Abstract
BackgroundLinkage of demographic, health, and developmental administrative data can enrich population-based surveillance and research on developmental and educational outcomes. Transparency of the record linkage process and results are required to assess potential biases.ObjectivesTo describe the approach used to link records of kindergarten children from the Early Development Instrument (EDI) in Ontario to health administrative data and test differences in characteristics of children by linkage status. We demonstrate how socio-demographic and medical risk factors amass in their contribution to early developmental vulnerability and test the concordance of health diagnoses in both the EDI and health datasets of linked records.MethodsChildren with records in the 2015 EDI cycle were deterministically linked to a population registry in Ontario, Canada. We compared sociodemographic and developmental vulnerability data between linked and unlinked records. Among linked records, we examined the contribution of medical and social risk factors obtained from health administrative data to developmental vulnerability identified in the EDI using descriptive analyses.ResultsOf 135,937 EDI records, 106,217 (78.1%) linked deterministically to a child in the Ontario health registry using birth date, sex, and postal code. The linked cohort was representative of children who completed the EDI in age, sex, rural residence, immigrant status, language, and special needs status. Linked data underestimated children living in the lowest neighbourhood income quintile (standardized difference [SD] 0.10) and with higher vulnerability in physical health and well-being (SD 0.11) , social competence (SD 0.10), and language and cognitive development (SD 0.12). Analysis of linked records showed developmental vulnerability is sometimes greater in children with social risk factors compared to those with medical risk factors. Common childhood conditions with records in health data were infrequently recorded in EDI records.ConclusionsLinkage of early developmental and health administrative data, in the absence of a single unique identifier, can be successful with few systematic biases introduced. Cross-sectoral linkages can highlight the relative contribution of medical and social risk factors to developmental vulnerability and poor school achievement.
Highlights
Collected health and administrative data contain a wealth of information that can be used to inform health system delivery [1, 2]
There were 135,937 Early Development Instrument (EDI) records completed in Ontario in 2015 available for linkage
Following deterministic linkage with birth date, sex and postal code, 100,780 (74.1%) of files were linked after the first pass using the 2015 Registered Person’s Database (RPDB) postal code file and a further 5,437 (4.0%) files were linked after the second pass using the 2014 RPDB postal code file
Summary
Collected health and administrative data contain a wealth of information that can be used to inform health system delivery [1, 2]. Adding cross-sectoral data linkages, including datasets that capture developmental and social services records can enrich the contextual understanding of each of these sectors’ data. At ICES, unique encoded health identification numbers allow for linkage across health datasets and privacy legislation allows for their use for research. In the absence of a unique identifier, errors are inevitable. Some records cannot be linked for a variety of reasons, including the incompleteness of the data used for linkage and the absence of identifiers common to both datasets [2, 3]. Study designs and interpretation can be strengthened with a good understanding of the linkage process, potential errors, and sources of bias. Health, and developmental administrative data can enrich population-based surveillance and research on developmental and educational outcomes. Transparency of the record linkage process and results are required to assess potential biases
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