# Olera CareNavigator - Increasing Affordability and Accessibility of Senior Care For Dementia Family Caregivers

> **NIH NIH R44** · OLERA INC. · 2024 · $963,410

## Abstract

Abstract
Senior care is unaffordable for millions, yet a large percentage of elderly Americans miss out on $30 billion yearly
in unclaimed financial aid because they are unaware that they qualify for assistance with food, housing,
prescriptions, and healthcare or they do not know how to apply. This presents a high-impact opportunity to help
millions with transformative innovation. Recent advances in artificial intelligence (AI) called Large Language
Models (LLMs) could allow for mass eligibility-screening of elderly Americans and optimal resource-matching
with underutilized local, state, or federal aid programs and other support programs. Novel applications of AI in
the eldercare ecosystem have the potential to help caregivers especially for individuals with demanding
conditions like Alzheimer's and related dementia (AD/ADRD) facing complex care demands and frequent access
and affordability issues. In this proposed study, we aim to develop, evaluate, and deploy an AI-powered care
planner technology to enable Americans to reclaim billions in underutilized aid and better access vital support
resources. This collaborative project, involving industrial, academic, and community partners, is oriented around
three specific aims: (Specific Aim 1) Development of novel specialized AI agents for elder care planning.
Three categories of AI “agents'' will be engineered for specialized care planning functionalities including: needs
assessment agents, resource & aid matching agents, and personalized care planning agents. (Specific Aim 2):
Integration of multi-agent network & preliminary usability testing of a novel intelligent user interface (UI)
among AD/ADRD caregivers. The agents will be integrated into a Multi-Agent Network and intelligent UI. The
UI will be evaluated among a pilot group of AD/ADRD family caregivers (n=25) using the User Experience in
Intelligent Environments (UXIE) framework to test for its acceptance and usability. Following a Build-Measure-
Learn approach, we will iteratively refine the UI through survey data, platform usage data, and interview feedback.
(Specific Aim 3): Evaluation of the user experience and caregiver perceptions of novel AI-powered care
planning technology among AD/ADRD caregivers with diverse backgrounds. The network will be evaluated
for usability, acceptance, and caregiving experience among AD/ADRD family caregivers (n=200) with diverse
backgrounds regarding demographic characteristics and health needs factors. The modified Technology
Acceptance Survey (TAS), the modified Mobile Application Rating Scale (MARS), Caregiver Self-Efficacy Scale
(CSES-8), and the positive and negative appraisals of caregiving (PANAC) will be used as key quantitative
survey tools to evaluate the technology acceptance and usability, and the caregiving experience in decision
making before and after using the technology. At Phase IIB conclusion, the care-planner technology will be ready
for service, commercially viable, and prepared for nati...

## Key facts

- **NIH application ID:** 10922402
- **Project number:** 2R44AG074116-04
- **Recipient organization:** OLERA INC.
- **Principal Investigator:** Tokunbo Falohun
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $963,410
- **Award type:** 2
- **Project period:** 2021-09-05 → 2027-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10922402

## Citation

> US National Institutes of Health, RePORTER application 10922402, Olera CareNavigator - Increasing Affordability and Accessibility of Senior Care For Dementia Family Caregivers (2R44AG074116-04). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10922402. Licensed CC0.

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