An AI-Powered Clinical Decision Support System to Predict Flares in Rheumatoid Arthritis: A Pilot Study.

ABSTRACT: Treat-to-target (T2T) is a main therapeutic strategy in rheumatology; however, patients and rheumatologists currently have little support in making the best treatment decision. Clinical decision support systems (CDSSs) could offer this support. The aim of this study was to investigate the accuracy, effectiveness, usability, and acceptance of such a CDSS-Rheuma Care Manager (RCM)-including an artificial intelligence (AI)-powered flare risk prediction tool to support the management of rheumatoid arthritis (RA). Longitudinal clinical routine data of RA patients were used to develop and test the RCM. Based on ten real-world patient vignettes, five physicians were asked to assess patients' flare risk, provide a treatment decision, and assess their decision confidence without and with access to

SUBMITTER: Labinsky H 

PROVIDER: S-EPMC9818406 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature