周亮, 李泽, 贺丽, 周邦富, 张治刚, 胡坤鹏, 唐硕, 张平. 重大地震灾害救援中医疗急救力量的部署需求分析[J]. 职业卫生与应急救援, 2022, 40(6): 721-726. DOI: 10.16369/j.oher.issn.1007-1326.2022.06.019
引用本文: 周亮, 李泽, 贺丽, 周邦富, 张治刚, 胡坤鹏, 唐硕, 张平. 重大地震灾害救援中医疗急救力量的部署需求分析[J]. 职业卫生与应急救援, 2022, 40(6): 721-726. DOI: 10.16369/j.oher.issn.1007-1326.2022.06.019
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ZHOU Liang, LI Ze, HE Li, ZHOU Bangfu, ZHANG Zhigang, HU Kunpeng, TANG Shuo, ZHANG Ping. Analysis of deployment needs of medical emergency force in rescue of severe earthquake disaster[J]. Occupational Health and Emergency Rescue, 2022, 40(6): 721-726. DOI: 10.16369/j.oher.issn.1007-1326.2022.06.019
Citation: ZHOU Liang, LI Ze, HE Li, ZHOU Bangfu, ZHANG Zhigang, HU Kunpeng, TANG Shuo, ZHANG Ping. Analysis of deployment needs of medical emergency force in rescue of severe earthquake disaster[J]. Occupational Health and Emergency Rescue, 2022, 40(6): 721-726. DOI: 10.16369/j.oher.issn.1007-1326.2022.06.019
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重大地震灾害救援中医疗急救力量的部署需求分析

Analysis of deployment needs of medical emergency force in rescue of severe earthquake disaster

    摘要
  • 摘要:
      目的  通过建立重大地震灾害救援中医疗急救力量的部署需求模型，在灾害救援初期灾情信息缺失的条件下，提供合理的人员抽组和力量编成策略，进而提升重大灾害应急医疗救援效率。
      方法  基于中国知网(CNKI)数据库中收录的相关文献，采用文本信息挖掘算法获取“地震灾害救援”与“医疗急救力量”之间的关联系数，构建医疗急救力量部署的各级指标，利用层次分析法建立各级指标的判断矩阵；通过计算指标间的综合权重，建立力量部署需求度的量化评估模型。
      结果  构建了医疗急救力量部署的3个一级指标和9个二级指标及其权重，具体如下: (1) 现场急救(权重40.54%)，其二级指标: 伤员搜寻(权重27.14%)，检伤分类(权重9.84%)，紧急处理(权重3.57%)；(2) 早期救治(权重11.40%)，其二级指标: 现场手术(权重8.86%)，医技保障(权重1.27%)，医疗留治(权重1.27%)；(3) 医疗后送(权重48.06%)，其二级指标: 急救车辆(权重11.66%)，直升机救援(权重32.17%)，卫生列车(权重4.23%)。
      结论  直升机救援、伤员搜寻和急救车辆是重大地震灾害救援中医疗急救力量部署的重要组成。基于文献数据库的信息挖掘研究，有助于发现灾害救援与力量部署之间的关联强度，为进一步构建重大地震灾害救援过程中医疗急救力量体系与能力生成，提供了数据支撑和参考依据。

     

    Abstract:
      Objective  To provide a reasonable strategy for personnel selection and force compilation under the condition of lack of disaster information in the early rescue stage of disaster, by establishing the need model for the deployment of medical emergency forces in rescue of severe major earthquake disaster, so that the efficiency of medical rescue in severe disasters can be improved.
      Methods  The text information mining algorithm was adopted to obtain the correlation coefficient of"earthquake disaster rescue" and"medical emergency force" based on the relevant literatures included in the National Knowledge Infrastructure (CNKI)database to establish indicators at all levels for the deployment of medical emergency forces. The analytic hierarchy process was used to establish the judgment matrix under the indexes at all levels and finally the comprehensive weight between the indicators was obtained through calculation and applied in the quantitative evaluation model of force deployment needs.
      Results  Three first level indicators and nine second level indicators and their weights of medical emergency force deployment were constructed, namely (1) On site first aid (weight 40.54%), with second level indicators including wounded search(weight 27.14%), injury classification(weight 9.84%), emergency treatment(weight 3.57%); (2) Early treatment(weight 11.40%), with secondary indicators including on -site surgery (weight 8.86%), medical technology support(weight 1.27%), medical retention(weight 1.27%); (3)Medical evacuation(weight 48.06%), with secondary indicators including emergency vehicles (weight 11.66%), helicopter rescue (weight 32.17%), and health trains (weight 4.23%).
      Conclusions  Helicopter rescue, wounded search and emergency vehicles are the important components of the deployment of medical emergency forces for severe earthquake disaster rescue. This development of the research based on the information mining research of the literature database could help find the correlation strength between disaster rescue and force deployment, so the data support and reference can be provided for further construction of the medical emergency force system and capacity generation in the process of severe earthquake disaster rescue, and a good practical application value is embodied.

     

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