青藏高原位于我国西部，该地区主要的组成部分西藏自治区与青海省少数民族聚集、自然环境较恶劣，且属于国家层面深度贫困地区“三区三州”的重要组成部分。掌握该地区的医疗资源配置现状，并根据该现状提出针对性的建议有助于实现《“健康中国”2030》规划纲要的相关目标，提升当地居民的生活福祉，巩固脱贫成果。

本文在掌握了各级别医疗设施单位时间内覆盖的人口比例的情况下，深入了解了各乡镇人口密度与人口加权就医时间的关系、就近就医与就地就医的时间差异、医疗设施配置的公平性与效率、医疗设施的空间优化，主要研究内容及结果如下：

（1）综合考虑坡度、高程、土地利用类型等自然地理要素，并根据道路设计速度构建成本栅格。结果表明，西藏自治区与青海省差异明显，青海省西宁市与海东市在所有医疗设施层面均可在3小时内覆盖全部人口，而西藏自治区那曲市与昌都市的三级医院在15分钟内只能覆盖不足10%的人口。

（2）评价西藏自治区与青海省医疗资源指标的结果表明，就卫生技术人员而言，西藏自治区与青海省大多数市级行政单元处于公平性较好的范围，仅有一些医疗资源丰富、内部医疗资源配置差异明显的城市的基尼系数高于总体水平。人口加权就医时间的基尼系数明显高于卫生技术人员的基尼系数，说明地域层面的公平性不如人口层面的公平性，医疗资源的配置是以人口分布为导向的。

（3）以乡/镇/街道为基本单元研究人口与就医时间的耦合关系，发现位于海东市、海北州、海南州的存在大量人口密度较高、就医时间偏长的区域，这些区域由于占其所属市/州比例较低而在可达性结果中未能较好体现，这些区域的基础医疗需求需要得到满足。该结果以更精细尺度评价了医疗可达性，补充了成本栅格结果中未能较好反映的缺少医疗资源的区域。

（4）通过构建综合成本指数与投入产出模型评价医疗资源配置效率，结果表明，远离行政中心、交通不便、自身医疗资源稀缺的县级行政单元的综合成本指数较高，新建医疗设施需要较高的成本，应谨慎布局新的医疗设施。投入产出模型结果表明，全域医疗资源配置的综合效率为0.348，投入产出水平较低，仅有西宁市城西区、城北区；拉萨市城关区实现了医疗资源配置的最优组合。

（5）空间优化结果表明，三级医院与二级医院均需要新建一定数量的医院以满足当地居民的就医需求。西藏自治区需将9家二级医院升级为三级医院，且主要位于昌都市，与可达性结果一致。而在满足当地居民基础医疗需求的二级医院方面，青海省需要新建27家，基本位于人口—就医时间耦合结果中人口密度偏大、就医时间偏长的乡镇。

本文以多个角度评价了西藏自治区与青海的医疗资源空间配置，发现目前该区域医疗资源配置均衡性有待提高，非省会城市的医疗可达性与省会城市差异悬殊，根据空间优化模型筛选出的新建医疗设施位置有助于提升当前该区域医疗可达性。

The Qinghai Tibet Plateau is located in western China, and its main components are the Tibet Autonomous Region and Qinghai Province, where ethnic minorities gather and the natural environment is harsh. It is also an important part of the "three regions and three prefectures" in the deeply impoverished areas at the national level. Mastering the current situation of medical resource allocation in the region and proposing targeted suggestions based on this situation will help to achieve the relevant goals of the "Healthy China" 2030 planning outline, improve the well-being of local residents, and consolidate poverty alleviation achievements.

This article delves into the relationship between population density and population weighted travel time to medical treatment in each township, the time difference between nearby and on-site medical treatment, the equity and efficiency of medical facility allocation, and the spatial optimization of medical facilities, while mastering the proportion of population covered by medical facilities at different levels per unit time. The main research contents and results are as follows:

(1) Physical geography factors such as slope, elevation and land use type are comprehensively considered, and the cost grid is constructed according to the road design speed. The results show that there is a significant difference between the Tibet Autonomous Region and Qinghai Province. Xining City and Haidong City in Qinghai Province can cover the entire population within 3 hours at all levels of medical facilities, while the tertiary hospitals in Nagqu City and Changdu City in the Tibet Autonomous Region can only cover less than 10% of the population within 15 minutes.

(2) The results of evaluating the indicators of medical resources in Tibet Autonomous Region and Qinghai Province indicate that, in terms of health technicians, most municipal administrative units in Tibet Autonomous Region and Qinghai Province are in a relatively fair range, with only some cities with abundant medical resources and significant differences in internal medical resource allocation having Gini coefficients higher than the overall level. The Gini coefficient of population weighted medical treatment time is significantly higher than that of health technicians, indicating that the equity at the regional level is not as good as that at the population level, and the allocation of medical resources is guided by population distribution.

(3) Taking the township/town/street as the basic unit to study the coupling relationship between population and medical treatment time, it is found that there are a large number of areas with high population density and long medical treatment time in Haidong City, Haibei Prefecture and Hainan Prefecture. These areas are not well reflected in the accessibility results due to their low proportion in the city/prefecture they belong to. The basic medical needs of these areas need to be met. This result evaluates the medical accessibility at a more precise scale, and supplements the areas lacking medical resources that are not well reflected in the cost grid results.

(4) By constructing a comprehensive cost index and input-output model to evaluate the efficiency of medical resource allocation, the results show that county-level administrative units far from administrative centers, with inconvenient transportation, and scarce medical resources have a higher comprehensive cost index. New medical facilities require higher costs and should be carefully arranged. The results of the input-output model indicate that the comprehensive efficiency of medical resource allocation in the entire region is 0.348, and the input-output level is relatively low, only in Chengxi District and Chengbei District of Xining City; The Chengguan District of Lhasa City has achieved the optimal combination of medical resource allocation.

(5) The spatial optimization results indicate that both tertiary and secondary hospitals need to build a certain number of hospitals to meet the medical needs of local residents. The Tibet Autonomous Region needs to build 9 new tertiary hospitals, mainly located in Changdu, which is consistent with the accessibility results. In terms of secondary hospitals that meet the basic medical needs of local residents, Qinghai Province needs to build 27 new ones, which are mainly located in townships with high population density and long medical treatment times in the population medical treatment time coupling results.

This paper evaluates the spatial allocation of medical resources in Tibet Autonomous Region and Qinghai from multiple perspectives, and finds that the balance of medical resource allocation in this region needs to be improved. The medical accessibility of non provincial capital cities is significantly different from that of provincial capital cities. The location of new medical facilities selected according to the spatial optimization model is conducive to improving the current medical accessibility in this region.