The Evolution of BioSense: Lessons Learned and Future Directions

Public Health Reports

Volumn 132, Issue 1, 2017, Pages 7S-11S

  Gould, Deborah W ^a   Walker, David ^a   Yoon, Paula W ^a  

^a CENTERS FOR DISEASE CONTROL AND PREVENTION   (United States)

Author keywords

Biosense; emergency department data; public health surveillance; syndromic surveillance

Indexed keywords

BIOTERRORISM; DEVICES; DISASTER PLANNING; DISEASE OUTBREAKS; HEALTH SURVEY; HUMAN; MEDICAL INFORMATICS; ORGANIZATION AND MANAGEMENT; PREVENTION AND CONTROL; PROCEDURES; PUBLIC HEALTH SERVICE; UNITED STATES;

BIOTERRORISM; CENTERS FOR DISEASE CONTROL AND PREVENTION (U.S.); DISASTER PLANNING; DISEASE OUTBREAKS; HUMANS; PUBLIC HEALTH INFORMATICS; PUBLIC HEALTH SURVEILLANCE; UNITED STATES;

EID: 85026304192     PISSN: 00333549     EISSN: 14682877     Source Type: Journal    
DOI: 10.1177/0033354917706954     Document Type: Article

References (27)

1. Pub L No. 107-188, 116 Stat 594 (2002).
2. Loonsk JW. BioSense: a national initiative for early detection and quantification of public health emergencies. MMWR Morb Mortal Wkly Rep. 2004;53(suppl):53-55.
3. Bradley CA, Rolka H, Walker D, et al. BioSense: implementa-tion of a national early event detection and situational awareness system. MMWR Morb Mortal Wkly Rep. 2005;54(suppl):11-19.
4. Tokars JI, English R, McMurray P, et al. Summary of data reported to CDC’s national automated biosurveillance system, 2008. BMC Med Inform DecisMak. 2010;10:30.
5. Ginsberg M, Johnson J, Tokars J, et al. Monitoring health effects of wildfires using the BioSense system: San Diego County, California, October 2007. MMWR Morb Mortal Wkly Rep. 2008;57(27):741-744.
6. Loonks JW, McGarvey SR, Conn LA, et al. The Public Health Information Network (PHIN) preparedness initiative. JAm Med Inform Assoc. 2006;13(1):1-4.
7. US Department of Homeland Security Digital Library. Hearing of the Subcommittee on Bioterrorism and Public Health Preparedness of the Committee on Health, Education, Labor, and Pensions. https://www.hsdl.org/?view&did=481999. Accessed April 4, 2016.
8. Barlas S. CDC’s BioSense network identifying possible bioter-rorism, but skeptics abound. Emerg Med News. 2007;29(9):17.
9. Buehler JW, Whitney EA, Smith D, et al. Situational uses of syndromic surveillance. Biosecur Bioterror. 2009;7(2): 165-177.
10. US Government Accountability Office. Health information technology: more detailed plans needed for the Centers for Disease Control and Prevention’s redesigned BioSense pro-gram. http://www.gao.gov/new.items/d09100.pdf. Published 2008. Accessed April 16, 2016.
11. US Government Accountability Office. Information technol-ogy: federal agencies face challenges in implementing initia-tives to improve public health infrastructure. http://www.gao. gov/new.items/d05308.pdf. Published 2005. Accessed June 22, 2016.
12. Centers for Disease Control and Prevention. National Syndro-mic Surveillance Program: syndromic surveillance data in action. http://www.cdc.gov/nssp/biosense/action.html. Accessed May 10, 2016.
13. Institute of Medicine. Assessing the Effects of the Gulf of Mex-ico Oil Spill on Human Health: A Summary of the June 2010 Workshop. Washington, DC: National Academies Press; 2010.
14. Centers for Medicare & Medicaid Services. Electronic health records (EHR) incentive programs. https://www.cms.gov/Reg ulations-and-Guidance/Legislation/EHRIncentivePrograms/index.html. Accessed April 28, 2016.
15. Gibson J, Karras BT, Gordon GS. BioSense 2.0 governance: surveying users and stakeholders for continued development. Online J Public Health Inform. 2014;6(1):e19.
16. Westheimer E, Paladini M, Balter S, et al. Evaluating the New York City emergency department syndromic surveillance for monitoring influenza activity during the 2009-10 influenza sea-son. PLoS Curr. 2012;4:e500563f3ea181.
17. Baer A, Elbert Y, Burkom HS, et al. Usefulness of syndromic data sources for investigating morbidity resulting from a severe weather event. Disaster Med Public Health Prep. 2011;5(1): 37-45.
18. Klekamp BG, Bodager D, Matthews SD. Use of surveillance systems in detection of a ciguatera fish poisoning outbreak— Orange County, Florida, 2014. MMWR Morb Mortal Wkly Rep. 2015;64(40):1142-1144.
19. Modarai F, Mack K, Hicks P, et al. Relationship of opioid prescription sales and overdoses, North Carolina. Drug Alcohol Depend. 2013;132(1-2):81-86.
20. Centers for Disease Control and Prevention. The National Syn-dromic Surveillance Program: enhancing syndromic surveillance capacity and practice. http://www.cdc.gov/nssp/foa. html. Accessed May 27, 2016.
21. Richards CL, Iademarco MF, Anderson TC. A new strategy for public health surveillance at CDC: improving national surveillance activities and outcomes. Public Health Rep. 2014;129(6): 472-476.
22. Johns Hopkins University Applied Physics Laboratory. Open-ESSENCE user guide. http://www.jhuapl.edu/sages/guides/OE-User-Guide-Feb-2013.pdf. Published 2013. Accessed June 1, 2016.
23. SAS Institute, Inc. SAS Version 9.4. Cary, NC: SAS Institute, Inc; 2013.
24. RStudio, Inc. RStudio Server. Boston, MA: RStudio, Inc; 2016.
25. International Society for Disease Surveillance. NSSP Data Quality Workgroup. http://www.syndromic.org/cop/nssp/nssp-workgroups/794-bug-data-quality-workgroup. Accessed May 27, 2016.
26. Centers for Disease Control and Prevention. National Syndromic Surveillance Program: community of practice. https://www.cdc.gov/nssp/community.html. Accessed May 27, 2016.
27. International Society for Disease Surveillance. NSSP Syn-drome Definitions Workgroup. http://www.syndromic.org/cop/nssp/nssp-workgroups/797-bug-syndrome-definitions-workgroup. Accessed May 27, 2016.