Summary of studies on RA starring remote health care
| Authors | Type of study | N (RA patients/apps reviewed) | Monitoring device | Outcome/Remarks |
|---|---|---|---|---|
| Azevedo et al. [5] (2015) | Cross-sectional | 100 | Willingness to use health-based assessment apps | Good compliance to apps |
| Barlas et al. [10] (2023) | Review article | 31 | Telemedicine, digital medicine, mHealth | PROMs showed good compliance, however, no significant difference between in-person consults. Data security is an issue |
| Chevallard et al. [11] (2021) | Retrospective | 431 | Tele-health with digital reporting of patient PROMs | General health and VAS was similar in patients who followed up digitally as compared to the ones who did an in-person clinic follow-up during COVID-19 |
| Colls et al. [12] (2021) | Observational | 78 | mHealth (electronic PRO app) | Good adherence, better remission rates |
| Cozad et al. [13] (2022) | Review article | 20 | mHealth apps | Better patient-centered care with mHealth apps, but better ones need to be developed in America |
| Dixon et al. [14] (2018) | Review article | NA | mHealth apps, EHRs | Summarized different EHRs and mHealth apps that can be integrated for better management |
| Doumen et al. [15] (2021) | Qualitative study | 58 | mHealth | Improved patient care, however, stakeholders felt that it can lead to negative-illness behavior |
| Fedkov et al. [16] (2022) | Prospective pilot | 17 | Mida Rheuma app for patients; DocBoard web-app for doctor | Improvement in QoL and disease activity |
| Ferucci et al. [17] (2022) | Observational | 122 | Telemedicine | Video telemedicine favored. Patients with higher disease activity, those who visited rheumatologist more often in the preceding year used it more |
| Ferucci et al. [18] (2022) | Observational | 122 | Telemedicine | No significant difference in outcome and quality measures between in-person follow-up group and telemedicine |
| Grainger et al. [4] (2017) | Review article | 19 apps (met inclusion criteria) | Mobile applications | Identification of good-quality apps for prospective monitoring of RA, including calculators for rheumatologists and data tracking tools for patients |
| Heiberg et al. [19] (2007) | Observational | 38 | PDA vs. pen-paper | PDA performed like traditional method |
| Foti et al. [20] (2022) | Observational | 171 | Telemedicine with use of PROMs | FM, depression and anxiety was uncovered in RA patients during the pandemic and those who needed in-person consults to address these were identified |
| Yun et al. [21] (2020) | Observational | 6,154 | CAT-PROMIS | RAPID3 and PROMIS-predicted RAPID3 had agreement |
Austin et al. [22] (2020) White et al. [23] (2021) | Proof-of-concept | 9 | Integrated patient generated health data from smartphone into EHRs | Acceptance of real time-RMT by the patient for RA self-management and care |
| McBeth et al. [24] (2022) | Prospective | 254 | Triaxial accelerometer with smartphone app | Assessed sleep variability and hygiene on QoL in RA patients |
| Mollard and Michaud [25] (2021) | Review article | NA | mHealth apps | mHealth apps aid and improve self-management of RA |
| Morales-Ivorra et al. [26] (2022) | Observational | 146 | ThermoDAI | ThermoDAI strongly correlated with USG-synovitis than PtGA |
| Müskens et al. [27] (2021) | Observational | 1,145 | eHealth platform | Better self-management, better disease control despite lesser utilization of healthcare |
| Radin et al. [28] (2022) | Prospective controlled | 20 | TuTOR app to tailor tofacitinib | TuTOR app was preferred by patients for ease of use and immediate response. However, no significant difference between paper dairy use and the app |
| Schougaard et al. [29] (2023) | Cross-sectional | 775 | Electronic questionnaire | Those compliant to remote care had a higher income, fewer comorbid conditions and faith in remote care |
| Seppen et al. [30] (2020) | Systematic scoping review | 10 studies | mHealth (SMS, web apps, mobile apps, pedometers) | mHealth tools led to positive outcome in nearly all studies included |
| Shenoy et al. [31] (2020) | Observational | 723 | Telemedicine | Aided in better disease control, compliance to treatment during the pandemic and switch was feasible and acceptable |
| van der Leeuw et al. [32] (2022) | Proof-of-concept | 279 | Dynamic flare prediction model | May aid in therapeutic decisions of tapering bDMARDs while maintaining continued remission |
| Vodencarevic et al. [33] (2021) | RCT data (from RETRO [34]) used to build a predictive model for flare | 41 | Machine learning models (stacking meta-classifier method) | Development of a clinical prediction tool for flare in patients who have achieved remission |
PROMs: patient-reported outcome measures; VAS: visual analogue scale; COVID-19: coronavirus disease 2019; PDA: personal digital assistant; FM: fibromyalgia; CAT-PROMIS: computer-adaptive testing-Patient Reported Outcomes Measurement Information System; EHR: electronic health record; QoL: quality of life; RAPID3: Routine Assessment of Patient Index Data 3; ThermoDAI: thermographic disease activity index; eHealth: electronic health; USG: ultrasonography; SMS: short message service; PtGA: patient global assessment; bDMARDs: biological disease modifying anti-rheumatic drugs; RETRO: REduction of Therapy in patients with RA in Ongoing remission study [34]; TuTOR: tailoring tofacitinib oral therapy in RA
