Search

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.)

Objective: Patients referred to rheumatologists are currently facing months of inefficient waiting time due to the increasing demand and rising workforce shortage. We piloted a pre-assessment of patients with suspected axial spondyloarthritis (axSpA) combining student-led clinics and telemedicine (symptom assessment, symptom monitoring and at-home capillary self-sampling) to improve access to rheumatology care. The aim of this study was to explore (1) current challenges accessing axSpA care and (2) patients' first-hand experiences., Methods: Embedded within a clinical trial, this study was based on qualitative interviews with patients with suspected axSpA (n = 20). Data was analysed via qualitative content analysis., Results: Student-led clinics were perceived as high-quality care, comparable to conventional rheumatologist-led visits. Patients expressed that their interactions with the students instilled a sense of trust. History-taking and examinations were perceived as comprehensive and meticulous. Telehealth tools were seen as empowering, offering immediate and continuous access to symptom assessment at home. Patients reported a lack of specificity of the electronic questionnaires, impeding accurate responses. Patients requested a comments area to supplement questionnaire responses. Some patients reported receiving help to complete the blood collection., Conclusion: Patients' access to rheumatology care is becoming increasingly burdensome. Pre-assessment including student-led clinics and telemedicine was highly accepted by patients. Patient interviews provided valuable in-depth feedback to improve the piloted patient pathway., (© 2024. The Author(s).)

Mobile health applications and digital therapeutics (DTx) aim to improve current patient care. Real-world data on DTx are, however, scarce. The aim of this study was to evaluate the adherence, acceptance, and efficacy of DTx in a clinical routine rheumatology setting. We conducted a prospective observational cohort study assessing the use, adherence, acceptance, and efficacy of the DTx DiGA (Digitale Gesundheitsanwendungen) by survey over 12 weeks. Patients included had to have a rheumatic disease and had been prescribed a DiGA. Acceptance was assessed using the Net promoter score (NPS). 48 patients were prescribed DiGA. Of these, 39/48 (81%) completed the follow-up survey. 21/39 (54%) patients downloaded the DTx and 20/39 (51%) used the DTx at least once. 9/39 (23%) of patients stopped quickly afterward and 5/39 (13%) reported having completed the whole DTx program. Lack of time and commitment were reported as the main reasons for non-use. Overall acceptance of DiGA was high (Net promoter score (NPS) mean (SD) 7.8/10 (2.3)). While the majority of patients (60%) reported no improvement, one subgroup of patients (7/20, 35%) who regularly used an exercise-based DTx for back pain reported symptom improvement. Acceptance of DTx in patients with rheumatic diseases is high, however onboarding to DTx use and adherence to DTx is still challenging in patients with rheumatic diseases. In a subgroup of patients with back pain, however, the use of an exercise-based DTx led to symptom improvement., (© 2022. The Author(s).)

Patient-reported outcomes (PRO) represent a cornerstone in the management of patients with rheumatoid arthritis (RA). However, PRO are currently recorded mainly on paper and only during on-site appointments. Electronic PRO (ePRO) enable continuous remote monitoring and could improve shared decision-making (SDM) and implementation of a treat-to-target (T2T) approach. This study aims to investigate patient and physician experiences, perceived drawbacks and benefits of using an ePRO web-app (ABATON RA) to digitally support SDM and T2T. A qualitative study embedded in a multicenter randomized controlled trial (RCT) consisting of interviews with RA patients and physicians that were subsequently analyzed using deductive-inductive qualitative content analysis. Between August 2021 and May 2022, interviews with ten RA patients and five physicians were completed. Three key themes emerged in the analysis: (i) App user experiences; (ii) perceived drawbacks of app-supported rheumatology care; and (iii) perceived benefits of app-supported rheumatology care. Continuous ePRO collection and a high level of standardization strained some RA patients. Certain ePRO seemed outdated and were hard to understand. Patients and physicians appreciated having an improved overview of disease activity, capturing disease flares and continuous remote monitoring. Paper- and time-saving were associated with using ePRO. Physicians feared to become too focused on ePRO data, stressed the lack of ePRO monitoring reimbursement and app interoperability. For RA patients and physicians, benefits seemed to outweigh observed drawbacks of the digitally supported SDM using ePRO. The software was easy to use and could lead to a better understanding of the individual disease course, resource allocation and treatment of rheumatoid arthritis., (© 2022. The Author(s).)

Background: The goal of the study was to investigate patients' with systemic rheumatic diseases and healthcare professionals' experiences and preferences regarding self-sampling of capillary blood in rheumatology care., Methods: Patients performed a supervised and consecutive unsupervised capillary blood self-collection using an upper arm based device. Subsequently, patients (n = 15) and their attending health care professionals (n = 5) participated in an explorative, qualitative study using problem-centered, telephone interviews. Interview data were analyzed using structured qualitative content analysis., Results: Interviewed patients reported easy application and high usability. Patients and health care professionals alike reported time and cost savings, increased independence and flexibility, improved monitoring and reduction of risk of infection during Covid-19 as benefits. Reported drawbacks include limited blood volume, limited usability in case of functional restrictions, and environmental concerns. Older, immobile patients with long journeys to traditional blood collection sites and young patients with little time to spare for traditional blood collection appointments could be user groups, likely to benefit from self-sampling services., Conclusions: At-home blood self-sampling could effectively complement current rheumatology telehealth care. Appropriateness and value of this service needs to be carefully discussed with patients on an individual basis., Trial Registration: WHO International Clinical Trials Registry: DRKS00024925. Registered on 15/04/2021., (© 2022. The Author(s).)

Objective: A steadily increasing demand and decreasing number of rheumatologists push current rheumatology care to its limits. Long travel times and poor accessibility of rheumatologists present particular challenges for patients. Need-adapted, digitally supported, patient-centered and flexible models of care could contribute to maintaining high-quality patient care. This qualitative study was embedded in a randomized controlled trial (TELERA) investigating a new model of care consisting of the use of a medical app for ePRO (electronic patient-reported outcomes), a self-administered CRP (C-reactive protein) test, and joint self-examination in rheumatoid arthritis (RA) patients. The qualitative study aimed to explore experiences of RA patients and rheumatology staff regarding (1) current care and (2) the new care model., Methods: The study included qualitative interviews with RA patients (n = 15), a focus group with patient representatives (n = 1), rheumatology nurses (n = 2), ambulatory rheumatologists (n = 2) and hospital-based rheumatologists (n = 3). Data was analyzed by qualitative content analysis., Results: Participants described current follow-up care as burdensome. Patients in remission have to travel long distances. Despite pre-scheduled visits physicians lack questionnaire results and laboratory results to make informed shared decisions during face-to-face visits. Patients reported that using all study components (medical app for ePRO, self-performed CRP test and joint self-examination) was easy and helped them to better assess their disease condition. Parts of the validated questionnaire used in the trial (routine assessment of patient index data 3; RAPID3) seemed outdated or not clear enough for many patients. Patients wanted to be automatically contacted in case of abnormalities or at least have an app feature to request a call-back or chat. Financial and psychological barriers were identified among rheumatologists preventing them to stop automatically scheduling new appointments for patients in remission. Rheumatology nurses pointed to the potential lack of personal contact, which may limit the holistic care of RA-patients., Conclusion: The new care model enables more patient autonomy, allowing patients more control and flexibility at the same time. All components were well accepted and easy to carry out for patients. To ensure success, the model needs to be more responsive and allow seamless integration of education material., Trial Registration: The study was prospectively registered on 2021/04/09 at the German Registry for Clinical Trials (DRKS00024928)., (© 2022. The Author(s).)

Introduction: An increasing number of digital tools, including dedicated diagnostic decision support systems (DDSS) exist to better assess new symptoms and understand when and where to seek medical care. The aim of this study was to evaluate patient's previous online assessment experiences and to compare the acceptability, usability, usefulness and potential impact of artificial intelligence (AI)-based symptom checker (Ada) and an online questionnaire-based self-referral tool (Rheport)., Materials and Methods: Patients newly presenting to three German secondary rheumatology outpatient clinics were randomly assigned in a 1:1 ratio to complete consecutively Ada or Rheport in a prospective non-blinded multicentre controlled crossover randomized trial. DDSS completion time was recorded by local study personnel and perceptions on DDSS and previous online assessment were collected through a self-completed study questionnaire, including usability measured with the validated System Usability Scale (SUS)., Results: 600 patients (median age 52 years, 418 women) were included. 277/600 (46.2%) of patients used an online search engine prior to the appointment. The median time patients spent assessing symptoms was 180, 7, and 8 min, respectively using online using search engines, Ada and Rheport. 111/275 (40.4%), 266/600 (44.3%) and 395/600 (65.8%) of patients rated the respective symptom assessment as very helpful or helpful, using online search engines, Ada and Rheport, respectively. Usability of both diagnostic decision support systems (DDSS) was "good" with a significantly higher mean SUS score (SD) of Rheport 77.1/100 (16.0) compared to Ada 74.4/100 (16.8), ( p < 0.0001). In male patients, usability of Rheport was rated higher than Ada ( p = 0.02) and the usability rating of older (52 years ≥) patients of both DDSS was lower than in younger participants ( p = 0.005). Both effects were independent of each other. 440/600 (73.3%) and 475/600 (79.2%) of the patients would recommend Ada and Rheport to friends and other patients, respectively., Conclusion: In summary, patients increasingly assess their symptoms independently online, however only a minority used dedicated symptom assessment websites or DDSS. DDSS, such as Ada an Rheport are easy to use, well accepted among patients with musculoskeletal complaints and could replace online search engines for patient symptom assessment, potentially saving time and increasing helpfulness., Competing Interests: JK and has received research support from Novartis Pharma GmbH. Qinum and RheumaDatenRhePort developed and hold rights for Rheport. WV, PB-B, and MW are members of RheumaDatenRhePort. WV and PB-B were involved in the development of Rheport. JK is a member of the scientific board of RheumaDatenRhePort. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Knitza, Muehlensiepen, Ignatyev, Fuchs, Mohn, Simon, Kleyer, Fagni, Boeltz, Morf, Bergmann, Labinsky, Vorbrüggen, Ramming, Distler, Bartz-Bazzanella, Vuillerme, Schett, Welcker and Hueber.)

Background: The development and potential of artificial intelligence (AI) is remarkable. Its application in all medical disciplines, including rheumatology, is attracting attention. To what extent AI is already used in clinical routine in rheumatology is unknown. In addition, the perceived barriers, potentials, and expectations regarding AI by rheumatologists have not yet been studied. Objectives: To examine the current usage and perceived barriers and facilitators of AI, including large language models (LLMs), among rheumatologists. Design: National, observational, non-interventional, and cross-sectional web-based study. Methods: A web-based survey was developed by the Working Group Young Rheumatology (AGJR) of the German Society for Rheumatology. The survey was distributed at the Congress of the German Society for Rheumatology and via social media, QR code, and email from August 30 until November 4, 2023. Results: Responses from 172 rheumatologists (55% female; mean age 43 years) were analyzed. The majority stated that they did not previously use AI (73%) in their daily practice. Eighty-eight percent of rheumatologists rated their AI knowledge as low to intermediate and 84% would welcome dedicated training on LLMs. The majority of rheumatologists anticipated AI implementation to improve patient care (60%) and reduce daily workload (62%). Especially for diagnosis (73%), writing medical reports (70%), and data analysis (70%), rheumatologists reported a potential positive benefit of AI. Main AI concerns addressed the responsibility for medical decisions (64%) and data security (58%). Conclusion: Overall, the results indicate that rheumatologists currently have little AI knowledge and make very little use of AI in clinical routine. However, the majority of rheumatologists anticipate positive AI effects and would welcome increased AI implementation and dedicated training programs. [ABSTRACT FROM AUTHOR]

The correction notice in the journal "Rheumatology International" addresses an error in the numbering of figures in an article discussing digital health applications for treating back pain in rheumatic patients. The corrected version of the article can be accessed online, and the correction has been made to accurately reflect the content. The correction was reported by multiple authors involved in the study. [Extracted from the article]