Validation of case definitions of depression derived from administrative data against the CIDI-SF as reference standard: results from the PROspective Québec (PROQ) study

Abstract

Background 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. Methods 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. Results 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. In known-groups analysis, the administrative cases of depression were comparable to that of CIDI-SF cases (RR for sex: 1.80 vs 2.03 respectively, age: 1.53 vs 1.40, education: 1.52 vs 1.28, psychological distress: 2.21 vs 2.65). Conclusion The results obtained in this large sample of a general population suggest that the dimensions of depression captured by administrative data and by the CIDI-SF are partially distinct. However, their known-groups validity in relation to risk factors for depression was similar to that of CIDI-SF cases. We suggest that neither of these data sources is superior to the other in the context of large epidemiological studies aiming to identify and quantify risk factors for depression.

Sensitivity and specificity of algorithms for the identification of nonspecific low back pain in medico-administrative databases

“…It is possible that the characteristics of our sample differed from those of the general population, but previous studies on this cohort have shown some characteristics that are similar to the general population in Canada and beyond. 39,48 For example, the estimated prevalence of depression and psychosocial stressors at work was comparable with that of the general population in Canada and other industrialised countries. In addition, the prevalence estimates of nonspecific LBP over 1 year in our sample are quite similar to those reported in the literature.…”

“…The limited performance of our algorithms could be interpreted in light of that of algorithms developed to identify other chronic health conditions such as mental illness (eg, depression, anxiety, and psychosis) in medico-administrative databases. 19,39 In one study that compared various algorithms for identifying mental health problems from ICD-9 codes to self-reported depression, post-traumatic stress disorder, or schizophrenia, the PPVs and NPVs were 47% and 86%, respectively, over a 1-year window. 19 In our study, these values ranged from 73.8% to 82.9% for PPV and 53.1% to 54.0% for NPV for the same period.…”

Gender differences in life expectancy free of depressive symptoms in Chile between 2003 and 2016

“…Depressive symptoms were measured with the Composite International Diagnostic Interview–Short Form (CIDI-SF) for Major Depression (Kessler et al, 1998 ). This is a screening tool for major depressive disorder, based on the fourth version of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) and the International Classification of Diseases (ICD-10) criteria (Pena-Gralle et al, 2021 ). A cutoff score of 5 or more points, including dysphoria, anhedonia and at least three other symptoms, was used to determine the possible cases of major depressive disorder (Ministerio de Salud, 2018 ).…”

Association between first-line antidepressant use and risk of dementia in older adults: a retrospective cohort study

“…We conducted a retrospective cohort study restricted to adults aged ≥ 50 years with a depression diagnosis in round 1 or 2 of a two-year panel period to allow at least a 1-year follow-up time. Depression was identified using International Classification of Disease (ICD) codes (ICD-9: 296.20-296.25, 296.30-296.35, 300.4, 311; positive predictive value [PPV] = 92.0%; ICD-10: F32.0-32.9, F33.0-33.3, F33.8, F33.9, F34.1 & F41.2; PPV = 91.1%) [ 18 ]. We further included those receiving SSRIs/SNRIs or psychotherapy at rounds 1 or 2, with an index round defined as the round when the first SSRI/SNRI or psychotherapy was prescribed.…”

“…We identified the outcome of interest, a new diagnosis of dementia within each two-year survey panel period, using ICD-9 codes (290, 331.0, 331.1, 331.2, 331.82, 331.83, 331.9, 438.0, 780.93) and ICD-10 codes (F00, F01, F03, F04, G30, G31.0, G31.1, G31.8, G31.9, I69.91, R41) from the Medical Conditions file (Appendix Table 1 ). The PPV values of using these ICD codes to identify dementia ranged from 73.2 to 93.6% [ 18 ].…”