XU Wen, FANG Zheng, YANG Lyujun. Research on R language time series and autoregressive integrated moving average model for predication of receiving and use of anesthetic consumables[J]. Journal of Clinical Medicine in Practice, 2021, 25(15): 18-21, 26. DOI: 10.7619/jcmp.20212104
Citation: XU Wen, FANG Zheng, YANG Lyujun. Research on R language time series and autoregressive integrated moving average model for predication of receiving and use of anesthetic consumables[J]. Journal of Clinical Medicine in Practice, 2021, 25(15): 18-21, 26. DOI: 10.7619/jcmp.20212104

Research on R language time series and autoregressive integrated moving average model for predication of receiving and use of anesthetic consumables

  •   Objective  To establish a suitable medical economics model of receiving and use of specialized surgery consumables in the elderly patient in Department of Anesthesiology by using the autoregressive integrated moving average (ARIMA) model, and to predict the changing trend of the consumables demand in Department of Anesthesiology.
      Methods  R software was used to establish the ARIMA model based on the data of consumables acquisition and expenditure of Anesthesiology Department in authors' hospital from January 2013 to December 2019. The actual value and the predicted value of consumables acquisition and expenditure were compared from January to December 2020, and prediction performance of the model was evaluated.
      Results  The consumption expenditure of Anesthesiology Department in authors' hospital was the lowest in February and the highest in May every year. ARIMA(0, 1, 1)(0, 0, 1)12 model was established to predict the consumable demand of Anesthesiology Department, and ARIMA model met and predicted the periodic fluctuation well. ARIMA(0, 1, 1)(0, 0, 1)12 model predicted that the consumption of consumables will fluctuate slightly from January to December in 2020.
      Conclusion  ARIMA(0, 1, 1)(0, 0, 1)12 model can better fit the needs of consumables in Anesthesiology Department, which is helpful to optimize the department decision support system and perioperative nursing management of elderly patients undergoing elective surgery.
  • loading

Catalog

    Turn off MathJax
    Article Contents

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return