Friday, April 26, 2024
4/26/2024
PROJECT SUMMARY / ABSTRACT The U.S. aging population is rapidly becoming more racially and ethnically diverse and addressing persistent disparities in Alzheimer's disease and related dementias (ADRD) diagnosis and care is an urgent research priority. Fundamentally, the causes of these disparities remain gravely understudied and the mechanisms underlying racial and ethnic healthcare inequities are lacking. The primary goal of this project is to elucidate the role of social determinants of health in racial and ethnic disparities in ADRD diagnosis and care using data from a nationally representative cohort of Medicare beneficiaries enrolled in the Medicare Current Beneficiary Survey (MCBS) linked to administrative claims data. The overarching hypothesis of this study is that social factors will substantially mediate the relationship between race and ethnicity and ADRD diagnostic and access to care outcomes. In Aim 1, we will identify key social determinants associated with the timeliness of ADRD diagnosis, etiological specificity of ADRD diagnosis, and access to ADRD diagnostic care (specialty evaluation and recommended diagnostic services). In Aim 2, we will empirically test the role of key social determinants of health as mediators of racial and ethnic disparities in diagnostic and access to care outcomes. The findings will provide critical contributions to existing health disparities frameworks and, if our hypotheses are supported, will have direct implications for clinical care by identifying most vulnerable populations in need for interventions and facilitating the establishment of diagnostic pipelines to guide practitioners and healthcare systems aimed at reducing health inequities in ADRD.
HHS’ Tracking Accountability in Government Grants System (TAGGS) website provides access to detailed descriptions of grants, loans, aggregated direct payments and other types of financial assistance awarded by the HHS Operating Divisions (OPDIVs) and the Office of the Secretary Staff Divisions (STAFFDIVs).
