title: The development of a data-matching algorithm to define the 'case patient'.
abstract: OBJECTIVE
  To describe a model that matches electronic patient care records within a given case to one or more patients within that case.
  
  
  METHODS
  his retrospective study included data from all metropolitan Ambulance Victoria electronic patient care records (n=445576) for the time period 1 January 2009-31 May 2010. Data were captured via VACIS (Ambulance Victoria, Melbourne, Vic., Australia), an in-field electronic data capture system linked to an integrated data warehouse database. The case patient algorithm included 'Jaro-Winkler', 'Soundex' and 'weight matching' conditions.
  
  
  RESULTS
  he case patient matching algorithm has a sensitivity of 99.98%, a specificity of 99.91% and an overall accuracy of 99.98%.
  
  
  CONCLUSIONS
  The case patient algorithm provides Ambulance Victoria with a sophisticated, efficient and highly accurate method of matching patient records within a given case. This method has applicability to other emergency services where unique identifiers are case based rather than patient based.
authors.affiliation: Ambulance Victoria, 375 Manningham Rd, Doncaster, VIC 3108, Australia. Shelley.Cox@ambulance.vic.gov.au
authors.forename: Shelley
authors.initials: S
authors.lastname: Cox
authors.forename: Rohan
authors.initials: R
authors.lastname: Martin
authors.forename: Piyali
authors.initials: P
authors.lastname: Somaia
authors.forename: Karen
authors.initials: K
authors.lastname: Smith
mesh_terms: D000465:Algorithms; D000552:Ambulances / Q000706:statistics & numerical data*; D016208:Databases, Factual; D057286:Electronic Health Records / Q000706:statistics & numerical data*; D006801:Humans; D008498:Medical Record Linkage / Q000379:methods*; D015233:Models, Statistical; D017063:Outcome Assessment, Health Care / Q000379:methods*; D012189:Retrospective Studies; D014739:Victoria