›› 2018, Vol. 30 ›› Issue (3): 171-178.

• 组织行为与人力资源管理 • 上一篇    下一篇

我国执业(助理)医师需求集成预测——基于GM、ARIMA和VAR模型的实证研究

李蕾1,3, 李超2,4, 丁雪辰1, 乔晗1   

  1. 1. 中国科学院大学经济与管理学院, 北京 100190;
    2. 中国科学院数学与系统科学研究院, 北京 100190;
    3. 清华大学第一附属医院(北京华信医院), 北京 100016;
    4. 中原航空港产业投资基金管理有限公司, 郑州 450019
  • 收稿日期:2017-08-09 出版日期:2018-03-28 发布日期:2018-03-26
  • 通讯作者: 乔晗(通讯作者),中国科学院大学经济与管理学院副教授,博士。
  • 作者简介:李蕾,中国科学院大学经济与管理学院博士研究生;李超,中国科学院数学与系统科学研究院硕士;丁雪辰,中国科学院大学经济与管理学院博士研究生
  • 基金资助:

    国家自然科学基金项目(71373262;71390330;71390331)。

Forecasting of Licensed (Assistant) Doctors' Demand in China——An Empirical Research Based on GM, ARIMA and VAR Models

Li Lei1,3, Li Chao2,4, Ding Xuechen1, Qiao Han1   

  1. 1. School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190;
    2. Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190;
    3. The First Hospital of Tsinghua University(Beijing Huaxin Hospital), Beijing 100016;
    4. Central China Airport Industry Fund Management CO., LTD, Zhengzhou 450019
  • Received:2017-08-09 Online:2018-03-28 Published:2018-03-26

摘要:

医疗卫生人员需求预测对于我国实施《"健康中国2030"规划纲要》、深入推进医药卫生制度改革具有重要的基础意义。本文通过建立GM(1,1)、ARIMA和VAR模型,分别对我国执业(助理)医师需求量进行了建模预测,基于集成方法的思想,将上述三个模型的预测结果进行集成分析,有效地提高了预测精度。集成预测模型的结果显示,2020年我国执业(助理)医师需求量恰与同期发布的《"健康中国2030"规划纲要》的目标吻合,但2030年规划目标值低于居民的需求。鉴于此,本文提出了以"扩大规模、稳定队伍、拓宽渠道、节约利用"为思路的若干政策建议,可供国家相关部门决策参考。

关键词: 执业(助理)医师需求量, GM(1, 1), ARIMA, VAR, 集成预测模型

Abstract:

The demand forecast of medical and health personnel is of great significance for the implementation of the "Healthy China 2030" Plan and is helpful for the promotion of medical and health system reform. We forecast China's licensed (assistant) doctors with GM (1,1), ARIMA and VAR model respectively. Based on a dynamic integration method, this paper integrates the forecast results of three models above, which effectively improve the prediction accuracy. Finally the empirical results show that the demand of licensed (assistant) doctors in 2020 is consistent with the goal set out by the State Council in "Healthy China 2030" Plan, while the planned goal in 2030 is lower than the demand. The research of this paper provides several guidance and management enlightenments to the National Health Department.

Key words: licensed (assistant) doctors' demand, GM (1,1), ARIMA, VAR, integrated forecasting model