title: [Construction and application of an ARIMA model for predicting the number of outpatient visits in general hospitals].
abstract: OBJECTIVE
  To investigate the variation patterns of the number of outpatient visits in hospitals to provide references for more effective management of general hospitals.
  
  
  METHODS
  The forecasting model of ARIMA(1,0,1)(0,1,1)12 was established using residual error analysis and least squares method according to the sequence stability, long-term trend and seasonal effect after logarithm transformation and differencing.
  
  
  RESULTS
  The residual sum of squares was 2.790, AIC=-178.126, SBC=-170.080. The relative predictive error of the model for predicting the outpatient visits in a general hospital in the year 2008 was 6.11%, smaller than that of exponential smoothing (8.78%). This model predicted a number of outpatient visits of 1,501,200 in this hospital in the year 2009.
  
  
  CONCLUSIONS
  The ARIMA model provides a means for predicting the number of total outpatient visits, its long-term tendency and seasonal variation. The parameters p,d,q in the ARIMA model may vary between different hospitals, and the ACF and PACF charts of the original sequences are helpful for determining these parameters.
authors.affiliation: Department Medical Statistics, School of Public Health and Tropical Medicine, Southern Medical University, Guangzhou 510515, China. xiangq2008@126.com
authors.forename: Qian
authors.initials: Q
authors.lastname: Xiang
authors.forename: Ping-yan
authors.initials: PY
authors.lastname: Chen
mesh_terms: D002681:China; D005544:Forecasting; D006801:Humans; D015233:Models, Statistical; D010044:Outpatient Clinics, Hospital / Q000706:statistics & numerical data*; D010045:Outpatients / Q000706:statistics & numerical data*; D010359:Patient Readmission / Q000706:statistics & numerical data*; D012621:Seasons