title: Electronic medical record (EMR) utilization for public health surveillance.
abstract: BACKGROUND
  Public health surveillance systems need to be refined. We intend to use a generic approach for early identification of patients with severe influenza-like illness (ILI) by calculating a score that estimates a patients disease-severity. Accordingly, we built the Intelligent Severity Score Estimation Model (ISSEM), structured so that the inference process would reflect experts decision-making logic. Each patients disease-severity score is calculated from numbers of respiratory ICD9 encounters, and laboratory, radiologic, and prescription-therapeutic orders in the EMR. Other ISSEM components include chronic disease evidence, probability of immunodeficiency, and the providers general practice-behavior patterns.
  
  
  RESULTS
  Sensitivity was determined from 200 randomly selected patients with upper- and lower-respiratory tract ILI; specificity, from 300 randomly selected patients with URI only. For different age groups, ISSEM sensitivity ranged between 90% and 95%; specificity was 72% to 84%.
  
  
  CONCLUSIONS
  Our preliminary assessment of ISSEM performance demonstrated 93.5% sensitivity and 77.3% specificity across all age groups.
authors.affiliation: Johns Hopkins University Applied Physics Laboratory, Laurel, MD, USA.
authors.forename: Zaruhi R
authors.initials: ZR
authors.lastname: Mnatsakanyan
authors.forename: Daniel J
authors.initials: DJ
authors.lastname: Mollura
authors.forename: John R
authors.initials: JR
authors.lastname: Ticehurst
authors.forename: Mohammad R
authors.initials: MR
authors.lastname: Hashemian
authors.forename: Lang M
authors.initials: LM
authors.lastname: Hung
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D020000:Decision Support Systems, Clinical / Q000458:organization & administration*; D006801:Humans; D007251:Influenza, Human / Q000145:classification / Q000175:diagnosis*; D008396:Maryland; D016347:Medical Records Systems, Computerized; D009323:Natural Language Processing; D010363:Pattern Recognition, Automated / Q000379:methods*; D011159:Population Surveillance / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012720:Severity of Illness Index