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Online Journal of Public Health Informatics * ISSN 1947-2579 * http://ojphi.org * 11(1): e267, 2019 

 

ISDS 2019 Conference Abstracts 

Using Syndromic Surveillance to Classify and Capture Non-
Fatal Occupational Injuries and Illnesses 

Marija Borjan, Margaret Lumia 

New Jersey Department of Health, Trenton, New Jersey, United States 

Objective 

To evaluate the use of a real-time surveillance tool to track a variety of occupationally-related emergency room visits through the 
state based syndromic surveillance system, EpiCenter. 

Introduction 

This study uses data from the New Jersey syndromic surveillance system (EpiCenter) as a data source to enhance surveillance of 
current non-fatal occupational injuries, illnesses, and poisonings. EpiCenter was originally developed for early detection and 
monitoring of the health of communities using chief complaints from people seeking acute care in hospital emergency rooms to 
identify health trends. Currently, syndromic surveillance has not been widely applied to identify occupational injuries and il lnesses. 
Incorporating syndromic surveillance data from EpiCenter, along with hospital discharge data, will enhance the classificat ion and 
capture of work-related non-fatal injuries with possible improved efforts at prevention. 

Methods 

EpiCenter Emergency Department data from January to December 2014 was evaluated, using work-related keywords and ICD-9 

codes, to determine its ability to capture non-fatal work-related injuries. A collection of keywords and phrases specific to work-
related injuries was developed by manually assessing the free text chief complaint data field’s. Sensitivity, specificity, an d positive 
predictive value (PPV), along with descriptive statistics was used to evaluate and summarize the occupational injuries identified in 
EpiCenter. 

Results 

Overall, 11,919 (0.3%) possible work-related injuries were identified via EpiCenter. Of these visits 956 (8%) indicated Workman’s 
Compensation as payer. Events that resulted in the greatest number of ED visits were falls, slips, trips (1,679, 14%). Nature  of 
injury included cuts, lacerations (1,041, 9%), burns (255, 2%), and sprains, strains, tears (185, 2). The part of the body most affected 

were the back (1,414, 12%). This work-related classifier achieved a sensitivity of 5.4%, a specificity of 99.8%, and a PPV of 2.8%. 

Conclusions 

Evaluating the ability and performance of a new and existing surveillance data source to capture work-related injuries can lead to 
enhancements in current data collection methods. This evaluation successfully demonstrated that the chief complaint reporting 
system can yield real-time knowledge of incidents and local conditions for use in identifying opportunities for prevention of work-
related injuries. 

Acknowledgement 

This project was funded by NIOSH Cooperative Grant #5U60OH008485-12. The authors would like to thank Stella 

Tsai and Teresa Hamby, NJDOH Communicable Disease Service, Infectious, and Zoonotic Disease Program staff, 

and Kristen Weiss, Health Monitoring. 

 

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