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Validation of case definitions of depression derived from administrative data against the CIDI-SF as reference standard: results from the PROspective Québec (PROQ) study
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 adminis...
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description | 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 ([greater than or equai to] 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. Keywords: Cohort, Population-based, Major depression, known-groups analysis, Known-groups validity, Predictive validity |
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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 ([greater than or equai to] 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. Keywords: Cohort, Population-based, Major depression, known-groups analysis, Known-groups validity, Predictive validity</description><identifier>ISSN: 1471-244X</identifier><identifier>EISSN: 1471-244X</identifier><identifier>DOI: 10.1186/s12888-021-03501-x</identifier><identifier>PMID: 34620134</identifier><language>eng</language><publisher>London: BioMed Central Ltd</publisher><subject>Age ; Classification ; Cohort ; Data collection ; Depression, Mental ; Diabetes ; Diagnosis ; Epidemiology ; Evaluation ; Family physicians ; Hospitals ; Interviews ; Kappa coefficient ; Known-groups validity ; Major depression, known-groups analysis ; Mental depression ; Mental disorders ; Mental health surveys ; Mental illness ; Population ; Population studies ; Population-based ; Population-based studies ; Predictive validity ; Psychiatry ; Questionnaires ; Regression analysis ; Risk factors ; Sensitivity analysis ; Sociodemographics ; Surveys</subject><ispartof>BMC psychiatry, 2021-10, Vol.21 (1), p.1-491, Article 491</ispartof><rights>COPYRIGHT 2021 BioMed Central Ltd.</rights><rights>2021. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>The Author(s) 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c540t-890e7ffa4b1e65fe10b4e8fa33935e0e3c96607ba50fbbe615be17f157905b7f3</citedby><cites>FETCH-LOGICAL-c540t-890e7ffa4b1e65fe10b4e8fa33935e0e3c96607ba50fbbe615be17f157905b7f3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8496029/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2583202085?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,37013,44590,53791,53793</link.rule.ids></links><search><creatorcontrib>Pena-Gralle, Ana Paula Bruno</creatorcontrib><creatorcontrib>Talbot, Denis</creatorcontrib><creatorcontrib>Trudel, Xavier</creatorcontrib><creatorcontrib>Aubé, Karine</creatorcontrib><creatorcontrib>Lesage, Alain</creatorcontrib><creatorcontrib>Lauzier, Sophie</creatorcontrib><creatorcontrib>Milot, Alain</creatorcontrib><creatorcontrib>Brisson, Chantal</creatorcontrib><title>Validation of case definitions of depression derived from administrative data against the CIDI-SF as reference standard: results from the PROspective Québec (PROQ) study</title><title>BMC psychiatry</title><description>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 ([greater than or equai to] 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. Keywords: Cohort, Population-based, Major depression, known-groups analysis, Known-groups validity, Predictive validity</description><subject>Age</subject><subject>Classification</subject><subject>Cohort</subject><subject>Data collection</subject><subject>Depression, Mental</subject><subject>Diabetes</subject><subject>Diagnosis</subject><subject>Epidemiology</subject><subject>Evaluation</subject><subject>Family physicians</subject><subject>Hospitals</subject><subject>Interviews</subject><subject>Kappa coefficient</subject><subject>Known-groups validity</subject><subject>Major depression, known-groups analysis</subject><subject>Mental depression</subject><subject>Mental disorders</subject><subject>Mental health surveys</subject><subject>Mental illness</subject><subject>Population</subject><subject>Population studies</subject><subject>Population-based</subject><subject>Population-based studies</subject><subject>Predictive validity</subject><subject>Psychiatry</subject><subject>Questionnaires</subject><subject>Regression analysis</subject><subject>Risk factors</subject><subject>Sensitivity analysis</subject><subject>Sociodemographics</subject><subject>Surveys</subject><issn>1471-244X</issn><issn>1471-244X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNptks1u1DAUhSMEoqXwAqwisSmLlOvYcRwWSNVAYaRKpfyJneXY11NXSTzYyah9JHgNXgxnpgIGIS9iHX_n-Ccny54SOCFE8BeRlEKIAkpSAK2AFDf3skPCalKUjH29_9f8IHsU4zUAqUVFHmYHlPESCGWH2Y8vqnNGjc4Pube5VhFzg9YNbpbirBlcB4xxJgwGt0GT2-D7XJk-YXEMyb1JLjWqXK2UG-KYj1eYL5avl8XHs1zFPKDFgIPGPI5qMCqYl0mLUzfGXdbMv_9wEdeot2GX08_vLer8OImXz5NrMrePswdWdRGf3H2Pss9nbz4t3hXnF2-Xi9PzQlcMxkI0gLW1irUEeWWRQMtQWEVpQysEpLrhHOpWVWDbFjmpWiS1JVXdQNXWlh5ly12u8eparoPrVbiVXjm5FXxYSRVGpzuUioPmumkYUMJIA6LiAlhLSWVKoYGnrFe7rPXU9mg0Dum5ur3Q_ZXBXcmV30jBGg5lkwKO7wKC_zZhHGXvosauUwP6KcqyElADKRlJ6LN_0Gs_hSE91UzREsp0vj_USqULuMH6tK-eQ-UprwWlFFidqJP_UGkY7J32Q2pI0vcM5c6gg48x_e_fdyQg57bKXVtlaqvctlXe0F-o-dyz</recordid><startdate>20211007</startdate><enddate>20211007</enddate><creator>Pena-Gralle, Ana Paula Bruno</creator><creator>Talbot, Denis</creator><creator>Trudel, Xavier</creator><creator>Aubé, Karine</creator><creator>Lesage, Alain</creator><creator>Lauzier, Sophie</creator><creator>Milot, Alain</creator><creator>Brisson, Chantal</creator><general>BioMed Central Ltd</general><general>BioMed Central</general><general>BMC</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7TK</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88G</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>M2M</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PSYQQ</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20211007</creationdate><title>Validation of case definitions of depression derived from administrative data against the CIDI-SF as reference standard: results from the PROspective Québec (PROQ) study</title><author>Pena-Gralle, Ana Paula Bruno ; Talbot, Denis ; Trudel, Xavier ; Aubé, Karine ; Lesage, Alain ; Lauzier, Sophie ; Milot, Alain ; Brisson, Chantal</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c540t-890e7ffa4b1e65fe10b4e8fa33935e0e3c96607ba50fbbe615be17f157905b7f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Age</topic><topic>Classification</topic><topic>Cohort</topic><topic>Data collection</topic><topic>Depression, Mental</topic><topic>Diabetes</topic><topic>Diagnosis</topic><topic>Epidemiology</topic><topic>Evaluation</topic><topic>Family physicians</topic><topic>Hospitals</topic><topic>Interviews</topic><topic>Kappa coefficient</topic><topic>Known-groups validity</topic><topic>Major depression, known-groups analysis</topic><topic>Mental depression</topic><topic>Mental disorders</topic><topic>Mental health surveys</topic><topic>Mental illness</topic><topic>Population</topic><topic>Population studies</topic><topic>Population-based</topic><topic>Population-based studies</topic><topic>Predictive validity</topic><topic>Psychiatry</topic><topic>Questionnaires</topic><topic>Regression analysis</topic><topic>Risk factors</topic><topic>Sensitivity analysis</topic><topic>Sociodemographics</topic><topic>Surveys</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pena-Gralle, Ana Paula Bruno</creatorcontrib><creatorcontrib>Talbot, Denis</creatorcontrib><creatorcontrib>Trudel, Xavier</creatorcontrib><creatorcontrib>Aubé, Karine</creatorcontrib><creatorcontrib>Lesage, Alain</creatorcontrib><creatorcontrib>Lauzier, Sophie</creatorcontrib><creatorcontrib>Milot, Alain</creatorcontrib><creatorcontrib>Brisson, Chantal</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Neurosciences Abstracts</collection><collection>Health & Medical Collection (Proquest)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Psychology Database (Alumni)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>PML(ProQuest Medical Library)</collection><collection>Psychology Database (ProQuest)</collection><collection>Publicly Available Content (ProQuest)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest One Psychology</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>Directory of Open Access Journals</collection><jtitle>BMC psychiatry</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pena-Gralle, Ana Paula Bruno</au><au>Talbot, Denis</au><au>Trudel, Xavier</au><au>Aubé, Karine</au><au>Lesage, Alain</au><au>Lauzier, Sophie</au><au>Milot, Alain</au><au>Brisson, Chantal</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Validation of case definitions of depression derived from administrative data against the CIDI-SF as reference standard: results from the PROspective Québec (PROQ) study</atitle><jtitle>BMC psychiatry</jtitle><date>2021-10-07</date><risdate>2021</risdate><volume>21</volume><issue>1</issue><spage>1</spage><epage>491</epage><pages>1-491</pages><artnum>491</artnum><issn>1471-244X</issn><eissn>1471-244X</eissn><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 ([greater than or equai to] 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. Keywords: Cohort, Population-based, Major depression, known-groups analysis, Known-groups validity, Predictive validity</abstract><cop>London</cop><pub>BioMed Central Ltd</pub><pmid>34620134</pmid><doi>10.1186/s12888-021-03501-x</doi><oa>free_for_read</oa></addata></record> |
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subjects | Age Classification Cohort Data collection Depression, Mental Diabetes Diagnosis Epidemiology Evaluation Family physicians Hospitals Interviews Kappa coefficient Known-groups validity Major depression, known-groups analysis Mental depression Mental disorders Mental health surveys Mental illness Population Population studies Population-based Population-based studies Predictive validity Psychiatry Questionnaires Regression analysis Risk factors Sensitivity analysis Sociodemographics Surveys |
title | Validation of case definitions of depression derived from administrative data against the CIDI-SF as reference standard: results from the PROspective Québec (PROQ) study |
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