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利用启发式方法和 GIS 提高伊朗胡齐斯坦省(西南部)农村卫生所的分布

Improving the Distribution of Rural Health Houses Using Elicitation and GIS in Khuzestan Province (the Southwest of Iran).

机构信息

Department of Health Information Technology, Paramedical School, Kermanshah University of Medical Sciences, Kermanshah, Iran.

Social Determinants of Health Research Center, Department of Health Information Technology, School of Allied Medical Sciences, Semnan University of Medical Sciences, Semnan, Iran.

出版信息

Int J Health Policy Manag. 2018 Apr 1;7(4):336-344. doi: 10.15171/ijhpm.2017.101.

DOI:10.15171/ijhpm.2017.101
PMID:29626401
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5949224/
Abstract

BACKGROUND

Rural health houses constitute a major provider of some primary health services in the villages of Iran. Given the challenges of providing health services in rural areas, health houses should be established based on the criteria of health network systems (HNSs). The value of these criteria and their precedence over others have not yet been thoroughly investigated. The present study was conducted to propose a model for improving the distribution of rural health houses in HNSs.

METHODS

The present applied study was conducted in Khuzestan province in the southwest of Iran in 2014-2016. First, the descriptive and spatial data required were collected and entered into ArcGIS after modifications, and the Geodatabase was then created. Based on the criteria of the HNS and according to experts' opinions, the main criteria and the sub-criteria for an optimal site selection were determined. To determine the criteria's coefficient of importance (ie, their weight), the main criteria and the sub-criteria were compared in pairs according to experts' opinions. The results of the pairwise comparisons were entered into Expert Choice and the weight of the main criteria and the sub-criteria were determined using the analytic hierarchy process (AHP). The application layers were then formed in geographic information system (GIS). A model was ultimately proposed in the GIS for the optimal distribution of rural health houses by overlaying the weighting layers and the other layers related to villages and rural health houses.

RESULTS

Based on the experts' opinions, six criteria were determined as the main criteria for an optimal site selection for rural health houses, including welfare infrastructures, population, dispersion, accessibility, corresponding routes, distance to the rural health center and the absence of natural barriers to accessibility. Of the main criteria proposed, the highest weight was given to "population" (0.506). The priorities suggested in the proposed model for establishing rural health houses are presented within five zoning levels -from excellent to very poor.

CONCLUSION

The results of the study showed that the proposed model can help provide a better picture of the distribution of rural health houses. The GIS is recommended to be used as a means of making the HNS more efficient.

摘要

背景

农村卫生所是伊朗农村地区提供部分初级卫生服务的主要机构。鉴于农村地区提供卫生服务的挑战,卫生所的建立应基于卫生网络系统(HNS)的标准。这些标准的价值及其优先顺序尚未得到彻底研究。本研究旨在提出一种改进 HNS 中农村卫生所分布的模型。

方法

本应用研究于 2014 年至 2016 年在伊朗西南部胡齐斯坦省进行。首先,收集并修改后输入 ArcGIS 的描述性和空间数据,并创建地理数据库。然后根据 HNS 的标准,并根据专家意见,确定了最佳选址的主要标准和子标准。为了确定标准的重要性系数(即权重),根据专家意见对主要标准和子标准进行了成对比较。成对比较的结果输入到专家选择中,并使用层次分析法(AHP)确定主要标准和子标准的权重。然后在地理信息系统(GIS)中形成应用层。最后,通过叠加加权层和与村庄和农村卫生所相关的其他层,在 GIS 中提出了农村卫生所最佳分布的模型。

结果

根据专家意见,确定了六个标准作为农村卫生所最佳选址的主要标准,包括福利基础设施、人口、分散度、可达性、相应路线、与农村卫生中心的距离以及可达性的自然障碍。在所提出的主要标准中,“人口”(0.506)的权重最高。在提出的模型中,建立农村卫生所的建议优先级分为五个分区级别-从优秀到非常差。

结论

研究结果表明,所提出的模型可以帮助更好地了解农村卫生所的分布情况。建议使用 GIS 作为提高 HNS 效率的手段。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6da6/5949224/7d05218d97d6/ijhpm-7-336-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6da6/5949224/09ba74bccc71/ijhpm-7-336-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6da6/5949224/786b5cf94509/ijhpm-7-336-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6da6/5949224/0cf8991aa311/ijhpm-7-336-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6da6/5949224/b3ce1685562d/ijhpm-7-336-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6da6/5949224/7d05218d97d6/ijhpm-7-336-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6da6/5949224/09ba74bccc71/ijhpm-7-336-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6da6/5949224/786b5cf94509/ijhpm-7-336-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6da6/5949224/0cf8991aa311/ijhpm-7-336-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6da6/5949224/b3ce1685562d/ijhpm-7-336-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6da6/5949224/7d05218d97d6/ijhpm-7-336-g005.jpg

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