# Population-Based Outcomes Research for Rheumatoid Arthritis: Rural Health Disparities

> **NIH NIH R01** · MAYO CLINIC ROCHESTER · 2024 · $828,682

## Abstract

PROJECT SUMMARY/ABSTRACT
In rheumatoid arthritis (RA), delaying initiation of treatment for ≥12 weeks is associated with irreversible joint
damage due to greater difficulty in achieving remission, but navigating the hurdles of the US healthcare system
in this short timeframe can be challenging. Time-consuming logistical steps must be carried out to be evaluated
by a qualified specialist, establish a diagnosis, and start antirheumatic drug therapy. These difficulties are
exacerbated for rural residents due to the closure of rural hospitals nationwide extending the distance to
healthcare facilities and the time to travel and obtain care. Additionally, there is very little information about the
timing and accuracy of RA diagnosis and their associated effects on outcomes for rural residents of the US. The
growing rheumatology workforce shortage further aggravates these issues, as <10% of rheumatologists practice
in rural or micropolitan areas yet 30% of the US population lives in these areas. Our goal is to improve outcomes
in patients with RA by reducing healthcare disparities. We aim to (1) identify rural healthcare disparities in the
diagnosis and treatment of early RA, (2) develop and validate an AI algorithm to enable early identification of
RA, and (3) assess long-term outcomes in patients with RA living in rural vs urban areas compared to those
without RA.
We are uniquely positioned to address these objectives as ours is the only population-based, longitudinal RA
inception cohort in the US, and we will extend our cohort to the expanded Rochester Epidemiology Project
catchment area, comprising 27 mixed rural-urban counties in MN and WI (60% rural). This area includes 73 rural
communities where 17 medical facilities have closed in the past 5 years. In addition, we have the only well-
curated database of patients with incident RA, as we manually screen all potential cases of RA to ensure they
meet the American College of Rheumatology/ European Alliance of Associations for Rheumatology
(ACR/EULAR) classification criteria for RA. This is essential for RA research because the diagnostic codes for
RA (especially seronegative RA) are often inaccurate. This research will provide real-world evidence regarding
the magnitude of healthcare disparities in rural residents with RA. Our AI algorithm to facilitate early recognition
of RA will improve clinical practice in three meaningful ways, 1) reducing underdiagnosis of RA in rural primary
care settings, 2) facilitating timely initiation of anti-rheumatic therapies to reduce joint damage and improve long-
term outcomes, and 3) optimizing referrals to rheumatology specialty care to reduce the impact of the workforce
shortage. This work will be foundational for the development of a pragmatic clinical trial testing implementation
of a clinical decision support tool to reduce disparities in early identification of RA. Furthermore, evaluating long-
term outcomes and identifying patient subgroups with the worst ou...

## Key facts

- **NIH application ID:** 10993850
- **Project number:** 1R01AR084831-01
- **Recipient organization:** MAYO CLINIC ROCHESTER
- **Principal Investigator:** Cynthia S Crowson
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $828,682
- **Award type:** 1
- **Project period:** 2024-09-24 → 2029-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10993850

## Citation

> US National Institutes of Health, RePORTER application 10993850, Population-Based Outcomes Research for Rheumatoid Arthritis: Rural Health Disparities (1R01AR084831-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10993850. Licensed CC0.

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