Telemedicine for patients with rheumatic diseases: Systematic review and proposal for research agenda

Author’s Accepted Manuscript Telemedicine for patients with rheumatic diseases : Systematic review and proposal for research agendaTele-Rheumatology Matteo Piga, Ignazio Cangemi, Alessandro Mathieu, Alberto Cauli www.elsevier.com/locate/semarthrit

PII: DOI: Reference:

S0049-0172(16)30454-1 http://dx.doi.org/10.1016/j.semarthrit.2017.03.014 YSARH51170

To appear in: Seminars in Arthritis and Rheumatism Cite this article as: Matteo Piga, Ignazio Cangemi, Alessandro Mathieu and Alberto Cauli, Telemedicine for patients with rheumatic diseases : Systematic review and proposal for research agendaTele-Rheumatology, Seminars in Arthritis and Rheumatism, http://dx.doi.org/10.1016/j.semarthrit.2017.03.014 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

RUNNING HEAD: Tele-Rheumatology Telemedicine for patients with rheumatic diseases : systematic review and proposal for research agenda.

Matteo Piga, MD,*, corresponding author. Ignazio Cangemi, MD,* Alessandro Mathieu, Prof., MD, Alberto Cauli, Prof., PhD, MD.

*MP and IC equally contributed to this work. Chair of Rheumatology and Rheumatology Unit, University Clinic and AOU of Cagliari, Cagliari, Italy. FUNDING: None DISCLOSURE STATEMENT: The authors declare no conflicts of interest. WORD COUNT: 4355 Address reprint requests and correspondence to: Dr Matteo Piga, MD Chair of Rheumatology and Rheumatology Unit University Clinic AOU of Cagliari SS 554 – 09 042 Monserrato – Cagliari Italy Phone: +39 (0)70 – 675.4069 Fax: +39(0)70 - 513157 E-mail address: [email protected] E-mail address: [email protected]

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ABSTRACT Objective. To systematically review the scientific literature regarding tele-rheumatology and draw conclusions about feasibility, effectiveness and patients satisfaction. Methods. Pubmed, Scopus and Cochrane database searches were performed (April 2016) using relevant MeSH and keyword terms for telemedicine and rheumatic diseases. Articles were selected if reporting outcomes for feasibility, effectiveness and patients satisfaction and methodologically appraised using the Cochrane Collaboration’s tool for assessing risk of bias and a modified version of CONSORT 2010 Statement. Results. A total of 177 articles were screened, 23 were selected for the present review butonly 9 were RCTs. Five studies reported on feasibility, 14 effectiveness and 9 satisfaction rates for different telerheumatology interventions grouped in synchronous (remotely delivered consultation) and asynchronous (remote disease activity assessment; tele-monitoring of treatment strategies or rehabilitation; remotely delivered self-management programs). Seven studies (30.4%) were on rheumatoid arthritis, 2 (8,7%) were on systemic sclerosis (1 including also rheumatoid arthritis patients), 5 (21,7%) on fibromyalgia, 2 (13.38,7%) on osteoarthritis, 3 (13,0%) on juvenile idiopathic arthritis and 4 (17,4%) on mixed disease cohorts.. Interventions and outcomes heterogeneity prevented meta-analysis of results. Overall, feasibility and patient satisfaction rates were high or very high across intervention types. Effectiveness was equal or higher than standard face-to-face approach in controlled trials which, however, were affected by small sample size and lack of blinding participants according to appraisal tools. Conclusion.

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Telemedicine may provide a well-accepted way to remotely deliver consultation, treatment and monitoring disease activity in rheumatology. Higher quality RCTs demonstrating effectiveness of different tele-rheumatology interventions are needed.

KEYWORDS: Telemedicine, Tele-Rheumatology, Systematic Literature Review, Rheumatic Diseases, Rheumatoid Arthritis, Fibromyalgia.

1. INTRODUCTION Telemedicine is the remote delivery of healthcare services and clinical practices through medical data transmission via Information and Communication Technologies (ICT). Undeniable benefits are associated with the spreading of telemedicine, which can represent an additional and potentially suitable tool for diagnosis, treatment, rehabilitation and follow-up monitoring of patients[1]. Growing prevalence of chronic diseases, shortages in economic resources, increased patients’ demands for greater availability and better quality of healthcare services make telemedicine an interesting challenge for present and future. It was firstly employed to ensure access to healthcare in rural areas enabling patients to easily obtain specialty services while remaining within their local community [2–4]. More recently, telemedicine has found wider application in chronic diseases for increasing the number of follow-up consultations and encouraging tight home-monitoring in order to improve patients outcome [5,6]. Furthermore, limiting the number of hospital visits reduces travel time and related stress but also promises financial advantages reducing costs for both patients and healthcare payers [3,4,7]. Telemedicine has different possible applications in rheumatology and an increasing number of articles was published on specialized journal in last years. A heated debate was engaged on the potential utility and efficacy of telemedicine service in rheumatology, but emerging studies in this field are so encouraging that led some Authors to coin the term “tele-rheumatology”[8–10]. 3

Although the number of studies on tele-rheumatology seems booming, it lacks a systematic review of the scientific literature focusing on unmet needs in this field and outlining a research agenda for future studies. The objective of our study was to systematically review the scientific literature regarding telemedicine applications in rheumatology and to draw conclusions about feasibility, effectiveness and patients satisfaction for tele-rheumatology interventions proposed so far.

2. MATERIALS AND METHODS A panel of 3 rheumatologists (AM, MP and IC) developed the review protocol according to PRISMA guidelines [11] and outlining search strategy, eligibility criteria for study inclusion, methods of study selection and quality assessment. 2.1 Search strategy. A MeSH terms search strategy was formulated in PubMed and then adapted for use in Scopus and Cochrane Library. A combination of the following terms was used: “rheumatology”, “rheumatic diseases”, “connective tissue diseases”, “spondylarthritis”, “telemedicine”, “remote consultation”, “remote sensing technology”, “telemetry”, “self-care” (see supplementary file). The databases were searched from 1st of January 1990 to 15th of April 2016 looking for articles reporting on feasibility, effectiveness and satisfaction (Outcome) of various telemedicine applications (Intervention), being or not being compared with standard procedure (Comparison), in patients with rheumatic diseases (Population). Afterwards, search was completed by checking the references from selected studies as well as from review articles and other sources known to the Authors.

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2.2 Inclusion criteria and study selection. Studies were included in this review if: a) published in English, French or Italian; b) published as full-length article; c) designed as randomized clinical trial (RCT), controlled clinical trial (CCT), “Before & After” (B&A) or observational study types. Exclusion criteria were: a) editorials, reviews, case reports and conference abstracts study types; b) lack of reporting measures of outcome (e.g. articles exclusively reporting on organization and structure of tele-rheumatology services were excluded); c) duplicated data. Title and abstract were screened for eligibility criteria by two reviewers (MP and IC) who also completed the full text review and data extraction. Using a standardized template designed for this review the following data were extracted: type of study, type of disease, number of patients, number of controls, blinding, type of intervention and comparison, measures of feasibility, effectiveness (or validity) and patients satisfaction. Disagreements were resolved by consensus. 2.3 Quality assessment. Quality of each study was independently evaluated by two reviewers (MP and IC) by applying the Cochrane Collaboration’s tool, a 7 domains tool, for assessing risk of bias [12,13]. It rates study characteristics in “High risk of bias”, “Low risk of bias” or “Unclear”. For RCTs a modified version of CONSORT 2010 Statement (Consolidated Standards of Reporting Trials) was used too [14]. CONSORT is a 25 items checklist providing guidance for reporting RCT, also applied to study quality assessment [15,16]. Our modified version considered items 2-14 and 17-19, excluding “Title and abstract”, “Baseline data”, “Numbers analyzed” and “Discussion” as they were useless for our study purposes. Each item was rated with a semi-quantitative scale (“Present and valid”, “Not present or not valid” or “Not evaluable”). Primary authors were contacted if necessary to provide additional data. Disagreements between reviewers were resolved by consensus.

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3. RESULTS 3.1 Search results. The electronic databases search yielded 177 publications for screening and 59 articles retrieved for further evaluation. After exclusion of 36 articles, 23 were selected for present review (Figure 1). Characteristics of controlled and uncontrolled studies are shown in Table 1 and Table 2, respectively. Worthy of note is the heterogeneity of published studies in terms of intervention. Therefore, we opted for clustering studies according to disease: 7 studies (30,4%) included patients with Rheumatoid Arthritis (RA), 2 (8,7%) were on Systemic Sclerosis (SSc) and 1 of them also included patients affected by RA, 5 (21,7%) studies were on Fibromyalgia (FM), 2 (8,7%) studies on Osteoarthritis (OA), 3 (13,0%) on Juvenile Idiopathic Arthritis (JIA) and 4 (17,4%) on mixed disease cohorts.

3.2 Rheumatoid Arthritis Studies on RA can be divided in 3 groups according to type of intervention: a) remote disease activity assessment [17–19]; b) tele-monitoring of treatment strategies [20]; c) ICT delivered self-management program [21–23]. Three observational studies proposed different options for remote self-assessment of RA disease activity. Connecting an hand dynamometer to a smartphone, Espinoza et al [17] showed a negative correlation between handgrip strength and DAS28 score (Power grip: r = - 0.65 (95% CI: 0.76, - 0.51, P<0.001) measured at one point in time and longitudinally between ΔPower grip and ΔDAS28 (r = - 0.76, 95% CI: - 0.88, - 0.56). Nishiguchi et al [18] used a smartphone application for self-evaluation of modified Health Assessment Questionnaire (mHAQ), tender (sTJC) and swollen joint counts in 65 patients. Using a stepwise linear regression model, sTJC (b=0.581, p<0.001) and mHAQ (b=0.264, p=0.013) resulted significantly associated with the DAS28 evaluated by a Rheumatologist. Another study [19], aimed to estimate the validity of a modified version of DAS28 6

(vDAS28), calculated with a phone self-reported tender/swollen joint count, compared with DAS28 assessed by a health care practitioner. The correlation between the two scores was good with an R value of 0.895. The only study included in the second group aimed to evaluate the efficacy of a therapeutic tight-control strategy based on tele-monitoring. This 12-months RCT named RETE-MARCHE (REmote Tele-monitoring for Managing Rheumatologic Condition and HEaltcare programs) [20] randomly allocated 44 early RA patients into two arms: i) the tele-monitoring intensive strategy (TIS) and ii) the conventional strategy. TIS consisted of a website platform for patient uploading of RA Impact of Disease (RAID) questionnaire data to remotely control disease activity. If RAID did not reach the improvement preset threshold in the first 2 or 3 months of treatment, the system notified it to the clinical case manager and patient was asked to return for follow-up visit and treatment modification. Patients in TIS achieved faster (median: 20 vs. 36 weeks; p<0.001) and higher CDAI remission rate (CDAI<2.8: 38.1% vs. 25% at 1-year; p<0.01) than conventionally treated patients. Patients in TIS reported a mean satisfaction rate of 4.28 on a 5-point scale. Studies in the third group remotely delivered different self-management programs to patients with RA. Shigaki et al [21] evaluated the effectiveness of a 10-week web-based self-management program (RAHelp.org) with weekly educational modules in a 2-group (1:1) waiting-list controlled RCT including 106 RA patients. Effect size was higher in the interventional group for the Arthritis Self-Efficacy Scale (ASES) and the Quality of Life Scale (QoLS) immediately post-intervention (ASES: ES 0.92, P<0.001; QoLS: ES 0.66, P = 0.003) and 9 months later (ASES: ES 0.92, P<0.001; QoLS: ES 0.71, P=0.004). Hoving et al. [22] performed a B&A study on 23 RA patients for evaluating effectiveness and patients satisfaction of an e-health self-managed program with a 3-step problem-solving strategy remotely delivered by a rheumatology nurse and provided with personal support and feedback. The Work Ability Index, RA-Work Instability Scale and Work Limitation Questionnaire, as work functioning measures, showed no statistically significant over 3 months. Overall, 95% of participants were satisfied with the program. Van den Berg et al. [23] allocated 160 7

RA physically inactive patients to: i) an interventional group providing web-based individualized training (IT) program with individual guidance, bicycle ergometer and group contacts, and ii) a control group providing only general training (GT) information on similar exercises and physical activity. Primary outcome, represented by the proportion of physically active patients according to the Dutch public health recommendations, was significantly higher in the IT than in the GT group at 6 (38% versus 22%; P=0.041) and 9 months (35% versus 11%; P=0.001) regarding a training moderate intensity level and at 6 (35% versus 13%), 9 (40% versus 14%), and 12 months (34% versus 10%; all P < 0.005) regarding a vigorous intensity level.

3.3 Systemic Sclerosis Studies on SSC focused on tele-monitoring of rehabilitation protocol [24] and ICT delivered self-management program [25]. The 12-week pilot RCT named Re.Mo.Te. [24], tested a store-and-forward tele-monitoring system for hand rehabilitation in 20 patients with SSC and 20 with RA allocated to two different experimental and control arms (10:10). The telemedicine system consisted of a portable device and the related tele-monitoring infrastructure enabling physicians to analyze exercise protocol execution, by measuring associated physical variables (e.g. strength, speed), at the end of workout session on a remotely connected computer [26]. According to a mixed ANOVA model patients enrolled in the experimental arms showed a statistically significant intra-group improvement on primary (SSc-HAQ p=0.016 and SSc-Dreiser’s index p=0.006; RA-HAQ p=0.015 and RA-Dreiser’s index p=0.013) and secondary (e.g. range of motion, hand grip) outcomes. However, no statistically significant difference was highlighted when compared to controls, who performed a comparable kinesiotherapy protocol using common objects, probably because the small number of participants. Feasibility was very high with 89.1% of remote sessions attended. Using QUEST 2.0 participants expressed a 4.5 mean satisfaction rate on a 5-point scale for the tele-monitoring system.

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Poole and Colleagues [25] enrolled 16 SSc patients in a B&A study aimed to test the effectiveness of a 10-week web-based self-management program. There were significant improvements in mean scores for outcomes measuring ability to manage care (ES 0.62, p=0.025) and health efficacy (ES 0.72, p=0.012), and significant decreases in fatigue (ES 0.55, p=0.045) and depression (ES 0.71, p=0.013) scales. The program received also a good satisfaction rate, mean scores ranging from 4.2 (web site was visually appealing) to 4.9 (information presented clearly) on a 5-point scale.

3.4 Fibromyalgia Studies on patients with FM were divided in 2 groups according to type of intervention: a) tele-monitoring of treatment strategies [27], b) ICT delivered self-management programs [28–31]. Salaffi et al. [27] evaluated the feasibility of a telemedicine intervention consisting of a special website to remotely monitor the Fibromyalgia Impact Questionnaire Revised (FIQR) and Fibromyalgia Activity Score, as primary outcomes of a RCT comparing a multi-component exercise program with conventional treatment. Feasibility resulted in 97.9% of sessions attended. Second group included 4 studies. Valleyo et al. [28] evaluated the effectiveness of an Internet-based Cognitive-Behavioral Therapy (ICBT) in 60 patients randomly assigned to either: a) the waiting list group, b) the CBT group, or c) the ICBT group. FIQ and other secondary outcomes were assessed at baseline, after 10 weeks, and at 3, 6, and 12-month follow-up. After 10 weeks of treatment, only the CBT group showed improvement in FIQ as primary outcome (F (1, 57) = 41.96, p < .001). Both CBT and ICBT groups demonstrated improvement in various secondary outcomes. Interestingly, results obtained after treatment were maintained or improved only in the ICBT group with a size effect for FIQ of d = 0.25 (p < .05), according to Cohen's, at 6 months and d = 0.32 (p < 0.001) at 12 months. In the CBT group, some measures worsened compared to post-treatment. Ljótsson et al. [29] published a B&A study testing effectiveness of an ICBT in 41 patients. Outcome measures were self-rated and administered online at 3 different moments: pretreatment, post9

treatment and after 6-month follow-up. Considering FIQ, the pretreatment to post-treatment effect size was d=0.71 (95% CI, 0.46-0.97), and the pre-treatment to 6-months post treatment follow-up effect size was even larger, d=0.96 (95% CI, 0.66-1.27). Camerini et al. [30] developed a 3-section website for Internet-based patient education intervention, named ONESELF (www.oneself.ch), and tested it on 209 FM patients enrolled in a B&A study. The main objective was to improve selfmanagement and health outcomes by increasing patients’ knowledge. Website usage increased exercise amount (p<0.05) which was directly related to reduced drug intake (p<0.001) and improvement in FIQ (p<0.001). ONESELF also received a positive feedback with 88% of patients being satisfied with the website. The RCT by Williams et al. [31] evaluated the effectiveness and satisfaction of adding an ICB self-management program, the Web-Enhanced Behavioral SelfManagement (WEB-SM), to the standard pharmacological care in 118 patients randomly allocated in two arms (59:59). The WEB-SM was based on an Internet website, named “Living Well with Fibromyalgia”. After 6 months, patients in the WEB-SM group showed a statistically significant improvement in pain intensity (Brief Pain Inventory: F(1,115)=5.67, p<0.01) and physical functional status (SF-36, Physical Functioning Scale: F(1,115)=5.08, p<0.03) compared to control group. Finally, general satisfaction and satisfaction with the amount of help were 91% and 82%, respectively, in WEB-SM group.

3.5 Osteoarthritis Two studies in patients with OA reporting on ICT delivered self-management programs [32,33], were included in this review. Umapathy et al. [32] conducted a 12-month CCT in 195 patients affected by knee and/or hip OA on a web-based self-management program called My Joint Pain. Intervention provided participants with general and user-specific information, monthly assessments with validated instruments, and progress-tracking tools whereas non-users served as controls. After 12 months of exposure to the program no difference were observed between the two groups in Health Evaluation 10

Impact Questionnaire as primary outcome, but there were significant improvements for users compared to nonusers in self-management (15% vs 2%, P=0.001) and weight reduction (3% vs –6%, P=0.03) measured on the Osteoarthritis Quality Indicator. In a 6-week RCT, Cuperus et al. [33] compared the effectiveness of a non-pharmacological multidisciplinary face-to-face self-management treatment program with a similar telephone-based program on daily function in 147 patients with generalized OA. The primary outcome was the difference in mean HAQ score between both treatment groups assessed at 6, 26 and 52 week time points. No differences in effectiveness between both treatment programs were observed on the primary outcome (-0.03; 95% CI -0.14 - 0.07) or on secondary outcome measure except for a larger improvement in pain in the face-to-face treatment group (1.61; 95% CI 0.01 - 3.21).

3.6 Juvenile Idiopathic Arthritis Overall, 3 studies in patients with JIA [34–36] evaluated ICT delivered self-management approaches for children and adolescents affected by rheumatic diseases. Armbrust et al. [34] published a feasibility study that evaluated an online interactive, educational and CB program aimed to increase physical activity, named Rheumates@Work (R@W), in 64 JIA patients (aged 8 to 13). At the end of a 14-week period, satisfaction with the program was that 82% of participants and 99% of their parents liked R@W. At the end of the program, 93.8% of participants had completely fulfilled all the assignments on a proper way and 95% of them understood the theoretical topics well or very well. Two studies [35,36] tested the effectiveness and feasibility of a self-management internetbased program, “Teens Taking Charge: Managing Arthritis Online”, aimed to improve diseasespecific knowledge and reducing pain by increasing the therapeutic alliance among patients with JIA and their healthcare providers (coach). A non-blind RCT allocated 46 adolescents with JIA in an interventional arm and an attention control arm in order to assess effectiveness of the web-based program. After 12 weeks of intervention exposure there were no significant group differences in QoL, self-efficacy 11

and adherence outcome measures. Overall, 91% of participants randomized to the experimental arm completed the program. Then, a 12-week B&A study tested the “Teens Taking Charge” effectiveness

in increasing the therapeutic alliance between patients and coaches The 14 participants (mean 14.57 years, range 12-18) reported relationship with their coach was strong (mean 4.2, on a 5-point scale) and rated their level of comfort with “telling their coach things about themselves” as high (mean 4.4, on a 5-point scale). Working Alliance Inventory for Chronic Care, as a measure of therapeutic alliance, was inversely correlated to a decrease in reported pain (r=0.625, p=0.03).

3.7 Mixed disease cohorts Last group is composed by 4 studies performed in mixed disease cohorts. According to type of intervention they were divided in 2 groups: a) telemedicine delivered consultation [37,38] and b) ICT delivered self-management program[39,40]. Satisfaction levels of 49 patients, attending tele-rheumatology service in a rural Australian region, were compared with those of 48 patients receiving traditional face-to-face outpatient consultation [37]. Comparing models of care, there were no statistically significant differences in satisfaction level apart from doctor-patient relationship which was in favor of the face-to-face approach (p=0.018). Overall, 90% of patients attending telemedicine consultations were satisfied with care received, 85% saved time and money and 63% reported they would rather receive telerheumatology evaluation than travel to the nearest referral center 3 hours away. Regardless telemedicine consultation was a first or a follow up appointment no difference in patient satisfaction was found. Graham et al. [38] evaluated the diagnostic accuracy of tele-delivered visits in a 4months observational study. The diagnostic accuracy of audio-visual and phone call visits was compared with face-to-face visit considered as the “gold standard”. Overall, 35% of diagnoses were made correctly over the telephone and 40% over the video-phone so there was no significant difference in the diagnostic accuracy between these two ICT methods.

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Ammerlaan and colleagues [39] tested feasibility of a 6-week internet-based program, named “Challenge your arthritis”, based on the Arthritis Self-Management Program of Stanford University. They involved 22 young adults (mean age 21.5 years, range 17-25) affected by rheumatic diseases (i.e. chronic arthritis, FM and connective tissue disease) voluntarily choosing either for online (n=12) or face-to-face program (n=10). No statistically significant differences were reported between groups. Seven out of 10 participants rated the online program as useful. All participants found it ‘easy to use’, appreciated the ‘look and feel’ of the website and even would participate again to the online program. Lorig et al. [40] conducted a RCT evaluating effectiveness of adding an Internet-based Arthritis Self-Management Program (ASMP) to usual care in patients with RA, osteoarthritis (OA) or FM (n=855) randomized into interventional (n=433) or usual care control (n=422) groups. Outcomes (6 health status, 4 health behavior and self-efficacy and 5 health care utilization measures) were evaluated by completion of online questionnaires after 6-month and 1year follow-up. Experimental intervention conferred statistically significant improvement in health statuses measures (health distress: p<0.001, activity limitation: p<0.001 and pain: p<0.001) compared to usual care control. 3.8 Studies Quality assessment. Quality of each study evaluated according to the “Cochrane Collaboration’s tool for assessing risk of bias” is summarized in Figure 2. Overall, quality of included studies was low due to high risk of bias in several domains, with the exception of RCTs which showed high quality (Table 3) also according to the modified CONSORT 2010 Statement (Table 4). However, RCTs major methodological bias related to lack of sample size determination [20,21,23,24,35,40] and poor blinding methods [20,21,24,28,31,33,35,40] raised concerns about the real effectiveness of telerheumatology interventions. Recruitment of small number of patients [20,24,35] might be due to high cost of telemedicine systems and devices which could be hardly covered by pilot-designed independent projects. Lack of participants blinding [20,21,24,28,31,33,35,39] was mainly due to telemedicine interventions requiring the use of specifically developed devices [24] and direct feed13

backs and interactions between patients and healthcare providers [20,24,28,31,39] who were also assessors.

4. DISCUSSION This systematic literature review of telemedicine applications to rheumatology provided evidence of a roused interest in tele-rheumatology leading to a remarkable increase in number of published studies mostly over the last 5 years. Synchronous tele-rheumatology application [41], requiring a live interaction between health professionals and patients, is meant to offer a virtual alternative to the in-person Rheumatologist’s visit. This ICT use probably represents what most people first think of about telemedicine and may represent the best way to improve timely healthcare access over distance [3], but surprisingly its application to rheumatology has been only addressed by a small number of studies. Telerheumatology visits were associated with high patient satisfaction rates and reported as a way to overcome personal expense and travel time lost [3,37]. However, evidence concerning accuracy of virtual visits was apparently disappointing, with a study showing only 40% of diagnosis made correctly through video-teleconferencing visits [38].However, reliability of this data was impaired by small sample size and some methodological concerns, including the use of ICT considered obsolete today [38]. In Canary Islands (Spain), 53% remote triage consultations to primary care physicians were resolved without the need for a patient’s appointment at the rheumatology offices [42]. Kulcsar and colleagues reported on their early experience of a tele-rheumatology service from the rural areas of New Hampshire and Vermont (U.S.A.) recognizing 20% of patients deemed unappropriated for tele-visiting and suggested a triage tool to identify them [43]. Moreover, Authors highlighted the need to employ qualified physicians in performing the role of presenter (the person who is with the patient in the remote site and facilitates the visit) in order to enhance the accuracy of tele-rheumatology consultation and suggested that the proper triage of patients would be more

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effective than try to improve the skills of a non-specialized presenter, such as a nurse or other health providers [43]. Asynchronous ICT uses [41], where doctors and patients do not need to be connected and communicating at the same time, have found wider application in tele-rheumatology. Tele-delivered ICBT and self-management interventions, proven to be effective in chronic pain [44] and chronic diseases such as diabetes [45], were designed for patients with rheumatic diseases. They relied on web-based platform allowing home-access to the program contents and making them readily accessible by patients at their easy convenience. Consequently, internet-delivered programs had very high feasibility [35,39] and satisfaction [25,30,31] rates, even in young patients [34–36]. However, effectiveness data showed conflicting results, in fact, most of the studies revealed improvement in outcome measures of health status [21,23,25,28–32,40] but few others did not [22,33,35]. Such a difference may lie in study design or in telemedicine protocol. Noteworthy, some studies proved greater and more lasting effect than standard approaches in the long time, but not in the short time [21,23,28–30,32,40], probably as an effect of better ability of participants to access the teledelivered programs at the expense of therapist-patient relationship. Remote monitoring of outcomes had its most enthusiastic applications in patients with RA, where the principles of tight-control and treat-to-target approach [46,47] were transferred to telemedicine, as done for management of other chronic diseases such as diabetes [5] and heart failure [6]. Two small RCTs demonstrated high feasibility [24] and satisfaction [20,24,48] rates for different tele-monitoring approaches. Higher and faster CDAI remission rates were demonstrated for patients on telemedicine-driven intensive treatment strategy [20], whereas tele-monitoring self-directed kinesiotherapy sessions was effective to improve hand function after drug-induced remission [24]. However, such a promising results were weakened by small sample size and methodological biases. According to retrieved findings, telemedicine may offer the opportunity to optimize rheumatology services by providing an additive way to deliver care through remote triage consultations and video-teleconferencing visits (synchronous), tight-control of disease activity, 15

treatment monitoring and delivering of self-management programs (asynchronous). Such an alternative approach would be very well-accepted by patients [20,24,31,37] solving the need for a timely access to healthcare over distance [3,47,48] by bridging the workforce gap [7] in areas/countries where rheumatologists lacks [49–51]. However, before tele-rheumatology could have substantial effect on healthcare and somewhat replace traditional services, more rigorous proofs for effectiveness [4] and cost-effectiveness [52] are major unmet needs. The research agenda should prioritize designing adequately powered RCTs in order to: a) confirm tele-visiting reliability and implement strategies to increase correct diagnosis rates and identify patients who can effectively benefit from video-teleconferencing visits; b) confirm the effectiveness of monitoring response to treatment in patients with RA and extend this model to other chronic inflammatory arthritis; c) implement strategies for tele-rehabilitation in patients with rheumatic diseases; d) explore new telemedicine application to patients with rheumatic disease (e.g. cardiac monitoring in selected connective tissue diseases). Future studies should apply the most modern technologies, in particular those Internet-based. Moreover, as attempted for other telemedicine applications [53], an accurate standardizing process to overcome methodological biases and define outcome panels for telerheumatology interventions is required. This is imperative to fill the gap with other fields of telemedicine, as diabetes care where a recent meta-analysis of 55 RCTs demonstrated a higher effectiveness (Hedges’s g = -0.48, p < 0.001) of telemedicine in determining changes of HbA1c level as well-defined target outcome [5]. Such a research agenda should be supported by specifically addressed financial programs to cover the cost of purchasing telemedicine hardware and software or developing new technologies. Although a sizeable inceptive economic effort, healthcare payers would be hopefully rewarded by future perspective of money savings through reduction of direct and indirect costs [3,48]. Furthermore, if tele-rheumatology systems would become more widely diffused the prorated cost will also decline, but to encourage the spread of telemedicine as a generalizable medical care model several legislative and regulatory challenges need to be addressed, possibly simplified and unified across countries [54]. 16

5. CONCLUSIONS In conclusion, improvement in ICT and the need for new healthcare solutions have pushed tele-rheumatology research leading to a remarkable increase in published RCTs and, consequently, to an improved quality of available data. Although proved having a high feasibility and patient satisfaction rates, the evidence for a superior or equal effectiveness of tele-rheumatology compared to the standard face-to-face approach was weakened by some methodological biases and wide heterogeneity of interventions preventing to draw definitive conclusions. Optimistically, by verifying and addressing these concerns in future studies, tele-rheumatology will become an important part of management in rheumatic diseases.

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[28] Vallejo MA, Ortega J, Rivera J, Comeche MI, Vallejo-Slocker L. Internet versus face-to-face group cognitive-behavioral therapy for fibromyalgia: A randomized control trial. J Psychiatr Res 2015;68:106–13. doi:10.1016/j.jpsychires.2015.06.006. [29] Ljótsson B, Atterlöf E, Lagerlöf M, Andersson E, Jernelöv S, Hedman E, et al. InternetDelivered Acceptance and Values-Based Exposure Treatment for Fibromyalgia: A Pilot Study. Cogn Behav Ther 2014;43:93–104. doi:10.1080/16506073.2013.846401. [30] Camerini L, Camerini A-L, Schulz PJ. Do participation and personalization matter? A modeldriven evaluation of an Internet-based patient education intervention for fibromyalgia patients. Patient Educ Couns 2013;92:229–34. doi:10.1016/j.pec.2013.04.007. [31] Williams DA, Kuper D, Segar M, Mohan N, Sheth M, Clauw DJ. Internet-Enhanced Management of Fibromyalgia: A Randomized Controlled Trial. Pain 2010;151:694–702. doi:10.1016/j.pain.2010.08.034. [32] Umapathy H, Bennell K, Dickson C, Dobson F, Fransen M, Jones G, et al. The Web-Based Osteoarthritis Management Resource My Joint Pain Improves Quality of Care: A QuasiExperimental Study. J Med Internet Res 2015;17:e167. doi:10.2196/jmir.4376. [33] Cuperus N, Hoogeboom TJ, Kersten CC, den Broeder AA, Vliet Vlieland TPM, van den Ende CHM. Randomized trial of the effectiveness of a non-pharmacological multidisciplinary faceto-face treatment program on daily function compared to a telephone-based treatment program in patients with generalized osteoarthritis. Osteoarthritis Cartilage 2015;23:1267–75. doi:10.1016/j.joca.2015.04.007. [34] Armbrust W, Bos JJFJ, Cappon J, van Rossum MAJJ, Sauer PJJ, Wulffraat N, et al. Design and acceptance of Rheumates@Work, a combined internet-based and in person instruction model, an interactive, educational, and cognitive behavioral program for children with juvenile idiopathic arthritis. Pediatr Rheumatol Online J 2015;13. doi:10.1186/s12969-015-0029-5. [35] Stinson JN, McGRATH PJ, Hodnett ED, Feldman BM, Duffy CM, Huber AM, et al. An Internet-based Self-management Program with Telephone Support for Adolescents with 21

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doi:10.3899/jrheum.091327. [36] White M, Stinson JN, Lingley-Pottie P, McGrath PJ, Gill N, Vijenthira A. Exploring Therapeutic Alliance with an Internet-Based Self-Management Program with Brief Telephone Support for Youth with Arthritis: A Pilot Study. Telemed E-Health 2012;18:271–6. doi:10.1089/tmj.2011.0150. [37] Poulsen KA, Millen CM, Lakshman UI, Buttner PG, Roberts LJ. Satisfaction with rural rheumatology telemedicine service. Int J Rheum Dis 2015;18:304–14. doi:10.1111/1756185X.12491. [38] Graham LE, McGimpsey S, Wright S, McClean G, Carser J, Stevenson M, et al. Could a lowcost audio-visual link be useful in rheumatology? J Telemed Telecare 2000;6 Suppl 1:S35-37. [39] Ammerlaan J, van Os-Medendorp H, Scholtus L, de Vos A, Zwier M, Bijlsma H, et al. Feasibility of an online and a face-to-face version of a self-management program for young adults with a rheumatic disease: experiences of young adults and peer leaders. Pediatr Rheumatol Online J 2014;12:10. doi:10.1186/1546-0096-12-10. [40] Lorig KR, Ritter PL, Laurent DD, Plant K. The internet-based arthritis self-management program: A one-year randomized trial for patients with arthritis or fibromyalgia. Arthritis Care Res 2008;59:1009–17. doi:10.1002/art.23817. [41] Allely EB. Synchronous and asynchronous telemedicine. J Med Syst 1995;19:207–12. [42] Tejera Segura B, Bustabad S. A new form of communication between rheumatology and primary

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doi:10.1016/j.reuma.2015.01.003. [43] Kulcsar Z, Albert D, Ercolano E, Mecchella JN. Telerheumatology: A technology appropriate for virtually all. Semin Arthritis Rheum 2016;0. doi:10.1016/j.semarthrit.2016.05.013.

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[44] Bender JL, Radhakrishnan A, Diorio C, Englesakis M, Jadad AR. Can pain be managed through the Internet? A systematic review of randomized controlled trials. Pain 2011;152:1740–50. doi:10.1016/j.pain.2011.02.012. [45] Davis RM, Hitch AD, Salaam MM, Herman WH, Zimmer-Galler IE, Mayer-Davis EJ. TeleHealth Improves Diabetes Self-Management in an Underserved Community. Diabetes Care 2010;33:1712–7. doi:10.2337/dc09-1919. [46] Smolen JS, Aletaha D, Bijlsma JWJ, Breedveld FC, Boumpas D, Burmester G, et al. Treating rheumatoid arthritis to target: recommendations of an international task force. Ann Rheum Dis 2010;69:631–7. doi:10.1136/ard.2009.123919. [47] Vermeer M, Kuper HH, Moens HJB, Drossaers-Bakker KW, van der Bijl AE, van Riel PLCM, et al. Sustained Beneficial Effects of a Protocolized Treat-to-Target Strategy in Very Early Rheumatoid Arthritis: Three-Year Results of the Dutch Rheumatoid Arthritis Monitoring Remission Induction Cohort. Arthritis Care Res 2013;65:1219–26. doi:10.1002/acr.21984. [48] Pani D, Piga M, Barabino G, Crabolu M, Uras S, Mathieu A, et al. Home tele-rehabilitation for rheumatic patients: impact and satisfaction of care analysis. J Telemed Telecare. 2017 Feb;23(2):292-300. doi: 10.1177/1357633X16632950. [49] Zhang F. The China rheumatology workforce: a status report. Int J Rheum Dis 2009;12:279– 82. doi:10.1111/j.1756-185X.2009.01439.x. [50] Souliotis K, Papageorgiou M, Politi A, Ioakeimidis D, Sidiropoulos P. Barriers to accessing biologic treatment for rheumatoid arthritis in Greece: the unseen impact of the fiscal crisis— the Health Outcomes Patient Environment (HOPE) study. Rheumatol Int 2014;34:25–33. doi:10.1007/s00296-013-2866-1. [51] American College of Rheumatology Committee on Rheumatology Training and Workforce Issues. Regional Distribution of Adult Rheumatologists. Arthritis Rheum 2013;65:3017–25. doi:10.1002/art.38167.

23

[52] Cuperus N, van den Hout WB, Hoogeboom TJ, van den Hoogen FHJ, Vliet Vlieland TPM, van den Ende CHM. Cost-Utility and Cost-Effectiveness Analyses of Face-to-Face Versus Telephone-Based Nonpharmacologic Multidisciplinary Treatments for Patients With Generalized Osteoarthritis. Arthritis Care Res 2016;68:502–10. doi:10.1002/acr.22709. [53] Wechsler LR, Demaerschalk BM, Schwamm LH, Adeoye OM, Audebert HJ, Fanale CV, et al. Telemedicine Quality and Outcomes in Stroke: A Scientific Statement for Healthcare Professionals From the American Heart Association/American Stroke Association. Stroke 2017;48:e3–25. doi:10.1161/STR.0000000000000114. [54] Harris SM. Practicing Telemedicine Raises Legal Considerations for Rheumatologists. The Rheumatologist n.d. http://www.the-rheumatologist.org/article/practicing-telemedicine-raiseslegal-considerations-rheumatologists/ (accessed November 11, 2016).

Figure 1. Flow diagram illustrating the results of the literature search.

Figure 2. (A) Resuming results of the Cochrane Collaboration’s tool Risk of Bias Assessment Tool in studies included in the systematic review. (B) Resuming results of the Cochrane Collaboration’s tool Risk of Bias Assessment Tool in CCT and RCT included in the systemic review.

24

Table 1. Characteristics of RCT and CCT included in the systemic review. Study type

Population (patients)

RCT

RA (41)

RCT

RA (106)

RCT

RA (160)

(24) Piga M et al. (2014)

RCT

SSc + RA (20+20)

Tele-monitoring of rehabilitation

(28) Vallejo MA et al. (2015)

RCT

FM (60)

ICT delivered selfmanagement

RCT

FM (118)

CCT

OA (195)

References (20) Salaffi F et al. (2016) (21) Shigaki CL et al. (2013) (23) van den Berg MH et al. (2006)

(31) Williams DA et al. (2010) (32) Umaphaty H et al. (2015)

Intervention

Comparison

Outcome

Tele-monitoring of treatment strategy ICT delivered selfmanagement ICT delivered selfmanagement

Conventional strategy Waiting list control General information Selfadministered rehabilitation Usual care and Face-toface delivered treatment

Effectiveness – Satisfaction

ICT delivered selfmanagement ICT delivered selfmanagement

Effectiveness Feasibility – Effectiveness – Satisfaction

Effectiveness

Usual care

Effectiveness Satisfaction

Non-users

Effectiveness

Face-to-face delivered treatment

Effectiveness

Usual care

Effectiveness Feasibility

Face-to-face consultation

Satisfaction

(33) Cuperus N et al. (2015)

RCT

OA (147)

(35) Stinson JN et al. (2010)

RCT

JIA (46)

CCT

Mixed Cohorts (107)

ICT delivered selfmanagement Remotely Delivered Consultation

CCT

Mixed Cohorts (22)

ICT delivered selfmanagement

Face-to-face delivered treatment

Feasibility and Satisfaction

RCT

Mixed Cohorts (855)

ICT delivered selfmanagement

Usual care

Validity

(37) Poulsen KA et al. (2015) (39) Ammerlaan J et al. (2014) (40) Lorig KR et al. (2008)

ICT delivered selfmanagement

Effectiveness

25

Table 2. Characteristics of B&A and observational studies included in the systemic review. References

Study type

(17) Espinoza F et al. (2016) (18) Nishiguchi S et al. (2014) (19) Potter T et al. (2006) (22) Hoving JL et al. (2014) (25) Poole JL et al. (2014) (27) Salaffi F et al. (2015) (29) Ljótsson B et al. (2014) (30) Camerini L et al. (2013) (34) Armbrust W et al. (2015) (36) White M et al. (2012) (38) Graham LE et al. (2000)

Observatio nal Observatio nal Observatio nal

Population (patients) RA (63) RA (65) RA (50)

B&A

RA (23)

B&A

SSc (16)

Observatio nal

FM (76)

B&A

FM (41)

B&A

FM (209)

Observatio nal

JIA (64)

B&A

JIA (14)

Observatio nal

Mixed Cohorts (20)

Intervention Remote disease activity assessment Remote disease activity assessment Remote disease activity assessment ICT delivered selfmanagement ICT delivered management Remote disease activity assessment ICT delivered selfmanagement ICT delivered selfmanagement ICT delivered selfmanagement ICT delivered selfmanagement Remotely Delivered Consultation

Outcome Validity Validity Validity Effectiveness Satisfaction Effectiveness Satisfaction Feasibility Effectiveness Effectiveness Satisfaction Feasibility Satisfaction Effectiveness Validity

26

Table 3. Results of the Risk of Bias Assessment Tool application to the studies included in the review. References Salaffi F et al. (20) Shigaki CL et al. (21) Hoving JL et al. (22) Van Den Berg MH et al. (23) Piga M et al. (24) Poole JL et al. (25) Vallejo MA et al. (28) Ljótsson B et al. (29) Camerini L et al. (30) Williams DA et al. (31) Umaphaty H et al. (32) Cuperus N et al. (33) Stinson JN et al. (35) White M et al. (36) Poulsen KA et al. (37) Ammerlaan J et al. (39) Lorig KR et al. (40)

Sequence Allocation Blinding Generation Concealment Participants

Blinding Incomplete Selective outcome Outcome Reporting assessment data

Low Risk

Low Risk

High Risk

Low Risk

Low Risk

Low Risk

Unclear

Unclear

High Risk

Low Risk

Low Risk

Low Risk

High Risk

High Risk

High Risk

Low Risk

Low Risk

Low Risk

Low Risk

Low Risk

Low Risk

Low Risk

Low Risk

Low Risk

Low Risk

Low Risk

High Risk

Low Risk

Low Risk

Low Risk

High Risk

High Risk

High Risk

Low Risk

Low Risk

Low Risk

Low Risk

Low Risk

High Risk

Low Risk

Low Risk

Low Risk

High Risk

High Risk

High Risk

Low Risk

Low Risk

Low Risk

High Risk

High Risk

High Risk

Low Risk

Low Risk

Low Risk

Low Risk

Low Risk

High Risk

Low Risk

Low Risk

Low Risk

High Risk

High Risk

High Risk

Low Risk

High Risk

Low Risk

Low Risk

Low Risk

High Risk

Low Risk

Low Risk

Low Risk

Low Risk

Low Risk

High Risk

Low Risk

Low Risk

Low Risk

High Risk

High Risk

High Risk

Low Risk

Low Risk

Low Risk

High Risk

High Risk

High Risk

Low Risk

Low Risk

Low Risk

High Risk

High Risk

High Risk

Low Risk

Low Risk

Low Risk

Low Risk

Low Risk

High Risk

Low Risk

High Risk

Low Risk

Authors excluded all observational studies from this Risk of Bias assessment table because they had a high risk of bias in all evaluated items.

27

Trial design (3)

Criteria (4)

Intervention (5)

Outcomes (6)

Sample size (7)

Randomization (8)

Allocation (9)

Implementation (10)

Blinding (11)

Statistics (12)

Participant flow (13)

Timing (14)

Results (17)

Principle analysis (18)

Harms (19)

References

Background (2)

Table 4. Quality Assessment of RCT according to the Modified CONSORT Statement 2010.

+

+

+

+

+

-

+

+

+

-

+

+

-

+

+

+

+

+

+

+

+

-

?

?

?

-

+

+

-

+

+

+

+

+

+

+

+

-

+

+

+

+

+

+

+

+

+

-

+

+

+

+

+

-

+

+

-

-

+

+

+

+

+

+

+

+

+

+

+

+

+

+

+

-

+

+

-

+

+

+

+

+

+

+

+

+

+

+

+

-

+

+

-

+

+

+

+

+

+

+

+

+

+

+

+

-

+

+

+

+

+

+

+

+

+

+

+

-

+

+

+

-

+

+

+

+

+

+

+

+

+

+

+

-

+

+

+

-

+

+

+

+

+

+

Salaffi F et al (20) Shigaki CL et al (21) Van Den Berg MH et al (23) Piga M et al (24) Vallejo MA et al (28) Williams DA et al (31) Cuperus N et al (33) Stinson JN et al (35) Lorig KR et al (40)

(+) present and valid. (-) Not considered or invalid. (?) Unclear. (2) Scientific background and explanation of rationale, specific objectives or hypotheses. (3) Description of trial design. (4) Eligibility criteria for participants. (5) Detailed description of intervention. (6) Pre-specified primary and secondary outcomes measures. (7) Sample size determination. (8) Random allocation sequence determination and type of randomization. (9) Allocation concealment mechanism. (10) Implementation (who generated the random allocation sequence, who enrolled participants and who assigned participants to interventions). (11) Blinding methods. (12) Statistical methods. (13) Participant flow. (14) Periods of recruitment and follow-up. (17) Results for group and estimated effect size. (18) Good distinguishing from principle analysis and other ones. (19) Harms or unintended effects. 28

29

30