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. 2024 Dec 11;103(2):136–147. doi: 10.2471/BLT.24.292168

Randomized controlled trials of digital health interventions for rheumatic disease management: a systematic review

Essais contrôlés randomisés d’interventions de santé numérique pour la gestion des maladies rhumatismales : revue systématique

Ensayos controlados aleatorizados de intervenciones de salud digital para el manejo de enfermedades reumáticas: una revisión sistemática

التجارب العشوائية الخاضعة للتحكم في التدخلات الصحية الرقمية لإدارة الأمراض الروماتيزمية: مراجعة منهجية

用于风湿病管理的数字化卫生保健干预措施的随机对照试验：系统评价

Рандомизированные контролируемые исследования медицинской помощи с применением цифровых технологий для лечения ревматических заболеваний: систематический обзор

Anindita Santosa a,✉, James Weiquan Li b, Tze Chin Tan c
PMCID: PMC11774214  PMID: 39882494

Abstract

Objective

To evaluate the adoption, effectiveness and cost-effectiveness of digital health interventions for rheumatic disease management.

Methods

Between 25 May 2024 and 2 June 2024, we systematically searched PubMed®, Scopus, ClinicalTrials.gov, the Global Observatory for eHealth and the World Bank Open Knowledge Repository for randomized controlled trials (RCTs) evaluating digital health interventions for rheumatic disease management. We included studies published between 2000 and 2024 that reported on adoption rates and efficacy. Two reviewers independently screened the studies, extracted data and categorized the digital interventions according to the World Health Organization’s classification of digital health interventions.

Findings

Of the 455 unique records identified, 21 RCTs met the inclusion criteria. Most digital health interventions (15 studies) focused on individual-centric interventions, such as targeted communication, personal health tracking, educational tools and wearable devices. Studies in high-income countries implemented advanced, integrated digital interventions combining individual-focused approaches with health worker interventions and data services using telemedicine platforms and decision support systems. In contrast, studies in low- and middle-income countries adapted accessible technologies such as mobile messaging and telephone-based education. Many telehealth, wearable technologies and educational interventions significantly improved disease control, patient adherence, knowledge and self-efficacy. Of the five studies assessing cost-effectiveness, all found digital interventions to be cost-effective.

Conclusion

Digital health interventions show promise for managing rheumatic diseases. Tailoring these interventions to local infrastructure and emphasizing patient engagement are crucial for successful adoption. Future research should focus on standardizing evaluation methods, addressing digital divides and enhancing provider support and data services.

Introduction

Rheumatic diseases impose health burdens worldwide, with notable disparities between high- and low- and middle-income countries.1,2 In low- and middle-income countries, the burden of rheumatic diseases is exacerbated by constrained health-care resources and socioeconomic challenges, leading to higher mortality than in high-income countries.3 For example, fewer than 20 rheumatologists serve over 800 million people in the World Health Organization (WHO) African Region, resulting in inadequate diagnosis and treatment of these diseases.4,5

Addressing these disparities requires coordinated global efforts to ensure equitable access to effective treatments for rheumatic diseases worldwide. WHO and the International League of Associations for Rheumatology have initiated programmes to document and address the prevalence of rheumatic diseases in low- and middle-income countries, highlighting the need for better education for patients, their family and other stakeholders, and improved health-care infrastructure.6,7

Digital health interventions have shown considerable promise for patients with rheumatic disease, by improving health outcomes, increasing access to care and reducing health-care costs.8–11 These interventions have emerged as valuable tools for improving rheumatic disease management by enhancing patient engagement, monitoring and communication with health workers.12,13 The expectation is that the adoption of these technologies will transform the delivery of rheumatic care in various health-care settings.14

In high-income countries, digital health interventions have been extensively studied and found to be cost-effective for managing chronic diseases and promoting behavioural changes, such as smoking cessation and obesity management.15,16 These interventions often use mobile health applications, text messaging and online platforms to deliver health-care services efficiently and at low costs.16 For example, in the Republic of Korea, digital health interventions have been recommended for obesity management, showing potential for scalable and cost-effective treatment.17 In contrast, the use of digital health interventions in low- and middle-income countries is less widespread and under-researched, particularly in primary health-care settings. A 2023 scoping review highlighted that only 14 of the 28 digital health intervention categories classified by WHO were used in low- and middle-income countries, indicating a considerable gap in innovation and application.15

Despite the growing interest in digital health interventions for managing rheumatic diseases, comprehensive evidence is needed to assess their adoption and effectiveness across different health-care settings.12 Such evidence is also important for informing the development of implementation strategies and optimizing these interventions.11,18

Here, we present the results of a systematic review assessing the current state of adoption and effectiveness of digital health interventions for managing rheumatic diseases across different settings.

Methods

We performed a systematic review to evaluate the effectiveness, implementation patterns and cost-effectiveness of digital health interventions for autoimmune rheumatic disease management, using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. We registered the review with PROSPERO (CRD42024547195).

Search

We integrated relevant keywords and medical subject headings pertaining to digital health interventions, autoimmune rheumatic conditions and national income classification in our search protocol (Box 1). The search criteria included digital health interventions; rheumatic disorders; country income categories; and terms related to their implementation, efficacy, adoption and administration. We searched PubMed®, Scopus and ClinicalTrials.gov, as well as grey literature repositories, such as the Global Observatory for eHealth and the World Bank Open Knowledge Repository between 25 May 2024 and 2 June 2024 for articles published in any language between 2000 and 2024.

Box 1. Search strategy for systematic review of digital health interventions in the management and implementation of rheumatic diseases.

PubMed®

(“Digital health interventions*” OR “Telemedicine” OR “Chatbots*” OR “Wearable technologies*” OR “AI-powered predictive tools*” OR “Artificial intelligence”)

AND

(“Rheumatic diseases*” OR “Rheumatoid arthritis” OR “Lupus” OR “Ankylosing spondylitis” OR “Psoriatic arthritis”)

AND

(“Adoption” OR “Effectiveness” OR “Efficacy” OR “Implementation” OR “Management”)

ClinicalTrials.gov

("Rheumatic" OR "Rheumatoid arthritis" OR "Systemic lupus erythematosus" OR "SLE" OR "Ankylosing spondylitis" OR "Psoriatic arthritis" OR "Autoimmune arthritis" OR "Inflammatory arthritis" OR "Spondyloarthritis" ) | Other terms: ( "Digital health" OR "Digital health intervention" OR "eHealth" OR "mHealth" OR "Telemedicine" OR "Telehealth" OR "Remote monitoring" OR "Chatbot" OR "Virtual assistant" OR "Wearable" OR "Mobile app" OR "Digital therapeutic" OR "Artificial intelligence" OR "Machine learning" OR "AI" ) | Digital health

Scopus

TITLE-ABS-KEY (( "Digital health" OR "Digital health intervention*" OR "eHealth" OR "mHealth" OR "Telemedicine" OR "Telehealth" OR "Remote monitoring" OR "Chatbot*" OR "Virtual assistant*" OR "Wearable" OR "Mobile app*" OR "Digital therapeutic" OR "Artificial intelligence" OR "Machine learning" OR "AI" ) AND ( "Rheumat" OR "Rheumatoid arthritis" OR "Systemic lupus erythematosus" OR "SLE" OR "Ankylosing spondylitis" OR "Psoriatic arthritis" OR "Autoimmune arthritis" OR "Inflammatory arthritis" OR "Spondyloarthritis" ) AND( "Adopt" OR "Accept" OR "Effect" OR "Efficacy" OR "Implementation" OR "Implement" OR "Manag*" OR "Outcome" OR "Impact" OR "Feasibility" OR "Usability" OR "Adherence" ))"

Eligibility criteria

We included studies if they (i) involved individuals living with autoimmune rheumatic conditions; (ii) evaluated digital health interventions; (iii) documented adoption levels or efficacy in managing rheumatic disorders; and (iv) were randomized controlled trials (RCT) detailing the effectiveness of digital health interventions. Conversely, we excluded studies if they (i) did not primarily address rheumatic diseases; (ii) lacked digital health intervention components; (iii) failed to provide clear information on country-specific implementation or economic classification; (iv) were categorized as systematic reviews, meta-analyses or academic theses; and (v) merely described digital health interventions without assessing their implementation or efficacy.

Selection and data extraction

Using the eligibility criteria, two reviewers independently screened the titles and abstracts of all identified records. Disagreements were resolved through discussion or by involving a third reviewer. Two reviewers independently assessed the full texts of potentially eligible studies, with conflicts resolved using the same approach. Two reviewers independently extracted data using a standardized form that included the study characteristics, participant characteristics, interventions and outcomes.

Classification of interventions

We classified identified digital health interventions according to WHO Classification of digital interventions, services and applications in health (second edition).19 We mapped each intervention into one or more of the four domains: individuals; health workers; health system managers; and data services. In each article, we identified primary user groups and predominant functions for classification purposes, with crosscutting interventions categorized based on their principal operational focus.

Risk of bias

Two reviewers independently assessed the risk of bias using RoB 2, the Cochrane risk-of-bias tool for RCTs.20 They evaluated five domains: randomization process; deviations from intended interventions; missing outcome data; measurement of outcomes; and selection of reported results. We rated each domain as either low risk, some concerns or high risk.

Digital health framework

Drawing upon insights from the WHO Digital health implementation framework,21 we used the findings from the review to conceptualize a framework delineating dimensions of digital health interventions in rheumatology.

Results

Study characteristics

Our search yielded 672 records. After removing duplicates, we screened 455 unique records and obtained 29 records for full-text review (Fig. 1). Of these, 21 RCTs met our eligibility criteria.22–42 The included studies were published between 2013 and 2023, and most studies (13)24–28,34–40,42 had been conducted in high-income countries. The sample size of the included studies ranged from 30 to 320, and follow-up time ranged from 1 to 12 months (Table 1).

Fig. 1.

Fig. 1

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Flowchart illustrating the selection of studies included in the review on digital health interventions for rheumatic disease management

Table 1. Characteristics of included studies on digital health interventions in rheumatology, categorized by WHO digital health intervention classifications19 .

Study, income category Country Sample size total (intervention/control) Disease Digital health intervention
 Follow-up, months
Type WHO classification
High-income country
Rimmer et al., 201338 USA 102 Various disabilities Telehealth weight management Targeted communication to individuals (1.1)
Person-to-person communication (1.3)
Person-centred longitudinal records (2.2)		 NR
Salaffi et al., 201637 Italy 41 Rheumatoid arthritis Telemonitoring Identification and registration of health services (2.1)
Person-centred longitudinal records (2.2)
Data management (4.1)		 12
Gosse et al., 201834 France 320 Rheumatoid arthritis eHealth platform Targeted communication to individuals (1.1)
Person-to-person communication (1.3)		 12
Thurah et al., 201835 Denmark 294 Rheumatoid arthritis Patient-reported outcomes by telehealth Identification and registration of health services (2.1)
Person-centred longitudinal records (2.2)		 12
Taylor-Gjevre et al., 201836 Canada 85 Rheumatoid arthritis Videoconferencing for follow-up Person-centred longitudinal records (2.2) 9
Boedecker et al., 202040 Germany 30 Systemic lupus erythematosus Internet-based 12-week exercise programme Targeted communication to individuals (1.1)
Person-to-person communication (1.3)		 3
Khan et al., 202042 USA 50 Systemic lupus erythematosus Digital app and telehealth coaching Targeted communication to individuals (1.1)
Person-to-person communication (1.3)
Person-centred longitudinal records (2.2)		 NR
Pers et al., 202128 France 89 Rheumatoid arthritis App for connected monitoring versus conventional monitoring Person-to-person communication (1.3)
Identification and registration of health services (2.1)
Data management (4.1)		 6
Bernard et al., 202227 France 89 Rheumatoid arthritis App for connected monitoring Person-to-person communication (1.3)
Identification and registration of health services (2.1)
Data management (4.1)		 6
Lopez-Olivo et al., 202226 USA 210 Rheumatoid arthritis Facebook peer group and educational website Targeted communication to individuals (1.1)
Untargeted communication to individuals (1.2)		 6
Pouls et al., 202225 Kingdom of the Netherlands 221 Rheumatoid arthritis Gaming and disease-modifying antirheumatic therapy Targeted communication to individuals (1.1)
Person-to-person communication (1.3)		 NR
Rodríguez Sánchez-Laulhé, et al., 202224 Spain 36 Rheumatoid arthritis App for hand exercise and self-management Targeted communication to individuals (1.1)
Person-to-person communication (1.3)		 6
Skovsgaard et al., 202339 Denmark 294 Rheumatoid arthritis Follow-up using telehealth. Patient reporting outcomes to a rheumatologist or a nurse Identification and registration of health services (2.1)
Person-centred longitudinal records (2.2)
Data management (4.1)		 12
Low- and middle-income country
Zhao et al., 201933 China 92 Rheumatoid arthritis Telephone-based health education Targeted communication to individuals (1.1) 6
Song et al., 202041 China 92 Rheumatoid arthritis Telephone-based health education Targeted communication to individuals (1.1) 6
Adly et al., 202130 Egypt 60 Rheumatoid arthritis Laser acupuncture and telerehabilitation Identification and registration of health services (2.1)
Person-centred longitudinal records (2.2)		 NR
Song et al., 202132 China 118 Ankylosing spondylitis WeChat-based education Targeted communication to individuals (1.1) 3
Adly et al., 202229 Egypt 60 Rheumatoid arthritis Laser acupuncture and telerehabilitation Identification and registration of health services (2.1)
Person-centred longitudinal records (2.2)		 NR
Song et al., 202231 China 118 Ankylosing spondylitis Health education via WeChat app Targeted communication to individuals (1.1)
Person-to-person communication (1.3)		 3
Sunthornsup et al., 202223 Thailand 100 Juvenile idiopathic arthritis Brochure versus video education Targeted communication to individuals (1.1) 1
Wang et al., 202222 China 55 Ankylosing spondylitis Wearable-assisted home exercise Targeted communication to individuals (1.1)
Person-to-person communication (1.3)		 4
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App: application; NR: not reported; WHO: World Health Organization.

The quality assessment revealed robust randomization processes in the studies, although methodological challenges were noted, particularly in blinding procedures and outcome data completeness (Fig. 2).

Fig. 2.

Risk of bias in the studies included in the systematic review on digital health interventions for rheumatic disease management

Notes: we used RoB 2, which is Version 2 of the Cochrane risk-of-bias tool for randomized trials.20 Low risk indicates that the study adequately addressed the domain with minimal potential for bias. Some concerns indicates that there is a possibility of bias due to limited information or methodological shortcomings. High risk indicates a significant potential for bias affecting the study's validity.

Fig. 2

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Digital health interventions

Among the digital interventions reviewed, nine studies evaluated application (app)-based interventions,24,25,27–32,42 followed by eight studies focusing on telehealth interventions,23,33,35–39,41 three studies evaluated platform-based interventions26,34,40 and one study assessed wearable technology.22

When aligning the identified digital health interventions in the studies with the WHO classification, we noticed distinct implementation categories (Table 1). Most studies focused on individual-focused interventions, such as targeted communication and personal health tracking, leveraging mobile apps, educational tools and wearable devices to enhance patient engagement and self-management. High-income countries predominantly implemented advanced, integrated digital health interventions combining individual-focused approaches with health worker interventions and data services, using robust telemedicine platforms and decision support systems. In contrast, low- and middle-income countries effectively adapted accessible technologies for individual-focused interventions, such as mobile messaging and telephone-based education, to overcome resource constraints.

Outcomes

Various interventions showed successful outcomes (Table 2). For example, a wearable technology intervention achieved 84.2% median adherence (interquartile range: 48.7–97.9) to ankylosing spondylitis management protocol.22

Table 2. Clinical outcomes, cost-effectiveness, and safety of digital health interventions in rheumatology.

Study Disease Intervention Key outcomes Adoption and satisfaction Cost–effectiveness Adverse events
High-income country
Rimmer et al., 201338 Various Disabilities Telehealth weight management Decreased weight, improved diet and fewer barriers Moderate; high engagement Cost-effective telehealth None
Salaffi et al., 201637 Rheumatoid arthritis Telemonitoring versus conventional Increased remission and shorter time to remission High satisfaction NA None
Gossec et al., 201834 Rheumatoid arthritis eHealth platform Increased patient–physician interactions and patient satisfaction High; limited reuse NA None
Thurah et al., 201835 Rheumatoid arthritis Patient reporting outcomes by telehealth versus conventional Disease Activity Score-28 non-inferior, decreased hospital visits High; equal to conventional Likely cost-effective None
Taylor-Gjevre et al., 201836 Rheumatoid arthritis Videoconferencing No change in disease control and increased dropout Moderate; high satisfaction Cost-effective rural focus None
Boedecker et al., 202040 Systemic lupus erythematosus Internet-based exercise programme Increased maximal O2 consumption, decreased fatigue and depression levels Positive adherence and satisfaction NA None
Khan et al., 202042 Systemic lupus erythematosus Digital app and telehealth Improved health-related quality of life (less fatigue and pain), high adherence High; symptom tracking effective Potential savings None
Pers et al., 202128 Rheumatoid arthritis Connected versus conventional monitoring Fewer visits and increased quality of life High; visits down significantly Cost-effective One unrelated event
Bernard et al., 202227 Rheumatoid arthritis Connected versus conventional monitoring Lower cost, improved quality of life and quality-adjusted life years High; fewer visits Highly cost-effective None
Lopez-Olivo et al., 202226 Rheumatoid arthritis Facebook and website Increased peer support satisfaction Moderate; high satisfaction Potentially cost-effective None
Pouls et al., 202225 Rheumatoid arthritis Gaming and disease-modifying antirheumatic therapy High engagement, no change in adherence High; median play 9.7h Low-cost ehealth None
Rodríguez Sánchez-Laulhé, et al., 202224 Rheumatoid arthritis App for hand exercise and self-management Improved Michigan Hand Outcomes scores and less pain High; regular use Fewer in-person care visits None
Skovsgaard et al., 202339 Rheumatoid arthritis Patient reporting outcomes to a rheumatologist or a nurse using telehealth Lower costs and no change in disease control High; decreased visits Savings with using either a telehealth rheumatologist or nurse compared to conventional outpatient follow-up None
Low- and middle-income country
Zhao et al., 201933 Rheumatoid arthritis Telephone-based health education Increased self-efficacy, no change in Disease Activity Score-28 and Health Assessment Questionnaire scores High; positive feedback Cost-effective remote support None
Song et al., 202041 Rheumatoid arthritis Telephone-based health education Increased medication adherence High; positive feedback Potentially cost-effective None
Adly et al., 202130 Rheumatoid arthritis Laser acupuncture and telerehabilitation Decreased levels of IL-6, MDA and CRP; improved rheumatoid arthritis quality of life and increased level of ATP High; preferred to in-person Remote management. Reduced costs None
Song et al., 202132 Ankylosing spondylitis WeChat education Improved quality of life and decreased depression High; preferred format Cost-effective WeChat None
Adly et al., 202229 Rheumatoid arthritis Laser acupuncture and telerehabilitation Consistent outcomes across a range of health assessments. Improvements in measures such as rheumatoid arthritis quality of life, and key biomarkers including CRP and IL-6 High; high Cost-effective None
Song et al., 202231 Ankylosing spondylitis Health education via WeChat app Increased knowledge, self-efficacy and exercise High; positive feedback Cost-effective (mobile) None
Sunthornsup et al., 202223 Juvenile idiopathic arthritis Video versus brochure Increased immediate knowledge High; more effective in participants with limited education Cost-effective education None
Wang et al., 202222 Ankylosing spondylitis Wearable-based exercise Improvement in ankylosing spondylitis disease activity score and Bath ankylosing spondylitis disease activity index and improved quality of life High (84% adherence); positive feedback Cost-effective; broad reach Minor
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ATP: adenosine triphosphate; CRP: C-reactive protein; IL-6: interleukin-6; MDA: malondialdehyde; NA: not applicable; O2: oxygen.

Notes: key outcomes cover health-related benefits. Adoption and satisfaction include patient and provider engagement and experience. Cost–effectiveness indicates economic feasibility or savings.

Several studies reported on outcomes from educational interventions. In Thailand, video-based education improved juvenile idiopathic arthritis knowledge more than brochure-based education, with score increases of 4.44 versus 3.74 points, respectively.23 In China, app-based education through WeChat improved disease knowledge and quality of life,31,32 whereas telephone education enhanced self-efficacy.33 Using a social networking group for rheumatoid arthritis education did not result in higher knowledge than the control group, but participants in the network group had higher self-efficacy (P-value: 0.02).26

Medication adherence was a reported outcome in some studies. One study reported improved medication adherence through telehealth educational interventions, with significantly higher adherence at 12 weeks (72.87% versus 63.79%; P-value: 0.014).41 The implementation of a gaming application was associated with a non-significant 9% increase in medical adherence relative to the control group.25

In Egypt, patients receiving an acupoint detector, allowing them to receive laser therapy interventions at home, and installing an app to communicate with health workers, had significantly improved quality of life (P-value < 0.05).29,30

A French self-assessment and self-monitoring platform improved patient-perceived patient–physician interaction.34 In two studies, telehealth consultations demonstrated non-inferiority compared to conventional outpatient follow-up.35,36

One of the earliest interventions reported that people living with disabilities who participated in a weight management programme incorporating a web-based remote coaching tool and regular coaching telephone calls lost body weight.38

Disease-specific outcomes

A Danish study showed that patients reporting outcomes through telephone-based follow-ups had similar disease control compared to those receiving conventional care. The telehealth group showed a mean change in disease activity score of −0.0 versus −0.19 in the conventional group at 12 months. The authors concluded that the level of disease control was similar between patients managed by rheumatologists and those managed by rheumatology nurses.35 This finding was substantiated by a study reporting superior outcomes with telemonitoring compared to conventional outpatient follow-ups. The telemonitoring group achieved higher remission levels (38.1% versus 25.0%; P-value < 0.01) and shorter time to remission (median 20 versus 36 weeks; P-value < 0.001).37 Another study demonstrated that monitoring through smartphones significantly reduced the total number of hospital visits between baseline and six months (0.42 versus 1.93; P-value < 0.05) while maintaining disease control.28 A self-management app-based programme improved hand function, with a significant time × group effect observed for the total Michigan hand questionnaire score (P-value < 0.001) and subscales like hand function, work performance, pain and satisfaction (all P-value < 0.05). Mean differences in total scores were 16.86 points at 3 months and 17.21 points at 6 months.24

A wearable technology-assisted home exercise programme has showed significant improvements in the ankylosing spondylitis disease activity score (−0.2; 95% confidence interval: −0.4 to −0.02) Additionally, at 16 weeks, notable improvements were observed in secondary outcomes, such as pain levels, fatigue, spinal pain and mobility, and morning stiffness.22

In patients with systemic lupus erythematosus, a trial showed that internet-based individualized exercise programmes were safe, with no serious adverse events reported, and 25 of the 30 participants completing the study.40 Another randomized controlled pilot study evaluated the effectiveness of a digital therapeutic intervention combined with usual care, compared to usual care alone in improving quality of life for with systemic lupus erythematosus patients. The intervention group showed significantly greater improvements in 9 out of 11 health-related quality of life domains. Key outcomes included a 34% improvement in fatigue scores compared to 1% in the control group (P-value < 0.001), a 25% versus 0% improvement in pain interference (P-value: 0.02), and gains in emotional health, planning and reduced burden to others.42 These findings indicate the potential of digital therapeutic approaches to enhance health-related quality of life in systemic lupus erythematosus patients.

Cost-effectiveness

Several studies conducted in high-income countries have evaluated the cost-effectiveness of digital health interventions versus conventional care for patients with rheumatic diseases. A Danish study using a telehealth intervention for patient-reported outcomes found that reporting to a rheumatologist was less costly than conventional follow-up, whereas reporting to a nurse had similar costs as conventional care.39 Two studies conducted in France found connected monitoring for rheumatic arthritis to be highly cost-effective, in contrast with the lower cost-effectiveness of conventional monitoring.27,28 In Canada, one study found video conferencing for rheumatic arthritis management to be more cost-effective than in-person care.36 Authors of an Italian study suggested that intensive telemonitoring was more cost-effective than conventional management, though exact figures were not provided.37

Country comparison

Studies conducted in both high-income and low- and middle-income countries demonstrated improvements in various outcome measures, including disease activity scores,22,31,39 physical function,24,29,30 quality of life,32,42 pain24,42 and fatigue.42 However, studies from high-income countries also evaluated additional outcomes, such as cost-effectiveness,39 patient satisfaction,28,35,36 health-care resource utilization28 and patient-physician interactions.34 There was no difference in follow-up time between studies conducted in high-income versus low-and middle-income countries (Table 1).

The type of digital intervention and implementation approach varied between high-income and low- and middle-income countries. Studies from high-income countries predominantly used advanced telehealth systems, mobile applications for disease monitoring, and eHealth platforms, often integrating features such as person-to-person communication, data management, and patient-centred longitudinal records.27,35,37Conversely, studies from low- and middle-income countries frequently focused on simpler digital tools, such as health education through messaging apps or telephone-based interventions.31,33 The success of digital health interventions appears to be influenced by contextual factors, including country income levels, digital literacy and the availability of supporting health-care infrastructure.23,29,30

In both high-income and low- and middle-income countries, digital health interventions were generally well received by participants. Several studies from high-income countries reported high levels of adoption and engagement,24,25 although some noted mixed engagement or lacked detailed information on adoption levels.26 Studies conducted in low- and middle-income countries also typically reported high levels of engagement and participation, particularly for educational interventions delivered via mobile apps or telephone.22,23,31,33,41

Digital health framework

Our framework, shown in Fig. 3, delineates three critical dimensions of digital health interventions in rheumatology. The first dimension, leadership and governance, shows that high-income countries benefit from established digital infrastructure and regulatory frameworks. In contrast, low- and middle-income countries face substantial resource constraints, underscoring the need for context-specific policy development. For the second dimension, we have identified telehealth, education, and monitoring digital health interventions as the predominant modalities for service delivery in rheumatology, with the type of intervention depending on health-care priorities and resource availability in the country. The third dimension focuses on the implementation process, which follows a structured four-stage approach: planning, development, implementation and evaluation. Low- and middle-income countries often require more needs assessments during planning due to limited infrastructure, while high-income countries typically face more challenges in integrating complex systems during implementation.

Fig. 3.

Framework for digital health implementation in rheumatology care

Notes: we adapted the framework from World Health Organization digital health implementation guidance.21 Intervention types presented in service delivery patterns box are types identified in this review.

Fig. 3

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Discussion

Through a systematic review, we analysed RCTs evaluating digital health interventions for managing rheumatic diseases across various economic settings, highlighting both the advancements and challenges in digital rheumatology care. The adoption of digital health interventions shows promising outcomes in both high-income countries and low- and middle-income countries, with variations in their implementation and outcomes. High-quality RCTs from high-income countries demonstrated significant clinical benefits.27,39 In low- and middle-income countries, innovative adaptations of accessible technologies achieved health improvements,22 demonstrating the potential for cost-effective digital solutions in resource-constrained settings.

We observed a difference in technological sophistication and implementation approaches between high-income countries and low- and middle-income countries. While studies from high-income countries evaluated advanced digital platforms,27,39 implementation in low- and middle-income countries focused on more accessible interventions, such as telephone-based health education33 and social media-based programmes.32 This disparity extends beyond technological differences to include variations in the health system infrastructure, user engagement patterns and implementation strategies. These differences show the importance of tailoring digital health interventions to the specific infrastructure and needs of each setting. While emphasizing patient engagement across all contexts, there are opportunities to improve provider support and data services, particularly in resource-constrained contexts. Therefore, adapting digital solutions to local contexts and available resources is a critical factor for intervention efficacy, particularly in resource-constrained settings.

Cost–effectiveness analyses from high-income countries demonstrated promising economic outcomes. Two studies showed comparable clinical outcomes and cost–effectiveness of telehealth interventions, although methodological approaches varied considerably across health systems and implementation contexts.35,36

Notably, despite the overall promising results of the digital health interventions, our analysis revealed gaps in methodological rigour. Only a limited number of self-management applications have been evaluated through RCTs, with many studies limited to pilot trials or feasibility assessments.43,44 This limitation is particularly evident in newer mobile applications and patient-facing tools with scarce robust effectiveness data. Heterogeneity in outcome measures and implementation strategies further complicates cross-study comparisons, as illustrated by contrasting findings between studies.26 Methods for safety monitoring varied across studies, warranting careful consideration in clinical implementation. Although many trials reported no adverse events,23,27 others have documented important safety concerns, including misdiagnoses in telemedicine consultations45 and increased pain in remote monitoring programmes.46

This review has some limitations. Considerable heterogeneity in study designs, intervention types, outcomes assessed and follow-up durations complicates comparisons of studies and result synthesis. Methodological concerns, including inadequate reporting of randomization and blinding, particularly in studies from low- and middle-income countries, were prevalent. We could only assess cost–effectiveness data from high-income countries, limiting the applicability of the findings to resource-constrained settings. Short follow-up periods restricted the ability to evaluate long-term outcomes and the sustainability of the interventions. Inconsistent adoption metrics and different outcome measures further hindered cross-study comparisons. Additionally, the review’s focus on RCTs excluded valuable insights from nonrandomized or observational studies, which could provide a comprehensive understanding of real-world challenges and facilitators. Addressing these limitations in future studies will enhance the generalizability, scalability and equity of digital health interventions for managing rheumatic diseases.

In conclusion, various digital health interventions for rheumatic disease management have been evaluated across economic settings. While evidence supports their effectiveness, decision-makers should carefully consider the methodological rigour of the RCTs, safety and context-specific strategies when integrating digital interventions into clinical practice.

The digital divide between high-income countries and low- and middle-income countries presents challenges to achieving equitable access to digital health solutions, including disparities in financial resources and technical competencies. However, global collaboration in digital health offers opportunities to harness the complementary strengths of different countries and foster international partnerships. For example, such collaborations could enable data sharing, facilitate knowledge sharing, and support the development of advanced algorithms, software and applications that address diverse health-care challenges across varying contexts. Organizations such as WHO, governmental bodies and private stakeholders could play a pivotal role in addressing these disparities to promote equitable access to digital health solutions.

Acknowledgements

We thank the staff of Aaria Rheumatology, Changi General Hospital, and Singapore General Hospital, Singapore.

Competing interests:

None declared.

References

  • 1.Dey D, Sciascia S, Pons-Estel GJ, Ding H, Shen N. Health disparities in rheumatic diseases: understanding global challenges in Africa, Europe, Latin America, and Asia and proposing strategies for improvement. Rheum Dis Clin North Am. 2021. Feb;47(1):119–32. 10.1016/j.rdc.2020.09.009 [DOI] [PubMed] [Google Scholar]
  • 2.Bouraoui A, Rutter M, Williamson L, Fisher C, Sofat R, Sen D. The urgent need to move upstream in caring for people with rheumatic and musculoskeletal diseases. Rheumatol Adv Pract. 2022. Nov 7;6(3):rkac092. 10.1093/rap/rkac092 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Li M, Wu C, Yin P, Zhou M, Li M, Zeng X. Pos0967 mortality-related health metrics in rheumatic and musculoskeletal diseases an epidemiological analysis of a nationwide register-based cohort. Ann Rheum Dis. 2023;82:797. 10.1136/annrheumdis-2023-eular.3404 [DOI] [PubMed] [Google Scholar]
  • 4.Adebajo A, Gabriel SE. Addressing musculoskeletal health inequity in Africa. Arthritis Care Res (Hoboken). 2010. Apr;62(4):439–41. 10.1002/acr.20032 [DOI] [PubMed] [Google Scholar]
  • 5.Oyoo O, Moots RJ, Ganda B. Stepping into the state of rheumatology in East Africa. Rheumatology (Oxford). 2012. Aug;51(8):1345–6. 10.1093/rheumatology/ker411 [DOI] [PubMed] [Google Scholar]
  • 6.Pfleger B. Burden and control of musculoskeletal conditions in developing countries: a joint WHO/ILAR/BJD meeting report. Clin Rheumatol. 2007. Aug;26(8):1217–27. 10.1007/s10067-007-0645-7 [DOI] [PubMed] [Google Scholar]
  • 7.Olufemi A, Hakeem OB, Olalade WK, Sunday OO, Oluwole AO. Epidemiology of rheumatic and musculoskeletal diseases in a Nigerian peri-urban community: results of a cross-sectional survey using the COPCORD stage 1 model. Reumatologia. 2022;60(6):366–75. 10.5114/reum.2022.123667 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Lu L, Gold LS, Koenig KM, Lee JH, Wang G. Digital musculoskeletal program is associated with decreased joint replacement rates. Am J Manag Care. 2024. Apr 1;30(4):e103–8. [DOI] [PubMed] [Google Scholar]
  • 9.Nowell WB, Curtis JR. Remote therapeutic monitoring in rheumatic and musculoskeletal diseases: opportunities and implementation. Med Res Arch. 2023. Jul;11(7.2):3957. 10.18103/mra.v11i7.2.3957 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Naredo E, D’Agostino MA, Terslev L, Pineda C, Miguel MI, Blasi J, et al. Validation and incorporation of digital entheses into a preliminary Global OMERACT ultrasound dactylitis score (GLOUDAS) in psoriatic arthritis. Ann Rheum Dis. 2024. Jul 15;83(8):1060–71. 10.1136/ard-2023-225278 [DOI] [PubMed] [Google Scholar]
  • 11.Knudsen LR, Ndosi M, Hauge E-M, Lomborg K, Dreyer L, Aaboe S, et al. Effectiveness of a novel digital patient education programme to support self-management of early rheumatoid arthritis: a randomized controlled trial. Rheumatology (Oxford). 2024. Sep 1;63(9):2547–56. 10.1093/rheumatology/keae177 [DOI] [PubMed] [Google Scholar]
  • 12.May S, Darkow R, Knitza J, Boy K, Schwarz J, Heinze M, et al. “The simpler, the better.” A qualitative study on digital health transformation in early adopter rheumatology outpatient clinics. Inquiry. 2024. Jan-Dec;61:469580241247021. 10.1177/00469580241247021 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Nowell WB, Gavigan K, Garza K, O’Beirne R, Safford M, George M, et al. Which education topics and smartphone app functions are prioritized by U.S. rheumatology patients? A mixed-methods study. J Rheumatol. 2024. Sep 1;51(9)904–12. 10.3899/jrheum.2023-1021 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.McCallum C, Campbell M, Vines J, Rapley T, Ellis J, Deary V, et al. A Smartphone app to support self-management for people living with Sjögren’s syndrome: qualitative co-design workshops. JMIR Hum Factors. 2024. Apr 17;11:e54172. 10.2196/54172 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Xiong S, Lu H, Peoples N, Duman EK, Najarro A, Ni Z, et al. Digital health interventions for non-communicable disease management in primary health care in low-and middle-income countries. NPJ Digit Med. 2023. Feb 1;6(1):12. 10.1038/s41746-023-00764-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Kyaw TL, Ng N, Theocharaki M, Wennberg P, Sahlen K-G. Cost-effectiveness of digital tools for behavior change interventions among people with chronic diseases: systematic review. Interact J Med Res. 2023. Feb 16;12:e42396. 10.2196/42396 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Kim S, Rhee SY, Lee S; Committee of IT-convergence Treatment of Metabolic Syndrome, the Korean Society for the Study of Obesity. Effectiveness of information and communications technology-based interventions for obesity and metabolic syndrome. J Obes Metab Syndr. 2022. Sep 30;31(3):201–7. 10.7570/jomes22027 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Blanchard M, Koller CN, Azevedo PM, Prétat T, Hügle T. Development of a management app for postviral fibromyalgia-like symptoms: patient preference-guided approach. JMIR Form Res. 2024. Apr 19;8:e50832. 10.2196/50832 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Classification of digital interventions, services and applications in health. Geneva: World Health Organization; 2023. Available from: https://iris.who.int/bitstream/handle/10665/373581/9789240081949-eng.pdf?sequence=1 [cited 2024 Nov 28].
  • 20.Sterne JAC, Savović J, Page MJ, Elbers RG, Blencowe NS, Boutron I, et al. RoB 2: a revised tool for assessing risk of bias in randomised trials. BMJ. 2019. Aug 28;366:l4898. 10.1136/bmj.l4898 [DOI] [PubMed] [Google Scholar]
  • 21.Monitoring the implementation of digital health: an overview of selected national and international methodologies. Copenhagen: World Health Organization Regional Office for Europe; 2022. Available from: https://www.who.int/europe/publications/i/item/WHO-EURO-2022-5985-45750-65816 [cited 2024 Oct 31].
  • 22.Wang Y, Liu X, Wang W, Shi Y, Ji X, Hu L, et al. Adherence, efficacy, and safety of wearable technology-assisted combined home-based exercise in Chinese patients with ankylosing spondylitis: randomized pilot controlled clinical trial. J Med Internet Res. 2022. Jan 18;24(1):e29703. 10.2196/29703 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Sunthornsup W, Vilaiyuk S, Soponkanaporn S. Effect of educational brochure compared with video on disease-related knowledge in patients with juvenile idiopathic arthritis: a randomized controlled trial. Front Pediatr. 2022. Dec 9;10:1048949. 10.3389/fped.2022.1048949 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Rodríguez Sánchez-Laulhé P, Luque-Romero LG, Barrero-García FJ, Biscarri-Carbonero Á, Blanquero J, Suero-Pineda A, et al. An exercise and educational and self-management program delivered with a smartphone app (CareHand) in adults with rheumatoid arthritis of the hands: randomized controlled trial. JMIR Mhealth Uhealth. 2022. Apr 7;10(4):e35462. 10.2196/35462 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Pouls BPH, Bekker CL, Gundogan F, Hebing RC, van Onzenoort HA, van de Ven LI, et al. Gaming for adherence to medication using ehealth in rheumatoid arthritis (GAMER) study: a randomised controlled trial. RMD Open. 2022. Nov;8(2):e002616. 10.1136/rmdopen-2022-002616 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Lopez-Olivo MA, Foreman JT, Leung C, Lin HY, Westrich-Robertson T, Hofstetter C, et al. A randomized controlled trial evaluating the effects of social networking on chronic disease management in rheumatoid arthritis. Semin Arthritis Rheum. 2022. Oct;56:152072. 10.1016/j.semarthrit.2022.152072 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Bernard L, Valsecchi V, Mura T, Aouinti S, Padern G, Ferreira R, et al. Management of patients with rheumatoid arthritis by telemedicine: connected monitoring. A randomized controlled trial. Joint Bone Spine. 2022. Oct;89(5):105368. 10.1016/j.jbspin.2022.105368 [DOI] [PubMed] [Google Scholar]
  • 28.Pers Y-M, Valsecchi V, Mura T, Aouinti S, Filippi N, Marouen S, et al. A randomized prospective open-label controlled trial comparing the performance of a connected monitoring interface versus physical routine monitoring in patients with rheumatoid arthritis. Rheumatology (Oxford). 2021. Apr 6;60(4):1659–68. 10.1093/rheumatology/keaa462 [DOI] [PubMed] [Google Scholar]
  • 29.Adly AS, Adly AS, Adly MS. Effects of laser acupuncture tele-therapy for rheumatoid arthritis elderly patients. Lasers Med Sci. 2022. Feb;37(1):499–504. 10.1007/s10103-021-03287-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Adly AS, Adly AS, Adly MS, Ali MF. A novel approach utilizing laser acupuncture teletherapy for management of elderly-onset rheumatoid arthritis: a randomized clinical trial. J Telemed Telecare. 2021. Jun;27(5):298–306. 10.1177/1357633X211009861 [DOI] [PubMed] [Google Scholar]
  • 31.Song Y, Reifsnider E, Chen Y, Wang Y, Chen H. The impact of a theory-based mHealth intervention on disease knowledge, self-efficacy, and exercise adherence among ankylosing spondylitis patients: randomized controlled trial. J Med Internet Res. 2022. Oct 20;24(10):e38501. 10.2196/38501 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Song Y, Xie X, Chen Y, Wang Y, Yang H, Nie A, et al. The effects of WeChat-based educational intervention in patients with ankylosing spondylitis: a randomized controlled trail. Arthritis Res Ther. 2021. Mar 4;23(1):72. 10.1186/s13075-021-02453-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Zhao S, Chen H. Effectiveness of health education by telephone follow-up on self-efficacy among discharged patients with rheumatoid arthritis: a randomised control trial. J Clin Nurs. 2019. Nov;28(21-22):3840–7. 10.1111/jocn.15002 [DOI] [PubMed] [Google Scholar]
  • 34.Gossec L, Cantagrel A, Soubrier M, Berthelot J-M, Joubert J-M, Combe B, et al. An e-health interactive self-assessment website (Sanoia®) in rheumatoid arthritis. A 12-month randomized controlled trial in 320 patients. Joint Bone Spine. 2018. Dec;85(6):709–14. 10.1016/j.jbspin.2017.11.015 [DOI] [PubMed] [Google Scholar]
  • 35.de Thurah A, Stengaard-Pedersen K, Axelsen M, Fredberg U, Schougaard LMV, Hjollund NHI, et al. Tele-health followup strategy for tight control of disease activity in rheumatoid arthritis: results of a randomized controlled trial. Arthritis Care Res (Hoboken). 2018. Mar;70(3):353–60. 10.1002/acr.23280 [DOI] [PubMed] [Google Scholar]
  • 36.Taylor-Gjevre R, Nair B, Bath B, Okpalauwaekwe U, Sharma M, Penz E, et al. Addressing rural and remote access disparities for patients with inflammatory arthritis through video-conferencing and innovative inter-professional care models. Musculoskeletal Care. 2018. Mar;16(1):90–5. 10.1002/msc.1215 [DOI] [PubMed] [Google Scholar]
  • 37.Salaffi F, Carotti M, Ciapetti A, Di Carlo M, Gasparini S, Farah S, et al. Effectiveness of a telemonitoring intensive strategy in early rheumatoid arthritis: comparison with the conventional management approach. BMC Musculoskelet Disord. 2016. Apr 2;17(1):146. 10.1186/s12891-016-1002-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Rimmer JH, Wang E, Pellegrini CA, Lullo C, Gerber BS. Telehealth weight management intervention for adults with physical disabilities: a randomized controlled trial. Am J Phys Med Rehabil. 2013. Dec;92(12):1084–94. 10.1097/PHM.0b013e31829e780e [DOI] [PubMed] [Google Scholar]
  • 39.Skovsgaard CV, Kruse M, Hjollund N, Maribo T, de Thurah A. Cost-effectiveness of a telehealth intervention in rheumatoid arthritis: economic evaluation of the telehealth in RA (TeRA) randomized controlled trial. Scand J Rheumatol. 2023. Mar;52(2):118–28. 10.1080/03009742.2021.2008604 [DOI] [PubMed] [Google Scholar]
  • 40.Boedecker SC, Philippi KFA, Neuberger E, Schmidt S, Pfirrmann D, Haller N, et al. Twelve-week internet-based individualized exercise program in adults with systemic lupus erythematosus: protocol for a randomized controlled trial. JMIR Res Protoc. 2020. Nov 3;9(11):e18291. 10.2196/18291 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Song Y, Reifsnider E, Zhao S, Xie X, Chen H. A randomized controlled trial of the effects of a telehealth educational intervention on medication adherence and disease activity in rheumatoid arthritis patients. J Adv Nurs. 2020. May;76(5):1172–81. 10.1111/jan.14319 [DOI] [PubMed] [Google Scholar]
  • 42.Khan F, Granville N, Malkani R, Chathampally Y. Health-related quality of life improvements in systemic lupus erythematosus derived from a digital therapeutic plus tele-health coaching intervention: randomized controlled pilot trial. J Med Internet Res. 2020. Oct 20;22(10):e23868. 10.2196/23868 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Strunz P-P, Le Maire M, Heusinger T, Klein J, Labinsky H, Fleischer A, et al. The exercise-app Axia for axial spondyloarthritis enhances the home-based exercise frequency in axial spondyloarthritis patients - a cross-sectional survey. Rheumatol Int. 2024. Jun;44(6):1143–54. 10.1007/s00296-024-05600-w [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Frade S, O’Neill S, Walsh S, Campbell C, Greene D, Bird SP, et al. Telehealth-supervised exercise in systemic lupus erythematosus: a pilot study. Lupus. 2023. Apr;32(4):508–20. 10.1177/09612033231157073 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Sloan M, Lever E, Harwood R, Gordon C, Wincup C, Blane M, et al. Telemedicine in rheumatology: a mixed methods study exploring acceptability, preferences and experiences among patients and clinicians. Rheumatology (Oxford). 2022. May 30;61(6):2262–74. 10.1093/rheumatology/keab796 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Berg IJ, Tveter AT, Bakland G, Hakim S, Kristianslund EK, Lillegraven S, et al. Follow-up of patients with axial spondyloarthritis in specialist health care with remote monitoring and self-monitoring compared with regular face-to-face follow-up visits (the ReMonit Study): protocol for a randomized, controlled open-label noninferiority trial. JMIR Res Protoc. 2023. Dec 27;12:e52872. 10.2196/52872 [DOI] [PMC free article] [PubMed] [Google Scholar]

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