# Leveraging Existing Data and Analytic Methods for Health Disparities Research Related to Aging and Alzheimer's Disease and Related Dementias (ADRD)

> **NIH NIH R13** · DUKE UNIVERSITY · 2020 · $50,000

## Abstract

Abstract
Two of a series of in-person workshops in 2020-2022 will be hosted at Duke to provide new knowledge on how
existing and recently developed analytic methods can be used for detailed population and clinical data analysis
in order to make progress in understanding the causes and mechanisms of health-related disparities in
Alzheimer’s disease (AD), related dementias (ADRD), and other prominent age-related diseases. The long-
term goal of the series is to provide a resource focused on diffusing methodological know-how in terms of
demonstrating the capabilities of newly developed methodologies, expanding on the rigor and range of
application of well-established and familiar methods, promoting correct use of big health data both from a
methodological and ethical prospective as well as providing a forum for experts and newcomers interested in
health disparities and age-related diseases to discuss their ideas and promote their research. The pilot Duke-
NIA workshop of the series held in February 2019 at Duke University was successful in drawing broad
scientific interest to the topic and generated the background for the current proposal. The focus of the first
workshop (planned in Winter 2020/2021) will be on demonstrating how studies using established administrative
health data resources such as the Medicare claims database combined with innovative analytic approaches
such as partitioning analyses, time-series based methods of projection/forecasting, and stochastic process
models can be used to uncover previously overlooked and/or understudied aspects in this area of research.
Specific topics to be discussed will include: i) disparities in risks and survival of AD/ADRD and other age-
related diseases; ii) forecasting approaches for prevalence and mortality of AD/ADRD and other age-related
diseases; iii) analysis of Medicare and other administrative claim-based data. The focus of the second
workshop (planned in Winter 2021/2022) will extend this to include the health records data routinely collected
in hospitals or University medical centers (e.g., the Duke Clinical Data Warehouse) and demonstrate how well-
established and new analytic methods can be rigorously applied to such data to contribute to identifying the
causes of persistent health disparities between specific groups of the U.S. population and narrowly defined
patient strata. Specific topics will be expanded to include: i) analytic approaches to identify and quantify the
contribution of treatment-related and medical care access-related factors to disparities in outcomes of
AD/ADRD and other age-related diseases; ii) comorbidity, multimorbidity, treatment-related, social and genetic
factors as sources of disparities in health outcomes of AD/ADRD and other age-related diseases; iii)
forecasting of health outcomes and approaches for analyses of potential health interventions. The proceedings
will be streamed live on the workshop website and presentations will be freely available in text and...

## Key facts

- **NIH application ID:** 10070960
- **Project number:** 1R13AG069381-01
- **Recipient organization:** DUKE UNIVERSITY
- **Principal Investigator:** IGOR AKUSHEVICH
- **Activity code:** R13 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $50,000
- **Award type:** 1
- **Project period:** 2020-08-01 → 2022-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10070960

## Citation

> US National Institutes of Health, RePORTER application 10070960, Leveraging Existing Data and Analytic Methods for Health Disparities Research Related to Aging and Alzheimer's Disease and Related Dementias (ADRD) (1R13AG069381-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10070960. Licensed CC0.

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