Despite well-documented disparities in Alzheimer?s disease (AD) prevalence, incidence, diagnosis, treatment, and mortality, individuals from disadvantaged backgrounds (e.g. racial/ethnic minorities) are disproportionately under-represented in clinical AD research. Current recruitment methods for AD research predominantly identify patients from outpatient clinics and community settings, or with pre-existing diagnoses. Reliance on these recruitment approaches may create barriers to participation for disadvantaged individuals as they are more likely to lack information about AD services, be undiagnosed and have limited access to outpatient care. Yet, greater enrollment of disadvantaged individuals into AD studies is critically needed to achieve national goals for AD research. Targeted AD screening and tailored recruitment within acute care settings has strong potential to address these gaps, as disadvantaged individuals often rely on these settings to meet their health needs. This K76 proposal is designed to provide Dr. Gilmore-Bykovskyi, PhD, a geriatric trained nurse and expert in AD symptom management with the training required for success as an independent clinician-scientist focused on improving AD identification to promote greater participation in research and access to effective care and therapies, specifically targeting high-risk disadvantaged populations. The overarching objective of the proposed research is to design screening and recruitment approaches for identifying and engaging disadvantaged AD patients/caregivers and their biological children in research from acute care settings. The proposal consists of validation of an electronic health record (EHR) Phenotype Model for AD using EHR clinical data identified in preliminary studies (Aim 1), and specification of this Model for performance among disadvantaged individuals (Aim 1a). To address recruitment from acute care environments, mixed methods strategies will inform the design of tailored recruitment approaches appropriate to acute care (Aim 2) which will be piloted with 30 AD patients/caregivers to determine their feasibility, acceptability and preliminary impact on willingness to enroll in a Trial Registry (Aim 2a). As a junior faculty member at an institution with extensive support for early stage investigators and significant infrastructure in AD disparities and EHR Phenotyping, Dr. Gilmore-Bykovskyi is in an ideal environment to complete the proposed research and pursue advanced training relevant to her career goals. Dr. Gilmore-Bykovskyi?s career development plan integrates didactic and practical training, individual mentoring and mentored research activities in the areas of 1) clinical trial design, 2) advanced statistical and machine learning techniques, 3) acute care research, 4) AD health disparities, 5) recruitment and retention of vulnerable populations and 6) leadership. This proposed award addresses fundamental gaps and barriers to improve inclusion of disadvantaged individuals in AD research while affording training and mentored research critical for Dr. Gilmore-Bykovskyi to lead an independent research program in clinical AD research.

Public Health Relevance

/RELEVANCE Under-representation of individuals from disadvantaged backgrounds (e.g. racial and ethnic minorities) in Alzheimer's disease (AD) research is a major barrier to achieving national AD research goals and exacerbates widespread health disparities in AD. The proposed research addresses fundamental barriers to research participation among disadvantaged individuals with AD through the development of novel 1) screening and 2) recruitment approaches within acute care settings, where many disadvantaged individuals routinely seek health care. The long-term goal of the proposed research is to improve access and engagement in AD research among disadvantaged groups.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Project #
5K76AG060005-02
Application #
9770763
Study Section
Special Emphasis Panel (ZAG1)
Program Officer
Fazio, Elena
Project Start
2018-09-01
Project End
2023-05-31
Budget Start
2019-08-01
Budget End
2020-05-31
Support Year
2
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of Wisconsin Madison
Department
Type
Schools of Nursing
DUNS #
161202122
City
Madison
State
WI
Country
United States
Zip Code
53715