Alyssa Howren1, J Antonio Aviña-Zubieta2, Joseph H Puyat3, John M Esdaile2, Deborah Da Costa4, Mary A De Vera1. 1. University of British Columbia and Collaboration for Outcomes Research and Evaluation, Vancouver, and Arthritis Research Canada, Richmond, British Columbia, Canada. 2. Arthritis Research Canada, Richmond, and University of British Columbia, Vancouver, British Columbia, Canada. 3. University of British Columbia, Vancouver, British Columbia, Canada. 4. McGill University, Montreal, Quebec, Canada.
Abstract
OBJECTIVE: To conduct a systematic review to describe how administrative health databases have been used to study depression and anxiety in patients with rheumatic diseases and to synthesize the case definitions that have been applied. METHODS: Search strategies to identify articles evaluating depression and anxiety among individuals with rheumatic diseases were employed in Medline, Embase, CINAHL, Cochrane Database of Systematic Reviews, and PsycINFO. Studies included were those using administrative health data and reporting case definitions for depression and anxiety using International Classification of Diseases (ICD) codes. We extracted information on study design and objectives, administrative health database, specific data sources (e.g., inpatient, pharmacy records), ICD codes, operational definitions, and validity of case definitions. RESULTS: Of the 36 studies included in this review, all studies assessed depression, and 13 studies (36.1%) evaluated anxiety. A number of specific ICD-9/10 codes were consistently applied to identify depression and anxiety, but the overall combination of ICD codes and operational definitions varied across studies. Twenty-four studies reported operational definitions, and 19 of these studies (79.2%) combined claims from more than 1 type of administrative data source (e.g., inpatient, outpatient). Validated case definitions were used by 6 studies (16.7%), with sensitivity estimates for depression and anxiety case definitions ranging from 33% to 74% and 42% to 76%, respectively. CONCLUSION: We identified numerous case definitions used to evaluate depression and anxiety among individuals with rheumatic diseases within administrative health databases. Recommendations include using case definitions with demonstrated validity as well as operationalizing case definitions within multiple data sources.
OBJECTIVE: To conduct a systematic review to describe how administrative health databases have been used to study depression and anxiety in patients with rheumatic diseases and to synthesize the case definitions that have been applied. METHODS: Search strategies to identify articles evaluating depression and anxiety among individuals with rheumatic diseases were employed in Medline, Embase, CINAHL, Cochrane Database of Systematic Reviews, and PsycINFO. Studies included were those using administrative health data and reporting case definitions for depression and anxiety using International Classification of Diseases (ICD) codes. We extracted information on study design and objectives, administrative health database, specific data sources (e.g., inpatient, pharmacy records), ICD codes, operational definitions, and validity of case definitions. RESULTS: Of the 36 studies included in this review, all studies assessed depression, and 13 studies (36.1%) evaluated anxiety. A number of specific ICD-9/10 codes were consistently applied to identify depression and anxiety, but the overall combination of ICD codes and operational definitions varied across studies. Twenty-four studies reported operational definitions, and 19 of these studies (79.2%) combined claims from more than 1 type of administrative data source (e.g., inpatient, outpatient). Validated case definitions were used by 6 studies (16.7%), with sensitivity estimates for depression and anxiety case definitions ranging from 33% to 74% and 42% to 76%, respectively. CONCLUSION: We identified numerous case definitions used to evaluate depression and anxiety among individuals with rheumatic diseases within administrative health databases. Recommendations include using case definitions with demonstrated validity as well as operationalizing case definitions within multiple data sources.