FANG Yan, SONG Tie, DAI Ji-ya, FU Jun- hua, YI Jian-rong. Feasibility of respiratory syndrome for respiratory diseases surveillance in a hospital[J]. Disease Surveillance, 2009, 24(7): 487-491. DOI: 10.3784/j.issn.1003-9961.2009.07.006
Citation: FANG Yan, SONG Tie, DAI Ji-ya, FU Jun- hua, YI Jian-rong. Feasibility of respiratory syndrome for respiratory diseases surveillance in a hospital[J]. Disease Surveillance, 2009, 24(7): 487-491. DOI: 10.3784/j.issn.1003-9961.2009.07.006

Feasibility of respiratory syndrome for respiratory diseases surveillance in a hospital

  • ObjectiveTo evaluate the feasibility to use respiratory syndrome indicators in respiratory disease surveillance. MethodsThe respiratory syndrome indicators were selected by analyzing the clinical records (in 2005) of outpatient department, inpatient department and X ray detection room in a hospital included in the hospital information system (HIS) in Guangzhou, and the correlation with the case number of influenza like illness (ILI) in Guangzhou and the case number of notifiable respiratory diseases in the hospital in same period was analyzed. ResultsSeven syndromes including pneumonia like illness in outpatient department, 4 syndromes including pneumonia like illness in inpatient department and 4 syndromes in X-ray room including x-ray test rate/positive rate in outpatient department were selected as candidate syndrome indicators. Curves of pneumonia like illness in outpatients closely correlated with ILI curve when it moved 4 weeks backward with the correlation coefficients of 0.558 (Iu/I=2.09,IP/I0.05), but without significant correlation with other times ILI cases. It indicated that the peak of pneumonia like illness was earlier than ILI in outpatient department, which suggested that the diagnosis of pneumonia like illness in outpatient department could indicate influenza epidemic specifically and timely. Curve of pneumonia like illness and asthma like illness in inpatient department, X-ray test rate/positive rate in outpatient department correlated with the curve of ILI in different time periods, which showed that these indicators could predict influenza specifically, but the difference on the correlation coefficients of these indicators with ILI in different period had no statistical significance (IP/I0.05), which indicated that they could not predict influenza epidemic timely. ConclusionIt is feasible to use pneumonia like illness in outpatient department as syndrome indicator for the surveillance of respiratory diseases (e.g. influenza like illness), indicators of pneumonia like illness and asthma like illness in inpatient department, x-ray test, rate/positive rate in outpatient department are less effective.
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