Prediction model of children's oral antipyretic drug consumption by autoregressive moving average model
Objective To predict the consumption of oral antipyretic drugs in hospitals by autoregressive integrated moving average(ARIMA)model,and to provide reference for drug supply in hospitals.Methods The monthly consumption of oral antipyretic drugs in the hospital from January 2013 to December 2018 was collected to establish an ARIMA model and predict whether the actual consumption of oral antipyretic drugs from January to December 2019 fit the model.Results The time series of consumption of oral antipyretic drugs from 2013 t0 2018 showed obvious seasonal features,with peaks in January,May-July and December each year.The sequence fit the ARIMA(1,1,1)(1,1,1)12 model well after seasonal decomposition.The relative error between the predicted value and the actual value in other months was less than 20％except for January and December 2019.Conclusion The consumption of oral antipyretic drugs and drug supply could be predicted by the ARIMA model.
autoregressive integrated moving average modeloral antipyretic drug consumptiondrug supply
NETL
NSTL
万方数据
