# Improving Cardiovascular Drug Safety With Automated Bleeding Classification

> **NIH NIH K08** · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · 2020 · $163,080

## Abstract

PROJECT SUMMARY
Atrial fibrillation (AF) treatment often includes drug therapy with oral anticoagulants (OAC) to prevent stroke.
Bleeding, however, is a common complication of these drugs, affecting up to one in four patients. The Center
for Medicare and Medicaid Services recently prioritized OAC-related drug safety as a key quality measure.
Currently, however, no method exists to accurately identify bleeding events and severity in large populations.
Prior methods use diagnoses codes, which lack sensitivity and clinical detail, or manual chart review, which
cannot be implemented in large populations. The proposed research aims address this knowledge gap by
applying a natural language processing (NLP)-based approach to identify bleeding events and classify severity
in a real-world AF population. The tools will be validated in patients treated at a different institution, to ensure
reproducibility across provider settings. In addition, we will apply the bleeding classification tool to evaluate the
association between bleeding severity and mortality. Dr. Shah is an emerging young investigator whose career
development plan is focused on acquiring the biomedical informatics skills to needed to accurately identify and
reduce patient harm. Her training plan focuses on learning core competencies in natural language processing,
with the goal of turning the wealth of data in the electronic medical record into useable knowledge. She will
combine mentorship from established experts and targeted coursework to acquire skills in biomedical
informatics, data science, advanced analytic methods, and research leadership. Completion of these research
and training aims will create a platform for future R01 proposals by: (i) enabling safety focused comparative
effectiveness research in AF (ii) setting the stage to identify bleeding complications in other cardiovascular
diseases and (iii) developing a skill set that allows leadership of a multidisciplinary research team. Through this
career development plan, Dr. Shah will build upon her prior training in clinical cardiology and research
methodology and lay a strong foundation for a high impact research career.

## Key facts

- **NIH application ID:** 9899862
- **Project number:** 5K08HL136850-04
- **Recipient organization:** UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH
- **Principal Investigator:** Rashmee U. Shah
- **Activity code:** K08 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $163,080
- **Award type:** 5
- **Project period:** 2017-04-01 → 2021-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9899862

## Citation

> US National Institutes of Health, RePORTER application 9899862, Improving Cardiovascular Drug Safety With Automated Bleeding Classification (5K08HL136850-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9899862. Licensed CC0.

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