# Using Medicare Claims to Advance Our Understanding of Guillain-Barre Syndrome

> **NIH NIH R21** · UNIV OF NORTH CAROLINA CHAPEL HILL · 2021 · $427,625

## Abstract

PROJECT SUMMARY
Guillain-Barré Syndrome (GBS) is a rare autoimmune disorder (annual incidence 0.4 – 3.3 cases per 100,000)
in which an infection or other stimulus causes the body's immune system to mistakenly attack the peripheral
nerves, resulting in muscle weakness, paresthesias, respiratory failure, and paralysis. With existing treatments,
including intravenous immunoglobulin and plasmapheresis, most individuals experience a significant degree of
recovery over weeks, months, or years. However, up to 14% of GBS patients remain permanently disabled and
the 1-year mortality rate is estimated to range from 3 – 20%. The rarity of GBS makes it hard to study. Most of
the literature is based on case reports and small samples, which limit generalizability and yield imprecise
estimates. Consequently, much remains unknown about GBS risk factors and disparities in GBS testing,
treatment, and outcomes across patient subgroups. In this context, clinicians confronted with an evolving case
of GBS must make decisions and develop prognoses in the absence of robust population-based data. Thus,
there is considerable value in leveraging large-scale administrative data to further our understanding of GBS.
We will use electronic health records matched to Medicare claims data to evaluate the accuracy of different
algorithms for identifying GBS in Medicare claims (Aim 1). Then, we will use the preferred algorithm to identify
GBS cases in Medicare claims and follow those individuals longitudinally before and after their GBS diagnosis.
Next, we will fully characterize GBS risk factors in the Medicare population and compare GBS patients to non-
GBS patients using a multivariable regression model to predict the likelihood of GBS onset as a function of
patients' clinical and demographic characteristics (Aim 2). Finally, using multivariable regression analysis, we
will model GBS diagnostic testing, treatment, and outcomes as a function of patients' clinical and demographic
factors, while adjusting for hospital fixed effects to identify disparities across patient subgroups within and
between facilities (Aim 3). The proposed study is innovative because it will be the first to validate an algorithm
to identify true GBS cases in adults using claims data, will generate the largest and most contemporary GBS
cohort in the U.S., and will be the first to use Medicare claims to characterize clinical and demographic risk
factors for GBS onset and identify disparities in GBS care delivery and outcomes. This is significant because it
will further our understanding of which individuals are at greatest risk of developing GBS, which GBS patients
are most likely to face barriers in access to GBS diagnosis and treatment, and which GBS patients are most
likely to experience worse GBS outcomes. We also expect to identify clinical conditions previously unknown to
be associated with GBS onset. Ultimately, our results will provide an important tool for future population health
research focused on...

## Key facts

- **NIH application ID:** 10303232
- **Project number:** 1R21NS119867-01A1
- **Recipient organization:** UNIV OF NORTH CAROLINA CHAPEL HILL
- **Principal Investigator:** Rebecca Traub
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $427,625
- **Award type:** 1
- **Project period:** 2021-09-27 → 2025-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10303232

## Citation

> US National Institutes of Health, RePORTER application 10303232, Using Medicare Claims to Advance Our Understanding of Guillain-Barre Syndrome (1R21NS119867-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10303232. Licensed CC0.

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