摘要
目的了解医院应对突发重大传染病事件的抗逆力建设,为今后提高其应对能力提供指导。方法设计聚焦网络爬虫获取国家卫健委、中国新闻网、今日头条和搜狗微信网站内有关上海市医院在2020年1月1日至2022年3月1日间的文本数据,编写python程序对纳排后的179条数据进行隐含狄利克雷分布(latent Dirichlet allocation,LDA)主题分析。结果确定LDA主题分析的最佳主题个数为12个,并根据各主题的前10位主题词为主题命名。结论医院需加强科技、科研以及管理等方面的建设,来提升自身对疫情防控能力,对各类资源的应急准备能力,从而确保医疗服务的稳定提供。
Objective To understand the construction of the hospital’s resilience to emergencies of major infectious diseases,and to provide guidance for improving its response capacity in the future.Methods The web crawler was designed to obtain text data of Shanghai hospitals from the National Health Commission,China News,Toutiao and Sogou wechat from January 1,2020 to March 1,2022.The python program was used to analyze 179 items by Latent Dirichlet Allocation(LDA)thematic analysis.Results The number of optimal topics for LDA topic analysis is determined to be 12,and the topics are named according to the first 10 topic words of each topic.Conclusions Hospitals need to strengthen the construction of science and technology,scientific research and management,so as to improve their own“prevention”of the epidemic,“preparedness”in terms of various resources and capabilities,and the“stability”of medical work.
作者
陈汝婕
王毅欣
刘晶晶
桂莉
CHEN Rujie;WANG Yixin;LIU Jingjing;GUI Li(School of Nursing,Naval Medical University,Shanghai 200433,China)
出处
《军事护理》
CSCD
北大核心
2023年第4期60-62,74,共4页
MILITARY NURSING
基金
国家自然科学基金项目(72174205)。
关键词
突发重大传染病事件
医院
抗逆力
网络数据
LDA主题分析
infectious diseases pandemic
hospital
resilience
web data
Latent Dirichlet Allocation thematic analysis
作者简介
陈汝婕,硕士在读,护士,电话:021-81871481;通信作者:桂莉,电话:021-81871481。
