BACKGROUND: Many infectious disease outbreaks, including those caused by intentional attacks, may first present insidiously as ill-defined syndromes or unexplained deaths. While there is no substitute for the astute healthcare provider or laboratorian alerting the health department of unusual patient presentations, suspicious patterns may be apparent at the community level well before patient-level data raise an alarm. METHODS: Through centralized Department of Defense medical information systems, diagnoses based on International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes are obtained daily from 99 military emergency rooms and primary care clinics across the Washington, DC, region. Similar codes are grouped together in seven diagnostic clusters that represent related presenting signs, symptoms, and diagnoses. Daily monitoring of the data is conducted and evaluated for variation from comparable historic patterns for all seven syndrome groups. Geospatial mapping and trend analysis are performed using geographic information systems software. Data were received on a daily basis beginning in December 1999 and collection continues. The data cut-off date for this manuscript was January 2002. RESULTS: Demographic breakdown of military beneficiaries covered by the surveillance area reveals a broad age, gender, and geographic distribution that is generalizable to the Washington DC region. Ongoing surveillance for the previous 2 years demonstrates expected fluctuations for day-of-the-week and seasonal variations. Detection of several natural disease outbreaks are discussed as well as an analysis of retrospective data from the Centers for Disease Control and Prevention's sentinel physicians-surveillance network during the influenza season that revealed a significantly similar curve to the percentage of patients coded with a respiratory illness in this new surveillance system. DISCUSSION: We believe that this surveillance system can provide early detection of disease outbreaks such as influenza and possibly intentional acts. Early detection should enable officials to quickly focus limited public health resources, decrease subsequent mortality, and improve risk communication. The system is simple, flexible, and, perhaps most critical, acceptable to providers in that it puts no additional requirements on them.
BACKGROUND: Many infectious disease outbreaks, including those caused by intentional attacks, may first present insidiously as ill-defined syndromes or unexplained deaths. While there is no substitute for the astute healthcare provider or laboratorian alerting the health department of unusual patient presentations, suspicious patterns may be apparent at the community level well before patient-level data raise an alarm. METHODS: Through centralized Department of Defense medical information systems, diagnoses based on International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes are obtained daily from 99 military emergency rooms and primary care clinics across the Washington, DC, region. Similar codes are grouped together in seven diagnostic clusters that represent related presenting signs, symptoms, and diagnoses. Daily monitoring of the data is conducted and evaluated for variation from comparable historic patterns for all seven syndrome groups. Geospatial mapping and trend analysis are performed using geographic information systems software. Data were received on a daily basis beginning in December 1999 and collection continues. The data cut-off date for this manuscript was January 2002. RESULTS: Demographic breakdown of military beneficiaries covered by the surveillance area reveals a broad age, gender, and geographic distribution that is generalizable to the Washington DC region. Ongoing surveillance for the previous 2 years demonstrates expected fluctuations for day-of-the-week and seasonal variations. Detection of several natural disease outbreaks are discussed as well as an analysis of retrospective data from the Centers for Disease Control and Prevention's sentinel physicians-surveillance network during the influenza season that revealed a significantly similar curve to the percentage of patients coded with a respiratory illness in this new surveillance system. DISCUSSION: We believe that this surveillance system can provide early detection of disease outbreaks such as influenza and possibly intentional acts. Early detection should enable officials to quickly focus limited public health resources, decrease subsequent mortality, and improve risk communication. The system is simple, flexible, and, perhaps most critical, acceptable to providers in that it puts no additional requirements on them.
Authors: Michael M Wagner; J Michael Robinson; Fu-Chiang Tsui; Jeremy U Espino; William R Hogan Journal: J Am Med Inform Assoc Date: 2003-06-04 Impact factor: 4.497
Authors: Per H Gesteland; Reed M Gardner; Fu-Chiang Tsui; Jeremy U Espino; Robert T Rolfs; Brent C James; Wendy W Chapman; Andrew W Moore; Michael M Wagner Journal: J Am Med Inform Assoc Date: 2003-08-04 Impact factor: 4.497
Authors: Julie A Pavlin; Farzad Mostashari; Mark G Kortepeter; Noreen A Hynes; Rashid A Chotani; Yves B Mikol; Margaret A K Ryan; James S Neville; Donald T Gantz; James V Writer; Jared E Florance; Randall C Culpepper; Fred M Henretig; Patrick W Kelley Journal: Am J Public Health Date: 2003-08 Impact factor: 9.308
Authors: Victoria L Edge; Frank Pollari; Gillian Lim; Jeff Aramini; Paul Sockett; S Wayne Martin; Jeff Wilson; Andrea Ellis Journal: Can J Public Health Date: 2004 Nov-Dec
Authors: D L Cooper; N Q Verlander; G E Smith; A Charlett; E Gerard; L Willocks; S O'Brien Journal: Epidemiol Infect Date: 2006-02 Impact factor: 2.451
Authors: Ben Y Reis; Chaim Kirby; Lucy E Hadden; Karen Olson; Andrew J McMurry; James B Daniel; Kenneth D Mandl Journal: J Am Med Inform Assoc Date: 2007-06-28 Impact factor: 4.497