# Characterizing longitudinal post-acute rehabilitation utilization and outcomes during the first year after stroke in Medicare beneficiaries

> **NIH NIH K01** · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · 2024 · $137,970

## Abstract

PROJECT SUMMARY/ABSTRACT
I am seeking a Mentored Research Scientist Development Award (K01) in order to acquire the necessary
training, practical experience, and knowledge to become a leading independent investigator focused on
improving the value of rehabilitation after stroke through an understanding of person and system level
variability. This award will provide the necessary support to achieve my Career Development Aims related to 1)
health services research, 2) the application of machine learning approaches, 3) scientific communication, and
4) leadership and management skills. To achieve these goals, I have assembled a Mentoring Committee
comprised of: Dr. Amit Kumar (primary mentor), a health services researcher and expert in Medicare data; Dr.
Julio Facelli (co-mentor), a biomedical informatician and recognized expert in the application of machine
learning clustering approaches to healthcare data; Dr. Angela Presson (co-mentor), an epidemiologist with
expertise in predictive modeling wit machine learning approaches. I have also created an Advisory Committee
of individuals with expertise in stroke care, rehabilitation, and health services research.
Individuals with stroke experience multiple care transitions from acute hospitals to post-acute settings and
between post-acute settings. Post-acute rehabilitation (PAR) is essential to recovery after stroke, yet many
individuals receive inadequate and interrupted PAR, which contributes to poor continuity of care, inefficient
care, and poor outcomes. To improve PAR utilization, we must transformation our healthcare system to
improve the value of PAR after stroke. However, because past work has only focused on PAR utilization cross
sectionally, we lack the foundational understanding of longitudinal PAR utilization that is needed to reshape
post-acute stroke care. My Scientific Aims directly address this gap and are to: 1A) identify subgroups of
longitudinal PAR utilization patterns during the first year after stroke, 1B) characterize subgroups of PAR
utilization with patient-, facility-, and community-level factors, and 2) determine the predictive strength of PAR
utilization on one-year outcomes after stroke.
The proposed work is significant because it will provide the required understanding of PAR utilization after
stroke that is needed to improve the continuity of care and the value of rehabilitative care. The proposed work
is innovative because it focuses on longitudinal PAR and long-term outcomes, uses cutting edge approaches
to access and analyze Medicare data, and incorporates nationally representative data sources. The expected
outcome will 1) lay the groundwork for subsequent R01 submissions examining the impact of PAR utilization
on functional outcomes and validating models of PAR utilization and outcomes and 2) facilitate my transition to
independence.

## Key facts

- **NIH application ID:** 10936749
- **Project number:** 1K01HD115543-01
- **Recipient organization:** UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH
- **Principal Investigator:** Margaret French
- **Activity code:** K01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $137,970
- **Award type:** 1
- **Project period:** 2024-08-15 → 2029-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10936749

## Citation

> US National Institutes of Health, RePORTER application 10936749, Characterizing longitudinal post-acute rehabilitation utilization and outcomes during the first year after stroke in Medicare beneficiaries (1K01HD115543-01). Retrieved via AI Analytics 2026-06-12 from https://api.ai-analytics.org/grant/nih/10936749. Licensed CC0.

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