OBJECTIVE: To review complaints (such as fever, respiratory symptoms, diarrhea, vomiting, and rashes) in the medical records of outpatients as potential sources of data for syndromic surveillance, and to examine the possibility of practical application from a statistical view point. MATERIALS AND METHODS: Using data obtained from a certain internal and pediatric clinic, we count the number of patients each day who suffered from one of the above five symptoms from January 1st, 2003 to June 30th, 2005. In order to detect outbreaks prospectively after January 1st, 2005, we at first estimate the baseline using the data from January 1st, 2003 to the day before any given day. We then predict the number of patients there ought to be in any given day and judge whether or not an outbreak has occurred. So as to evaluate the system, we check the sensitivity and specificity in its ability to detect outbreaks other than those seen in previous patterns. RESULTS: The total number of cases in which each of the above symptoms occurred were respectively: 11,896 cases of fever, 16,273 cases of respiratory symptoms, 3,672 cases of diarrhea, 3,485 cases of vomiting, and 542 cases of rash. We found prolonged outbreaks of fever and respiratory symptoms in February and March and shorter outbreaks of vomiting and diarrhea in January. The sensitivity and specificity of this system' s ability to detect outbreaks was very high and thus we can confirm that it showed satisfactory performance. DISCUSSION: We found large-scale outbreaks of influenza late in the 2004/2005 season, and small outbreaks of GI that seemed to be particularly related to the Noro virus. In both cases, these outbreaks seemed to be natural phenomena, not artificial, human induced phenomena such as outbreaks caused by bioterrorism attacks. However, since this system was able to detect these outbreaks, we would also be able to use it to detect an outbreak caused by a bioterrorism attack if the size of the outbreak was similar to these cases. CONCLUSION: In order to use this system to detect outbreaks in the community on a smaller level we would have to increase the number of medical institutions cooperating in this study. Moreover, we would need to find a way to handle the different electronic medical record systems and different writing styles used by different medical institutions in order to move toward the practical use of Syndromic Surveillance.
OBJECTIVE: To review complaints (such as fever, respiratory symptoms, diarrhea, vomiting, and rashes) in the medical records of outpatients as potential sources of data for syndromic surveillance, and to examine the possibility of practical application from a statistical view point. MATERIALS AND METHODS: Using data obtained from a certain internal and pediatric clinic, we count the number of patients each day who suffered from one of the above five symptoms from January 1st, 2003 to June 30th, 2005. In order to detect outbreaks prospectively after January 1st, 2005, we at first estimate the baseline using the data from January 1st, 2003 to the day before any given day. We then predict the number of patients there ought to be in any given day and judge whether or not an outbreak has occurred. So as to evaluate the system, we check the sensitivity and specificity in its ability to detect outbreaks other than those seen in previous patterns. RESULTS: The total number of cases in which each of the above symptoms occurred were respectively: 11,896 cases of fever, 16,273 cases of respiratory symptoms, 3,672 cases of diarrhea, 3,485 cases of vomiting, and 542 cases of rash. We found prolonged outbreaks of fever and respiratory symptoms in February and March and shorter outbreaks of vomiting and diarrhea in January. The sensitivity and specificity of this system' s ability to detect outbreaks was very high and thus we can confirm that it showed satisfactory performance. DISCUSSION: We found large-scale outbreaks of influenza late in the 2004/2005 season, and small outbreaks of GI that seemed to be particularly related to the Noro virus. In both cases, these outbreaks seemed to be natural phenomena, not artificial, human induced phenomena such as outbreaks caused by bioterrorism attacks. However, since this system was able to detect these outbreaks, we would also be able to use it to detect an outbreak caused by a bioterrorism attack if the size of the outbreak was similar to these cases. CONCLUSION: In order to use this system to detect outbreaks in the community on a smaller level we would have to increase the number of medical institutions cooperating in this study. Moreover, we would need to find a way to handle the different electronic medical record systems and different writing styles used by different medical institutions in order to move toward the practical use of Syndromic Surveillance.