# PrEDICT ADRD: Predicting the Effects of Diagnosis in Individuals across Countries and Time in ADRD

> **NIH NIH RF1** · BROWN UNIVERSITY · 2024 · $2,393,910

## Abstract

PROJECT SUMMARY / ABSTRACT
As the overall prevalence of mild cognitive impairment (MCI) and Alzheimer’s disease and related dementias
(ADRD) grows, there is an urgent need to improve diagnosis rates and identify people earlier in their disease
process. An early diagnosis could not only help implement timely measures to reduce or prevent further
progression, but also help individuals and families prepare for future financial and care needs. This work aims
to gain a better understanding of the individual- and system-level characteristics that influence diagnosis,
alongside local culture and practice, and how diagnosis can moderate the effects of cognitive decline and its
impact on employment, future care, and quality of life. Our first aim examines whether older adults
experiencing cognitive decline during their working life are more likely to experience an earlier, unplanned exit
from the workforce than individuals who do not experience cognitive decline. Making use of harmonized,
longitudinal survey data across countries, we examine the cognitive and employment trajectories of older
adults (born in 1931-1960) from the US, England, and 28 European countries, first observing these individuals
during employment age and following them throughout working life and after labor force exit. Our second aim
uses linked survey and claims data to assess the concordance between harmonized, survey-based cognitive
tests and claims-based diagnosis of MCI and ADRD in the US and six other high-income countries with
different approaches to detection. Our analysis of how concordance/discordance in dementia prevalence
varies across countries and over time, and for which populations, can help identify scope for cross-country
learning. Our third aim is to develop communication-efficient, federated learning algorithms for counterfactual
analyses to quantify the relationship between individual characteristics and time to diagnosis and
institutionalization across populations in US and peer countries, all the while ensuring strict adherence to each
country’s data protection principles. Ultimately, our project aims to leverage longitudinal, harmonized, patient-
level data across high-income countries to compare health outcomes for older adults, to gain a comprehensive
understanding of the effects of cognitive decline on employment for older adults, and to inform policies related
to the detection and care of MCI and ADRD.

## Key facts

- **NIH application ID:** 10985639
- **Project number:** 1RF1AG089680-01
- **Recipient organization:** BROWN UNIVERSITY
- **Principal Investigator:** Irene N Papanicolas
- **Activity code:** RF1 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $2,393,910
- **Award type:** 1
- **Project period:** 2024-09-20 → 2027-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10985639

## Citation

> US National Institutes of Health, RePORTER application 10985639, PrEDICT ADRD: Predicting the Effects of Diagnosis in Individuals across Countries and Time in ADRD (1RF1AG089680-01). Retrieved via AI Analytics 2026-08-17 from https://api.ai-analytics.org/grant/nih/10985639. Licensed CC0.

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