Using technology to support clinical care and research in rheumatoid arthritis

Dixon, William G; Michaud, Kaleb

doi:10.1097/bor.0000000000000485

Cited by 49 publications

(41 citation statements)

References 32 publications

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“…The number of available mobile health applications (apps) has exponentially grown over the past few years and so has the number of users 4. Apps are designed for a wide range of users, from healthy individuals to people living with long-term conditions including, but not limited to, rheumatic and musculoskeletal diseases (RMDs),5 psychiatric,6 respiratory,7 cardiovascular diseases8 and diabetes mellitus 9…”

Section: Introductionmentioning

confidence: 99%

EULAR points to consider for the development, evaluation and implementation of mobile health applications aiding self-management in people living with rheumatic and musculoskeletal diseases

et al. 2019

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BackgroundMobile health applications (apps) are available to enable people with rheumatic and musculoskeletal diseases (RMDs) to better self-manage their health. However, guidance on the development and evaluation of such apps is lacking.ObjectivesThe objective of this EULAR task force was to establish points to consider (PtC) for the development, evaluation and implementation of apps for self-management of RMDs.MethodsA systematic literature review of app content and development strategies was conducted, followed by patient focus group and an online survey. Based on this information and along with task force expert opinion, PtC were formulated in a face-to-face meeting by a multidisciplinary task force panel of experts, including two patient research partners. The level of agreement among the panel in regard to each PtC was established by anonymous online voting.ResultsThree overarching principles and 10 PtC were formulated. Three PtC are related to patient safety, considered as a critical issue by the panel. Three are related to relevance of the content and functionalities. The requirement for transparency around app development and funding sources, along with involvement of relevant health professionals, were also raised. Ease of app access across ages and abilities was highlighted, in addition to considering the cost benefit of apps from the outset. The level of agreement was from 8.8 to 9.9 out of 10.ConclusionThese EULAR PtC provide guidance on important aspects that should be considered for the development, evaluation and implementation of existing and new apps.

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Section: Introductionmentioning

confidence: 99%

EULAR points to consider for the development, evaluation and implementation of mobile health applications aiding self-management in people living with rheumatic and musculoskeletal diseases

et al. 2019

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“…It has been suggested that the use of smartphone applications has a great potential to achieve these goals (18). In fact, the combination of smartphone apps with healthcare professionals' intervention to promote self-management may improve adherence, participation, and long-term e cacy (24)(25)(26). Technology implantation has a key role in current practice for the control and treatment of RA, and to enhance patients' satisfaction and general wellness (26).…”

Section: Introduction Background and Rationale {6a}mentioning

confidence: 99%

A mobile app using therapeutic exercise and education for self-management in patients with hand rheumatoid arthritis. A randomized controlled trial protocol.

Sánchez-Laulhé¹,

Romero

Blanquero

et al. 2020

Preprint

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• Background: Therapeutic exercise is a safe and cost-effective approach to alleviate hand rheumatoid arthritis (RA) related symptoms. This study aims to investigate the differences in self-management between a smartphone app (CareHand), using hand exercises and educational advices, compared with a standard approach, on hand overall function, pain intensity, stiffness, and grip and pinch strength in patients with hand RA.• Methods: The project is a prospective, longitudinal, superiority, randomized controlled trial. Fifty-eight participants with hand RA will be randomly assigned into an experimental group (CareHand app) or a control group (conventional treatment). Control intervention involves a paper sheet with exercises and recommendations, and the experimental group includes the use of a smartphone app, which provides individualized exercise programmes, self-management and educational strategies to promote adherence to treatment. Both intervention protocols will last for 3 months. The principal investigator will conduct an educational session at baseline for all participants. Primary outcome comprises the overall hand function, assessed with the Michigan Hand Outcome Questionnaire (MHQ). Secondary outcomes include self-reported functional ability with the Quick DASH questionnaire, self-reported pain intensity and morning stiffness using a Visual Analogue Scale (VAS), and hand grip and pinch strength (dynamometer). Outcome measures will be collected at baseline, and at 1 month and 3-month follow-up.• Discussion: This study will evaluate the effectiveness of a telerehabilitation tool, which uses exercise and self-management strategies, compared to a conventional approach, in patients with hand RA. The smartphone app will allow to monitor the patient´s status, and to enhance patient-therapist communication. Some limitations may be related to the short follow-up duration and the lack of evaluation of psychosocial factors. Overall, this new way of promoting long-term effects in patients with a chronic rheumatic disease could be feasible and easy to implement in daily life clinical practice and current musculoskeletal care.• Trial registration: ClinicalTrials.gov Identifier: NCT04263974. Registered 7 March 2020. Date of last update 15 April 2020. Ethics committee code: PI_RH_2018.

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“…As elegantly elaborated by Topol, the use of big data in medicine is going to disrupt the medical system as we know it 2. Big data include both clinical data (eg, originating from electronic health records, healthcare system claims data or patient-generated data such as from apps), biological data issued from the development of molecular research leading to multi-omics complex molecular data,3 social data (eg, originating from social networks, Internet of Things, physical social connexions or economic data repositories), imaging data and environmental data (eg, urbanistic data, pollution or atmospheric conditions) 4 5. In parallel, artificial intelligence–based methodologies allowing computer systems to ‘learn’ from data (ie, progressively improve performance on a specific task without being explicitly programmed) are more and more accessible 6 7.…”

Section: Introductionmentioning

confidence: 99%

“…However, big data is an emergent area in need of guidelines and general recommendations on how to move this field forward in a collaborative and ethical way. Some of the challenges presented by big data and artificial intelligence include data sources and data collection: how to collect and store the data, while guaranteeing ethics and data privacy12; how to interpret data models of complex analyses13 14; and what are the clinical implications of big data: how to go from big data to clinical decision-making 3 15 16…”

Section: Introductionmentioning

confidence: 99%

EULAR points to consider for the use of big data in rheumatic and musculoskeletal diseases

Gossec

Kedra

Servy³

et al. 2019

Ann Rheum Dis

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BackgroundTremendous opportunities for health research have been unlocked by the recent expansion of big data and artificial intelligence. However, this is an emergent area where recommendations for optimal use and implementation are needed. The objective of these European League Against Rheumatism (EULAR) points to consider is to guide the collection, analysis and use of big data in rheumatic and musculoskeletal disorders (RMDs).MethodsA multidisciplinary task force of 14 international experts was assembled with expertise from a range of disciplines including computer science and artificial intelligence. Based on a literature review of the current status of big data in RMDs and in other fields of medicine, points to consider were formulated. Levels of evidence and strengths of recommendations were allocated and mean levels of agreement of the task force members were calculated.ResultsThree overarching principles and 10 points to consider were formulated. The overarching principles address ethical and general principles for dealing with big data in RMDs. The points to consider cover aspects of data sources and data collection, privacy by design, data platforms, data sharing and data analyses, in particular through artificial intelligence and machine learning. Furthermore, the points to consider state that big data is a moving field in need of adequate reporting of methods and benchmarking, careful data interpretation and implementation in clinical practice.ConclusionThese EULAR points to consider discuss essential issues and provide a framework for the use of big data in RMDs.

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Using technology to support clinical care and research in rheumatoid arthritis

Cited by 49 publications

References 32 publications

EULAR points to consider for the development, evaluation and implementation of mobile health applications aiding self-management in people living with rheumatic and musculoskeletal diseases

EULAR points to consider for the development, evaluation and implementation of mobile health applications aiding self-management in people living with rheumatic and musculoskeletal diseases

A mobile app using therapeutic exercise and education for self-management in patients with hand rheumatoid arthritis. A randomized controlled trial protocol.

EULAR points to consider for the use of big data in rheumatic and musculoskeletal diseases

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