CeASES-ADRD Pilot Project Awardees

2024-2025 Pilot Awardees Have Been Selected

We are delighted to announce the three projects selected for the Center for Advancing Sociodemographic and Economic Study of Alzheimer’s Disease and Related Dementias (CeASES-ADRD)  2023-2024 pilot grant awards. These three projects were selected from a number of competitive applications. Please join us in congratulating our newest cohort of pilot grant recipients. 

Eric T. Klopack, PhD, University of Southern California

Eric T. Klopack, is a postdoctoral researcher in the Leonard Davis School of Gerontology at USC. He received his doctorate in Sociology from the University of Georgia. His research focuses on the processes by which social circumstances and relationships interact with biological and developmental systems to produce inequalities in aging. His current research investigates the ways that social gender and biological sex interact to affect biosocial health processes and how life experiences (especially early life adversity and social stressors) influence immunological aging and biological hallmarks of aging that may lead to impaired cognitive functioning, risk of Alzheimer’s disease and related dementias (ADRD), chronic disease morbidity, and mortality.

Understanding the Roles of Accelerated Aging, Sex, and Gender in ADRD Risk

Sex—biological differences between men and women—and gender—social and cultural factors—are fundamental forces in health and aging, with large differences between men and women in risk of Alzheimer’s disease and related dementias (ADRD). Identifying biological sex-specific and social gender-specific pathways that generate differences in health and aging is critical for developing sex and gender responsive interventions that will most efficaciously reduce ADRD risk. To address these complex processes, this study will utilize the recently released, rich biomarker data from the 2016 Health and Retirement Study Venous Blood Study, which present a unique opportunity to understand how social gender-related and biological sex-related aging processes interact with biological and immune aging to affect ADRD risk at the population level. This type of data is essential for understanding what processes can be detected at the population level, and thus, what interventions may have large, robust effects for addressing sex and gender differences in the aging process and for promoting interventions to promote healthy cognitive aging. This project focuses on two main questions: 1) Do differences in rates of aging in multiple biological systems (e.g., epigenetic, immune, metabolic, neurological, cardiovascular, renal) help explain sex and gender differences in ADRD and 2) Do gender differences in social exposures (e.g., stressors, social support) explain sex/gender differences in ADRD risk and do aging biomarkers (e.g., epigenetic clocks, cytokines) mediate those effects?

Kun Li, PhD, Duke University

Dr. Li is a Postdoctoral Associate at the Duke-Margolis Institute for Health Policy at Duke University. She received her PhD in Health Policy from George Washington University. She has developed expertise in large-scale secondary data analyses using econometric and causal inference methodologies. Her research examines how organizational structure, market concentration, and payment policies affect health care providers and patients, with emphasis on safety net providers and medically underserved populations. Her recent work focuses on evaluating quality of care received by older adults seeking care from federally qualified health centers and assessing the relationship between provider competition and health disparities.

Primary Care Delivery Organization and Socioeconomic Disparities in Patient Outcomes Among Medicare Beneficiaries Living With Alzheimer’s Disease and Related Dementias

Primary care providers play an increasingly important role in post-diagnostic care for people with Alzheimer’s Disease and Related Dementia (ADRD). High-quality primary care is especially critical for socioeconomically disadvantaged populations due to their limited access to specialty care. However, primary care providers’ role in providing dementia care is not always facilitated by their organizations. Organization-level barriers to optimal dementia care often include the lack of available support services and difficulties in coordinating with other providers. These barriers are more alarming for physician organizations (POs) that predominantly serve patients with low-socioeconomic status. Hence, variations in available resources across POs could enlarge socioeconomic disparities in quality of dementia care. This study will use administrative claims data to examine different PO models that provide care to Medicare fee-for-service beneficiaries living with ADRD. Specific aims include: (1) Identify trends in the setting in which community-based Medicare beneficiaries with ADRD receive primary care and the extent to which primary care setting differs by socioeconomic status; (2) Assess trends and socioeconomic disparities in specialty care use and patient outcomes by PO model; (3) Examine how receiving primary care from different PO models affects socioeconomic disparities. Study results could inform policies to support different types of POs in terms of providing equitable, high-quality dementia care.

Andrea Piano Mortari, PhD, Economics at the University of Rome Tor Vergata

Andrea Piano Mortari, an Assistant Professor of Economics at the University of Rome Tor Vergata, specializes in health economics, applied econometrics, and microsimulation. He has made significant contributions to international projects such as Global FEM and has conducted research on the psychological impacts of COVID-19. Currently, he is involved in EU-funded projects such as LongITools, STAGE, and Obelisk, holding leadership roles. His teaching experience includes courses in Microeconomics, Research Methods in Social Sciences, and Health Economics. His research, focusing on dynamic microsimulation modelling, has been applied in various contexts, including the assessment of the returns to preventing chronic disease and the prediction of future elderly population health status. His scholarly contributions have been published in several peer-reviewed journals and reports.

Forecasting the Impact of Dementia and Alzheimer’s in Europe Using Dynamic Microsimulation

As Europe’s population ages, the burden of Alzheimer’s disease and related dementias (ADRD) is expected to grow, despite a decreasing incidence of the disease. Predicting future trends and understanding their implications is challenging due to changing risk factors and the varied impact of the disease across different countries. Dementia rates differ significantly among European nations. To effectively study future disease burden and estimate the effects of new treatments, advanced tools are needed for accurate disease progression modeling. This project, in collaboration with researchers from Masaryk University, Brno, will introduce a new ADRD module to the European Future Elderly Model (EUFEM), a dynamic simulation tool that includes key risk factors likely to affect ADRD rates. EUFEM simulates health trends in Europe’s older population. Adding the ADRD module will allow for consistent projections, taking into account major factors influencing future ADRD rates, thus supporting research and policy-making. Expanding EUFEM to include more data waves and countries will significantly enhance its ability to make reliable predictions for 60 million Europeans aged 50 or older. The introduction of the Harmonized Cognitive Assessment Protocol (HCAP) will allow researchers to analyze future scenarios using advanced econometric methods for accurate ADRD predictions. The project plans to expand EUFEM with more data from the harmonized version of the Survey of Health, Ageing, and Retirement in Europe (SHARE) and additional countries, develop and validate the ADRD module, and prepare EUFEM for integrating further data, including more HCAP waves.

2023-2024 Pilots

Emma Aguila, PhD, University of Southern California

Dr. Emma Aguila is an Associate Professor at the USC Sol Price School of Public of Policy. She was previously a Senior Economist and Director of the RAND Center for Latin American Social Policy (CLASP). My research focuses on using microeconometrics to assess the effects of safety net policies and social security programs on cognitive decline and well-being of older adults, and the interrelation between social and behavioral factors. Dr. Aguila’s research is novel designing, implementing, and evaluating randomized controlled trials to understand the effects of cash assistance programs on the wellbeing of population. Her research on the social security system, retirement behavior, and health and well-being of Hispanic and Mexican-origin older adults won the First Prize of the Inter-American Award for Research in Social Security in 2007, the RAND Gold Merit Award in 2008, and the Faculty High Impact Research Award from USC Sol Price School of Public Policy in 2016. She is Editor of the Journal of Pension Economics & Finance and Editorial Board Member for the Journal of Aging and Social Policy and the Journal Work, Aging and Retirement. Dr. Aguila is Council Member of the Institute on Minority Health and Health Disparities (NICHMD) of the National Institutes of Health (NIH).

Education, Occupation, and Cognition of Vulnerable Older Adults

Recent studies have documented decreases in age-specific prevalence of dementia associated with increases in educational attainment and better chronic disease management over time. Also, mental work demands are associated with higher levels of cognitive functioning and lower cognitive decline. However, little is known about the protective factors associated with the prevalence of dementia for populations with low levels of education. We examine the association between education and mental work demands in the lifetime occupations, and their influence on cognition. We focus on Mexican-origin populations in the United States and Mexico using the Health and Retirement Study (HRS) and the Mexican Health and Aging Study (MHAS).

Takashi Amano, PhD, MSW, Rutgers University Newark

Takashi Amano is an assistant professor in the Department of Social Work, School of Arts and Sciences, at Rutgers University – Newark. Prior to joining Rutgers, he obtained his PhD from the Brown School at Washington University in St. Louis. His personal experience with his grandmother, coupled with his professional background as a researcher and social worker, has profoundly influenced his dedication to assisting individuals with Alzheimer’s disease and related dementias (ADRD), as well as their family members. His expertise lies in gerontological, geriatric, and social work research, employing quantitative methodologies with population-based data. Through a comprehensive biopsychosocial approach, his current research endeavors center around comprehending and providing support for individuals with cognitive impairments and ADRD. One of his recent research projects has focused on investigating the impacts of receiving an ADRD diagnosis on social aspects of individuals’ lives.

Racial/Ethnic disparities in advance care planning among people with dementia

Receiving a diagnosis of ADRD may encourage the patient and their family members to initiate ACP since it provides supports and resources. Nevertheless, previous studies have shown that vast majority of people with Alzheimer’s disease and related dementias (ADRD) do not engage in advance care planning (ACP) or start too late. This suggests that there exists variations in the presumed effects of receiving a diagnosis of dementia. The effects may be attenuated for racial/ethnic minorities due to limited and culturally insensitive medical and social resources. However, the effects of receiving a diagnosis on engagement in ACP and its racial/ethnic variations have not been empirically examined. Guided by the NIA Health Disparities Research Framework, this pilot project aims to gain a better understanding of the causal relationship between diagnostic labeling of Alzheimer’s disease and related dementias (ADRD) and the process of advance care planning (ACP) in the context of racial/ethnic disparity. It has two specific aims: (1) it estimates Estimate the effects of receiving a diagnosis of ADRD on ACP and (2) it examines racial/ethnic variations in ACP among people with dementia. This proposed project utilizes a longitudinal design with data from the nationally representative survey of the Health and Retirement Study (HRS) and propensity score analysis to gain higher generalizability and minimize the influence of confounding factors. With the design and method, this study will be able to examine the effects of receiving a diagnosis of ADRD on the process of ACP with a pseudo experimental setting. Results would suggest possible strategies to promote ACP after the diagnosis of ADRD.

Elham Mahmoudi, PhD, University of Michigan

Elham Mahmoudi, PhD is an Associate Professor of Health Economics at the University of Michigan Department of Family Medicine. Dr. Mahmoudi has more than 70 peer-reviewed publications and has extensive experience in using a variety of large secondary data (including nationally representative survey data, public and private administrative claims data, and electronic health records), quantitative analysis, and econometric methodologies. Her research has been focused on evaluating healthcare policies aimed at reducing racial/ethnic disparities in access to care and quality of care. She is a mixed methods researcher, and her research extends to examine healthcare use and cost, and efficiency of care for older adults with cognitive decline (Alzheimer’s disease and related dementia and mild cognitive impairment) and individuals with disabilities. She also works internationally with programs in China. She is on the editorial board of eLife and PLOS One.

Efficiency and Equity in Health Care Use and Costs among Older People with Alzheimer’s Disease and Related Dementia: Medicare Advantage Versus Traditional Medicare

Alzheimer’s disease and related dementias (ADRD) is a substantial economic, medical, and social burden. Medicare is the primary health insurance for older adults (65+) living in the U.S. Eligible beneficiaries must choose between two different plan types: traditional Medicare (TM) and Medicare Advantage (MA). MA enrollment has doubled in the last decade, currently covering about 45% of all Medicare beneficiaries. This growth has been driven in part by an increasing proportion of Black and Hispanic MA enrollees. While evidence suggests that some MA patient populations have lower health care costs and experience fewer racial/ethnic disparities in care, it is unknown whether this is true for socioeconomically disadvantaged Black and Hispanic Medicare beneficiaries, who are at substantially greater risk of incident ADRD. Racial/ethnic disparity research in health care has been mainly observational and descriptive, thus limiting its usefulness in informing policy. The specific aims of this study are to use innovative econometric causal methods to (1) examine trends and explain differences in health care use and total and out-of-pocket health care costs in MA vs. TM; (2) examine racial/ethnic disparities in health care use and cost between MA and TM. Study results can inform Medicare policies to promote more efficient and equitable health care for Medicare beneficiaries with ADRD. It will also provide preliminary data for an R01 proposal, to be submitted to the NIA, to investigate the same topic using administrative claims data.

2022-2023 Pilots

Annie Chen, PhD, RAND

Annie Yu-An Chen (DDS, MS) is an Assistant Policy Researcher at RAND and a PhD candidate at Pardee RAND Graduate School. Her research covers analyses of healthcare utilization, healthcare cost, and quality of care, especially those based on large healthcare databases such as Medicare and Medicaid claims data.  She is experienced in using microsimulation models to project future disease burden, with a focus on Alzheimer’s disease. Her dissertation will be using microsimulation models to predict the societal impact of advancements in Alzheimer’s disease.

Dynamic Microsimulation Projections of ADRD and Associated Functional Limitations in Taiwan and the United States

Taiwan is projected to become a super-aged society where at least 20 percent of the population are 65 or older by 2026, and the time it takes to transition from an aged society (10% of the population 65 years or older) to a super-aged society is about half the time it will take the United States. In an aging society, burden from age-related diseases such as Alzheimer’s disease and related dementias (ADRD) is highly uncertain due to complex interactions between individuals, families, health systems, and policy changes. Predicting the effects of policy intervention requires new tools and microsimulation models of aging fill this gap. In the past year, we have combined early waves from the Taiwan Longitudinal Study on Aging (TLSA) with the Future Elderly Microsimulation (FEM) software. Through this pilot, we will (1) extend the Taiwan Future Elderly Model (TFEM) using TLSA to incorporate medical expenditures, cognitive function, and functional limitations; (2) extend the TFEM to incorporate population (rather than just cohort) simulation; (3) validate outcomes from TFEM with observed data; (4) compare the simulated future prevalence of ADRD and informal caregiving needs between Taiwan and the US. 

Katherine Miller, PhD, University of Pennsylvania

Dr. Miller is a Postdoctoral Research Fellow in the Division of Medical Ethics and Health Policy at the University of Pennsylvania and Associate Fellow at the Leonard Davis Institute of Health Economics. She received her Ph.D. from The University of North Carolina at Chapel Hill. She has developed expertise in program evaluation and use a variety of empirical approaches used in both health services research and economics. Dr. Miller’s research interests include access to health care in rural communities and the intersection of aging and health policy. Her recent work focuses on (1) policies impacting formal and family caregivers and (2) the supply of and access to long-term care services in rural settings.

The Mediating Role of State Policies Supporting Care Partners of Persons with Dementia on Care Partner Outcomes

Over six million persons living with dementia in the U.S received unpaid care from nearly 16 million care partners. Demand for care provided in the home by family care partners is expected to increase. Care partners of persons living with dementia generally report worse physical health and high levels of depressive symptoms and care partner burden. Variation in state policies supporting care partners yields heterogenous access to and generosity of services for care partners. Unpacking the potential mediating role of polices intended to benefit care partners is critical to support and improve the health of care partners of persons living with dementia. Our objectives are to: (1) provide systematic documentation of policies supporting care partners of persons living with dementia; and (2) examine association of policies and care partners’ outcomes. This study leverages an existing dataset of policies supporting care partners to expand upon and survey data of nationally representative sample of care partners. This research will advance our understanding of the effects of dementia caregiving on care partners and persons living with dementia by building a database for future research to examine persons living with dementia and care partner outcomes. Moreover, understanding the pathways by which policies and policy interactions impact these outcomes is essential to inform the policy discussions regarding evidence-based supports for care partners of persons living with dementia.

Anna H. Wu, PhD, University of Southern California

Dr. Anna Wu is a Professor in the Department of Population and Public Health Sciences (DPHHS) at the University of Southern California (USC).  A unifying theme of her epidemiologic research is to identify modifiable lifestyle and environmental factors to reduce the risk of specific cancers, to improve outcomes among those diagnosed with cancer, with the ultimate goal of reducing racial and ethnic and socioeconomic disparities in cancer incidence and mortality.  Using this rich experience in cancer epidemiology, she is now studying environmental exposures and risk of aging, ADRD and other phenotypes in the Multiethnic Cohort (MEC).  The MEC has over 200,000 men and women in California and Hawaii, with rich baseline and follow-up assessments (residential history and lifestyle information from 1993 to present) and linkage to Medicare claims data since 1999. 

Risk of ADRD among first-, second-, and third-generation Latinos in the Multiethnic Cohort (MEC)

The overall objective of this pilot study is to better understand factors driving purported variation in Alzheimer’s disease and related dementia (ADRD) risk across Latino populations.  This prospective analysis will be conducted among 20,093 California Latinos in the well-established Multiethnic Cohort (MEC) Study.  The three specific aims are: (1)  To determine the age and sex-adjusted diagnostic incidence rates of ADRD for 11,413 first-, 6,125 second-, and 2,555 third-generation Latinos. (2) To investigate ADRD risk associations with outdoor air pollution (gaseous and particulate matter pollutants) and to compare associations of established lifestyle factors (education, neighborhood socioeconomic status, marital status, history of hypertension, stroke, diabetes and heart disease, smoking status, physical activity, short/long sleep, body mass index, and diet quality) across first-, second-, and third-generation Latinos. We will also compare hazard ratio (HR) and 95% confidence interval (CI) from Cox regression models for these Latino populations to those of White California MEC participants.  (3)  To estimate the ADRD population attributable risk for lifestyle factors and outdoor air pollution among first-, second-, and third-generation Latinos.  Completion of this pilot project should provide new information on the incidence, as well as lifestyle and environmental determinants of late-onset ADRD for Latinos by generation status.   

2021-2022 Pilots

Sarah Mawhorter studies housing inequality. She is an assistant professor of housing in the real estate and planning programs of the University of Groningen Faculty of Spatial Sciences. She holds a Master of Planning and PhD in Urban Planning and Development degrees from the University of Southern California Price School of Public Policy, and completed postdoctoral research at the University of California, Berkeley Terner Center for Housing Innovation and the USC/UCLA Center for Biodemography and Population Health. Sarah’s research involves the connections between population and housing, with implications for planning and development. She interrogates the housing market dynamics and urban development processes that contribute to unequal housing conditions—with special attention to disparities between renters and homeowners—and the downstream links between housing and health. Her recent research topics include housing affordability and residential mobility among older adults, student housing development in university neighborhoods, and housing tenure and health. 

Housing Transitions Associated with Cognitive Decline

While existing research addresses the suitability of various housing alternatives for persons with dementia (PWD), little is known about PWDs’ housing transitions over the course of cognitive decline. This study investigates PWDs’ housing transitions using Health and Retirement study data from 2002 through 2016. We find that over half (56%) of PWD move in the years around dementia onset: 28% move once, and 28% move twice or more. Examining various types of moves, we see that slightly over a third of respondents move to another home at some point during cognitive decline, just under a third move into nursing homes, and around ten percent move in with relatives, with overlap between these categories since some PWD move more than once. We find strong patterns by educational attainment and race/ethnicity: Black and Hispanic PWD and those with lower education levels are less likely to move to another home or enter a nursing home than White and college-educated PWD. This suggests the importance of providing support for PWD and their families to transition into different living arrangements as their housing needs change.

Peter May, PhD, Trinity College of Dublin

Dr. May is a health economist at Trinity College Dublin, Ireland with a focus on palliative and end-of-life care.  He works with a network of collaborators across the United States, United Kingdom and European Union using a range of study designs including multi-country randomized trials, quasi-experiments, prospective cohort studies, longitudinal studies on ageing, and retrospective analysis of routinely collected data.  His particular research interests include heterogeneity of treatment effects, outcome measurement in end-of-life care and medical decision-making under high complexity and uncertainty. 

Dynamic Microsimulation Projections of ADRD in Ireland and the United States 

Projecting the future burden of Alzheimer’s Disease and Related Diseases (ADRD) is of critical importance to understand implications for individuals, families, health systems, and government planning.  Previously, the applicants have developed dynamic microsimulation models in longitudinal panel data to estimate statistical models of aging and predict future outcomes. This pilot has five Aims:  1. Extend and validate the TILDA-based microsimulation to model new outcomes: cognitive function, depressive behavior, functional limitations and time spent in residential care; 2. Extend and validate the HRS-based microsimulation to model the depressive behavioral domain of ADRD; 3. Produce population and subpopulation (gender, education, and race) projections, and compare these projections within and between countries; 4. Recommend best practices for projecting cognition, depressive behavior, functional status, and ADRD to guide other researchers using panel studies similar to HRS and TILDA.  Scope the potential for novel inclusion of biomarkers and laboratory measures in projections; 5. Use the results as a basis for large-scale international study proposal to project future needs, estimate future health and social care costs, and evaluate the effect of different systems and payment models on care, health and economic outcomes. We anticipate three outcomes associated with the pilot aims: (a) Projections of ADRD prevalence, associated depressive symptoms and functional limitations, and associated residential care use in the United States and Ireland, for the population and for subgroups of interest (Aims 1-3); (b) Lessons learned in validating the domains of ADRD will be documented to inform other modelers undertaking similar work, including assessment of how biomarkers and lab data may improve prediction (Aim 4); (c) An R01 proposal for modeling future ADRD prevalence and associated costs in different countries covered by the g2aging family of longitudinal studies (Aim 5).

Leah Richmond-Rakerd, PhD, University of Michigan

Dr. Richmond-Rakerd is an Assistant Professor of Psychology in the Clinical Science area at the University of Michigan. She received her Ph.D. from the University of Missouri; completed her clinical internship at the Durham Veterans Affairs Medical Center; and completed postdoctoral training at Duke University, supported by a fellowship from the NICHD through the Carolina Consortium on Human Development. Dr. Richmond-Rakerd’s research focuses on the origins, mechanisms, and outcomes of emotional and behavioral dysregulation, including the consequences of self-regulation difficulties for processes of aging and neurodegenerative disease. She uses genetically-informative, longitudinal, and nationwide administrative-register study designs in her research. 

Do Mental Disorders Forecast ADRD in Nationwide Administrative Registers?

Neurodegenerative conditions, including Alzheimer’s disease and related dementias (ADRD), have an outsized impact on disability and loss of independence in older adults. As such, there is a growing need to identify modifiable factors that drive variation in ADRD risk at the population level. We propose to investigate mental disorders as a potential preventable risk factor for later-life ADRD. Using three decades of nationwide health-register data on 1.7 million New Zealand citizens aged 21-60 at baseline, we will test whether mental disorders forecast the development of ADRD in the subsequent 30 years. We will test whether these associations hold across sex and age, across different types of mental disorders, within pairs of siblings matched on family-level risk factors, and after controlling for pre-existing physical-health conditions. Through this project, we will (1) quantify the degree to which preventing mental-health problems in young people might reduce the health and social burden of neurodegenerative diseases, and (2) create exportable tools, including a new linked-sibling data resource and a method for ascertaining ADRD across multiple health registers, that can be used by other ADRD researchers employing linked administrative data in their work. If results of the proposed project indicate that mental disorders forecast neurodegenerative diseases, this would also suggest novel hypotheses about mechanisms that underlie the development of ADRD and that may drive variation in ADRD risk across populations (e.g., inflammation, low education, poor health behaviors, social isolation, or psychiatric medications), to be tested in future basic-science and administrative-register studies.

2020-2021 Pilot Awardees

National Longitudinal Study, 1972 (NLS-72) Record Matching to Centers for Medicare and Medicaid Services (CMS) records. Investigator: Chandra Muller, PhD, University of Texas, Austin 

Education is among the most important determinants of later life cognitive health. Over the life course, education leads to better cognitive functioning and healthier aging through access to better jobs, health care, residential neighborhood, wealth accumulation, and economic security. But, research on early-life educational processes that affect cognitive functioning has been severely limited by a lack of prospective longitudinal data. We do not have data sufficient to identify the specific (and potentially manipulability) organizational, curricular, social, or skill aspects of education that shape cognitive functioning. The proposed project will: link information from sample members of the National Longitudinal Study of 1972 NLS-72 cohort to CMS records; use information gained from matching to provide valuable data on health for analysis of educational precursors (adolescence and early adulthood) of health and cognitive aging among individuals in their mid 60’s as they enter old age; and establish a proof of concept and results for potential re-interviewing of the NLS-72 sample members. The proof of concept will involve not only the possibility of locating respondents but also the value of the education data as a resource for understanding cognitive aging. This study would create new data for analysis of the role of education in cognitive aging among individuals currently age 65 and older. It will also make possible comparisons to the HS&B cohort that is approximately a decade younger.

The Impact of Cognitive Screening on Early ADRD Diagnosis, Treatment and Spending. Investigators: Mireille Jacobson, PhD, University of Southern California; Jason Doctor, PhD, University of Southern California 

As part of a new benefit created under the Affordable Care Act (ACA), Medicare now covers an Annual Wellness Visit (AWV) that requires, among other things, an assessment to detect cognitive impairment. In newly collected data on about 1000 seniors ages 65 and over, we find systematic differences by Medicare plan type (traditional fee-for-service vs. commercial Medicare Advantage (MA)) in the likelihood that seniors ever received either an annual wellness visit or a cognitive assessment. Seniors enrolled in MA plans are about 20 percentage points (p<0.001) more likely to have had an annual wellness visit than those in traditional Medicare (traditional group mean = 47%) and about 13 percentage points more likely to have had a cognitive assessment (traditional group mean = 30%). These findings hold even after controlling flexibly for age, gender, race, education, retiree status, general health and mental health status. The specific aims of the broad project are to: (1) Assess whether, consistent with higher self-reported screening rates, MA plan enrollees are more likely to receive an early ADRD diagnosis, where early is captured by age or an MCI diagnosis; (2) Describe health care service use before, during, and after a beneficiary screens positive for cognitive impairment both overall and by plan type (traditional versus MA); (3) Assess the impact of early diagnosis on the trajectory of health care use and spending. In this pilot, we will leverage the difference in MA plan cognitive screening to study the implications for early diagnosis, treatment and spending. Combining both Medicare Fee- for-service claims and MA plan encounter files, we will study how plan type affects the likelihood of an early ADRD diagnosis, where early is defined as prior to and including age 70. As an alternative definition of early diagnosis, we will consider diagnosis of mild cognitive impairment (MCI). Conditional on a diagnosis, we will describe health care utilization and spending and the impact of early diagnosis on them. These aims will help fill an enormous gap in our understanding of the impact of early ADRD diagnosis on health care utilization and spending in both the short and long term.

ADRD Care in New Delivery and Payment Models. Investigator: Alice Chen, PhD, University of Southern California 

Over the last few decades, US health policy has focused on new payment and delivery models to improve the organization and financing of care. Within the Medicare population, there has been a shift away from traditional fee-for-service payments toward alternative payment models that emphasize value-based care. However, there is little empirical evidence on the efficacy of these programs in managing the care of patients with ADRD. In this pilot, we will estimate the impact of new payment and delivery models—including accountable care organization (ACO) models, patient centered medical care homes (PCMH), value-based payment modifiers, and merit-based incentive payments (MIPS)—on the health care and drug use and cost for ADRD patients. Data on health care and drug use will come from Medicare claims data from 2008 to 2019. Data on provider (a) ACO participation will come from the Centers for Medicare and Medicaid Services’ (CMS) Medicare Shared Savings Program Files from 2013 onward and the Next Generation ACO variable in the Carrier Claims data from 2016 onward, (b) PCMH participation will come from the National Committee for Quality Assurance’s PCMH practice location files from 2012 onward; and (c) provider value-based payments from CMS’ Value Modifier NPI-Practice file from 2013-2016. We anticipate that data on MIPS incentives, which affected Medicare Part B reimbursements in 2019, will be available from administrative claims data. For each delivery model, we will employ a differences-in-differences framework that compares providers and beneficiaries participating in the model (treatment) to those unaffected (control), pre- and post-model implementation. We will focus on responses by primary care providers of ADRD patients and consequential changes in ED reliance, hospital lengths of stay, and access to new technologies among ADRD patients. Results from this research will identify which delivery and payment models are most effective in improving dementia care.

Trends and Projections of ADRD in Asia. Investigators: Jay Bhattacharya, MD, PhD, Stanford University; Karen Eggleston, PhD, Stanford University 

Dementia prevalence is increasing at an even faster rate in Asia than many other parts of the world. The study will focus on the social and economic burden of ADRD over the life course in heterogeneous Asian populations, with three specific aims: (1) To develop innovative methods for estimating cognitive decline and dementia incidence and prevalence in Asian economies within pseudo-panel-based microsimulation models such as the Japanese Future Elderly Model (JFEM); (2) To study heterogeneity in the future disability burden associated with dementias and the implications for labor supply, and caregiver burden, using microsimulation models; and (3) To project the implications of cognitive decline and ADRD for health spending and long-term care spending in East Asia. We will work with members of the Japanese Future Elderly Model (JFEM) team to extend the current microsimulation model built from repeated cross-sectional data to include cognitive function and dementia. We will use this expanded JFEM to study the social and economic burden of ADRD in Japan, and compare to other FEM for North America and Europe. Existing Asia microsimulation models include those for South Korea and Singapore, with a model under development for Taiwan, and in the planning stages for Hong Kong, the rest of China, and India. We will project the health and cost implications of cognitive decline and ADRD and implications of long-term care insurance (LTCI) programs in Japan and South Korea. Changing educational attainment within and across countries, is one important element of heterogeneity for understanding cognitive decline and ADRD burden. Our research will be important for understanding these important changes in Asia and their interaction with rapid demographic and economic change.