The use of administrative health care databases to identify patients with rheumatoid arthritis
Authors Hanly J, Thompson K, Skedgel C
Received 18 July 2015
Accepted for publication 5 October 2015
Published 6 November 2015 Volume 2015:7 Pages 69—75
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 4
Editor who approved publication: Professor Chuan-Ju Liu
John G Hanly,1,2 Kara Thompson,3 Chris Skedgel4
1Division of Rheumatology, Department of Medicine, 2Department of Pathology, 3Department of Medicine, Queen Elizabeth II Health Sciences Centre, Dalhousie University, 4Atlantic Clinical Cancer Research Unit, Capital Health, Halifax, Nova Scotia, Canada
Objective: To validate and compare the decision rules to identify rheumatoid arthritis (RA) in administrative databases.
Methods: A study was performed using administrative health care data from a population of 1 million people who had access to universal health care. Information was available on hospital discharge abstracts and physician billings. RA cases in health administrative databases were matched 1:4 by age and sex to randomly selected controls without inflammatory arthritis. Seven case definitions were applied to identify RA cases in the health administrative data, and their performance was compared with the diagnosis by a rheumatologist. The validation study was conducted on a sample of individuals with administrative data who received a rheumatologist consultation at the Arthritis Center of Nova Scotia.
Results: We identified 535 RA cases and 2,140 non-RA, noninflammatory arthritis controls. Using the rheumatologist's diagnosis as the gold standard, the overall accuracy of the case definitions for RA cases varied between 68.9% and 82.9% with a kappa statistic between 0.26 and 0.53. The sensitivity and specificity varied from 20.7% to 94.8% and 62.5% to 98.5%, respectively. In a reference population of 1 million, the estimated annual number of incident cases of RA was between 176 and 1,610 and the annual number of prevalent cases was between 1,384 and 5,722.
Conclusion: The accuracy of case definitions for the identification of RA cases from rheumatology clinics using administrative health care databases is variable when compared to a rheumatologist's assessment. This should be considered when comparing results across studies. This variability may also be used as an advantage in different study designs, depending on the relative importance of sensitivity and specificity for identifying the population of interest to the research question.
Keywords: inflammatory arthritis, case definitions, incidence, prevalence, population health
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