Abstract
BackgroundThe linkage of records across administrative databases has become a powerful tool to increase information available to undertake research and analytics in a privacy protective manner. ObjectiveThe objective of this paper was to describe the data integration strategy used to link the Ontario Ministry of Children, Community and Social Services (MCCSS)-Social Assistance (SA) database with administrative health care data. MethodsDeterministic and probabilistic linkage methods were used to link the MCCSS-SA database (2003-2016) to the Registered Persons Database, a population registry containing data on all individuals issued a health card number in Ontario, Canada. Linkage rates were estimated, and the degree of record linkage and representativeness of the dataset were evaluated by comparing socio-demographic characteristics of linked and unlinked records. ResultsThere were a total of 2,736,353 unique member IDs in the MCCSS-SA database from the 1st January 2003 to 31st December 2016; 331,238 (12.1%) were unlinked (linkage rate = 87.9%). Despite 16 passes, most record linkages were obtained after 2 deterministic (76.2%) and 14 probabilistic passes (11.7%). Linked and unlinked samples were similar for most socio-demographic characteristics (i.e., sex, age, rural dwelling), except migrant status (non-migrant versus migrant) (standardized difference of 0.52). Linked and unlinked records were also different for SA program-specific characteristics, such as social assistance program, Ontario Works and Ontario Disability Support Program (standardized difference of 0.20 for each), data entry system, Service Delivery Model Technology only and both Service Delivery Model Technology and Social Assistance Management System (standardized difference of 0.53 and 0.52, respectively), and months on social assistance (standardized difference of 0.43). ConclusionsAdditional techniques to account for sub-optimal linkage rates may be required to address potential biases resulting from this data linkage. Nonetheless, the linkage between administrative social assistance and health care data will provide important findings on the social determinants of health.
Highlights
In Canada, universal health care is delivered through provincial and territorial publicly funded health care systems, which, in turn, collect administrative data that reflect patients’ interactions with the health care system across multiple sectors and over time
Ontario has two social assistance programs, which provide income and employment support to single adults and families who are in financial need: Ontario Works (OW), which provides financial and employment assistance to help people move towards paid employment and independence, and the Ontario Disability Support Program (ODSP), which provides financial assistance and employment support to enable individuals with disabilities and their families to live as independently as possible in their communities
We examined the number of records linked by deterministic and probabilistic record linkages in each step of the process, as well as the linkage rates over time
Summary
In Canada, universal health care is delivered through provincial and territorial publicly funded health care systems, which, in turn, collect administrative data that reflect patients’ interactions with the health care system across multiple sectors (e.g., inpatient and ambulatory care) and over time. To ensure the privacy and protection of data, ICES implements a series of physical and logical controls to govern access to information, like the use of secure zones within ICES facilities, complex passwords, and encryption. The use of these data has enabled scientists to answer important policy-relevant questions across different disciplines such as health services research, health economics, epidemiology and public health [2–5]. The linkage of records across administrative databases has become a powerful tool to increase information available to undertake research and analytics in a privacy protective manner
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