This K99/R00 award will provide education and mentored research study experiences for Dr. Reeder to achieve success as an independent investigator. Dr. Reeder's program of research is aimed at improving self- management and clinical care outcomes of patients with cardiovascular disease, the nation's number-one killer. K99/R00 coursework and mentored research activities will support 1) implementation of a clinical research study to explore how adult patients living with heart failure (HF) recognize, interpret, and report symptoms, 2) verification of the content and construct validity of a theoretical and clinically-based interview questionnaire on HF symptom recognition, interpretation, and reporting using novel Bayesian analyses, 3) advancement of knowledge about self-management of HF, with respect to symptom recognition, interpretation, and reporting, and 4) development and submission of a future intervention research proposal to examine empirically the effect of an evidence-based intervention that is informed by findings from this K99/R00 study on HF outcomes. Dr. Reeder has strong research support and training from a team that includes Carol Smith, PhD, RN, professor, KU-SON and Preventive Medicine, mentor, with 23 consecutive years of NIH-funded research and a long history of mentoring graduate students, medical residents, post doctoral fellows, and junior faculty who have become successful independent researchers, and co-mentor, Byron Gajewski, PhD, associate professor, KU Department of Biostatistics. During the K99 phase of the award, Dr. Reeder will also have the support of 3 significant contributors, an internationally known health care economist and outcomes researcher, a cardiologist with extensive NIH outcomes research funding, and an exemplary data base development specialist. Many of Dr. Reeder's research development activities will draw from KUMC's interdisciplinary research development programs, resources, and seminars. Proposed educational activities will provide Dr. Reeder with new knowledge integral to developing an independent program of research to improve outcomes for people living with cardiovascular diseases. Dr. Reeder will apply this knowledge through corresponding mentored research activities within a clinical research study, entitled """"""""Timeliness of Symptom Recognition, Interpretation, and Reporting in HF,"""""""" as a logical progression of her academic research dissertation and current position. Building on her doctoral dissertation that evaluated the influences of social interactions on pre-hospital delay in acute myocardial infarction (AMI), Dr. Reeder will use an exploratory descriptive design to investigate symptom recognition, interpretation, and reporting by employing both the innovative Day Reconstruction Method for data collection and novel Bayesian analysis. The ultimate goal is an independent program of research to promote effective self-management of cardiovascular diseases, enhance quality of care, and reduce costs.

Public Health Relevance

The relevance of this research to public health priorities is that it explores patients'self-management methods used to monitor their bodily changes and symptoms and the timeliness of reporting heart failure symptoms to health care providers. Understanding patient methods can help health care providers to identify ways improve heart failure status and reduce untimely, repeated heart failure hospitalizations.

National Institute of Health (NIH)
National Institute of Nursing Research (NINR)
Career Transition Award (K99)
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National Institute of Nursing Research Initial Review Group (NRRC)
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Huss, Karen
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University of Kansas
Schools of Allied Health Profes
Kansas City
United States
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Reeder, Katherine M; Sims, Jessica L; Ercole, Patrick M et al. (2017) Lay Consultations in Heart Failure Symptom Evaluation. SOJ Nurs Health Care 3:
Reeder, Katherine M; Ercole, Patrick M; Peek, Gina M et al. (2015) Symptom perceptions and self-care behaviors in patients who self-manage heart failure. J Cardiovasc Nurs 30:E1-7
Jiang, Yu; Boyle, Diane K; Bott, Marjorie J et al. (2014) Expediting Clinical and Translational Research via Bayesian Instrument Development. Appl Psychol Meas 38:296-310