title: Linking ambulance, emergency department and hospital admissions data: understanding the emergency journey.
abstract: OBJECTIVE
  To assess the accuracy of data linkage across the spectrum of emergency care in the absence of a unique patient identifier, and to use the linked data to examine service delivery outcomes in an emergency department (ED) setting.
  
  
  METHODS
  Automated data linkage and manual data linkage were compared to determine their relative accuracy. Data were extracted from three separate health information systems: ambulance, ED and hospital inpatients, then linked to provide information about the emergency journey of each patient. The linking was done manually through physical review of records and automatically using a data linking tool (Health Data Integration) developed by the CSIRO (Commonwealth Scientific and Industrial Research Organisation). Match rate and quality of the linking were compared.
  
  
  METHODS
  10,835 patient presentations to a large, regional teaching hospital ED over a 2-month period (August - September 2007).
  
  
  RESULTS
  Comparison of the manual and automated linkage outcomes for each pair of linked datasets demonstrated a sensitivity of between 95% and 99%; a specificity of between 75% and 99%; and a positive predictive value of between 88% and 95%.
  
  
  CONCLUSIONS
  Our results indicate that automated linking provides a sound basis for health service analysis, even in the absence of a unique patient identifier. The use of an automated linking tool yields accurate data suitable for planning and service delivery purposes and enables the data to be linked regularly to examine service delivery outcomes.
authors.affiliation: ED Clinical Network, Gold Coast Hospital, and Griffith Health Institute, Queensland Health, Southport, QLD, Australia. julia_crilly@health.qld.gov.au
authors.forename: Julia L
authors.initials: JL
authors.lastname: Crilly
authors.forename: John A
authors.initials: JA
authors.lastname: O'Dwyer
authors.forename: Marilla A
authors.initials: MA
authors.lastname: O'Dwyer
authors.forename: James F
authors.initials: JF
authors.lastname: Lind
authors.forename: Julia A L
authors.initials: JA
authors.lastname: Peters
authors.forename: Vivienne C
authors.initials: VC
authors.lastname: Tippett
authors.forename: Marianne C
authors.initials: MC
authors.lastname: Wallis
authors.forename: Nerolie F
authors.initials: NF
authors.lastname: Bost
authors.forename: Gerben B
authors.initials: GB
authors.lastname: Keijzers
mesh_terms: D000552:Ambulances / Q000706:statistics & numerical data*; D003625:Data Collection; D004632:Emergency Medical Services / Q000706:statistics & numerical data; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D006760:Hospitalization / Q000706:statistics & numerical data*; D006784:Hospitals, Teaching / Q000706:statistics & numerical data; D006801:Humans; D017063:Outcome Assessment, Health Care / Q000379:methods / Q000706:statistics & numerical data; D010355:Patient Identification Systems; D011793:Queensland