Natasha Stout

Assistant Professor in Population Medicine Harvard Medical School and Harvard Pilgrim Health Care Institute
Assistant Professor
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Dr. Natasha Stout is an Assistant Professor in Population Medicine at the Harvard Medical School and Harvard Pilgrim Health Care Institute. Her research agenda focuses on applying decision-analytic modeling methods to better understand if existing and emerging medical technologies are implemented and used to their fullest capacity to improve population health. Her methodological interests are in the development and calibration of population-based discrete-event simulation models of disease. She has particular expertise in the area of breast cancer natural history modeling. Since its inception in 2000, she has been participating in National Cancer Institute’s Cancer Intervention and Surveillance Modeling Network (CISNET), a collaboration of independent modeling teams formed to address unresolved policy questions in cancer control. She is the current recipient of an American Cancer Society career development award to evaluate MRI as it is used for breast cancer screening in the community. The research involves analyzing electronic health data from a large medical group practice to understand test performance and integrating the results into a decision-analytic model for policy evaluation. She is active in the Society for Medical Decision Making where she served on the Board of Trustees from 2010 to 2013 and coordinated career development and mentoring programs.  Dr. Stout received a B.A. in Mathematics from Oberlin College, and an M.S. in Industrial Engineering focusing on Operations Research and Decision Science and Ph.D. in Population Health Sciences from the University of Wisconsin. Prior to her Ph.D., she worked at Epic Systems, a firm in healthcare information software.

Community Breast MRI Screening: Clinical and Economic Implications

Learning about the use, clinical outcomes and economic consequences of screening breast MRI in the community to assess its cost-effectiveness

Comparative Modeling: Informing Breast Cancer Control Practice and Policy

Modeling population effects of novel breast cancer control approaches

Expanding National Health Accounts: Project 4: Trends in the Value of Cancer Care in the US

Comparing the benefits and costs of medical care to understand the interventions that improve health most efficiently

Future of Risk-Based Breast Cancer Screening In Community Settings

Maximizing the benefits of breast cancer screening in women with diverse levels of breast cancer risk

Impact of Radiation Therapy on Breast Conservation in DCIS

Investigating patient-specific risk factors underlying specific outcomes in people treated for Ductal Carcinoma In-situ