Remote patient-reported outcome measure triage score for monitoring disease activity and allocation of consultations in rheumatoid arthritis patients.

Abstract

Currently, expedited by the coronavirus disease 2019 pandemic, there is high demand for allocating patients in a state of low disease activity to telehealth, ideally based on remote measurements. This cross-sectional study assesses the discriminative accuracy of the Rheumatoid Arthritis Impact of Disease (RAID) questionnaire regarding high and low disease activity. Furthermore, we aimed to optimize this classification, developing a remote triage score based on RAID and other patient-reported outcome measures (PROMs). Data were acquired from an outpatient clinic cohort of chronic rheumatoid arthritis patients at a large trainee hospital in the Netherlands. Patients were divided into high and low disease categories, based on 28-joint Disease Activity Score-C-reactive protein. Least absolute shrinkage and selection operator logistic regression were performed, including RAID item scores and other PROMs. Receiver operating characteristics curves and areas under the curve (AUCs) were obtained, and cut-off scores were based on predefined criteria of 90% and 95% sensitivity. In total, 278 patients were analysed, of whom 77.2% were identified as having low disease activity. RAID results correlated with DAS28-CRP, showing good performance. The regression model included the RAID items pain and functional disability assessment, and the self-reported swollen joint count (SR-SJC). With an AUC of 0.88 (95% confidence interval 0.84-0.92), this model performed better than the RAID total score. A remote triage score based on a composite score of pain, functional disability assessment, and SR-SJC can detect a sufficient proportion of patients with low disease activity who can be allocated to remote consultations.