Objective:To investigate the temporal distribution characteristics of ICU infection incidences in a tertiary TCM hospital,and to predict the law and trend of its occurrence,so as to provide data support for the monitoring of ICU infection in TCM hospital.Methods:The data of nosocomial infection in ICU were collected from January 2019 to February 2024 in a tertiary TCM hospital,ARIMA model was utilized to predict the trend of ICU infection and predict its predicitive effects.Results:The incidence of nosocomial infection in ICU between January 2019 and February 2024 was 2.61%(232/8895)in a tertiary TCM hospital;time series analysis showed that the ICU hospital infection incidence rate fluctuated and had a certain periodicity with an overall decreasing trend.ARIMA(0,1,1)was the optimal prediction model according to the Akaike informativeness criterion(AIC)and Bayesian information criterion(BIC)fitting.After parameter estimation and effectiveness evaluation,the actual values of infection incidence were within the 95%confidence interval of the predicted values,and the model has a good predictive effect.Conclusion:ARIMA can be used to predict the incidence of hospital infection in ICU of a tertiary hospital,and it can show the long-term pattern and trend of the occurrence,which could provide scientific basis for the monitoring of hospital infection.
NETL
NSTL
万方数据
