title: Identification of dynamic prehospital changes with continuous vital signs acquisition.
abstract: OBJECTIVE
  In most trauma registries, prehospital trauma data are often missing or unreliable because of the difficult dual task consigned to prehospital providers of recording vital signs and simultaneously resuscitating patients. The purpose of this study was to test the hypothesis that the analysis of continuous vital signs acquired automatically, without prehospital provider input, improves vital signs data quality, captures more extreme values that might be missed with conventional human data recording, and changes Trauma Injury Severity Scores compared with retrospectively compiled prehospital trauma registry data.
  
  
  METHODS
  A statewide vital signs collection network in 6 medevac helicopters was deployed for prehospital vital signs acquisition using a locally built vital signs data recorder (VSDR) to capture continuous vital signs from the patient monitor onto a memory card. VSDR vital signs data were assessed by 3 raters, and intraclass correlation coefficients were calculated to test interrater reliability. Agreement between VSDR and trauma registry data was compared with the methods of Altman and Bland including corresponding calculations for precision and bias.
  
  
  RESULTS
  Automated prehospital continuous VSDR data were collected in 177 patients. There was good agreement between the first recorded vital signs from the VSDR and the trauma registry value. Significant differences were observed between the highest and lowest heart rate, systolic blood pressure, and pulse oximeter from the VSDR and the trauma registry data (P< .001). Trauma Injury Severity Scores changed in 12 patients (7%) when using data from the VSDR.
  
  
  CONCLUSIONS
  Real-time continuous vital signs monitoring and data acquisition can identify dynamic prehospital changes, which may be missed compared with vital signs recorded manually during distinct prehospital intervals. In the future, the use of automated vital signs trending may improve the quality of data reported for inclusion in trauma registries. These data may be used to develop improved triage algorithms aimed at optimizing resource use and enhancing patient outcomes.
authors.affiliation: University of Maryland Department of Anesthesiology, Baltimore, MD.
authors.forename: Peter
authors.initials: P
authors.lastname: Hu
authors.affiliation: University of Maryland Department of Anesthesiology, Baltimore, MD. Electronic address: sgalvagno@anes.umm.edu.
authors.forename: Samuel M
authors.initials: SM
authors.lastname: Galvagno
authors.affiliation: Mayo Clinic, Scottsdale, AZ.
authors.forename: Ayan
authors.initials: A
authors.lastname: Sen
authors.affiliation: Anesthesia Quality Institute, Park Ridge, IL.
authors.forename: Richard
authors.initials: R
authors.lastname: Dutton
authors.affiliation: University of Maryland Department of Anesthesiology, Baltimore, MD.
authors.forename: Sean
authors.initials: S
authors.lastname: Jordan
authors.affiliation: Maryland Institute for Emergency Medical Services Systems, Baltimore, MD.
authors.forename: Douglas
authors.initials: D
authors.lastname: Floccare
authors.affiliation: Maryland Institute for Emergency Medical Services Systems, Baltimore, MD.
authors.forename: Christopher
authors.initials: C
authors.lastname: Handley
authors.affiliation: University of Maryland/US Air Force-Baltimore CSTARS, Baltimore, MD.
authors.forename: Stacy
authors.initials: S
authors.lastname: Shackelford
authors.affiliation: University of Maryland/US Air Force-Baltimore CSTARS, Baltimore, MD.
authors.forename: Jason
authors.initials: J
authors.lastname: Pasley
authors.affiliation: University of Maryland Department of Anesthesiology, Baltimore, MD.
authors.forename: Colin
authors.initials: C
authors.lastname: Mackenzie
mesh_terms: D001794:Blood Pressure; D006339:Heart Rate; D006801:Humans; D015601:Injury Severity Score; D008991:Monitoring, Physiologic / Q000295:instrumentation / Q000379:methods*; D015588:Observer Variation; D010100:Oxygen / Q000097:blood*; D012042:Registries; D012815:Signal Processing, Computer-Assisted
chemical_list: D010100:Oxygen