AcademyHealth’s Medicaid Data Learning Network (MDLN) Research Faculty Explore Promises and Challenges of Medicaid Research Using T-MSIS Analytic Files (TAF) in New Blog from The Commonwealth Fund

The lack of high quality, accessible national claims data has long been a roadblock to robust Medicaid research and subsequent evidence-based policymaking in the United States. While the release of TAF marked a significant improvement, research faculty with AcademyHealth’s Medicaid Data Learning Network (MDLN) outline important steps that state and federal policy makers can take to improve data quality, accessibility, and usability.

Since its release in 2019, the T-MSIS Analytic Files (TAF) have opened the floodgates to greater Medicaid research opportunities. Maternal morbidity, reimbursement for psychiatric services, racial and ethnic disparities in medication for opioid use disorder, and the health effects of segregation are just a few of the myriad of topics examined in new TAF studies. Despite the opportunities the data inspire, however, researchers emphasize TAF are still too expensive to obtain, complex to analyze, and imperfect to work with to realize its potential.

In an effort to improve data and allow for continued groundbreaking Medicaid research, AcademyHealth’s MDLN research faculty pose three recommendations to state and federal policy makers:

Address Missing Demographic Information
Enhance Transparency of Managed Care Payments
Improve Accessibility to the New Medicaid Analytic Files

Read more about the envisioned next steps for improving data and the potential it promises here.