Open Source Code for the T-MSIS Analytic Files (TAF)
The Medicaid Data Learning Network (MDLN) released a report on its open source efforts for researchers using T-MSIS Analytic Files (TAF) data.
Sarah Gordon is an assistant professor in the Department of Health Law, Policy, and Management at the Boston University School of Public Health. Her research is dedicated to studying coverage and access to care among low-income populations, with a particular emphasis on Medicaid policy. Her work seeks to understand how the fragmentation of the U.S. health insurance system impacts utilization, quality, and continuity of care. Her recent projects leverage state-level datasets, such as all payer claims databases, and quasi-experimental study designs to evaluate the effects of state-level policies. She received her doctorate in Health Services Research from the Brown University School of Public Health and a MS in Social and Behavioral Sciences from the Harvard T. H. Chan School of Public Health.
Authored by Sarah Gordon, Ph.D., M.S.
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.
Medicaid Data Learning Network
Managed by AcademyHealth, this learning network facilitates peer-to-peer learning and dialogue among researchers working with the Centers for Medicare and Medicaid’s T-MSIS Analytic Files.