title: Improved diagnostic accuracy of group A streptococcal pharyngitis with use of real-time biosurveillance.
abstract: BACKGROUND
  Clinical prediction rules do not incorporate real-time incidence data to adjust estimates of disease risk in symptomatic patients.
  
  
  OBJECTIVE
  To measure the value of integrating local incidence data into a clinical decision rule for diagnosing group A streptococcal (GAS) pharyngitis in patients aged 15 years or older.
  
  
  METHODS
  Retrospective analysis of clinical and biosurveillance predictors of GAS pharyngitis.
  
  
  METHODS
  Large U.S.-based retail health chain.
  
  
  METHODS
  82 062 patient visits for pharyngitis.
  
  
  METHODS
  Accuracy of the Centor score was compared with that of a biosurveillance-responsive score, which was essentially an adjusted Centor score based on real-time GAS pharyngitis information from the 14 days before a patient's visit: the recent local proportion positive (RLPP).
  
  
  RESULTS
  Increased RLPP correlated with the likelihood of GAS pharyngitis (r(2) = 0.79; P < 0.001). Local incidence data enhanced diagnostic models. For example, when the RLPP was greater than 0.30, managing patients with Centor scores of 1 as if the scores were 2 would identify 62, 537 previously missed patients annually while misclassifying 18, 446 patients without GAS pharyngitis. Decreasing the score of patients with Centor values of 3 by 1 point for an RLPP less than 0.20 would spare unnecessary antibiotics for 166, 616 patients while missing 18, 812 true-positive cases.
  
  
  CONCLUSIONS
  Analyses were conducted retrospectively. Real-time regional data on GAS pharyngitis are generally not yet available to clinicians.
  
  
  CONCLUSIONS
  Incorporating live biosurveillance data into clinical guidelines for GAS pharyngitis and other communicable diseases should be considered for reducing missed cases when the contemporaneous incidence is elevated and for sparing unnecessary antibiotics when the contemporaneous incidence is low. Delivering epidemiologic data to the point of care will enable the use of real-time pretest probabilities in medical decision making.
authors.affiliation: Harvard Medical School, Harvard-MIT Health Sciences and Technology, Boston, MA, USA.
authors.forename: Andrew M
authors.initials: AM
authors.lastname: Fine
authors.forename: Victor
authors.initials: V
authors.lastname: Nizet
authors.forename: Kenneth D
authors.initials: KD
authors.lastname: Mandl
mesh_terms: D000293:Adolescent; D000328:Adult; D000900:Anti-Bacterial Agents / Q000627:therapeutic use; D055877:Biosurveillance; D005260:Female; D006801:Humans; D015994:Incidence; D008297:Male; D008875:Middle Aged; D010612:Pharyngitis / Q000175:diagnosis* / Q000188:drug therapy / Q000453:epidemiology; D012189:Retrospective Studies; D013290:Streptococcal Infections / Q000175:diagnosis* / Q000188:drug therapy / Q000453:epidemiology; D013297:Streptococcus pyogenes; D014481:United States / Q000453:epidemiology; D055815:Young Adult
chemical_list: D000900:Anti-Bacterial Agents