Strengths and Limitations of Health and Disability Support Administrative Databases for Population‐Based Health Research in Intellectual and Developmental Disabilities. Issue 4 (December 2014)

• Record Type: Journal Article
• Authors: Lin, Elizabeth; Balogh, Robert; Isaacs, Barry; Ouellette‐Kuntz, Helene; Selick, Avra; Wilton, Andrew S.; Cobigo, Virginie; Lunsky, Yona
• Is Part Of: Journal of policy and practice in intellectual disabilities. Volume 11:Issue 4(2014)
• Page Start: 235
• Page End: 244
• Publication Date: 2014-12
• Subjects: Mental retardation -- Periodicals; People with mental disabilities -- Services for -- Periodicals; Developmental disabilities -- Periodicals; Learning disabilities -- Periodicals; 362.205
• DOI: 10.1111/jppi.12098
• Languages: English
• ISSNs: 1741-1122

Abstract

<abstract abstract-type="main"> <title>Abstract</title> <p>Individuals with intellectual and developmental disabilities (IDD) experience high rates of social and health disadvantage. Planning effective services that meet the needs of this vulnerable population requires good population‐based data that are collected on a routine, ongoing basis. However, in most jurisdictions, none of the commonly available data (e.g., health or disability benefits administrative data) completely captures the IDD population. To more accurately identify persons with IDD in a population, one solution is to link data across multiple sources. To do this, the authors report on an effort to create a linked database to identify a cohort of adults, aged 18–64, with IDD in Ontario and use these data to examine how the linkage can help study health and healthcare access. The linked dataset was created using four health and one disability income support databases. Standardized differences were used to compare sociodemographic and clinical characteristics of the IDD cohorts identified through the health, disability income support, and linked datasets. Indirect estimation was used to evaluate which IDD subgroups might be over‐ or underestimated if only a single source of data was available. The linked database identified a cohort of 66, 484 adults with IDD (0.78% prevalence). The health and disability income support data each uniquely identified approximately a third of the cohort. Health data were more likely to identify younger adults (18–24 years), those with psychiatric illnesses, and hospitalized individuals. The disability income support data were more likely to identify adults aged 35–54 and those living in lower income neighborhoods. By linking multiple databases, the authors were able to identify a much larger cohort of individuals with IDD than if they had used a single data source. It also enabled the creation of a more accurate sociodemographic and clinical profile of this population as each source captured different segments of it.</p> </abstract>