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.
William Schpero is a health economist and an assistant professor in the Division of Health Policy and Economics of the Department of Population Health Sciences at the Joan & Sanford I. Weill Medical College of Cornell University. He studies Medicaid and the health care safety net in the United States. Through his research, he aims to identify policy levers to address racial, ethnic, and socioeconomic disparities in health and health care. In past work, he has studied the drivers of waste in the U.S. health care system and analyzed the effect of key provisions of the Affordable Care Act. Dr. Schpero received his Ph.D. in health policy and economics from Yale University, during which he was also a pre-doctoral fellow in aging and health economics at the National Bureau of Economic Research. Before coming to Yale, he completed a master's degree and a research fellowship at The Dartmouth Institute for Health Policy & Clinical Practice. He received his undergraduate degree from Dartmouth College.
Authored by William Schpero, Ph.D.
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.