School of Nursing
University at Buffalo
201 A Wende Hall
Buffalo, NY 14214-8013
As a home health and hospice nurse, I have often been distressed by how frequently people living with serious illness experience unwanted or non-beneficial treatments at the end-of-life because they have not engaged in discussions about serious illness goals for care. I hope that my research will uncover new opportunities to assist nurses in this area.
Suzanne Sullivan is an assistant professor at the School of Nursing and dedicates her research to end-of-life care. Recently, Sullivan has developed two predictive models using a large, nationally representative home health care dataset for identifying 12-month mortality risk among community-dwelling, older adults. She plans to develop the models into a clinical decision support tool that assists nurses in identifying older adults at risk for decline/death so that they can support patients and their families in transitioning to appropriate care models such as palliative and hospice care.
In the future, Sullivan plans to conduct a qualitative study that explores how home health nurses recognize risk for decline in older adults and the challenges they face in transitioning their patients to supportive care services. The ultimate goal of this research is to integrate the model into clinical workflows and test the effect on post-acute care transitions and advance care planning activities.
Additionally, Sullivan is working with a team of researchers from the School of Nursing, Jacobs School of Medicine and Biomedical Sciences, and Department of Biomedical Informatics to develop a customized informatics training program for research scientists in the context of Alzheimer’s disease and related dementias (AD/ADRD). With data science approaches, the team focuses on predicting functional decline, mortality risk, and sleep in people with AD/ADRD.
*Sullivan, S. S. (2019). TakingAIM: A precision health framework for promoting person-centered advance care planning. Journal of Hospice and Palliative Nursing, 21(6). Advance online publication. https://doi.org/10.1097/NJH.0000000000000560
Sullivan, S. S., Hewner, S., Chandola, V., & Westra, B. (2019). A predictive model to identify mortality risk in homebound older adults using routinely collected nursing data. Nursing Research, 68(2), 156-166. https://doi.org/10.1097/NNR.0000000000000328
Sullivan, S. S., & Klingman, K. J. (2019). Advance care plans associated with demographics but not necessarily preferences: A cross sectional analysis of NHATS data. Applied Nursing Research. Advance online publication. https://doi.org/10.1016/j.apnr.2019.03.008
*Hewner, S., Sullivan, S. S., & Yu, G. (2018). Reducing emergency room visits and in-hospitalizations by implementing best practice for transitional care using innovative technology and big data. Worldviews on Evidence-Based Nursing, 15(3), 170-177. doi:10.1111/wvn.12286
*Klingman, K. & Sullivan, S. S. (2018). Associations between sleep disorders and comfort at end-of-life: Opportunities for improvement. Sleep Medicine Review, 9(2), 110-114. https://doi.org/10.17241/smr.2018.00276
*Sullivan, S.S., Hewner, S., Chandola, V., & Westra, B. (2018). Mortality risk in homebound older adults predicted from routinely collected nursing data. Nursing Research. Advance online publication. doi:10.1097/NNR.0000000000000328
*Hewner, S., Casucci, S., Sullivan, S. S., Mistretta, F., & Xue, Y. Q. (2017). Integrating social determinants of health into primary care clinical and informational workflow during care transitions. eGEMS (Generating Evidence & Methods to improve patient outcomes), 5(2), 2. http://doi.org/10.13063/2327-9214.1282
*Sullivan, S. S., Li, J., Wu, Y., & Hewner, S. (2017). Complexity of chronic conditions impact on end of life expense trajectories of Medicare decedents. Journal of Nursing Administration, 47(11), 545-550. doi:10.1097/NNA.0000000000000541
*Sullivan, S. S., Mistretta, F. Casucci, S., & Hewner, S., (2017). Integrating social context into comprehensive shared care plans: A scoping review. Nursing Outlook, 65(5), 597-606. http://dx.doi.org/10.1016/j.outlook.2017.01.014
Castner, J., Klingman, K., Sullivan, S. S., Xu, W., & Titus, A. (2016). Hitting home with technology development for asthma. The Lancet Respiratory Medicine, 4, 102-103. doi:10.1016/S2213-2600(15)00525-1
*Castner, J., Sullivan, S. S., & Klingman, K. (2016). Strengthening the role of nurses in medical device development. Journal of Professional Nursing, 32(4), 300-305. doi:10.1016/j.profnurs.2016.01.002
*Sullivan, S. S., & Dickerson, S. S. (2016). Facing Death: A critical analysis of advance care planning in the United States. Advances in Nursing Science, 39(4), 320-332. doi:10.1097/ANS.0000000000000138
*Porock, D., Bakk, L., Sullivan, S. S., Love, K., Pinkowitz, J., & Barsness, S. (2015). National priorities for dementia care: Perspectives of individuals living with dementia and their care partners. Journal of Gerontological Nursing, 41(8), 9-16. doi:10.3928/00989134-20150710-02
*Sullivan, S. S., Ferreira da Rosa Silva, C., & Meeker, M. (2015). Family meetings at end of life: A systematic review. Journal of Hospice and Palliative Nursing, 17(3), 196-205. doi:10.1097/NJH.0000000000000147
*Denotes data-based research
Co-Investigator (PI: P. Elkin)
Buffalo Research Innovation in Genomic and Healthcare Technology Education: Alzheimer’s and related dementias Care improvement Through Data Science Education (ACT-DSE): Custom training for Research Scientists
National Institutes of Health (NIH)/National Library of Medicine (NLM)
Award Amount: $270,000
Abstract: To customize a biomedical informatics-training program for research scientists in the context of Alzheimer's disease and related dementias (AD/ADRD). With data science approaches, we focus on predicting functional decline, mortality risk, and sleep in people with AD/ADRD.
Nurse's Perspectives on Identifying Changes in Condition and Facilitating Care Transitions Prior to Decision Support Tool Design
Patricia H. Garman Award, University at Buffalo, School of Nursing
Award Amount Requested: $10,000
Abstract: Nurses play a critical role in recognizing risk for decline so they may engage, support, and guide patients and families facing serious illness in transitions to palliative and hospice care programs. This study explores the challenges that nurses face in identifying at-risk patients for the development of a framework for future implementation of clinical decision support for mortality risk into nursing care workflows.
Using the Home Health OASIS to Promote Advance Care Planning for Community-Dwelling Frail Elders.
National Institutes of Health -- National Institute of Nursing Research (NINR) Ruth L. Kirschstein National Research Service Award (NRSA) Individual Predoctoral Fellowship (F31)
Award Amount: $63,856.
Abstract: This study used data science methods to examine the potential of using the home health OASIS dataset to prognosticate death risk within a year for community dwelling frail elders receiving home healthcare as a trigger for the use of clinical decision support and to promote provider-patient advanced care planning action.
Jonas Nurse Leader Scholar Award
Jonas Center for Nursing and Veterans Healthcare/American Association of Colleges of Nursing
Award Amount: $10,000
Shirley DeVoe Doctoral Dissertation Research Award
University at Buffalo, School of Nursing, State University of New York
Award Amount: $5,000