The development of a data-matching algorithm to define the 'case patient'

Aust Health Rev. 2013 Feb;37(1):54-9. doi: 10.1071/AH11161.


Objectives: To describe a model that matches electronic patient care records within a given case to one or more patients within that case.

Method: 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.

MeSH terms

  • Algorithms
  • Ambulances / statistics & numerical data*
  • Databases, Factual
  • Electronic Health Records / statistics & numerical data*
  • Humans
  • Medical Record Linkage / methods*
  • Models, Statistical
  • Outcome Assessment, Health Care / methods*
  • Retrospective Studies
  • Victoria