# Identifying primary care patients at increased risk of atrial fibrillation for screening interventions

> **NIH NIH K01** · MASSACHUSETTS GENERAL HOSPITAL · 2020 · $177,770

## Abstract

Project Summary/Abstract
Atrial Fibrillation (AF) increases the risk of stroke 5-fold and accounts for roughly 15% of all strokes in the
United States. Many individuals may have undiagnosed AF whose arrhythmia does not prompt evaluation
either because of minimal symptoms or brief episodes. Oral anticoagulation (OAC) is highly effective at
reducing stroke risk in patients with AF, but is only prescribed to individuals with recognized disease.
Identifying subjects with undiagnosed AF is important so they may be treated with OAC and prevent strokes
from occurring. This project will help advance our knowledge of screening patients for undiagnosed AF in the
primary care setting by identifying patients at high risk of developing AF for targeted clinic and home-based
screening strategies. Fundamental questions of who to target and how to implement a screening program in
the United States remain unanswered. To address these gaps in knowledge, the principal investigator (PI)
proposes a career development program that blends rigorous methodologic and content area training with an
innovative research agenda. This plan has three scientific objectives: 1) To identify predictors of AF incidence
from electronic health record structured and free-text data, 2) To develop and implement an electronic
algorithm that improves upon existing models to identify patients at increased risk for AF in a primary care
population, and 3) To implement and evaluate feasibility, acceptability, appropriateness, and usability of a clinic
and home-based screening program to identify undiagnosed AF. This project aligns with several objectives of
the National Heart, Lung, and Blood Institute’s Strategic Vision by implementing novel diagnostic tools to
diagnose AF and prevent strokes, by optimizing clinical and implementation research to improve health and
reduce disease, and leveraging emerging opportunities in data science, through the use of natural language
processing of text data in the electronic health record, to improve identification of patients at high risk for AF.
The long-term goal of this career development award is to establish the PI as an independent researcher with
expertise in cardiovascular disease and targeting populations for prevention of cardiovascular disease events.
Career development activities include training in biomedical informatics, data mining and risk prediction, survey
research design, implementation research, and cardiovascular disease pathophysiology and clinical
management through formal coursework, clinical shadowing, as well as mentorship by an exceptionally
qualified team of senior scientists. Successful completion of this career development proposal will improve
prediction of which patients are at the highest risk of developing AF, and evaluate how to use this risk
information to implement an effective screening strategy in primary care. Pilot data from this award will lay the
groundwork for a highly competitive application for NIH R01 funding.

## Key facts

- **NIH application ID:** 9982695
- **Project number:** 5K01HL148506-02
- **Recipient organization:** MASSACHUSETTS GENERAL HOSPITAL
- **Principal Investigator:** Jeffrey M Ashburner
- **Activity code:** K01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $177,770
- **Award type:** 5
- **Project period:** 2019-08-01 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9982695

## Citation

> US National Institutes of Health, RePORTER application 9982695, Identifying primary care patients at increased risk of atrial fibrillation for screening interventions (5K01HL148506-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9982695. Licensed CC0.

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