The goal of this project is to integrate decision modeling into decision aid (DA) development.
We aim to help older women with early stage breast cancer decide whether to receive radiotherapy (RT). The guidelines suggest that adjuvant RT after breast-conserving surgery may be omitted for breast cancer patients who are older, have limited life expectancy due to comorbidities, and have favorable tumor characteristics, highlighting the necessity of individualized considerations. This issue is particularly important for the older population because approximately two-thirds of older Americans have at least two chronic health conditions. DAs hold the promise of facilitating patient-centered care by helping patients make decisions based on their goals and preferences. Successful DAs should be created in a truly patient-engaged manner: patients want information that is individually tailored, and clinicians aim to provide patient-specific advice. We envision two separate steps where decision modeling has the potential to improve current DAs. First, we will apply decision modeling to obtain individualized outcomes estimates, which are intended to replace generic information based on average outcomes. Second, we will use decision modeling to provide a treatment recommendation by integrating information about the probabilities of specific outcomes and the patient values regarding treatments and outcomes. We will then rigorously assess how individualized recommendations affect decision conflict, health outcomes, and RT utilization. Our findings will have important implications, including emphasizing patient-centeredness care, encouraging patient-physician communication, and shedding light on future DA development. Throughout the entire research, we place a great emphasis on incorporating input from patients and physicians in every step of the design and evaluation of our DA. We will organize a patient advisory board (patients, family members, and community members) and a steering committee (providers and researchers), and both will also have joint meetings regularly. We will apply the philosophy of community-based participatory research to monitor the conduct of the project, help plan the dissemination of the project's results, and formulate future research questions and study design. Our proposed DA can disseminate evidence-based information to patients and physicians, enhance their use of this information, and help them communicate risks and benefits. Regarding the candidate's experience, I went to the University of Minnesota to pursue a PhD degree in Health Services Research In 2007. My interests focus on outcomes research and decision modeling, specifically for breast cancer care. Applying different methodologies, I have been the lead author of five breast-cancer-related papers since 2009. After graduation in 2012, I became an assistant professor at Yale School of Public Health. I have been working closely with Dr. Cary Gross and other colleagues at the Yale Cancer Center. Furthermore, I have been expanding my research into the area of shared decision-making, which has the potential to improve the health of individual patients and help control healthcare spending. I clearly see the advantages of incorporating decision modeling into DAs, yet realize that I have not had the experience in developing DAs or engaging patients in the research process. Additional training in these two areas will be crucial for my career development. The proposed project builds upon my earlier work, to further our understanding of the utility of decision modeling in decision aid development. There are many resources available to facilitate my career development, including the academic facilities of Yale University School of Medicine, School of Public Health, and School of Management. My interdisciplinary mentoring/research team consists of renowned investigators. With collaborative input from them, I will perform the research and career development activities outlined in this grant application. My immediate career goals are to bolster expertise in individualized medical decision making, enhance research skills and integrate patient values in research process, and improve stakeholder engagement. By allotting five years to this important phase of my career development, I will be able to foster patient-centered and evidence-based healthcare, as well as to become an independent investigator to advance methodologies in decision aid development. Upon completion of the proposed project, I look forward to pursuing additional patient-centered projects beyond the current scope.

Public Health Relevance

The guidelines suggest that adjuvant radiotherapy after breast-conserving surgery may be omitted for breast cancer patients who are older, have limited life expectancy due to comorbidities, or have favorable tumor characteristics, highlighting the necessity of individualized considerations. Integrating decision modeling into decision aid development provides not only individualized estimates of outcomes but also patient-specific recommendations according to individual overall health status and tumor characteristics. Developing a decision aid in a truly patient-engaged manner can encourage patient-physician communication and ultimately help to facilitate patient-centered decision-making in practice.

Agency
National Institute of Health (NIH)
Institute
Agency for Healthcare Research and Quality (AHRQ)
Type
Research Scientist Development Award - Research & Training (K01)
Project #
5K01HS023900-05
Application #
9665680
Study Section
Healthcare Research Training (HCRT)
Program Officer
Willis, Tamara
Project Start
2015-04-01
Project End
2020-12-31
Budget Start
2019-04-01
Budget End
2020-12-31
Support Year
5
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Yale University
Department
Public Health & Prev Medicine
Type
Schools of Medicine
DUNS #
043207562
City
New Haven
State
CT
Country
United States
Zip Code
06520
Wang, Shi-Yi; Hsu, Sylvia H; Huang, Siwan et al. (2018) Regional Practice Patterns and Racial/Ethnic Differences in Intensity of End-of-Life Care. Health Serv Res 53:4291-4309
Wang, Shi-Yi; Aldridge, Melissa D; Gross, Cary P et al. (2017) End-of-Life Care Transition Patterns of Medicare Beneficiaries. J Am Geriatr Soc 65:1406-1413
Wang, Shi-Yi; Kelly, Gabrielle; Gross, Cary et al. (2017) Information Needs of Older Women With Early-Stage Breast Cancer When Making Radiation Therapy Decisions. Int J Radiat Oncol Biol Phys 98:733-740
Wang, Shi-Yi; Dang, Weixiong; Aldridge, Melissa D et al. (2017) Associations of Hospice Disenrollment and Hospitalization With Continuous Home Care Provision. Med Care 55:848-855
Wang, Shiyi; Hsu, Sylvia H; Huang, Siwan et al. (2017) Longer Periods Of Hospice Service Associated With Lower End-Of-Life Spending In Regions With High Expenditures. Health Aff (Millwood) 36:328-336
Kelly, Gabrielle; Wang, Shi-Yi; Lucas, Georgina et al. (2017) Facilitating Meaningful Engagement on Community Advisory Committees in Patient-Centered Outcome Research. Prog Community Health Partnersh 11:243-251
Wang, Shi-Yi; Hall, Jane; Pollack, Craig E et al. (2016) Trends in end-of-life cancer care in the Medicare program. J Geriatr Oncol 7:116-25
Wang, Shi-Yi; Aldridge, Melissa D; Gross, Cary P et al. (2016) End-of-Life Care Intensity and Hospice Use: A Regional-level Analysis. Med Care 54:672-8
Wang, Shi-Yi; Hsu, Sylvia H; Gross, Cary P et al. (2016) Association between Time since Cancer Diagnosis and Health-Related Quality of Life: A Population-Level Analysis. Value Health 19:631-8
Wang, Shi-Yi; Hall, Jane; Pollack, Craig E et al. (2016) Associations Between End-of-Life Cancer Care Patterns and Medicare Expenditures. J Natl Compr Canc Netw 14:1001-8

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