, Malcolm Rucker, MS; Lauren Zichittella, MS Alexander Mai; Daniel Kiernan; Suzanne Carter, PhD, MS, MBA; Department of Population Medicine, Harvard Pilgrim Health Care Institute and Harvard Medical School, Boston, MA

    Robert Rosofsky, MA; Health Information Systems Consulting LLC, Milton, MA