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ISDS 2016 Conference Abstracts

Using Sydromic Surveillance to Track E-cigarette 
Related Emergency Department Visits
Jill K. Baber* and Tracy Miller
Division of Disease Control, North Dakota Department of Health, Bismarck, ND, USA

Objective
To explore the use of emergency department syndromic 

surveillance data to identify adverse health events related to electronic 
cigarettes in order in enhance existing surveillance.

Introduction
The North Dakota Department of Health (NDDoH) investigated 

the feasibility of using syndromic surveillance (SyS) data to identify 
health care visits due to electronic cigarette (e-cigarette) use. 
E-cigarettes have been associated with injuries and fatalities in all 
age groups, including young children attracted to the colorful liquid 
nicotine carriage packaging [1]. Previously, poison control data was 
the only resource available to the NDDoH for e-cigarette adverse 
outcomes surveillance.

Methods
Data for all visits from June 28, 2014 to June 28, 2015 were 

downloaded using the BioSense 2.0 SyS analytic tool. Excel was used 
to identify visits containing key words related to e-cigarettes in line-
level data. We initially searched for visits using variations of the term 
“e-cigarette.” After meeting with NDDoH subject matter experts, we 
expanded our search to include other related terms: nicotine, clouding, 
vaping and variations of “electronic nicotine delivery system 
(ENDS)”. No diagnosis codes were used as none refer specifically to 
e-cigarettes. Visits were identified solely through searching free text 
chief complaint and triage notes fields. Not all facilities participating 
in the NDDoH SyS program during this time period submitted free 
text data.

Results
Out of 650,069 unique visits, four e-cigarette-related visits were 

identified in rich-text data fields searching for “E-cig” and “E cig.” 
An additional visit was identified using the search term “nicotine,” 
although this search primarily identified visits including references 
to nicotine patches. Of the five visits identified, two were poisonings 
resulting from small children sucking on liquid nicotine cartridges, 
one referred to eye irritation as a result of accidentally using liquid 
nicotine as eye drops, and two referred to cardiac issues (chest 
pain, heart palpitations) after e-cigarette use. Searches including 
terms “clouding” and “vaping,” street terms related to e-cigarettes, 
did not result in the identification of any additional visits related to 
e-cigarettes; nor did searches related to ENDS. Poison control data 
from the same time period yielded two calls related to e-cigarette 
adverse events.

Conclusions
It is possible to identify emergency department visits associated 

with e-cigarette use utilizing SyS data. More visits were identified 
using SyS data than poison control data, although neither source 
identified many occurrences of adverse outcomes related to 
e-cigarettes. E-cig, e cig and nicotine were the most useful search 
terms, although a search for “nicotine” must exclude the word “patch” 
to avoid false identifications. The NDDoH receives free-text data for 
a majority of the visits in our system, but not all facilities submit 
free-text fields, and the number that did varied over the study period. 

Because no drop-down chief complaints or diagnosis codes related 
to e-cigarettes exist, data from facilities that did not provide free text 
data were not helpful in identifying e-cigarette-related visits. This 
investigation emphasizes the need for free text fields when using SyS 
to investigate emerging issues.

Keywords
Syndromic Surveillance; Electronic Cigarettes; Injury

References
1. Hua M, Talbot P. Potential Health Effects of Electronic Cigarettes:

A Systematic Review of Case Reports. Prev Med Rep; 2016 Dec;4: 
169-178.

*Jill K. Baber
E-mail: jbaber@nd.gov

Online Journal of Public Health Informatics * ISSN 1947-2579 * http://ojphi.org * 9(1):e144, 2017