Sasha Bernatsky1, Tina Linehan, John G Hanly. 1. Division of Clinical Epidemiology, Department of Medicine, McGill University Health Centre (MUHC), Montreal, Quebec, Canada. sasha.bernatsky@mail.mcgill.ca
Abstract
OBJECTIVE: To examine the validity of case definitions for systemic autoimmune rheumatic diseases [SARD; systemic lupus erythematosus (SLE), systemic sclerosis (SSc), myositis, Sjögren's syndrome, vasculitis, and polymyalgia rheumatica] based on administrative data, compared to rheumatology records. METHODS: A list of rheumatic disease diagnoses was generated from population-based administrative billing and hospitalization databases. Subjects who had been seen by an arthritis center rheumatologist were identified, and the medical records reviewed. RESULTS: We found that 844 Nova Scotia residents had a diagnosis of one of the rheumatic diseases of interest, based on administrative data, and had had ≥ 1 rheumatology assessment at a provincial arthritis center. Charts were available on 824 subjects, some of whom had been identified in the administrative database with > 1 diagnosis. Thus a total of 1136 diagnoses were available for verification against clinical records. Of the 824 subjects, 680 (83%) had their administrative database diagnoses confirmed on chart review. The majority of subjects who were "false-positive" for a given rheumatic disease on administrative data had a true diagnosis of a similar rheumatic disease. Most sensitivity estimates for specific administrative data-based case definitions were > 90%, although for SSc, the sensitivity was 80.5%. The specificity estimates were also > 90%, except for SLE, where the specificity was 72.5%. CONCLUSION: Although health administrative data may be a valid resource, there are potential problems regarding the specificity and sensitivity of case definitions, which should be kept in mind for future studies.
OBJECTIVE: To examine the validity of case definitions for systemic autoimmune rheumatic diseases [SARD; systemic lupus erythematosus (SLE), systemic sclerosis (SSc), myositis, Sjögren's syndrome, vasculitis, and polymyalgia rheumatica] based on administrative data, compared to rheumatology records. METHODS: A list of rheumatic disease diagnoses was generated from population-based administrative billing and hospitalization databases. Subjects who had been seen by an arthritis center rheumatologist were identified, and the medical records reviewed. RESULTS: We found that 844 Nova Scotia residents had a diagnosis of one of the rheumatic diseases of interest, based on administrative data, and had had ≥ 1 rheumatology assessment at a provincial arthritis center. Charts were available on 824 subjects, some of whom had been identified in the administrative database with > 1 diagnosis. Thus a total of 1136 diagnoses were available for verification against clinical records. Of the 824 subjects, 680 (83%) had their administrative database diagnoses confirmed on chart review. The majority of subjects who were "false-positive" for a given rheumatic disease on administrative data had a true diagnosis of a similar rheumatic disease. Most sensitivity estimates for specific administrative data-based case definitions were > 90%, although for SSc, the sensitivity was 80.5%. The specificity estimates were also > 90%, except for SLE, where the specificity was 72.5%. CONCLUSION: Although health administrative data may be a valid resource, there are potential problems regarding the specificity and sensitivity of case definitions, which should be kept in mind for future studies.
Authors: Sudumpai Jarukitsopa; Deana D Hoganson; Cynthia S Crowson; Olayemi Sokumbi; Mark D Davis; Clement J Michet; Eric L Matteson; Hilal Maradit Kremers; Vaidehi R Chowdhary Journal: Arthritis Care Res (Hoboken) Date: 2015-05 Impact factor: 4.794
Authors: Natalie Jane Shiff; Lisa M Lix; Lawrence Joseph; Ciaran Duffy; Lori B Tucker; Lawrence W Svenson; Patrick Belisle; Sasha Bernatsky Journal: Rheumatol Int Date: 2014-09-26 Impact factor: 2.631
Authors: Rachel A Bender Ignacio; Amy T Madison; Ata Moshiri; Noel S Weiss; Beth A Mueller Journal: Paediatr Perinat Epidemiol Date: 2017-12-01 Impact factor: 3.980
Authors: Gretchen Bandoli; Namrata Singh; Jennifer Strouse; Rebecca J Baer; Brittney M Donovan; Sky K Feuer; Nichole Nidey; Kelli K Ryckman; Laura L Jelliffe-Pawlowski; Christina D Chambers Journal: Arthritis Care Res (Hoboken) Date: 2020-01-09 Impact factor: 4.794
Authors: Ada Man; Yanyan Zhu; Yuqing Zhang; Maureen Dubreuil; Young Hee Rho; Christine Peloquin; Robert W Simms; Hyon K Choi Journal: Ann Rheum Dis Date: 2012-08-17 Impact factor: 19.103
Authors: Candace H Feldman; Linda T Hiraki; Jun Liu; Michael A Fischer; Daniel H Solomon; Graciela S Alarcón; Wolfgang C Winkelmayer; Karen H Costenbader Journal: Arthritis Rheum Date: 2013-03
Authors: Sara R Schoenfeld; Hyon K Choi; Eric C Sayre; J Antonio Aviña-Zubieta Journal: Arthritis Care Res (Hoboken) Date: 2016-02 Impact factor: 4.794