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Injury Epidemiology

, 2:11

First Online: 01 June 2015Received: 06 March 2015Accepted: 12 May 2015DOI: 10.1186-s40621-015-0044-5

Cite this article as: Seil, K., Marcum, J., Lall, R. et al. Inj. Epidemiol. 2015 2: 11. doi:10.1186-s40621-015-0044-5


BackgroundThe New York City emergency department ED syndromic surveillance SS system provides near real-time data on the majority of ED visits. The utility of ED SS for injury surveillance has not been thoroughly evaluated. We created injury syndromes based on ED chief complaint information and evaluated their utility compared to administrative billing data.

MethodsSix injury syndromes were developed: traffic-related injuries to pedal cyclists, pedestrians, and motor vehicle occupants; fall-related injuries; firearm-related injuries; and assault-related stabbings. Daily injury counts were compared for ED SS and the administrative billing data for years 2008–2010. We examined characteristics of injury trends and patterns between the two systems, calculating descriptive statistics for temporal patterns and Pearson correlation coefficients r for temporal trends. We also calculated proportions of demographic and geospatial patterns for both systems.

ResultsAlthough daily volume of the injuries varied between the two systems, the temporal patterns were similar all r values for daily volume exceeded 0.65. Comparisons of injuries by time of day, day of week, and quarter of year demonstrated high agreement between the two systems—the majority had an absolute percentage point difference of 2.0 or less. Distributions of injury by sex and age group also aligned well. Distribution of injury by neighborhood of residence showed mixed results—some neighborhood comparisons showed a high level of agreement between systems, while others were less successful.

ConclusionsAs evidenced by the strong positive correlation coefficients and the small absolute percentage point differences in our comparisons, we conclude that ED SS captures temporal trends and patterns of injury-related ED visits effectively. The system could be used to identify changes in injury patterns, allowing for situational awareness during emergencies, timely response, and public messaging.

KeywordsPublic health surveillance Epidemiology Wounds and injuries Emergency service, hospital AbbreviationsDOHMHDepartment of Health and Mental Hygiene

E-codeexternal cause of injury code

EDEmergency department

ICD-9-CMInternational Classification of Diseases, Ninth Revision, Clinical Modification

NYCNew York City

PRXPerl regular expression

SPARCSStatewide Planning and Research Cooperative System

SSsyndromic surveillance

Electronic supplementary materialThe online version of this article doi:10.1186-s40621-015-0044-5 contains supplementary material, which is available to authorized users.

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Autor: Kacie Seil - Jennifer Marcum - Ramona Lall - Catherine Stayton

Fuente: https://link.springer.com/

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