Evaluating a Smartphone App–Based Module for Joint Self‐Assessment as a Complementary Tool in Rheumatoid Arthritis Remote Disease Management

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Abstract
Objective: The objective of this study was to develop and evaluate a new patient‐facing tool to facilitate patient self‐examination of joints as a complement to telehealth during the management of rheumatoid arthritis (RA). Methods: Using a community‐based rheumatology network, we evaluated the efficacy of an in‐app cartoon‐based joint examination module that guides patients through self‐conducted physical examinations by comparing patient‐derived joint counts with those recorded by physicians during in‐office visits. A total of 100 patients were enrolled from outpatient rheumatology clinics. Scatter plots and regression models were used to analyze the data. Results: Overall, rheumatologists recorded fewer tender and swollen joints than patients with RA. The correlation between patient and provider assessments was higher for the tender joint count (r = 0.5, P < 0.0001) than for the swollen joint count (r = 0.33, P < 0.001). In terms of disease activity, patients’ joint counts led to composite disease activity scores that were accurate in predicting low disease activity (LDA) or remission but were likely to overestimate active disease compared to physicians’ assessments, with a positive predictive value of a patient assessing that they were in LDA at 95% with specificity of 94%, whereas the negative predictive value was only 50% with a sensitivity of 54%. Conclusion: As remote therapeutic monitoring becomes increasingly used in health care, this study has relevance for the future expansion and application of telehealth procedures in rheumatology, particularly in providing insights regarding the types of patient training that might be required and the choice of patients in whom RA disease activity remote monitoring will have the highest utility.
Funding Information
  • Rheumatology Research Foundation
  • National Institute of Arthritis and Musculoskeletal and Skin Diseases (P30AR072583)

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