The comparative effectiveness research (CER) that we propose conducting within the New England Collaborative Breast Surveillance Network, will use registry data and modeling to advance systems-based approaches to improving the processes of care for breast cancer screening with a focus on health information technology (IT). We propose three specific aims:
Specific Aim 1 : To develop a quantitative modeling framework that depicts screening processes across clinical practice network sites and incorporates findings from Project 1 (screening process measurement and feedback) to identity high-value targets for screening process improvement.
Specific Aim 2 : To use decision-analytic methods to estimate and compare the benefits and harms of alternative breast cancer screening strategies over various age horizons for use in the risk tools that will be developed and trialed within Project 2 (personalized modules for risk).
Specific Aim 3 : To compare breast cancer screening outcomes between study sites and across time to assess the impact that care processes involving health IT have as they are disseminated within the New England Collaborative Breast Surveillance Network. We hypothesize that a limited number of key attributes of care processes can be identified that are most associated with improved screening outcomes. To achieve this aim longitudinal data obtained by the Screening Process Documentation Unit on women undergoing digital mammography will be analyzed to compare process outcomes, benefits, and harms. Secondary analyses will address digital breast tomosynthesis, an emerging technology whose regulatory approval for use in clinical practice is imminent, in comparison with digital mammography. Comparing outcomes for an emerging technology relative to digital mammography will provide early evidence on the best uses of digital breast tomosynthesis.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Specialized Center--Cooperative Agreements (U54)
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Special Emphasis Panel (ZCA1-SRLB-R)
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Dartmouth College
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