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

Shelley Cox, Rohan Martin, Piyali Somaia, Karen Smith

Research output: Contribution to journalArticleResearchpeer-review

34 Citations (Scopus)

Abstract

Objectives. To describe a model that matches electronic patient care records within a given case to one or more patients within that case. Method. This 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. The 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. What is known about the topic? Accurate pre-hospital data that can be linked to patient outcomes is widely accepted as critical to support pre-hospital patient care and system performance. What does this paper add? There is a paucity of literature describing electronic matching of patient care records at the patient level rather than the case level. Ambulance Victoria has developed a complex yet efficient and highly accurate method for electronically matching patient records, in the absence of a patient-specific unique identifier. Linkage of patient information from multiple patient care records to determine if the records are for the same individual defines the 'case patient'. What are the implications for practitioners? This paper describes a model of record linkage where patients are matched within a given case at the patient level as opposed to the case level. This methodology is applicable to other emergency services where unique identifiers are case based.

Original languageEnglish
Pages (from-to)54-59
Number of pages6
JournalAustralian Health Review
Volume37
Issue number1
DOIs
Publication statusPublished - 2013
Externally publishedYes

Keywords

  • ambulance
  • deterministic linkage
  • electronic patient care record
  • pre-hospital
  • probabilistic linkage
  • record linkage

Cite this

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title = "The development of a data-matching algorithm to define the 'case patient'",
abstract = "Objectives. To describe a model that matches electronic patient care records within a given case to one or more patients within that case. Method. This 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. The 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. What is known about the topic? Accurate pre-hospital data that can be linked to patient outcomes is widely accepted as critical to support pre-hospital patient care and system performance. What does this paper add? There is a paucity of literature describing electronic matching of patient care records at the patient level rather than the case level. Ambulance Victoria has developed a complex yet efficient and highly accurate method for electronically matching patient records, in the absence of a patient-specific unique identifier. Linkage of patient information from multiple patient care records to determine if the records are for the same individual defines the 'case patient'. What are the implications for practitioners? This paper describes a model of record linkage where patients are matched within a given case at the patient level as opposed to the case level. This methodology is applicable to other emergency services where unique identifiers are case based.",
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The development of a data-matching algorithm to define the 'case patient'. / Cox, Shelley; Martin, Rohan; Somaia, Piyali; Smith, Karen.

In: Australian Health Review, Vol. 37, No. 1, 2013, p. 54-59.

Research output: Contribution to journalArticleResearchpeer-review

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AU - Martin, Rohan

AU - Somaia, Piyali

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