Pilot surveillance and evaluation of influenza-like illness based on automatic computer analysis of electronic medical record in sentinel hospital
10.3760/cma.j.cn112150-20200225-00186
- VernacularTitle:基于哨点医院电子病历计算机自动识别技术的流感样病例试点监测评价
- Author:
Aiqin ZHU
1
;
Jianhua LIU
;
Chengzhong XU
;
Hao ZHANG
;
Xiaokun YANG
;
Hongting ZHAO
;
Zhili LI
;
Liping WANG
;
Luzhao FENG
;
Yaming ZHENG
;
Ying QIN
;
Zhongjie LI
Author Information
1. 中国疾病预防控制中心传染病监测预警重点实验室 传染病管理处，北京 102206
- Keywords:
Influenza-like illness;
Automatic computer analysis;
Electronic medical record;
Surveillance methodology evaluation
- From:
Chinese Journal of Preventive Medicine
2020;54(6):691-695
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To compare the accuracy of influenza-like illness (ILI) surveillance by automatic computer analysis based on electronic medical records and by doctor’s report.Methods:A total of 3 542 patients who presented to Yichang Central Hospital fever clinic, respiratory department or emergency department between April to October 2019 with an ICD-10 code for acute respiratory illness (J00-J22) and complete electronic medical information of ILI related syndromes were drawn as the study sample. Taking the classification of the study sample according to the ILI case definition by influenza surveillance professionals as the gold standard, draw the receiver operating characteristic (ROC) curve and calculate sensitivity, specificity, diagnostic consistency to compared the accuracy of ILI surveillance by automatic computer analysis and by doctor's report.Results:Median age of 3 542 cases was 30 (24, 38) years old; 1 179 cases (33.29%) compliance with the case definition, ILI reported by doctors was 1 306 cases (36.87%), and computer automatic identification ILI were 1 150 cases (32.47%); 1 391 (39.27%) cases were men. The results of automatic computer analysis and doctor report consistency of kappa values with gold standard judgment were 0.97 and 0.66 respectively; area under the ROC curve was 0.98 and 0.84, respectively. And the sensitivity and specificity of automatic computer analysis were higher than that of doctor's report (all P values were <0.001), the sensitivity was 96.95% and 82.27%, and the specificity was 99.70% and 85.78%, respectively. Conclusion:The automatic computer analysis based on electronic medical records can identified ILI cases with good sensitivity and specificity in ILI case surveillance.
