Development and Evaluation of a Patient Self-Report Case-Finding Method for Rheumatoid Arthritis

Published in: Seminars in Arthritis and Rheumatism, v. 34, no. 1, Aug. 2004, p. 484-499

Posted on on January 01, 2004

by Andrew L. Wong, Judith O. Harker, Brian Mittman, Gerald D. Levy, Ken J. Bulpitt, Keith K. Colburn, Honghu H. Liu, Katherine L. Kahn, Bevra H. Hahn, H. E. Paulus, et al.

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OBJECTIVE: To describe the development and evaluation of a patient self-report case-finding method for rheumatoid arthritis (RA) not dependent on direct contact with the treating physicians. METHODS: The American College of Rheumatology criteria for RA diagnosis were adapted for patient self-report using a questionnaire, and alternative scoring algorithms were evaluated to balance case-finding sensitivity and specificity. Positive rheumatoid factor tests were used to identify 1053 individuals in 2 large healthcare organizations; 440 agreed to receive study materials. Case-finding results were validated by medical record review (MRR) for a random sample of 90 patients. Three scoring algorithms were compared with MRR for likelihood of RA diagnosis. Cases not classifiable by algorithm were flagged and reviewed by 2 expert physicians for likelihood of RA diagnosis. RESULTS: Pilot testing demonstrated that patients comprehended the questionnaire and were willing to answer the questions. Completed questionnaires were returned by 265 (60%) of the 440 patients contacted. Following expert physician review of 16 flagged cases in the 90-patient MRR subsample, the most accurate scoring algorithm demonstrated 80% sensitivity, 67% specificity, 74% accuracy, and 77% positive predictive value for detecting early RA. CONCLUSION: The case-finding method represents a promising tool for identifying RA patients, with potential application in research and quality-assurance activities. RELEVANCE: This case-finding method should be useful in research and quality-assurance efforts requiring identification of RA patients treated by all types of providers in healthcare organizations in which centralized laboratory data are available.

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