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首页> 外文会议>International Conference on Informatics, Management, and Technology in Healthcare >Using Structured and Unstructured Data to Refine Estimates of Military Sexual Trauma Status Among US Military Veterans
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Using Structured and Unstructured Data to Refine Estimates of Military Sexual Trauma Status Among US Military Veterans

机译：使用结构化和非结构化数据来改进美国军事退伍军人中军事性创伤地位的估计

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Sexual trauma survivors are reluctant to disclose such a history due to stigma. This is likely the case when estimating the prevalence of sexual trauma experienced in the military. The Veterans Health Administration has a program by which all former US military service members (Veterans) are screened for military sexual trauma (MST) using a questionnaire. Administrative data on MST screens and a change of status from an initial negative answer to positive and natural language processing (NLP) on electronic medical notes to extract concepts related to MST were used to refine initial estimates of MST among a random sample of 20,000 Veterans. The initial MST positive screen of 15.4% among women was revised upward to 21.8% using administrative data and further to 24.5% by adding NLP results. The overall estimate of MST status in women and men in this sample was revised from 8.1% to 13.1% using both data elements.
机译：性创伤幸存者不愿意披露由于耻辱而披露这种历史。在估计军队中经历的性创伤患病率时可能是这种情况。退伍军人健康管理局有一个计划，其中所有以前的美国军事服务成员（退伍军人）都会使用调查问卷筛查军事性创伤（MST）。关于MST屏幕的管理数据以及从电子医疗说明的初始负面答案（NLP）的初始消极答案的变化，以提取MST相关的概念，用于改进20,000名退伍军人的随机样本中MST的初始估计。妇女15.4％的初始MST正面筛网使用行政数据向上向上修改为21.8％，并通过添加NLP结果进一步为24.5％。使用两个数据元素的8.1％至13.1％修订了妇女和男性中MST状态的整体估计。

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