Fever detection from free-text clinical records for biosurveillance

被引:41
作者
Chapman, WW [1 ]
Dowling, JN [1 ]
Wagner, MM [1 ]
机构
[1] Univ Pittsburgh, Ctr Biomed Informat, RODS Lab, Pittsburgh, PA 15260 USA
基金
美国医疗保健研究与质量局;
关键词
disease outbreaks; fever; natural language processing; computerized patient medical records; public health surveillance; surveillance; infection control;
D O I
10.1016/j.jbi.2004.03.002
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Automatic detection of cases of febrile illness may have potential for early detection of outbreaks of infectious disease either by identification of anomalous numbers of febrile illness or in concert with other information in diagnosing specific syndromes, such as febrile respiratory syndrome. At most institutions, febrile information is contained only in free-text clinical records. We compared the sensitivity and specificity of three fever detection algorithms for detecting fever from free-text. Keyword CC and CoCo classified patients based on triage chief complaints; Keyword HP classified patients based on dictated emergency department reports. Keyword HP was the most sensitive (sensitivity 0.98, specificity 0.89), and Keyword CC was the most specific (sensitivity 0.61, specificity 1.0). Because chief complaints are available sooner than emergency department reports, we suggest a combined application that classifies patients based on their chief complaint followed by classification based on their emergency department report, once the report becomes available. (C) 2004 Elsevier Inc. All rights reserved.
引用
收藏
页码:120 / 127
页数:8
相关论文
共 38 条
  • [1] Baud RH, 2001, J AM MED INFORM ASSN, P37
  • [2] BRAVATA DM, 2002, BIOTERRORISM INFORMA
  • [3] BRINSFIELD KH, 2001, ACAD EMERG MED, V8, P492
  • [4] Creating a text classifier to detect radiology reports describing mediastinal findings associated with inhalational anthrax and other disorders
    Chapman, WW
    Cooper, GF
    Hanbury, P
    Chapman, BE
    Harrison, LH
    Wagner, MM
    [J]. JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION, 2003, 10 (05) : 494 - 503
  • [5] Chapman WW, 2001, J AM MED INFORM ASSN, P105
  • [6] A simple algorithm for identifying negated findings and diseases in discharge summaries
    Chapman, WW
    Bridewell, W
    Hanbury, P
    Cooper, GF
    Buchanan, BG
    [J]. JOURNAL OF BIOMEDICAL INFORMATICS, 2001, 34 (05) : 301 - 310
  • [7] CHAPMAN WW, 2004, IN PRESS AI MED
  • [8] Predictive model of diagnosing probable cases of severe acute respiratory syndrome in febrile patients with exposure risk
    Chen, SY
    Su, CP
    Ma, MHM
    Chiang, WC
    Hsu, CY
    Ko, PCI
    Tsai, KC
    Yen, ZS
    Shih, FY
    Chen, SC
    Chen, WJ
    [J]. ANNALS OF EMERGENCY MEDICINE, 2004, 43 (01) : 1 - 5
  • [9] CHO PS, 2003, P AMIA ANN FAL S
  • [10] Automatic detection of acute bacterial pneumonia from chest x-ray reports
    Fiszman, M
    Chapman, WW
    Aronsky, D
    Evans, RS
    Haug, PJ
    [J]. JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION, 2000, 7 (06) : 593 - 604