{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T22:39:56Z","timestamp":1790894396635,"version":"4.1.0"},"reference-count":37,"publisher":"The Journal of Rheumatology","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J Rheumatol"],"published-print":{"date-parts":[[2013,1]]},"abstract":"<jats:sec><jats:title>Objective.<\/jats:title><jats:p>Administrative data are increasingly being used for research and surveillance about rheumatic diseases. However, literature reviews have revealed a lack of consistency in methods for conducting observational rheumatic disease studies, a situation that can lead to findings that cannot be compared. Our purpose was to develop best-practice consensus statements about the use of administrative data for rheumatic disease research and surveillance in Canada.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods.<\/jats:title><jats:p>We convened 52 decision makers, epidemiologists, clinicians, and researchers to a 2-day workshop. Prior to this, participants formed working groups to examine 3 best-practice categories: case definitions, epidemiology methods, and comorbidity and outcomes measurement. The groups conducted systematic or scoping reviews on key topics. At the workshop, evidence from the reviews was presented and consensus-building techniques were used to develop the best-practice statements. The statements were presented, discussed, revised (as needed), and then subjected to voting.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results.<\/jats:title><jats:p>Thirteen best-practice consensus statements were developed and endorsed by consensus. For the first category, these consensus statements addressed validation techniques for rheumatic disease case definitions and case ascertainment bias. The consensus statements for epidemiology methods focused on confounding and drug exposure measurement. For comorbidity and outcomes measurement, consensus statements were developed for multiple conditions, including osteoporosis and fragility fractures, cancer, infections, cardiovascular disease, and renal disease. Strengths and limitations of administrative data were identified in relation to each topic.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion.<\/jats:title><jats:p>Our best-practice consensus statements are consistent with other recent guidelines, including those for rheumatic disease biologics registries, but address additional issues specific to administrative data. Continuing work focuses on disseminating these consensus statements to multiple audiences.<\/jats:p><\/jats:sec>","DOI":"10.3899\/jrheum.120835","type":"journal-article","created":{"date-parts":[[2012,11,2]],"date-time":"2012-11-02T05:33:02Z","timestamp":1351834382000},"page":"66-73","source":"Crossref","is-referenced-by-count":32,"title":["Consensus Statements for the Use of Administrative Health Data in Rheumatic Disease Research and Surveillance"],"prefix":"10.3899","volume":"40","author":[{"given":"SASHA","family":"BERNATSKY","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"LISA","family":"LIX","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"SIOBHAN","family":"O\u2019DONNELL","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"DIANE","family":"LACAILLE","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"name":"CANRAD Network","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2262","published-online":{"date-parts":[[2012,11,1]]},"reference":[{"key":"2018112909284149000_40.1.66.1","unstructured":"Health Canada . 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