OBJECTIVE: To strengthen application management of antibiotics in outpatients, promote rational use of antibiotics, and to provide reference for scientific management and decision-making in the hospital. METHODS: The proportion of outpatients receiving antibiotics in total outpatients was analyzed statistically during Jan. 2008-Jun. 2016. Utilization rate data of antibiotics in outpatients during 2008-2015 were used to establish Autoregressive integrated moving average model(ARIMA), and the data of the first half of 2016 was used to validate established model; the utilization rate trend of antibiotics in outpatients in the second half of 2016 was predicted. SPSS 20.0 statistical software was adopted for statistical analysis. RESULTS: Established ARIMA (2,1,0) (2,1,0) 12 model has higher fitting degree. There was a small difference between measured value and fitted value of utilization rate of antibiotics in outpatients in 2016. Average absolute error was 0.72%, and average relative error was 4.20%, within 95% confidence interval of fitted value. Dynamic trend of model predicted value was basically consistent with measured value. CONCLUSIONS: ARIMA model simulates utilization rate trend of antibiotics in outpatients well, can be used for short-term prediction and dynamic analysis of utilization rate trend of antibiotics. However, for long-term prediction, various factors should be considered.
关键词
抗菌药物时间序列自回归移动平均模型预测
Keywords
AntibioticsTime seriesAutoregressive integrated moving average modelPrediction