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

项目总结

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.