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目的:使用改进的GM(1,1)(Grey Model,一阶灰色理论微分方程型模型)方法快速预测长短期中国卫生总费用,有效缩短预测时间,提高预测可靠性。方法:依据卫生总费用历史数据中年平均增长率的变化,选用GM(1,1)方法从长期趋势预测卫生总费用可能的突变年份及相应总费用值;采用线性回归模型以突变年份为临界点从短期趋势分段预测突变年份间的总费用值。结果:预测结果与年平均增长率、ARIMA模型、快速推算法等方法比较,精度高,更高效便捷。结论:基于改进的GM(1,1)模型的我国卫生总费用预测方法快速、有效、可行。
OBJECTIVE: To rapidly predict the total short and long-term health expenditure in China by using the improved GM (1,1) model (Gray Model, first-order gray theory) and effectively shorten the forecasting time and improve the forecasting reliability. Methods: Based on the change of average annual growth rate of total health expenditure data, GM (1,1) method was used to predict the possible year and the corresponding total cost of total health expenditure from the long-term trend. The linear regression model was adopted to change the year Point to predict the total cost of the year of the mutation from the short-term trend segment. Results: Compared with the average annual growth rate, ARIMA model and rapid estimation method, the prediction result is more accurate, more efficient and more convenient. Conclusion: The prediction method of China’s total health expenditure based on the improved GM (1,1) model is fast, effective and feasible.