This K24 proposal combines mentoring in patient oriented cancer control research; research to translate evidence-based shared decision-support for screening mammography to the clinic; and career development in Implementation Science. The PI, Dr. Elizabeth Burnside, has been an influential mentor throughout her career at the University of Wisconsin (UW), fostered by leadership positions like her role as the co-lead of the Cancer Control Program in the UW NCI designated Comprehensive Cancer Center. Her mentoring and research both promote team science, which unites medical and translational disciplines like informatics, engineering, and population health, all areas for which she has expertise and departmental affiliate appointments. This award would carve out the necessary time for her to build a platform on which to formalize her mentoring approach and a curriculum to support a cadre of physician/scientists developing decision support tools aimed for clinical translation. This proposal takes advantage of a successful Clinical Translational Science Award (CTSA) funded at UW in 2006, committed to mentoring, patient oriented team science, and translational research.
The aims i ncluded in this proposal are closely aligned with the UW CTSA -KL2 and other institutional training grants and fully leverage the rich mentoring and career development resources. The patient oriented scientific aims proposed arise from healthcare shortfalls that she, a radiologist practicing in breast imaging, sees every day in clinic. They buid on her NCI funded R01 which asks the question: How can decision support in the clinic help healthcare providers optimize breast cancer screening and diagnosis in aging women? Breast cancer screening recommendations are ambiguous for women = 65 and poorer breast cancer outcomes are seen in this population. Accurate and personalized strategies are needed to decrease morbidity and mortality, while minimizing harms (false positives and overdiagnosis-the detection of cancer that would not go on to cause symptoms or death). Though validated decision aids currently exist, immense opportunities still remain: personalization, integration in the clinical workflow, and implementation with high fidelity; all goals of this proposal. Personalized decision support tools will only be useful if they are thoughtfully designed and rigorously implemented. Both her scientific aims and her career development plans integrate the new discipline of Implemenation Science. These methodologies will enable her to translate advances into an EMR-embedded decision tool for improved breast cancer screening decision-making for women = 65 and their physicians. Innovation is substantial; creating a tool that incorporates national simulation models to accurately convey outcomes that is integrated into the EMR has not been done. This award will enable Dr. Burnside to become an influential mentor of clinician-scientists using implementation science to advance personalized decision support into the clinic.
This grant proposes to build a mentorship program for clinicians who are developing tools that use a patient's unique characteristics to help make optimal health care decisions. The proposed research exemplifies this important goal by using the newest scientific techniques to develop and test a personalized decision tool to help women age 65 or over decide (with their physician) whether to undergo breast cancer screening. By combining mentoring, research, and new scientific methodologies, this plan will powerfully translate the science of personalized prediction to patients to help make decisions that are right for them.
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|Schrager, Sarina; Burnside, Elizabeth (2018) Breast Cancer Screening in Primary Care: A Call for Development and Validation of Patient-Oriented Shared Decision-Making Tools. J Womens Health (Larchmt) :|
|Bulu, Hakan; Sippo, Dorothy A; Lee, Janie M et al. (2018) Proposing New RadLex Terms by Analyzing Free-Text Mammography Reports. J Digit Imaging 31:596-603|
|Schumacher, Jessica R; Neuman, Heather B; Chang, George J et al. (2018) A National Study of the Use of Asymptomatic Systemic Imaging for Surveillance Following Breast Cancer Treatment (AFT-01). Ann Surg Oncol 25:2587-2595|
|Net, Jose M; Whitman, Gary J; Morris, Elizabteh et al. (2018) Relationships Between Human-Extracted MRI Tumor Phenotypes of Breast Cancer and Clinical Prognostic Indicators Including Receptor Status and Molecular Subtype. Curr Probl Diagn Radiol :|
|DuBenske, Lori L; Schrager, Sarina B; Hitchcock, Mary E et al. (2018) Key Elements of Mammography Shared Decision-Making: a Scoping Review of the Literature. J Gen Intern Med 33:1805-1814|
|van Ravesteyn, Nicolien T; van den Broek, Jeroen J; Li, Xiaoxue et al. (2018) Modeling Ductal Carcinoma In Situ (DCIS): An Overview of CISNET Model Approaches. Med Decis Making 38:126S-139S|
|Feld, Shara I; Fan, Jun; Yuan, Ming et al. (2018) Utility of Genetic Testing in Addition to Mammography for Determining Risk of Breast Cancer Depends on Patient Age. AMIA Jt Summits Transl Sci Proc 2017:81-90|
|van den Broek, Jeroen J; van Ravesteyn, Nicolien T; Mandelblatt, Jeanne S et al. (2018) Comparing CISNET Breast Cancer Incidence and Mortality Predictions to Observed Clinical Trial Results of Mammography Screening from Ages 40 to 49. Med Decis Making 38:140S-150S|
|Wu, Yirong; Fan, Jun; Peissig, Peggy et al. (2018) Quantifying predictive capability of electronic health records for the most harmful breast cancer. Proc SPIE Int Soc Opt Eng 10577:|
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