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Christopher McMaster FRACP, MBBS Department of Rheumatology, Austin Health, Victoria, Melbourne, Australia Department of Clinical Pharmacology and Therapeutic, Austin Health, Victoria, Melbourne, Australia Centre for Digital Transformation of Health and School of Computing and Information Systems, University of Melbourne, Victoria, Melbourne, Australia Search for more papers by this author
Abstract and Introduction Abstract Rheumatoid arthritis is an autoimmune condition that predominantly affects the synovial joints, causing joint destruction, pain, and disability. Historically, the standard for measuring the long-term efficacy of disease-modifying antirheumatic drugs has been the assessment of plain radiographs with scoring techniques that quantify joint damage.
Predicting disease activity using EHRs Rheumatology, as a specialty dealing with chronic, relapsing–remitting disease, has maintained a strong interest in the task of predicting future disease activity. Frequent outpatient follow-up with clinical and laboratory testing is used to detect changes in disease state and allow for interventions to treat any disease relapse or deterioration; yet precisely predicting who will experience relapse or deterioration remains a difficult task.
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