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Research on Predicting the Number of Outpatient Visits

  • Hang Lu
  • Yi Feng
  • Zhaoxia Zhu
  • Liu Yang
  • Yuezhong Xu
  • Yingjia Jiang
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 269)

Abstract

Objective To build prediction model and provide data for the management and policy-making of the hospital by analyzing the data of outpatient visits by time series analysis. Methods The prediction model was built by regression equation and elimination method to perform value prediction and interval prediction about the future trend of outpatient visits. Standard value was calculated according to staff distribution. Results The change of the number of outpatient visits was closely related to seasonality. Error rate of outpatient visits prediction was less than 5 % except that the rate was about 10 % in 2003 and 2006. Actual number of every year was within the scope of prediction interval. The prediction value of 2013 was 549856 (497739, 601974), an increase of 7.22 % compared with that of 2012 (512852). Standard values of 2013 were 887680 and 543120, increasing by 73.09 and 5.90 % respectively compared with that of 2012 (512852). Conclusion Based on the prediction, we can rationally allocate resources, guide the management of outpatient departments, increase the number of outpatient visits and improve the efficiency of outpatient service.

Keywords

Time series analysis Season index Regression equation and elimination method 

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Hang Lu
    • 1
  • Yi Feng
    • 1
  • Zhaoxia Zhu
    • 1
  • Liu Yang
    • 1
  • Yuezhong Xu
    • 1
  • Yingjia Jiang
    • 1
  1. 1.Sichuan Provincial Hospital for Women and ChildrenChengduChina

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