Concordance between health administrative data and survey‐derived diagnoses for mood and anxiety disorders. (26th January 2020)

• Record Type: Journal Article
• Authors: Edwards, J.; Thind, A.; Stranges, S.; Chiu, M.; Anderson, K. K.
• Is Part Of: Acta psychiatrica Scandinavica. Volume 141:Number 4(2020)
• Page Start: 385
• Page End: 395
• Publication Date: 2020-01-26
• Subjects: depression -- anxiety -- population surveys -- epidemiology -- health service; Psychiatry -- Periodicals; 616.89
• DOI: 10.1111/acps.13143
• Languages: English
• ISSNs: 0001-690X

Abstract

Abstract : Objective: To assess whether estimates of survey structured interview diagnoses of mood and anxiety disorders were concordant with diagnoses of these disorders obtained from health administrative data. Methods: All Ontario respondents to the 2012 Canadian Community Health Survey‐Mental Health (CCHS‐MH) were linked to health administrative databases at ICES (formerly known as the Institute for Clinical Evaluative Sciences). Survey structured interview diagnoses were compared with health administrative data diagnoses obtained using a standardized algorithm. We used modified Poisson regression analyses to assess whether socio‐demographic factors were associated with concordance between the two measures. Results: Of the 4157 Ontarians included in our sample, 20.4% had either a structured interview diagnosis (13.9%) or health administrative diagnosis (10.4%) of a mood or anxiety disorder. There was high discordance between measures, with only 19.4% agreement. Migrant status, age, employment, and income were associated with discordance between measures. Conclusions: Our findings indicate that previous estimates of the 12‐month prevalence of mood and anxiety disorders in Ontario may be underestimating the true prevalence, and that population‐based surveys and health administrative data may be capturing different groups of people. Understanding the limitations of data commonly used in epidemiologic studies is a key foundation for improving population‐based estimates of mental disorders.