中国全科医学 ›› 2024, Vol. 27 ›› Issue (07): 849-856.DOI: 10.12114/j.issn.1007-9572.2023.0413

• 论著 • 上一篇    下一篇

基于DEA-GIS方法的我国农村医疗卫生资源配置效率及公平性研究

高点1, 史卢少博1, 林锦慧1, 王兴民2, 王冬1,*()   

  1. 1.510515 广东省广州市,南方医科大学卫生管理学院
    2.510515 广东省广州市,南方医科大学公共卫生学院
  • 收稿日期:2023-06-14 修回日期:2023-09-11 出版日期:2024-03-05 发布日期:2023-12-19
  • 通讯作者: 王冬

  • 作者贡献:高点负责构思与设计、数据收集与整理、统计学处理、结果的分析与解释、论文撰写;史卢少博、林锦慧负责文章修订,监督管理;王兴民负责文献/资料/图表整理;王冬负责研究的实施和可行性分析、文章的质量控制及审校,对文章整体负责。
  • 基金资助:
    2023年广东省科技创新战略专项资金(pdjh2023b0115); 广州市人文社会科学重点研究基地:广州市公共卫生服务体系建设研究基地(2021—2023年)

Research on the Efficiency and Equity of Rural Medical and Health Resources Allocation in China Based on DEA-GIS Methodology

GAO Dian1, SHI Lushaobo1, LIN Jinhui1, WANG Xingmin2, WANG Dong1,*()   

  1. 1. School of Health Management, Southern Medical University, Guangzhou 510515, China
    2. School of Public Health, Southern Medical University, Guangzhou 510515, China
  • Received:2023-06-14 Revised:2023-09-11 Published:2024-03-05 Online:2023-12-19
  • Contact: WANG Dong

摘要: 背景 "强基层"是我国医改重心之一,研究我国农村医疗卫生资源配置的效率及公平性对推动基层医疗卫生服务有序发展具有重要意义,但目前罕有基于数据包络分析-地理信息系统(DEA-GIS)方法兼具公平和效率研究的相关文献。 目的 分析2020年我国29个省份农村医疗卫生资源配置的效率及公平性,为优化我国农村医疗卫生资源配置和完善乡村医疗卫生服务体系提供参考。 方法 本研究数据来源于《中华人民共和国行政区划统计表》《2021中国卫生健康统计年鉴》。综合现有文献研究、数据可得性及征得专家咨询意见,选取我国29个省份(不含北京市、上海市和港澳台地区)的乡镇卫生院和村卫生室作为研究对象,以乡镇卫生院和村卫生室机构数(以下简称卫生机构数)、乡镇卫生院床位数(以下简称床位数)、乡镇卫生院和村卫生室卫生技术人员数(以下简称卫生技术人员数)作为投入指标;乡镇卫生院和村卫生室诊疗人次数(以下简称诊疗数)、乡镇卫生院入院数(以下简称入院数)作为产出指标。运用DEA模型评估我国农村医疗卫生资源配置效率,利用卫生资源集聚度和GIS技术将农村医疗卫生资源配置情况进行空间制图,分析其公平性。 结果 2020年我国农村医疗卫生资源有4个省份DEA有效、7个省份DEA弱有效、18个省无效。其中,DEA无效地区均存在不同程度的投入过剩现象,仅山东省和西藏自治区存在产出不足的问题。分区域分析结果显示,农村医疗卫生资源集中分布在东部地区,中部地区次之,西部地区集聚度最低。 结论 政府需重视提升农村医疗卫生资源配置的技术效率,通过优化投入产出结构、减少资源冗余,合理统筹东中西部的资源配置,对各地区精准施策促进公平和效率。

关键词: 卫生资源, 乡村卫生服务, 医疗卫生资源, 健康不平等, 资源配置, 数据包络分析法, 地理信息系统

Abstract:

Background

"Strengthening primary health care" is one of the focuses of China's health care reform, and the study of the efficiency and equity of rural medical and health resources allocation in China is of great significance in promoting the orderly development of primary health care services, but at present, there are few relevant literature based on the DEA-GIS methodology with both equity and efficiency.

Objective

To analyze the efficiency and equity of rural medical and health resources allocation in 29 provinces in China in 2020, in order to provide a reference for optimizing the allocation of rural medical and health resources and improving the rural medical and health service system in China.

Methods

The data for this study were collected from the Statistical Tables of Administrative Divisions of the People's Republic of China, the 2021 China Health Statistical Yearbook. After synthesizing the existing literature research, data availability and soliciting expert advice, the township hospitals and village clinics in 29 provinces in China (excluding Beijing, Shanghai, Hong Kong, Macao and Taiwan) were selected as the study objects, and the number of township hospitals and village clinics (hereinafter referred to as the number of health institutions) , the number of beds in township hospitals (hereinafter referred to as the number of beds) , and the number of health technicians in township hospitals and village clinics (hereinafter referred to as the number of health technicians) were used as input indicators; the number of consultations in township hospitals and village clinics (hereinafter referred to as the number of consultations) , and the number of hospital admissions to township hospitals (hereinafter referred to as the number of admissions) were used as output indicators. The data envelopment analysis (DEA) model was used to assess the efficiency of rural medical and health resources allocation in China, and the health resource agglomeration degree and geographic information system (GIS) technology were used to spatially map the rural medical and health resources allocation to analyze its equity.

Results

In 2020, China's rural medical and health resources had 4 provinces with effective DEA, 7 provinces with weakly effective DEA, and 18 provinces with ineffective DEA. Among them, the DEA ineffective regions all had different degrees of excess inputs, and only Shandong Province and Tibet Autonomous Region had insufficient outputs. The results of regional analysis showed that rural medical and health resources were concentrated in the eastern region, followed by the central region, with the lowest degree of concentration in the western region.

Conclusion

The government needs to pay attention to improving the technical efficiency of rural medical and health resources allocation, and promote equity and efficiency by applying precise measures to each region based on optimizing the input and output structure, reducing resource redundancy, rationally coordinating the allocation of resources in the eastern, central and western regions.

Key words: Health resources, Rural health services, Medical and health resource, Health inequities, Resource allocation, Data envelopment analysis, Geographic information system