CAPRA - Year 1 Pilot Awardees

​Antoinette B. Coe, PharmD, PhD
University of Michigan​, College of Pharmacy 

Impact of Medicare Part D medication therapy management programs on medication use in older adults with AD/ADRD:
​Are there disparities by race and gender?

​Effective medication therapy for older adults to treat AD/ADRD is limited and older adults are at high risk for medication-related problems resulting in increased hospitalizations, ED visits, and health care costs. Comprehensive medication reviews (CMRs), a required service in Medicare Part D medication therapy management (MTM) programs for eligible beneficiaries, are a potential solution to optimize medication use and reduce adverse events. However, the extent of MTM services eligibility and receipt is unknown in older adults with AD/ADRD. In older adults with AD/ADRD, this pilot study aims to: generate nationally representative estimates of MTM eligibility and CMR receipt; quantify disparities in Medicare Part D MTM eligibility and CMR receipt by race and gender; and identify the impact of a CMR on medication use in patients that receive a CMR and potential heterogeneity of benefit by race and gender. 

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Joshua Ehrlich MD, MPH
​Univeristy of Michigan, ​Michigan Medicine

The Population Attributable Risk of Dementia due to Vision Impairment​

​There is an urgent need to identify potentially modifiable risk factors for Alzheimer’s disease and related dementias (ADRD). Vision impairment is consistently and strongly associated with cognitive decline and ADRD in prior studies. However, it has not been integrated into life course models of ADRD risk factors, and the fraction of ADRD cases attributable to poor vision in the U.S. and globally is not known. This project will use data from the Health and Retirement Study and the Global Burden of Disease Project to estimate the number of ADRD cases attributable to vision impairment, as well as the potential for dementia prevention through cost-effective improvements in vision health.

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Geoffrey Hoffman, PhD, MPH
​University of Michigan, School of Nursing

Patterns of Informal & Formal LTSS Use by Race & Ethnicity among Older Americans with Dementia

​Gaps in institutional and home-based care for older Americans with dementia adversely affect health outcomes and increase reliance on other, costly health services that may disproportionately affect racial and ethnic minorities. For dementia-related care, minority groups are overall less likely to rely on formal caregivers; however, little is known about specific care and service use patterns among minority groups over the course of disease progression, including whether informal care patterns vary by race/ethnicity before and after a clinical diagnosis. We will conduct retrospective cohort studies using survey data from the 2000-2018 Health and Retirement Survey and linked Medicare claims. First, we will examine time-to-diagnosis following dementia onset by race/ ethnicity, income and education level, and receipt of informal care. We then assess whether changes in informal caregiving, medical spending, and sick days at home after ADRD onset vary by race/ethnicity and by whether the ADRD was clinically diagnosed or not.

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Elham Mahmoudi, PhD
​Michigan Medicine, University of Michigan

Developing and Validating Algorithms a Natural Language Processing Algorithm for Caregiver Availability Among Patients with Alzheimer’s Disease and Related Dementia

​Patients with Alzheimer’s disease and related dementia (ADRD) are at higher risk of adverse health events, including 30-day hospital readmission,1 emergency department visits,2 and mortality.3 Caregiver support has been identified as a salient component of care for ADRD patients;4 therefore, there is a critical need for healthcare systems to identify patients lacking support. These critical data elements for ADRD patients are not collected in structured Electronic Medical Records (EMRs), and primary data collection via questionnaires is time and labor-intensive, distracting from the focused care ADRD patients require.  Unstructured EMRs (i.e. physician and operative notes) can be leveraged to obtain this information. We will use Natural Language Processing (NLP) that has been successfully implemented to extract value-added information in other settings and populations.5 We will use NLP to extract data from physician and operative notes to collect information on caregiver support relevant for ADRD patients. 

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​Duncan Thomas, PhD
Department of Economics, Duke University 

Elizabeth Frankenberg, PhD
​Carolina Population Center,
​University of North Carolina at Chapel Hill

Cognitive decline after a major natural disaster

​Stress exposures have been linked to premature cognitive decline but isolating a causal pathway remains challenging because in observational studies stress exposures are likely to be correlated with other unobserved factors that affect cognitive decline. The aim of this pilot project is to provide evidence on the long-term impact of exposure to the trauma of a large-scale natural disaster, the 2004 Indian Ocean tsunami, on cognitive performance of older adults. This evidence can be given a causal interpretation because exposure to the extreme stressor based on location at the time of the tsunami is plausibly exogenous. Data are drawn from the Study of the Tsunami Aftermath and Recovery (STAR), a population-representative longitudinal survey of households located in districts along the coast of Aceh and North Sumatra, Indonesia at the time of the pre-tsunami baseline. The baseline, conducted 10 months before the tsunami, 5 annual follow-ups and follow-ups at 10 and 15 years post-tsunami are combined to provide evidence on the long-term impacts of large-scale stressors on cognitive performance of older adults. In addition, the analyses lay the foundation for collaborations to improve the assessments and develop clinical validation protocols that will be designed to be integrated with future waves of STAR.