Describing the linkages of the immigration, refugees and citizenship Canada permanent resident data and vital statistics death registry to Ontario's administrative health database

Abstract

Background: Ontario, the most populous province in Canada, has a universal healthcare system that routinely collects health administrative data on its 13 million legal residents that is used for health research. Record linkage has become a vital tool for this research by enriching this data with the Immigration, Refugees and Citizenship Canada Permanent Resident (IRCC-PR) database and the Office of the Registrar General's Vital Statistics-Death (ORG-VSD) registry. Our objectives were to estimate linkage rates and compare characteristics of individuals in the linked versus unlinked files.

Methods: We used both deterministic and probabilistic linkage methods to link the IRCC-PR database (1985-2012) and ORG-VSD registry (1990-2012) to the Ontario's Registered Persons Database. Linkage rates were estimated and standardized differences were used to assess differences in socio-demographic and other characteristics between the linked and unlinked records.

Results: The overall linkage rates for the IRCC-PR database and ORG-VSD registry were 86.4 and 96.2 %, respectively. The majority (68.2 %) of the record linkages in IRCC-PR were achieved after three deterministic passes, 18.2 % were linked probabilistically, and 13.6 % were unlinked. Similarly the majority (79.8 %) of the record linkages in the ORG-VSD were linked using deterministic record linkage, 16.3 % were linked after probabilistic and manual review, and 3.9 % were unlinked. Unlinked and linked files were similar for most characteristics, such as age and marital status for IRCC-PR and sex and most causes of death for ORG-VSD. However, lower linkage rates were observed among people born in East Asia (78 %) in the IRCC-PR database and certain causes of death in the ORG-VSD registry, namely perinatal conditions (61.3 %) and congenital anomalies (81.3 %).

Conclusions: The linkages of immigration and vital statistics data to existing population-based healthcare data in Ontario, Canada will enable many novel cross-sectional and longitudinal studies to be conducted. Analytic techniques to account for sub-optimal linkage rates may be required in studies of certain ethnic groups or certain causes of death among children and infants.

Keywords: Health Administrative Data; Immigrant and refugee data; Record linkage; Vital statistics death data.

Fig. 1

Deterministic and Probabilistic Linkage process used to link the IRCC-PR database to the RPDB. Legend. Abbreviations: IRCC-PR, Immigration, Refugees and Citizenship Canada Permanent Resident file; DOB, date of birth; RPDB, Registered Persons Database

Fig. 2

Deterministic and Probabilistic Linkage rates and percentage Unlinked for the IRCC-PR by Landing Year

Fig. 3

Deterministic and Probabilistic Linkage process used to link the ORG-VSD-Death to the RPDB. Legend. Abbreviations: DOB, date of birth; DOLC, date of last contact; NYSIIS, New York State Identification and Intelligence System; RG, Registrar General; RPDB, Registered Persons Database

Fig. 4

Deterministic and Probabilistic Linkage rates and percentage Unlinked for the ORG-VSD Data by Fiscal Year. Legend. ^aFiscal Year: April 1^st to March 31^st (e.g. Fiscal year 1990/91 is April 1, 1990 to March 31, 1991)