# Investigating the documentation of E-cigarette use in the VA EHR

> **NIH NIH R03** · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · 2020 · $76,250

## Abstract

PROJECT SUMMARY
Electronic cigarettes were developed in China in the early 2000s and first introduced to the US market in 2007.
Once established in the US, the product experienced explosive growth, with the number of electronic cigarette
users doubling every year between 2008 and 2012. In 2012, it was estimated that 75% of US adults had heard
of electronic cigarettes, and 8% had tried them. While electronic cigarettes have been studied over the last sev-
eral years, no scientific consensus has emerged regarding either the safety of electronic cigarettes, or their po-
tential as a smoking cessation aid.
With this proposal, we will investigate how electronic cigarette use is documented in the Veterans Association
Electronic Health Record, focusing specifically on the relationship between electronic cigarette use and com-
bustible tobacco use, with the goal of understanding both how electronic cigarette use is documented in the
context of the United States’ only nationwide health system, and how electronic cigarette related information
can be reliably extracted from narrative clinical text using fully automated Natural Language Processing meth-
ods.

## Key facts

- **NIH application ID:** 9852435
- **Project number:** 5R03DA047577-02
- **Recipient organization:** UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH
- **Principal Investigator:** Michael Ambrose Conway
- **Activity code:** R03 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $76,250
- **Award type:** 5
- **Project period:** 2019-02-01 → 2022-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9852435

## Citation

> US National Institutes of Health, RePORTER application 9852435, Investigating the documentation of E-cigarette use in the VA EHR (5R03DA047577-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9852435. Licensed CC0.

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