Using the generalized risk-adjusted cost-effectiveness (GRACE) model to advance an efficient and fair use of novel treatments for Alzheimer’s Disease and Related Dementias

The newer disease-modifying drugs for Alzheimer’s Disease (AD) target Aβ42 proteins and p-tau production and accumulation and include antibodies directed at Aβ epitopes. While these drugs offer hope for individuals affected by AD and related dementias (ADRD) and their families, best practices are unclear due to potential harms, substantial costs, and modest efficacy. Those affected by ADRD, along with their families, clinicians, and payers, dynamically make decisions about therapies in response to the evolving cognitive, physical, behavioral, financial, and emotional challenges as dementia progresses. Standard cost effectiveness analyses fall short in incorporating the perspectives of the users of new treatments from varied backgrounds, who differ in clinical responsiveness, side effects tolerance, risk acceptance, spending preferences, and use of therapies driven by differences in healthcare access and preferences. In the planning phase (R61), we will conduct focus groups with individuals from varied backgrounds affected by ADRD to understand their medication decision-making processes. With this information, we will design discrete choice experiments to learn how different attributes of a therapy are valued by affected individuals and what tradeoffs they would make between treatments with different attributes. In the implementation phase (R33), we will administer the survey, in a web-based format, to a large, nationally representative sample of older adults conversant in English or Spanish. Experiment results will inform a risk-adjusted cost-effectiveness (GRACE) model, incorporating relative preferences and health risk attitudes, overall, and by specific subpopulations of interest. Using these estimates, data from the National Health and Aging Trends Study cohort (2011-2024) with their Medicare claims, and other input data from the literature, we will develop, validate, and calibrate a health economic evaluation microsimulation model of ADRD progression and outcomes. We will apply the model to estimate the cost-effectiveness as well as financial risk protection and the impacts of new existing and hypothetical ADRD drugs on health differences, overall and for specific patient populations disproportionately impacted by ADRD. We will prepare the final models so that they are accessible for use as additional novel therapies become available.