Trend Prediction of Antibiotics Utilization Rate in Outpatients by Time Series Model
10.6039/j.issn.1001-0408.2017.23.08
- VernacularTitle:运用时间序列模型预测门诊患者抗菌药物使用率趋势
- Author:
Haihuan LIU
;
Haichen LIU
;
Chenfan WU
;
Fangfang ZHENG
- Keywords:
Antibiotics;
Time series;
Autoregressive integrated moving average model;
Prediction
- From:
China Pharmacy
2017;28(23):3197-3200
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVE:To strengthen application management of antibiotics in outpatients,promote rational use of antibiot-ics,and to provide reference for scientific management and decision-making in the hospital. METHODS:The proportion of outpa-tients receiving antibiotics in total outpatients was analyzed statistically during Jan. 2008-Jun. 2016. Utilization rate data of antibiot-ics 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. CONCLU-SIONS: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.
