# Measuring the Impact of the Value Flower and Unobserved Heterogeneity on the Cost Effectiveness and Use of Novel Treatments for Alzheimer's Disease and Related Dementias

> **NIH NIH R61** · VIRGINIA COMMONWEALTH UNIVERSITY · 2024 · $305,718

## Abstract

Project Summary
This purpose of this project is to use a combination of Markov models, stated preference data and econometric
models of treatment take-up to calculate the costs, benefits, societal value and health equity impacts of novel
treatments or Alzheimer disease and Alzheimer's disease-related dementias (AD/ADRD). In this project, we
will study the health equity implications of the cost effectiveness models new novel treatments for AD/ADRD
using a combination of Markov models, data from the literature and clinical trials, community based
participatory research (CBPR) with focus groups and experimental preference data. First, we will update our
existing cost effectiveness Markov model (developed for aducanumab and donanemab for early Alzheimer
disease in the United States) in incorporate race specific inputs into the start values and transition probabilities.
Next, we will engage in CBPR by conducting focus groups on AD/ADRD with at-risk African-American/Black
individuals in a poor, underserved area (Richmond, VA). In this, we will leverage pre-existing relationships to
engage with community partners working on healthy aging. We will also conduct focus groups with caregivers
to understand the effect of caregiver burden. We will use the results of the models to measure the economic
value of reducing AD/ADRD in different populations using experimental stated preference data from Discrete
Choice Experiments. Finally, we will estimate models of treatment take-up using a combination of latent
choice and mixed logit models to control for both observed and unobserved preference heterogeneity both
between different racial groups and within racial groups. We will calibrate our models using nationally
representative Medicare data to simulate take-up rates, and subsequent costs and benefits to new treatments
plus the impact of health equity. Finally, we will develop simulation models based on the take-up rates to
identify policy changes that could be used to ensure that new treatment improve health equity.

## Key facts

- **NIH application ID:** 10864045
- **Project number:** 5R61AG081939-02
- **Recipient organization:** VIRGINIA COMMONWEALTH UNIVERSITY
- **Principal Investigator:** ADAM J ATHERLY
- **Activity code:** R61 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $305,718
- **Award type:** 5
- **Project period:** 2023-06-15 → 2025-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10864045

## Citation

> US National Institutes of Health, RePORTER application 10864045, Measuring the Impact of the Value Flower and Unobserved Heterogeneity on the Cost Effectiveness and Use of Novel Treatments for Alzheimer's Disease and Related Dementias (5R61AG081939-02). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10864045. Licensed CC0.

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