Literature DB >> 15717390

Field investigations of emergency department syndromic surveillance signals--New York City.

Linda Steiner-Sichel1, J Greenko, R Heffernan, M Layton, D Weiss.   

Abstract

INTRODUCTION: The New York City (NYC) Department of Health and Mental Hygiene (DOHMH) has operated a syndromic surveillance system based on emergency department (ED) chief-complaint data since November 2001. This system was created for early detection of infectious-disease outbreaks, either natural or intentional. However, limited documentation exists regarding epidemiologic field investigations conducted in response to syndromic surveillance signals.
OBJECTIVE: DOHMH conducted field investigations to characterize syndromic surveillance signals by person, place, and time and to determine whether signals represented true infectious-disease outbreaks.
METHODS: A DOHMH physician reviews ED-based syndromic surveillance results daily to look for signals. When necessary, field investigations are conducted and consist of a review of the patient line list, telephone interviews with hospital staff, chart reviews, interviews with patients, and collection and testing of specimens.
RESULTS: In November 2002, a series of citywide signals for diarrhea and vomiting syndromes, which coincided with institutional outbreaks consistent with viral gastroenteritis, prompted DOHMH to send mass e-mail notification to NYC ED directors and institute collection of stool specimens. Three of four specimens collected were positive for norovirus. In December 2002, DOHMH investigated why an ED syndromic signal was not generated after 15 ill patients were transferred to a participating ED during a gastrointestinal outbreak at a nursing home. Field investigation revealed varying chief complaints, multiple dates of ED visits, and a coding error in a complementary DOHMH syndromic system, and confirmed a seasonal norovirus outbreak. During March 2003, the system generated a 4-day citywide respiratory signal and a simultaneous 1-day hospital-level fever signal in a predominantly Asian community. In those instances, epidemiologic investigation provided reassurance that severe acute respiratory syndrome was not present.
CONCLUSION: Detailed field investigations of syndromic signals can identify the etiology of signals and determine why a given syndromic surveillance system failed to detect an outbreak captured through traditional surveillance. Validation of the utility of syndromic surveillance to detect infectious-disease outbreaks is necessary to justify allocating resources for this new public health tool.

Entities:  

Mesh:

Year:  2004        PMID: 15717390

Source DB:  PubMed          Journal:  MMWR Suppl        ISSN: 2380-8942


  9 in total

1.  Evaluating real-time syndromic surveillance signals from ambulatory care data in four states.

Authors:  W Katherine Yih; Swati Deshpande; Candace Fuller; Dawn Heisey-Grove; John Hsu; Benjamin A Kruskal; Martin Kulldorff; Michael Leach; James Nordin; Jessie Patton-Levine; Ella Puga; Edward Sherwood; Irene Shui; Richard Platt
Journal:  Public Health Rep       Date:  2010 Jan-Feb       Impact factor: 2.792

Review 2.  Review of syndromic surveillance: implications for waterborne disease detection.

Authors:  Magdalena Berger; Rita Shiau; June M Weintraub
Journal:  J Epidemiol Community Health       Date:  2006-06       Impact factor: 3.710

3.  A multi-data source surveillance system to detect a bioterrorism attack during the G8 Summit in Scotland.

Authors:  N Meyer; J McMenamin; C Robertson; M Donaghy; G Allardice; D Cooper
Journal:  Epidemiol Infect       Date:  2007-08-03       Impact factor: 2.451

4.  Detecting Suicide-Related Emergency Department Visits Among Adults Using the District of Columbia Syndromic Surveillance System.

Authors:  S Janet Kuramoto-Crawford; Erica L Spies; John Davies-Cole
Journal:  Public Health Rep       Date:  2017 Jul/Aug       Impact factor: 2.792

5.  Suitability of bovine portion condemnations at provincially-inspected abattoirs in Ontario Canada for food animal syndromic surveillance.

Authors:  Gillian D Alton; David L Pearl; Ken G Bateman; W Bruce McNab; Olaf Berke
Journal:  BMC Vet Res       Date:  2012-06-22       Impact factor: 2.741

6.  A concept for routine emergency-care data-based syndromic surveillance in Europe.

Authors:  A Ziemann; N Rosenkötter; L Garcia-Castrillo Riesgo; S Schrell; B Kauhl; G Vergeiner; M Fischer; F K Lippert; A Krämer; H Brand; T Krafft
Journal:  Epidemiol Infect       Date:  2014-01-24       Impact factor: 4.434

7.  Tracking the spatial diffusion of influenza and norovirus using telehealth data: a spatiotemporal analysis of syndromic data.

Authors:  Duncan L Cooper; Gillian E Smith; Martyn Regan; Shirley Large; Peter P Groenewegen
Journal:  BMC Med       Date:  2008-06-26       Impact factor: 8.775

Review 8.  Syndromic surveillance: two decades experience of sustainable systems - its people not just data!

Authors:  Gillian E Smith; Alex J Elliot; Iain Lake; Obaghe Edeghere; Roger Morbey; Mike Catchpole; David L Heymann; Jeremy Hawker; Sue Ibbotson; Brian McCloskey; Richard Pebody
Journal:  Epidemiol Infect       Date:  2019-01       Impact factor: 2.451

Review 9.  The initial hospital response to an epidemic.

Authors:  Nicola Petrosillo; Vincenzo Puro; Antonino Di Caro; Giuseppe Ippolito
Journal:  Arch Med Res       Date:  2005 Nov-Dec       Impact factor: 2.235

  9 in total

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