Jiajia Chen

Jiajia Chen


Jiajia Chen is a researcher whose work focuses on health policies, Medicaid programs, and maternal and infant health. He has expertise in using commercial and Medicaid administrative data for quality measures and policy evaluations.

Chen has worked on a range of topic areas at Mathematica, including COVID-19 cohort data analytics, development of claims-based algorithms to identify pregnancy episodes, and probabilistic linkage of mother’s and infant’s records in the Transformed Medicaid Statistical Information System (T-MSIS) Analytic Files (TAF). Currently, he is leading evaluations of the effect of the COVID-19 pandemic on Medicaid home- and community-based services, and the relationship between 12-month extension of postpartum Medicaid coverage and behavioral health treatment utilization. He conducts complex studies using the T-MSIS data for the Medicaid and CHIP (Children’s Health Insurance Program) Business Information System Business Analytics (MACBIS) project and supports data request tasks under MACBIS.

Before joining Mathematica, Chen completed the Steven M. Teutsch Prevention Effectiveness Fellowship at the Centers for Disease Control and Prevention (CDC), working on topics such as severe maternal morbidity, preterm birth and stillbirth, perinatal depression, and long-acting reversible contraception. His work was nominated for the Charles C. Shepard Science Award, the highest scientific award at the CDC. His research has appeared in peer-reviewed publications, including Journal of Policy Analysis and Management, American Journal of Preventive Medicine, and JAMA Network Open. He also serves as a reviewer for journals such as Annals of Internal Medicine, Journal of Women’s Health, BMJ Open, and Southern Economic Journal, among others. Chen holds a Ph.D. in economics from the University of Illinois at Chicago.

  • Evaluation design and methods
  • Maternal and infant health
  • Health policy
  • Medicaid data and data analytics
  • National health survey data
Focus Area Topics
  • Health
  • Medicaid and CHIP
  • State Health Policy
  • COVID-19
  • Population Health

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