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Background: The diagnosis of inflammatory rheumatic diseases (IRDs) is often delayed due to unspecific symptoms and a shortage of rheumatologists. Digital diagnostic decision support systems (DDSSs) have the potential to expedite diagnosis and help patients navigate the health care system more efficiently., Objective: The aim of this study was to assess the diagnostic accuracy of a mobile artificial intelligence (AI)-based symptom checker (Ada) and a web-based self-referral tool (Rheport) regarding IRDs., Methods: A prospective, multicenter, open-label, crossover randomized controlled trial was conducted with patients newly presenting to 3 rheumatology centers. Participants were randomly assigned to complete a symptom assessment using either Ada or Rheport. The primary outcome was the correct identification of IRDs by the DDSSs, defined as the presence of any IRD in the list of suggested diagnoses by Ada or achieving a prespecified threshold score with Rheport. The gold standard was the diagnosis made by rheumatologists., Results: A total of 600 patients were included, among whom 214 (35.7%) were diagnosed with an IRD. Most frequent IRD was rheumatoid arthritis with 69 (11.5%) patients. Rheport's disease suggestion and Ada's top 1 (D1) and top 5 (D5) disease suggestions demonstrated overall diagnostic accuracies of 52%, 63%, and 58%, respectively, for IRDs. Rheport showed a sensitivity of 62% and a specificity of 47% for IRDs. Ada's D1 and D5 disease suggestions showed a sensitivity of 52% and 66%, respectively, and a specificity of 68% and 54%, respectively, concerning IRDs. Ada's diagnostic accuracy regarding individual diagnoses was heterogenous, and Ada performed considerably better in identifying rheumatoid arthritis in comparison to other diagnoses (D1: 42%; D5: 64%). The Cohen κ statistic of Rheport for agreement on any rheumatic disease diagnosis with Ada D1 was 0.15 (95% CI 0.08-0.18) and with Ada D5 was 0.08 (95% CI 0.00-0.16), indicating poor agreement for the presence of any rheumatic disease between the 2 DDSSs., Conclusions: To our knowledge, this is the largest comparative DDSS trial with actual use of DDSSs by patients. The diagnostic accuracies of both DDSSs for IRDs were not promising in this high-prevalence patient population. DDSSs may lead to a misuse of scarce health care resources. Our results underscore the need for stringent regulation and drastic improvements to ensure the safety and efficacy of DDSSs., Trial Registration: German Register of Clinical Trials DRKS00017642; https://drks.de/search/en/trial/DRKS00017642., (©Johannes Knitza, Koray Tascilar, Franziska Fuchs, Jacob Mohn, Sebastian Kuhn, Daniela Bohr, Felix Muehlensiepen, Christina Bergmann, Hannah Labinsky, Harriet Morf, Elizabeth Araujo, Matthias Englbrecht, Wolfgang Vorbrüggen, Cay-Benedict von der Decken, Stefan Kleinert, Andreas Ramming, Jörg H W Distler, Peter Bartz-Bazzanella, Nicolas Vuillerme, Georg Schett, Martin Welcker, Axel Hueber. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 23.07.2024.)

The categorization of axial spondyloarthritis (axSpA) into radiographic (r-axSpA) and non-radiographic (nr-axSpA) subtypes is important in clinical trials but may be of less value in clinical practice. This exploratory cross-sectional, multi-center study evaluated patients with axSpA under routine care at German clinical rheumatology sites (RHADAR real-world database), with a focus on imaging data used for diagnostic classifications. Our analyses included 371 patients with axSpA. The mean (standard deviation [SD]) age was 50.9 (14.0) years, disease duration was 16.4 (13.5) years, and 39.6% were female. Based on the rheumatologist's final assessment, almost half of patients had definite r-axSpA (n = 179; 48.2%), 53 (14.3%) had suspected r-axSpA, 112 (30.2%) had non-radiographic-axSpA (nr-axSpA), and 27 (7.3%) had undefined axSpA. Patients assessed with definite or suspected r-axSpA were more likely to be treated with disease-modifying antirheumatic drugs (DMARDs) (62.0% and 64.2%, respectively) compared with nr-axSpA or undefined axSpA patients (37.5% and 48.1%, respectively). Almost all patients (348/371; 93.8%) had sacroiliac joint imaging data (radiographs or magnetic resonance imaging) documented in their charts, but only 216 (58.2%) had conventional radiographs required for formal diagnosis of r-axSpA by modified New York criteria. Follow-up radiographic imaging in nr-axSpA patients was uncommon (23/216 [25.0%]) but confirmed r-axSpA in 9/23 patients (39.1%). In conclusion, radiographs were available for slightly more than half of axSpA patients. Follow-up imaging was infrequent during rheumatology care in Germany but confirmed r-axSpA in ~ 40% of patients originally considered to have nr-axSpA. The distinction between r-axSpA and nr-axSpA may be ill-defined in routine clinical practice., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Real-world data are crucial to continuously improve the management of patients with rheumatic and musculoskeletal diseases (RMDs). The German RheumaDatenRhePort (RHADAR) registry encompasses a network of rheumatologists and researchers in Germany providing pseudonymized real-world patient data and allowing timely and continuous improvement in the care of RMD patients. The RHADAR modules allow automated anamnesis and adaptive coordination of appointments regarding individual urgency levels. Further modules focus on the collection and integration of electronic patient-reported outcomes in between consultations. The digital RHADAR modules ultimately allow a patient-centered adaptive approach to integrated medical care starting as early as possible in the disease course. Such a closed-loop system consisting of various modules along the whole patient pathway enables comprehensive and timely patient management in an unprecedented manner., (©Stefan Kleinert, Peter Bartz-Bazzanella, Cay von der Decken, Johannes Knitza, Torsten Witte, Sándor P Fekete, Matthias Konitzny, Alexander Zink, Georg Gauler, Patrick Wurth, Peer Aries, Kirsten Karberg, Christoph Kuhn, Florian Schuch, Susanna Späthling-Mestekemper, Wolfgang Vorbrüggen, Matthias Englbrecht, Martin Welcker, RHADAR Group. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 20.05.2021.)

Background: Timely diagnosis and treatment are essential in the effective management of inflammatory rheumatic diseases (IRDs). Symptom checkers (SCs) promise to accelerate diagnosis, reduce misdiagnoses, and guide patients more effectively through the health care system. Although SCs are increasingly used, there exists little supporting evidence., Objective: To assess the diagnostic accuracy, patient-perceived usability, and acceptance of two SCs: (1) Ada and (2) Rheport., Methods: Patients newly presenting to a German secondary rheumatology outpatient clinic were randomly assigned in a 1:1 ratio to complete Ada or Rheport and consecutively the respective other SCs in a prospective non-blinded controlled randomized crossover trial. The primary outcome was the accuracy of the SCs regarding the diagnosis of an IRD compared to the physicians' diagnosis as the gold standard. The secondary outcomes were patient-perceived usability, acceptance, and time to complete the SC., Results: In this interim analysis, the first 164 patients who completed the study were analyzed. 32.9% (54/164) of the study subjects were diagnosed with an IRD. Rheport showed a sensitivity of 53.7% and a specificity of 51.8% for IRDs. Ada's top 1 (D1) and top 5 disease suggestions (D5) showed a sensitivity of 42.6% and 53.7% and a specificity of 63.6% and 54.5% concerning IRDs, respectively. The correct diagnosis of the IRD patients was within the Ada D1 and D5 suggestions in 16.7% (9/54) and 25.9% (14/54), respectively. The median System Usability Scale (SUS) score of Ada and Rheport was 75.0/100 and 77.5/100, respectively. The median completion time for both Ada and Rheport was 7.0 and 8.5 min, respectively. Sixty-four percent and 67.1% would recommend using Ada and Rheport to friends and other patients, respectively., Conclusions: While SCs are well accepted among patients, their diagnostic accuracy is limited to date., Trial Registration: DRKS.de, DRKS00017642 . Registered on 23 July 2019.