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Development and implementation of a digital health intervention in routine care for long COVID patients: a comprehensive synopsis

Goodfellow, H; Blandford, A; Bradbury, K; Gomes, M; Hamilton, F; Henley, W; Stevenson, F; ... Ismaila, H; + view all (2025) Development and implementation of a digital health intervention in routine care for long COVID patients: a comprehensive synopsis. Health and Social Care Delivery Research , 13 (39) pp. 1-28. 10.3310/GJHG0331. Green open access

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Abstract

Background: By July 2020, large numbers of post-COVID patients were experiencing symptoms for weeks or months, but traditional National Health Service models of rehabilitation service delivery could not meet demand. Objectives: Design and deploy a digital health intervention to provide digitally delivered, remotely supported rehabilitation to long COVID patients on complicated and evolving pathways. Methods: The multidisciplinary team combined established research methods based on engineering and computer science (considering safety, stability and user requirements) with those based on biomedical and health service research (considering effectiveness and population impact). Qualitative data comprised recordings of meetings between study team members and clinicians and semistructured interviews with clinician and patient users. Quantitative data comprised referral, registration and usage rates; demographic and clinical characteristics of patients; and patient-reported outcome measures. Results: We created a modifiable digital health intervention, 'Living With COVID RecoveryTM developed by Living With Ltd', London, UK, that continues to be used by National Health Service trusts. The digital health intervention included integration into a clinical pathway, a clinician-facing dashboard, two-way messaging and a patient-facing app with information and evidence-based treatments. We aimed to register 1000 users. By study completion on 20 December 2022, there were 9781 patients invited, of whom 7679 (78.5%) had registered, at 33 National Health Service clinics. Limitations: Data came from patients at long COVID clinics, however data were unlikely to be representative of people with long COVID. We could not observe clinics under lockdown and had limited access to patient digital health intervention users or to people not engaging with the digital health intervention. Patient user data were incomplete, with inconsistent patient-reported outcome measure and other questionnaire data completion and no data on initial severity of disease, vaccination status, comorbidities or other individual circumstances. Conclusions: Long COVID can be extremely debilitating, comparable to stage IV lung cancer in relation to fatigue and health-related quality of life. Care and rehabilitation should address the management of fatigue and reflect the impact of social disadvantage on symptom severity. With sufficient resources, a digital health intervention can be developed quickly and effectively using agile methodology and bringing together a genuinely multidisciplinary team, including, importantly, an industry partner. Digital health intervention product design and deployment are both important in getting National Health Service trusts, healthcare professionals and patients to engage with a digital health intervention. Projects should work closely with all user groups. Lockdown and the unmet need of a new patient group encouraged those who might otherwise have been reluctant to try a digital health intervention. Many patients and clinics accepted this digital remote support, which helped patients feel cared for while reducing strain on health services. This may encourage acceptance of other digital health intervention, although medical record integration remains a deterrent to clinics. Future work: This research focused on the development, deployment and evaluation of a digitally enabled rehabilitation programme for long COVID. Clinical effectiveness will be assessed within the Symptoms, Trajectory, Inequalities and Management: Understanding Long-COVID to Address and Transform Existing Integrated Care Pathways (UCL, London, UK) study. Funding: This synopsis presents independent research funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme as award number NIHR132243.

Type: Article
Title: Development and implementation of a digital health intervention in routine care for long COVID patients: a comprehensive synopsis
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.3310/GJHG0331
Publisher version: https://doi.org/10.3310/gjhg0331
Language: English
Additional information: This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: DIGITAL HEALTH, IMPLEMENTATION SCIENCE, LONG COVID, POST-COVID SYNDROME, REHABILITATION, REMOTE, SUPPORTED SELF-MANAGEMENT, Humans, COVID-19, Male, Female, Telemedicine, Middle Aged, SARS-CoV-2, Adult, Patient Reported Outcome Measures, United Kingdom, Aged, State Medicine, Digital Health
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine > Respiratory Medicine
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Epidemiology and Health > Applied Health Research
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Epidemiology and Health > Primary Care and Population Health
URI: https://discovery.ucl.ac.uk/id/eprint/10217836
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