Data Linkage: Canadian and Australian Perspectives on a Valuable Methodology for Intellectual and Developmental Disability Research.
Linking existing admin files can reveal the true IDD population and guide policy without new data collection.
01Research in Context
What this study did
Balogh et al. (2019) explain how to glue together health, school, and social files. They show the Canadian and Australian way.
The paper is a recipe, not an experiment. It tells you how to count people with IDD across whole provinces.
What they found
Once the files were linked, the true size of the IDD group appeared. Hidden hospital trips and medicine use came to light.
The new numbers gave lawmakers hard facts to fund better services.
How this fits with other research
Jackson et al. (2025) later used the same Ontario pipeline. They tracked doctor visits during COVID-19 and proved the method keeps working.
Titlestad et al. (2019) and Dudley et al. (2019) warned that U.S. surveys miss most adults with IDD. Robert et al. answer with a ready-made fix: link the files you already have.
Hewitt et al. (2013) complained we lack big, scalable data. The 2019 paper shows how to build it, turning that old worry into today's toolkit.
Why it matters
If your state still guesses IDD numbers, send this paper to your IT team. Ask them to copy the Canadian steps: get consent, match IDs, run secure linkage. You will finally see how many clients need ABA, where they live, and what medical risks they face. Better maps mean better funding and sharper treatment plans.
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02At a glance
03Original abstract
Data linkage holds great promise for generating new information about people with intellectual and developmental disabilities (IDD) as a population, yet few centers have developed the infrastructure to utilize this methodology. Two examples, from Canada and Australia, describe their efforts in building data linkage capabilities, and how linked databases can be used to identify persons with IDD and used for population-based research. The value of data linkage is illustrated through new estimates of prevalence of IDD; health service utilization patterns; associations with sociodemographic characteristics, and with physical and mental health conditions (e.g., chronic diseases, injury, fertility, and depression); and findings on equity in medical treatments. Examples are provided of findings used for governmental policy and program planning.
Intellectual and developmental disabilities, 2019 · doi:10.1352/1934-9556-57.5.439