BMC Medical Informatics and Decision Making
Volume 16, Issue 1, 2016

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

Chiu M. , Lebenbaum M. , Lam K. , Chong N. , Azimaee M. , Iron K. , Manuel D. , Guttmann A.*
  • a Institute for Clinical Evaluative Sciences, G-106, 2075 Bayview Avenue, Toronto, ON M4N 3M5, Canada
  • b Institute for Clinical Evaluative Sciences, G-106, 2075 Bayview Avenue, Toronto, ON M4N 3M5, Canada
  • c Canadian Institute for Health Information, 4110 Yonge Street, Toronto, ON M2P 2B7, Canada
  • d Institute for Clinical Evaluative Sciences, G-106, 2075 Bayview Avenue, Toronto, ON M4N 3M5, Canada
  • e Institute for Clinical Evaluative Sciences, G-106, 2075 Bayview Avenue, Toronto, ON M4N 3M5, Canada
  • f CPSO, 80 College Street, Toronto, ON M5G 2E2, Canada
  • g Ottawa Hospital Research Institute, 725 Parkdale Ave, Ottawa, ON K1Y 4E9, Canada
  • h Institute for Clinical Evaluative Sciences, G-106, 2075 Bayview Avenue, Toronto, ON M4N 3M5, Canada

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. © 2016 The Author(s).

Author Keywords

Immigrant and refugee data Record linkage Health Administrative Data Vital statistics death data

Index Keywords

statistics and numerical data Emigrants and Immigrants Canada Databases, Factual medical record factual database refugee Medical Record Linkage Refugees Registries cause of death Ontario human Humans migrant register
Link
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84992199442&doi=10.1186%2fs12911-016-0375-3&partnerID=40&md5=0642fa2874b575ca34e77dea559ac26b
DOI: 10.1186/s12911-016-0375-3
ISSN: 14726947
Cited by: 27
Original Language: English