Developing & Optimizing a National Bioterrorism Syndromic Surveillance System (SSS)
PI: Trish M. Perl, M.D., M.Sc.
Sponsor: Centers for Disease Control and Prevention (CDC) Early illness detection is essential to minimize morbidity and mortality in the event of a bioterrorist attack. Development of surveillance systems to detect early symptoms of possible bioterrorism (BT) agents has been driven by the urgency of implementing “real-time” programs following the terrorism attacks on the United States in September 2001. Syndromic surveillance systems, based on collection of illness syndromes rather than clinical or laboratory confirmed diseases, largely depend on manual or semi-automated transfer of data from emergency departments (ED) to public health authorities. Monitoring of ambulatory care visits should result in earlier detection of BT events as the mildest, and hence earliest, symptoms would prompt a visit to the ambulatory care provider before illness progression results in an ED visit. Systems that evaluate ambulatory care visits have relied on broadly defined discharge International Classification of Diseases, 9th revision (ICD-9) code groups to define syndromes. Very few of the current systems incorporate patient-specific clinical data, from electronic medical records, such as are available in the Veterans Health Administration (VHA). Syndromic surveillance based on ICD-9 codes alone is unlikely to demonstrate sufficient sensitivity and specificity to serve as a useful real-time system for identifying and responding to potential BT events. However, detection systems that incorporate clinical and laboratory variables may demonstrate significantly improved operating characteristics. Data mining from a computerized patient record system (CPRS) can be automated and may well represent the best avenue toward a robust, cost-effective BT surveillance system. The central hypothesis of this proposal is that modeled syndromes based on ICD-9 codes in combination with selected CPRS parameters are superior to modeled syndromes based on IDC-9 code-only for the early detection of bioterrorism. This is a multi-center study, funded by the CDC and coordinated by Johns Hopkins University. Using influenza as a syndromic model for bioterrorism, representative cases of influenza-like-illness (ILI) will be determined at the Baltimore VA for the 2003-2004 flu season. After a sufficient number of cases have been found, computerized surveillance, looking at symptomatology, pharmacy and lab records, will be set up to retrospectively review patient records for the same time period for ILI. When it is determined that this method will find the previously defined cases and its sensitivity and specificity are within pre-determined tolerances, the outbreak (of documented influenza) will be verified using the surveillance system at the Salt Lake City VA and Kaiser-Permanente. For more information on this study please email Ericka Kalp or contact her at (410) 614-6206. |
