中国全科医学 ›› 2024, Vol. 27 ›› Issue (07): 829-833.DOI: 10.12114/j.issn.1007-9572.2023.0282

所属专题: 儿科最新文章合集

• 论著 • 上一篇    下一篇

供给-需求综合视角下江苏儿科医师队伍紧缺情况研究

季纹舟1, 黄龙毅2, 徐爱军3,*(), 赵霞1,*()   

  1. 1.210023 江苏省南京市,南京中医药大学第一临床医学院
    2.210023 江苏省南京市,南京中医药大学卫生经济管理学院
    3.210023 江苏省南京市,南京中医药大学护理学院
  • 收稿日期:2023-05-15 修回日期:2023-07-11 出版日期:2024-03-05 发布日期:2023-12-19
  • 通讯作者: 徐爱军, 赵霞

  • 作者贡献:季纹舟负责资料的整理、数据分析,负责论文的撰写;黄龙毅协助进行数据分析;徐爱军负责数据的收集;赵霞提出研究思路,负责论文的修订、质量控制,对论文整体负责。
  • 基金资助:
    国家社会科学基金资助项目(2018VJX065); 江苏省教育厅哲学社会科学重点研究基地基金资助(JKFXFK-001)

Analysis of the Shortage of Pediatrician Workforce in Jiangsu from the Integrated Perspective of Supply and Demand

JI Wenzhou1, HUANG Longyi2, XU Aijun3,*(), ZHAO Xia1,*()   

  1. 1. The First Clinical Medical College of Nanjing University of Chinese Medicine, Nanjing 210023, China
    2. School of Health Economic and Management, Nanjing University of Chinese Medicine, Nanjing 210023, China
    3. School of Nursing, Nanjing University of Chinese Medicine, Nanjing 210023, China
  • Received:2023-05-15 Revised:2023-07-11 Published:2024-03-05 Online:2023-12-19
  • Contact: XU Aijun, ZHAO Xia

摘要: 背景 基于儿童群体的特殊性及近几年生育政策的调整,儿科医师队伍建设越来越重要,但当前儿科医师紧缺且研究多为定性研究,定量研究较缺乏。 目的 建立多角度需求预测模型,综合分析江苏儿科医生队伍紧缺情况,为推动江苏省"十四五"时期儿童健康事业发展,加快建设新时代儿科队伍提供参考。 方法 根据《2018年江苏省卫生服务调查分析报告》获得2018年江苏省儿科医疗服务相关指标,利用《2019年江苏省统计年鉴》和从江苏省卫生统计信息中心数据库中获取江苏省各市儿科的基本情况,运用SPSS 24.0分析软件,从供给-需求两个视角建立多角度需求预测模型,对江苏省儿科医师紧缺数量进行综合分析。 结果 江苏省儿科医师队伍女性医师占比较高;年龄以中青年为主;学历以本科为主;职称结构较为合理;工作年限大部分在20年以上。结合江苏儿科医师队伍基本情况并综合供给-需求视角,江苏省儿科医师紧缺数在1.83万人,13个设区市平均紧缺医师数为0.15万人。 结论 儿科诊疗资源供不应求,医师工作负荷较高;儿科医师队伍的性别和职称结构失衡;特殊的执业环境导致执业风险增加。需加强人才培养及引进政策,夯实人才专业基础,探索"互联网+医联体"管理新模式。

关键词: 儿童, 儿科医师, 供给需求, 人才紧缺, 预测模型, 江苏省

Abstract:

Background

Based on the particularity of children and the adjustment of birth policy in recent years, the development of pediatrician team is becoming more and more important. However, most of the current studies on the shortage of pediatricians are qualitative, lacking of quantitative researches.

Objective

To establish a multi-perspective demand forecasting model, comprehensively analyze the shortage of pediatricians in Jiangsu, and provide reference for promoting the development of children's health during the "14th Five-Year Plan" period in Jiangsu Province and accelerating the construction of pediatrician team in the new era.

Methods

According to the relevant indicators of pediatric medical services in Jiangsu Province in 2018 obtained from "2018 Jiangsu Provincial Health Service Survey and Analysis Report", and the basic data of pediatrics in each city of Jiangsu Province was obtained from "2019 Jiangsu Provincial Statistical Yearbook" and the database of the Jiangsu Provincial Health Statistics Information Center. Using SPSS 24.0 analysis software, a multi-perspective demand forecasting model was developed from the perspectives of supply and demand, and a comprehensive analysis of the number of pediatrician shortage in Jiangsu Province was performed.

Results

The proportion of female physicians in the pediatrician team in Jiangsu is relatively high. The young and middle pediatricians occupy a leading position. The academic backgrounds of the pediatricians are mainly undergraduate. The professional title structure is much reasonable. Most of pediatricians have been working for over 20 years. Combined with the basic situation of the pediatrician team in Jiangsu and the perspective of supply and demand, the shortage number of pediatricians in Jiangsu Province was 18 300 and the average shortage number of physicians in 13 cities was 1 500.

Conclusion

There is an overdemand of resources for pediatric care and a high workload for physicians with an imbalance in the gender and title structure of the workforce; the special practice environment leads to increased practice risk. It is necessary to strengthen the personnel training and introduction policies, consolidate the professional foundation of personnel, and explore a new management model of "Internet + medical consortium".

Key words: Children, Pediatricians, Supply and demand, Short supply talents, Predictive model, Jiangsu