基于组合预测模型的人均卫生费用预测研究

Predictive analysis of per capita health expenditure based on combined forecasting model

目的:探讨组合预测模型在我国人均卫生费用预测中的可行性,并预测我国人均卫生费用的发展趋势。方法:收集2000—2009年我国人均卫生费用数据,拟合多个单项模型构建组合预测模型,并对各模型的拟合程度及预测效果进行比较分析。结果:与灰色预测模型、二次指数平滑模型、二次回归模型相比,组合预测模型的平均绝对误差(MAE)、均方误差(MSE)、平均绝对百分比误差(MAPE)均最小,分别为46.800 0、26.697 7、0.023 1;组合预测结果提示2015—2020年我国人均卫生费用增长趋势明显。结论:组合预测模型效果最佳,可作为预测我国人均卫生费用发展趋势的有效工具。费用增长速度较快,卫生部门应采取相关措施合理控制人均卫生费用的增长。

Objective： To explore the feasibility of combined forecasting model in predicting per capita health expenditure and to forecast the development trend of per capita health expenditure in China. Methods： Multiple single prediction models were combined into a new model based on the data of per capita health expenditure in China from 2000 to 2009 and the results were compared and analyzed. Results： Compared with the grey model, quadric exponential smoothing model and quadratic regression model, the mean absolute error（ MAE ）, the mean square error（ MSE ） and the mean absolute percentage error（ MAPE ） of the combined forecasting model were all the minimum, which were 46.800 O, 26.697 7 and 0.023 1, respectively. Results of the combination forecasting model indieated a sustained growth trend of per eapita health expenditure from 2015 to 2020. Conclusiou： The combination forecasting model is superior to any one of the single forecasting models and it can be used as an effective tool to predict per capita health expenditure. The growth of per capita health expenditure is rapid and it is suggested that the health departments control the growth rate.