摘要
目的分析基于自然语言的电子病历识别系统EMRRS识别门急诊病历中与新冠肺炎相关的主要症状指标的准确性,探索其在疾病监测中的应用。方法随机抽取2020年4月1日—4月10日期间在某三甲综合医院门急诊就诊的4 802例患者电子病历,以临床医生判定的指标为金标准,对比EMRRS识别指标和患者自填指标,分别计算EMRRS和患者自填指标的阳性预测值、灵敏度、特异度和Youden指数,并与金标准进行一致性检验。结果 EMRRS的各项评价指标均优于患者自填结果,与金标准高度一致。对于关键的2项指标发热和咳嗽,其灵敏度均超过93%,阳性预测率均超过95%,Kappa值均超过0.94。结论 EMRRS对目标指标的识别与金标准有很高的一致性,可用于新冠肺炎相关症状的识别和监测。
Objective Electronic medical record recognition system(EMRRS)based on natural language was adopted to extract COVID-19 related symptoms from electronic medical record of the outpatients and the emergency patients.The accuracy of Electronic medical record recognition system(EMRRS)was analyzed and compared to explore the application of EMRRS in disease monitoring.Methods The 4802 electronic medical records of the outpatients and the emergency patients were randomly selected from a tertiary comprehensive hospital during April 1st-April 10th,2020.Using the symptoms judged by the clinicians as the gold standard,the EMRRS identification symptoms and the patients'self-reported;symptoms were compared.The positive predictive value,sensitivity,specificity and Youden index of EMRRS and the self-reported symptoms of the patients were calculated and consistency test was conducted with the golden standard.Results All of the evaluation indexes of EMRRS were better than the results of the patients'self-reported,and EMRRS were highly consistent with the gold standard.For the two key indicators,fever and cough,the sensitivities were over 93%,the positive prediction rates were more than 95%,and the Kappa values were more than 0.94.Conclusion EMRRS has high consistency with target gold target and can be used for the identification and monitoring of COVID-19 pneumonia related symptoms.
作者
吴晓云
汤学民
周小明
曹潇潇
郑银雄
WU Xiaoyun;TANG Xuemin;ZHOU Xiaoming;CAO Xiaoxiao;ZHENG Yinxiong(Shenzhen People's Hospital,Shenzhen 518020,Guangdong,China)
出处
《中国卫生信息管理杂志》
2021年第2期258-262,共5页
Chinese Journal of Health Informatics and Management
基金
深圳市科技研发资金自由探索项目《基于人工智能的全电子病历自动识别系统》(项目编号:JCYJ20180228164327786)。
关键词
自然语言处理
电子病历识别系统
新冠肺炎
疾病监测
naturallanguage processing
electronic medical record recognition system,COVID-19
disease surveillance