The unbalanced distribution of medical resources restricts the improvement of primary medical service capabilities. Traditional strategies for allocating resources to lower-level facilities lack precise spatial analysis and intelligent decision support. This study constructs a model for allocating medical resources to lower-level facilities that integrates GIS spatial analysis technology and multi-agent simulation modeling. Taking Jinan City as the research area, kernel density analysis is adopted to identify the spatial agglomeration characteristics of medical resources, and network accessibility evaluation is applied to quantify the differences in service coverage. A multi-agent simulation system is established to simulate the process of resource allocation to lower-level facilities, and a GIS-agent coupling framework is designed to achieve in-depth integration. Experimental results show that this integrated model significantly improves the precision of allocated resources to lower-level facilities and enhances the coverage of primary medical services, providing effective technical support for the targeted allocation of medical resources.

Lin Zhenrong. Research on a Model for Allocating Medical Resources to Lower-Level Facilities by Integrating GIS and Multi-Agent Systems. Frontiers in Medical Science Research (2025), Vol. 7, Issue 6: 79-84. https://doi.org/10.25236/FMSR.2025.070609.

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