- Quantitative methods
- Medicaid data analytics
- Maternal and infant health
- Behavioral health
- Health Information Technology and Analytics
- Medicaid and CHIP
- Population Health
Laura Nolan’s research focuses on Medicaid data analytics and quality measurement. She currently leads a pilot to replace states’ reporting of Early and Periodic Screening, Diagnostic, and Treatment services with calculations from Transformed Medicaid Statistical Information System (T-MSIS) data. Nolan also leads the development of technical specifications for new measures of physical and mental health integration for the Medicaid program. Her other work includes developing tools for identifying pregnant women in T-MSIS and measuring the quality of health care services provided to fee-for-service beneficiaries in Medicare.
Before joining Mathematica, Nolan completed a Data Science for Social Good Summer Fellowship at the University of Chicago and a postdoctoral fellowship at the Columbia University School of Social Work. Her research has been published in the Journal of Economic and Social Measurement, Survey Research Methods, Social Science & Medicine, the American Journal of Public Health, and Population Research and Policy Review, among other publications. Nolan holds a Ph.D. in demography and social policy from Princeton University and an M.Sc. from the Harvard School of Public Health.