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Catalyzing Medicaid Policy Research with T-MSIS Analytic Files (TAF): Learnings from Year 1 of the Medicaid Data Learning Network (MDLN)

In its first year, the Medicaid Data Learning Network (MDLN) facilitated expert presentations and collaboration among TAF experts and member research teams by hosting an in-person meeting at AcademyHealth's Annual Research Meeting (ARM) and eight virtual learning sessions. This publication presents a summary of the findings from the first year of the Medicaid Data Learning Network, including key takeaways for the research and policy communities from each learning session.

A purple cover of the MDLN Year 1 Summary Report.

MDLN Year 1 Summary Report

The MDLN's ultimate goal is to improve the quality of the TAF data over time, expand opportunities for health services researchers to use Medicaid claims data, and increase the number of researchers engaged in Medicaid-focused work by fostering peer learning among TAF users. The eight learning sessions from Year One of the MDLN focused on priority topics identified by the MDLN research teams, created space for researchers working with TAF data to share their progress, questions, and solutions in a collaborative environment.

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The T-MSIS Analytic Files (TAF) represent a significant improvement in quality and usability over the previous generation of federal Medicaid claims data, the Medicaid Analytic eXtract (MAX), indicating CMS' efforts to enhance the Medicaid Statistical Information System (MSIS). However, TAF remain highly complex. As researchers begin to work with these data, there is an opportunity to share learnings and approaches to avoid duplicative efforts and to distill key methodological standards - enter the Medicaid Data Learning Network (MDLN).
Through a learning series curriculum, the MDLN provides a forum for TAF researchers to share what they have learned using the dataset and to develop consensus on best practices. This report summarizes the substance from the first year of learning sessions, including the key takeaways for both the research and policy communities. 

Learning session topics in Year One included:

  • Approaches to Standard Measures of Utilization 
  • Linking MAX and TAF Data
  • Navigating Race and Ethnicity Data in TAF
  • Methods for Maternal and Reproductive Health Research Using TAF
  • Measuring Managed Care Utilization Using Encounter Data in TAF
  • Spending in Fee-For-Service and Managed Care Organization Delivery Systems
  • Identifying Medications for Opioid Use Disorder in TAF
Committee Member, Member

Sarah Gordon, Ph.D., M.S.

Assistant Professor - Boston University School of Public Health

Sarah Gordon is an assistant professor in the Department of Health Law, Policy, and Management at the Boston U... Read Bio

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Annaliese Johnson, M.P.P.

AcademyHealth - Senior Manager

Annaliese Johnson is a Senior Manager of AcademyHealth’s Evidence-Informed State Health Policy Institute, wher... Read Bio

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K. John McConnell, Ph.D.

Director of the Center for Health Systems Effectiveness - Oregon Health & Science University

K. John McConnell, PhD, is Director of the Center for Health Systems Effectiveness (CHSE) at Oregon Health & S... Read Bio

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Committee Member, Member

William Schpero, Ph.D.

Assistant Professor - Weill Cornell Medical College

Dr. William Schpero is an Assistant Professor in the Department of Healthcare Policy and Research at Weill Cor... Read Bio