Irina Degtiar

Irina Degtiar

Name Pronunciation eye-REE-nah DEGH-tee-are
Pronouns she/her/hers

Irina Degtiar combines statistical and health policy expertise to advance patient and public health. She is an expert in generalizability (e.g., estimating the impacts of scaling up interventions). She develops and applies Bayesian and frequentist semiparametric estimators to address causal questions in Medicare and Medicaid policy evaluation.

Degtiar joined Mathematica in 2021 after an internship in 2019. During the internship, she developed a novel approach for estimating the impacts of scaling up the Comprehensive Primary Care Plus evaluation and worked on projects related to the Comprehensive Care for Joint Replacement Model.

Before coming to Mathematica, Degtiar’s research focused on addressing the causal impact of Medicaid insurance plans on patient costs using semiparametric double-robust and g-computation estimators. She also conducted health economics and outcomes research, assessing the cost-effectiveness of personalized medicine diagnostics across mental health, rheumatology, and oncology. Degtiar holds a Ph.D. in biostatistics from Harvard University.

  • Generalizability, transportability, and scalability analysis
  • Causal inference
  • Flexible estimation approaches (machine learning as well as nonparametric and semiparametric estimators)
  • Program evaluation
Focus Area Topics
  • Health
  • Medicare
  • Medicaid and CHIP
  • Population Health
  • State Health Policy

See Clearly. Act Quickly.

Our experts can help you make smart, sustainable decisions. From local to global challenges in health, human services, and international development, we’re here to improve public well-being and make progress together.

Work With Us