Evidence map›Paper›PMID 39407290›Full record

ArticleTrials2024

Remote monitoring of rheumatoid arthritis (REMORA): study protocol for a stepped wedge cluster randomized trial and process evaluation of an integrated symptom tracking intervention.

Sabine N van der Veer, Deb Griffiths-Jones, Matthew Parkes, Katie L Druce, Paul Amlani-Hatcher, Christopher J Armitage, Nicholas Bansback, Peter Bower, Dawn Dowding, Benjamin Ellis and 8 more

Abstract readClinical Trial Protocol
In one paragraph

Article in Trials, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors.

Sabine N van der VeerCentre for Health Informatics, Division of Informatics, Imaging and Data Science, University of Manchester, Manchester Academic Health Science Centre, Vaughan House, Portsmouth Street, Manchester, M13 9GB, UK. sabine.vanderveer@manchester.ac.uk.ORCID http://orcid.org/0000-0003-0929-436X
Deb Griffiths-JonesCentre for Health Informatics, Division of Informatics, Imaging and Data Science, University of Manchester, Manchester Academic Health Science Centre, Vaughan House, Portsmouth Street, Manchester, M13 9GB, UK.
Matthew ParkesCentre for Biostatistics, Division of Population Health, Health Services Research & Primary Care, School of Health Sciences, The University of Manchester, Manchester, UK.
Katie L DruceCentre for Epidemiology Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.
Paul Amlani-HatcherCentre for Epidemiology Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.
Christopher J ArmitageManchester Centre for Health Psychology, Division of Psychology and Mental Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.
Nicholas BansbackSchool of Population and Public Health, University of British Columbia, Vancouver, Canada.
Peter BowerCentre for Primary Care and Health Services Research, Division of Population Health, Health Services Research and Primary Care, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.
Dawn DowdingDivision of Nursing, Midwifery and Social Work, School of Health Sciences, Faculty of Biomedicine and Health, The University of Manchester, Manchester, UK.
Benjamin EllisImperial College Healthcare NHS Trust, London, UK.
Jill FirthPennine MSK Partnership, Integrated Care Centre, Oldham, UK.
Sean GavanManchester Centre for Health Economics, Division of Population Health, Health Services Research and Primary Care, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK.
Elaine MackeyCentre for Epidemiology Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.
Caroline SandersCentre for Primary Care and Health Services Research, Division of Population Health, Health Services Research and Primary Care, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.
Charlotte A SharpCentre for Epidemiology Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.
Karen StanilandCentre for Epidemiology Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.
William G DixonCentre for Health Informatics, Division of Informatics, Imaging and Data Science, University of Manchester, Manchester Academic Health Science Centre, Vaughan House, Portsmouth Street, Manchester, M13 9GB, UK.
REMORA team

Funding

Programme Grants for Applied Research NIHR202030
6 · The paper itself

Abstract

backgroundManagement of rheumatoid arthritis (RA) relies on symptoms reported by patients during infrequent outpatient clinic visits. These reports are often incomplete and inaccurate due to poor recall, leading to suboptimal treatment decisions and outcomes. Asking people to track symptoms in-between visits and integrating the data into clinical pathways may improve this. However, knowledge on how to implement this into practice and its impact on services and outcomes remains scarce in RA. Therefore, we evaluate the comparative effectiveness and cost-effectiveness of integrated symptom tracking in people with RA over and above usual care, while generating insights on factors for successful implementation.

methodsIn this superiority stepped wedge cluster-randomized controlled trial with continuous recruitment short exposure design, 16 rheumatology outpatient departments (clusters) recruit a total of 732 people with active RA. They initially offer clinic visits according to standard of care before switching in pairs to visits with integrated symptom tracking. Clusters switch in randomized order every 3 weeks. Integrated symptom tracking consists of (1) a mobile app for patients to track their symptoms daily and other RA aspects weekly/monthly, and (2) an interactive dashboard visualizing the app data, which healthcare professionals access from their electronic health record system. Clinic visits happen according to usual practice, with tracked symptom data only reviewed during visits. Our primary outcome is a difference in marginal mean disease activity score at 12 ± 3 months between standard of care and integrated symptom tracking, after accounting for baseline values, cluster, and other covariates. Secondary outcomes include patient-reported disease activity, quality of life and quality-adjusted life-years, medication/resource use, consultation and decision-making experience, self-management, and illness perception. We also conduct interviews and observations as part of a parallel process evaluation to gather information on implementation. DISCUSSION: Our trial will generate high-quality evidence of comparative and cost-effectiveness of integrated symptom tracking compared to standard of care in people with RA, with our process evaluation delivering knowledge on successful implementation. This optimizes the chances of integrated symptom tracking being adopted more widely if we find it is (cost-) effective.

trial registrationRegistered 4-Jun-2024 on https://www.isrctn.com/ , ISRCTN51539448. TRIAL OPEN SCIENCE FRAMEWORK REPOSITORY: https://osf.io/sj9ha/ .

Indexed as

Arthritis, RheumatoidCost-Benefit AnalysisMobile ApplicationsComparative Effectiveness ResearchEquivalence Trials as TopicHumansMulticenter Studies as TopicQuality of LifeRandomized Controlled Trials as TopicSymptom AssessmentTelemedicineTime FactorsTreatment OutcomeMobile healthPatient-generated health dataRandomized controlled trialRheumatologySigns and symptomsTelemedicine

Identifiers

PMID39407290
PMCPMC11481815

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.