Patient cost burden (PCB) for healthcare, as influenced by the rapidly changing health policy landscape, is a
common patient-reported outcome for uninsured individuals and enrollees in high deductible health plans
(HDHPs, 30% of employer-sponsored plans). In these contexts, PCB has important effects on adherence to
medications that help manage cardiovascular and metabolic health (CMH). The management of CMH, including
type 2 diabetes mellitus (T2DM), is an important part of healthy aging, and affects risk of Alzheimer's disease
and related dementias (ADRD). In order to understand the long-term consequences of today's PCB on the
healthy aging and ADRD risk of tomorrow, it is critical to develop methods and models that can simulate the
complicated interplay between PCB, medication adherence, and ADRD. The proposed work in this application
builds upon my experience investigating effects of insurance design and pharmacoepidemiology of ADRD, and
enhances it by adding training in areas that are critical to achieving my long-term career goal: to become a
leading independent investigator of the relationships between health policies and the burden of chronic diseases.
The training of this award includes development and application of simulation models of healthcare interventions,
policy and stakeholder engagement, T2DM and ADRD, geriatric research and care, and leadership. The newly
acquired skills and knowledge obtained are necessary to conduct the proposed research, which aims to examine
the effects of PCB on management of T2DM, and simulating how health policies that influence PCB affect the
burden of ADRD. With mentorship from established leaders in simulation modeling, geriatrics, health economics,
health policy, ADRD, and T2DM, I will accomplish the following specific aims: 1) Simulate long-term effects of
PCB on T2DM management and progression using the Real-World Progression in Diabetes Model (RAPIDS).
PCB will be examined in the context of uninsurance and HDHPs, and we will simulate how effects of PCB on
T2DM management translate into long-term CMH outcomes in RAPIDS, a validated model of T2DM progression.
2) Build a new simulation model using a near-elderly/elderly lifetime perspective to connect PCB, T2DM
progression, and ADRD incidence and burden. The new Healthcare Access Today and Healthy Aging Tomorrow
(HATHAT) Model will connect the RAPIDS Model to the validated Future Elderly Model (FEM), in order to
comprehensively relate PCB, T2DM treatments, micro- and macro- vascular events, and biomarkers to the future
burden of ADRD. 3) Evaluate long-term consequences of highly relevant state and national policies on healthy
aging in the HATHAT Model. Policy experts will advise on the most relevant and impactful policies to evaluate,
and simulations will delineate effects along the PCB-->Treatment Use-->CMH-->ADRD nexus. Success of this
project can lead to future models that examine health policies yet to be conceived, in a range of disease areas.
This will leave me well-positioned to lead an independent research program that influences future policy by
identifying how PCB and access to care relate to long-term healthy aging and ADRD.