Administrative data have several advantages over questionnaire and interview data to identify cases of depression: they are usually inexpensive, available for a long period of time and are less subject to recall bias and differential classification errors. However, the validity of administrative data in the correct identification of depression has not yet been studied in general populations. The present study aimed to 1) evaluate the sensitivity and specificity of administrative cases of depression using the validated Composite International Diagnostic Interview – Short Form (CIDI-SF) as reference standard and 2) compare the known-groups validity between administrative and CIDI-SF cases of depression.
Therefore The 5487 participants seen at the last wave (2015–2018) of the PROQ cohort had CIDI-SF questionnaire data linked to hospitalization and medical reimbursement data provided by the provincial universal healthcare provider and coded using the International Classification of Disease. We analyzed the sensitivity and specificity of several case definitions of depression from this administrative data. Their association with known predictors of depression was estimated using robust Poisson regression models.
Administrative cases of depression showed high specificity (≥ 96%), low sensitivity (19–32%), and rather low agreement (Cohen’s kappa of 0.21–0.25) compared with the CIDI-SF. These results were consistent over strata of sex, age and education level and with varying case definitions.
Reference link- https://bmcpsychiatry.biomedcentral.com/articles/10.1186/s12888-021-03501-x
