地球信息科学学报 ›› 2021, Vol. 23 ›› Issue (4): 604-616.doi: 10.12082/dqxxkx.2021.200489

• 地球信息科学理论与方法 • 上一篇    下一篇

融合地图数据的山地城市医疗设施服务覆盖评估方法研究

廖心治(), 王华, 赵万民*()   

  1. 重庆大学建筑城规学院,重庆 400030
  • 收稿日期:2020-08-26 修回日期:2021-01-04 出版日期:2021-04-25 发布日期:2021-06-25
  • 通讯作者: 赵万民
  • 作者简介:廖心治(1996— ),男,四川眉山人,硕士生,主要从事GIS与城市空间研究。E-mail: 644609584@qq.com
  • 基金资助:
    国家自然科学基金面上项目(51678086);重庆市研究生科研创新项目资助(CYS20028)

Evaluation Method of Medical Facilities Service Coverage in Mountainous Cities based on Map Data

LIAO Xinzhi(), WANG Hua, ZHAO Wanmin*()   

  1. Chongqing university, Faculty of Architecture and Urban Planning, Chongqing 400030, China
  • Received:2020-08-26 Revised:2021-01-04 Online:2021-04-25 Published:2021-06-25
  • Contact: ZHAO Wanmin
  • Supported by:
    National Natural Science Foundation of China(51678086);Project Supported by Graduate Scientific Research and Innovation Foundation of Chongqing, China(CYS20028)

摘要:

随着我国社会经济的不断发展,居民对医疗的需求不断增加,分析评估城市医疗设施服务范围,对解决医疗供需矛盾,提升城市健康水平具有重要意义。目前国内医疗设施服务覆盖评估,多忽视交通网络与人群分布因素,致使城市医疗服务存在不少覆盖盲区。山地城市复杂地形环境影响居民出行能力与出行方式,增大医疗设施服务覆盖的难度,传统方法难以对其准确评估。本文在分析比对现有医疗可达性研究方法优劣势的基础上,以重庆市主城区为实验区,试图针对性地采用优化两步移动搜寻法,并根据网络地图数据、官方统计数据,基于GIS平台建立医疗设施可达性分析模型,从市域、片区与社区3个层级科学评估医疗设施服务覆盖范围与各街镇医疗可达性。结果表明,改进后的方法更能处理海量医疗数据,准确模拟医疗服务范围,并输出全层级医疗设施服务覆盖评估结果,更适用于交通复杂的山地地区与多层级医疗设施服务覆盖评估。综合评估显示,重庆市主城区医疗设施服务存在大型综合医院空间分布不均、基层医疗设施内部覆盖不全的问题,并且医疗覆盖度较好的街镇仅占总数的33.1%。据此,建议老城区集聚的优质大型医疗资源向新城地区共享的同时,按照地理区位与技术能力划分、组建层级完备的医疗片区,补齐老城区基层医疗服务的短板,以期完善重庆主城区医疗设施配置。

关键词: 山地城市, 医疗设施, 可达性, 地图数据, 重庆市主城区, GIS, POI, 两步移动搜寻法

Abstract:

With the continuous development of China's social economy, residents' demand for medical services is increasing. It is of great significance to analyze and evaluate the service scope of urban medical facilities to solve the contradiction between medical supply and demand and improve the level of urban health. At present, the coverage assessment of medical facilities in China mostly ignores the traffic network and population distribution, resulting in many blind areas of urban medical services. The complex terrain environment of mountainous high-density city affects the travel ability and mode of residents, and increases the difficulty of medical facilities service coverage, so it is difficult to accurately evaluate it by traditional methods. Based on the analysis and comparison of the advantages and disadvantages of the existing medical accessibility research methods, taking the main urban area of Chongqing as the experimental area, this paper attempts to adopt the optimized 2SFCA, and according to the network map data and official statistical data, establishes the medical facility accessibility analysis model based on GIS platform, The coverage of medical facilities and medical accessibility of each street and town were scientifically evaluated from three levels of city, district, and community. The results show that the improved method can deal with massive medical data, accurately simulate the scope of medical services, and output the evaluation results of full level medical facility service coverage, which is more suitable for mountainous areas with complex transportation and multi-level medical facility service coverage evaluation. The comprehensive evaluation shows that the medical facilities in the main urban area of Chongqing have the problems of uneven spatial distribution of large general hospitals and incomplete internal coverage of primary medical facilities, and the streets and towns with better medical coverage only account for 33.1% of the total. Therefore, it is suggested that the high-quality large-scale medical resources gathered in the old urban areas should be shared with the new urban areas. At the same time, according to the geographical location and technical ability, medical districts with complete levels should be established to make up for the shortcomings of primary medical services in the old urban areas, to improve the allocation of medical facilities in the main urban areas of Chongqing.

Key words: mountainous city, medical facilities, accessibility, map data, main urban area of Chongqing, GIS, POI, 2SFCA