J Edwards1,2, A Thind1,3,4, S Stranges1,4,5, M Chiu6,7, K K Anderson1,2,8. 1. Department of Epidemiology & Biostatistics, Schulich School of Medicine & Dentistry, The University of Western Ontario, London, ON, Canada. 2. Lawson Health Research Institute, London, ON, Canada. 3. Interfaculty Program in Public Health, Schulich School of Medicine & Dentistry, The University of Western Ontario, London, ON, Canada. 4. Department of Family Medicine, Schulich School of Medicine & Dentistry, The University of Western Ontario, London, ON, Canada. 5. Department of Population Health, Luxembourg Institute of Health, Strassen, Luxembourg. 6. ICES, Toronto, ON, Canada. 7. Institute of Health Policy and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada. 8. Department of Psychiatry, Schulich School of Medicine & Dentistry, The University of Western Ontario, London, ON, Canada.
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.
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.
Authors: Jordan Edwards; Li Wang; Laura Duncan; Jinette Comeau; Kelly K Anderson; Katholiki Georgiades Journal: Child Adolesc Psychiatry Ment Health Date: 2022-06-21 Impact factor: 7.494
Authors: Jordan Edwards; Maria Chiu; Rebecca Rodrigues; Amardeep Thind; Saverio Stranges; Kelly K Anderson Journal: Can J Psychiatry Date: 2021-10-29 Impact factor: 5.321
Authors: Jordan Edwards; A Demetri Pananos; Amardeep Thind; Saverio Stranges; Maria Chiu; Kelly K Anderson Journal: Epidemiol Psychiatr Sci Date: 2021-01-08 Impact factor: 6.892
Authors: Janna Marie Bas-Hoogendam; Nynke A Groenewold; Moji Aghajani; Gabrielle F Freitag; Anita Harrewijn; Kevin Hilbert; Neda Jahanshad; Sophia I Thomopoulos; Paul M Thompson; Dick J Veltman; Anderson M Winkler; Ulrike Lueken; Daniel S Pine; Nic J A van der Wee; Dan J Stein Journal: Hum Brain Mapp Date: 2020-07-03 Impact factor: 5.399