title: Dispatcher recognition of stroke using the National Academy Medical Priority Dispatch System.
abstract: OBJECTIVE
  Emergency medical dispatchers play an important role in optimizing stroke care if they are able to accurately identify calls regarding acute cerebrovascular disease. This study was undertaken to assess the diagnostic accuracy of the current national protocol guiding dispatcher questioning of 911 callers to identify stroke (QA Guide version 11.1 of the National Academy Medical Priority Dispatch System).
  
  
  METHODS
  We identified all Los Angeles Fire Department paramedic transports of patients to University of California Los Angeles Medical Center during the 12-month period from January to December 2005 in a prospectively maintained database. Dispatcher-assigned Medical Priority Dispatch System codes for each of these patient transports were abstracted from the paramedic run sheets and compared to final hospital discharge diagnosis.
  
  
  RESULTS
  Among 3474 transported patients, 96 (2.8%) had a final diagnosis of stroke or transient ischemic attack. Dispatchers assigned a code of potential stroke to 44.8% of patients with a final discharge diagnosis of stroke or TIA. Dispatcher identification of stroke showed a sensitivity of 0.41, specificity of 0.96, positive predictive value of 0.45, and negative predictive value of 0.95.
  
  
  CONCLUSIONS
  Dispatcher recognition of stroke calls using the widely employed Medical Priority Dispatch System algorithm is suboptimal, with failure to identify more than half of stroke patients as likely stroke. Revisions to the current national dispatcher structured interview and symptom identification algorithm for stroke may facilitate more accurate recognition of stroke by emergency medical dispatchers.
authors.affiliation: University of California at Los Angeles Stroke Center, Department of Neurology, UCLA Medical Center, Los Angeles, CA, USA. brianhbuck@gmail.com
authors.forename: Brian H
authors.initials: BH
authors.lastname: Buck
authors.forename: Sidney
authors.initials: S
authors.lastname: Starkman
authors.forename: Marc
authors.initials: M
authors.lastname: Eckstein
authors.forename: Chelsea S
authors.initials: CS
authors.lastname: Kidwell
authors.forename: Jill
authors.initials: J
authors.lastname: Haines
authors.forename: Rainy
authors.initials: R
authors.lastname: Huang
authors.forename: Daniel
authors.initials: D
authors.lastname: Colby
authors.forename: Jeffrey L
authors.initials: JL
authors.lastname: Saver
mesh_terms: D000465:Algorithms; D000488:Allied Health Personnel; D015331:Cohort Studies; D003627:Data Interpretation, Statistical; D004632:Emergency Medical Services; D004634:Emergency Medical Technicians; D006801:Humans; D002546:Ischemic Attack, Transient / Q000175:diagnosis / Q000453:epidemiology; D015141:Los Angeles / Q000453:epidemiology; D020521:Stroke / Q000175:diagnosis* / Q000453:epidemiology