Hostname: page-component-7c8c6479df-94d59 Total loading time: 0 Render date: 2024-03-27T22:52:51.523Z Has data issue: false hasContentIssue false

Framework for the Development of Response Protocols for Public Health Syndromic Surveillance Systems: Case Studies of 8 US States

Published online by Cambridge University Press:  08 April 2013

Abstract

Objectives: To describe current syndromic surveillance system response protocols in health departments from 8 diverse states in the United States and to develop a framework for health departments to use as a guide in initial design and/or enhancement of response protocols.

Methods: Case study design that incorporated in-depth interviews with health department staff, textual analysis of response plans, and a Delphi survey of syndromic surveillance response experts.

Results: All 8 states and 30 of the 33 eligible health departments agreed to participate (91% response rate). Fewer than half (48%) of surveyed health departments had a written response protocol, and health departments reported conducting in-depth investigations on fewer than 15% of syndromic surveillance alerts. A convened panel of experts identified 32 essential elements for inclusion in public health protocols for response to syndromic surveillance system alerts.

Conclusions: Because of the lack of guidance, limited resources for development of response protocols, and few examples of syndromic surveillance detecting previously unknown events of public health significance, health departments have not prioritized the development and refinement of response protocols. Systems alone, however, are not effective without an organized public health response. The framework proposed here can guide health departments in creating protocols that will be standardized, tested, and relevant given their goals with such systems. (Disaster Med Public Health Preparedness. 2009;3(Suppl 1):S29–S36)

Type
Original Research and Critical Analysis
Copyright
Copyright © Society for Disaster Medicine and Public Health, Inc. 2009

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

1.Bravata, D, McDonald, K, Smith, W, et alSystematic review: surveillance systems for early detection of bioterrorism-related diseases. Ann Intern Med. 2004;140:910922.Google Scholar
2.Uscher-Pines, L, Farrell, C, Cattani, J, et alA survey of usage and response protocols of syndromic surveillance systems by state public health departments in the United States. Adv Dis Surveill. 2008;5:132.Google Scholar
3.BioSense. http://www.cdc.gov/BioSense. Accessed May 20, 2008.Google Scholar
4.Buehler, J, Sonricker, A, Paladini, M, et alSyndromic surveillance practice in the United States: findings from a survey of state, territorial, and selected local health departments. Adv Dis Surveill. 2008;6:120.Google Scholar
5.Buckeridge, D.Outbreak detection through automated surveillance: a review of the determinants of detection. J Biomed Inform. 2007;40:370379.CrossRefGoogle ScholarPubMed
6.Hurt-Mullen, K, Coberly, J.Syndromic surveillance on the epidemiologist’s desktop. MMWR Morb Mortal Wkly Rep. 2005;54:141146.Google ScholarPubMed
7.Duchin, J.Epidemiological response to syndromic surveillance signals. J Urban Health. 2003;80 Suppl 1i115i116.CrossRefGoogle ScholarPubMed
8.Pavlin, J.Investigation of disease outbreaks detected by “syndromic” surveillance systems. J Urban Health. 2003;80 Suppl 1i107i114.Google Scholar
9.Steiner-Sichel, L, Greenko, J, Heffernan, R, et alField investigations of emergency department syndromic surveillance signals—New York City. MMWR Morb Mortal Wkly Rep. 2004;53:184189.Google Scholar
10.Terry, W, Ostrowsky, B, Huang, A.Should we be worried? Investigation of signals generated by an electronic syndromic surveillance system—Westchester County, New York. MMWR Morb Mortal Wkly Rep. 2004;53:190195.Google ScholarPubMed
11.Sokolow, L, Grady, N, Rolka, H, et alDeciphering data anomalies in BioSense. MMWR Morb Mortal Wkly Rep. 2005;54:133139.Google Scholar
12.Mostashari, F, Hartman, J.Syndromic surveillance: a local perspective. J Urban Health. 2003;80 Suppl 1i1i7.Google Scholar
13.Eban, K.Biosense or biononsense? Scientist. 2007;21:3238.Google Scholar
14.Bravata, D, McDonald, K, Owens, D, et alRegionalization of Bioterrorism Preparedness and Response. Evidence Report/Technology Assessment No 96. Rockville, MD: Agency for Healthcare Research and Quality; 2004.Google Scholar
15.Homeland Security Programs. http://www.ojp.usdoj.gov/odp/grants_programs.htm#fy2007hsgp. Accessed April 11, 2008.Google Scholar
16.Hasson, F, Keeney, S, McKenna, H.Research guidelines for the Delphi survey technique. J Adv Nurs. 2000;32:10081015.Google Scholar
17.Marshall, M, Lockwood, A, Lewis, S, et alEssential elements of an early intervention service for psychosis: the opinions of expert clinicians. BMC Psychiatry. 2004;4:17.Google Scholar
18.Buehler, J, Hopkins, R, Overhage, J, et alFramework for evaluating public health surveillance systems for early detection of outbreaks: recommendations from the CDC Working Group. MMWR Recomm Rep. 2004;53 RR-5111.Google ScholarPubMed
19.The Federal Response to Hurricane Katrina: Lessons Learned. Washington, DC: The White House; 2006.Google Scholar