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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

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

  •   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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