scholarly journals Utility of a near real-time emergency department syndromic surveillance system to track injuries in New York City

2015 ◽  
Vol 2 (1) ◽  
Author(s):  
Kacie Seil ◽  
Jennifer Marcum ◽  
Ramona Lall ◽  
Catherine Stayton
2019 ◽  
Vol 14 (1) ◽  
pp. 44-48
Author(s):  
Priscilla W. Wong ◽  
Hilary B. Parton

ABSTRACTObjective:Syndromic surveillance has been useful for routine surveillance on a variety of health outcomes and for informing situational awareness during public health emergencies. Following the landfall of Hurricane Maria in 2017, the New York City (NYC) Department of Health and Mental Hygiene (DOHMH) implemented an enhanced syndromic surveillance system to characterize related emergency department (ED) visits.Methods:ED visits with any mention of specific key words (“Puerto,” “Rico,” “hurricane,” “Maria”) in the ED chief complaint or Puerto Rico patient home Zip Code were identified from the DOHMH syndromic surveillance system in the 8-week window leading up to and following landfall. Visit volume comparisons pre- and post-Hurricane Maria were performed using Fisher’s exact test.Results:Analyses identified an overall increase in NYC ED utilization relating to Puerto Rico following Hurricane Maria landfall. In particular, there was a small but significant increase in visits involving a medication refill or essential medical equipment. Visits for other outcomes, such as mental illness, also increased, but the differences were not statistically significant.Conclusions:Gaining this situational awareness of medical service use was informative following Hurricane Maria, and, following any natural disaster, the same surveillance methods could be easily established to aid an effective emergency response.


Author(s):  
Robert Mathes ◽  
Jessica Sell ◽  
Anthony W. Tam ◽  
Alison Levin-Rector ◽  
Ramona Lall

The New York City (NYC) syndromic surveillance system has been monitoring syndromes from city emergency department (ED) visits since 2001. We conducted an evaluation of statistical aberration detection methods currently in use in our system as well as alternative methods, applying six temporal and four spatio-temporal aberration detection methods to two years of ED visits in NYC spiked with synthetic outbreaks. We found performance varied between the methods in regard to sensitivity, specificity, and timeliness, and implementation of these methods will depend on needs, frequency of signals, and technical skill.


2012 ◽  
Vol 127 (2) ◽  
pp. 195-201 ◽  
Author(s):  
Brooke Bregman ◽  
Sally Slavinski

Objectives. Most animal bites in the United States are due to dogs, with approximately 4.7 million reports per year. Surveillance for dog and other animal bites requires a substantial investment of time and resources, and underreporting is common. We described the use and findings of electronic hospital emergency department (ED) chief complaint data to characterize patients and summarize trends in people treated for dog and other animal bites in New York City (NYC) EDs between 2003 and 2006. Methods. Retrospective data were obtained from the syndromic surveillance system at the NYC Department of Health and Mental Hygiene. We used a statistical program to identify chief complaint free-text fields as one of four categories of animal bites. We evaluated descriptive statistics and univariate associations on the available demographic data. The findings were also compared with data collected through the existing passive reporting animal bite surveillance system. Results. During the study period, more than 6,000 animal bite patient visits were recorded per year. The proportion of visits for animal bites did not appear to change over time. Dog bites accounted for more than 70% and cat bites accounted for 13% of animal bite patient visits. Demographic characteristics of patients were similar to those identified in NYC's passive surveillance system. Conclusions. Our findings suggest that the use of ED data offers a simple, less resource-intensive, and sustainable way of conducting animal bite surveillance and a novel use of syndromic surveillance data. However, it cannot replace traditional surveillance used to manage individual patients for potential rabies exposures.


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