Title: Supported remote rehabilitation post Covid-19: development, deployment and evaluation of a digitally-enabled rehabilitation programme
Funder: Department of Health and Social Care

Abstract: Nearly 300,000 people in the UK had been affected by Covid-19 by 6/7/20, and the pandemic is ongoing. Many patients have symptoms that last for months after the acute infection, particularly breathlessness, fatigue and anxiety. _x000D_ _x000D_ Breathlessness, fatigue and anxiety can be treated. Physiotherapy helps people rebuild their muscles, regain their strength, and learn to breathe normally again. People with Covid-19 need dietary advice to help recover lost weight and rebuild muscles. Cognitive Behavioural Therapy (CBT) and psycho-education (advice and education about mental health) can help with anxiety and fatigue. These treatments are normally delivered by skilled clinicians (physiotherapists, dieticians, psychologists). However, there are not enough of these clinicians for all the patients who need help, and services are trying to avoid bringing patients to hospitals or clinics to stop the spread of Covid-19. Patients report feeling “abandoned” by the NHS and left to deal with these problems on their own. _x000D_ _x000D_ We plan to deliver these treatments remotely, but with clinician support, using a digital tool. There are three parts to the tool. (1) an app for patients which collects symptoms and uses this information to deliver tailored, personalised advice on exercise, diet and mental health. (2) a dashboard that allows clinicians to review patient progress and communicate with patients, and (3) a clinical pathway that specifies how patients can safely receive this remote supported care. This will benefit patients, as they will have access to effective treatments, and benefit clinicians and the health service by enabling them to look after many more patients efficiently and safely. _x000D_ _x000D_ The research is to find out how best to do this. We will identify what patients and clinicians need from such a service, and how to deliver this with digital technology. We will see whether Artificial Intelligence (AI) can help with tailoring the app to individual patients. We will find out whether this service reaches the target population, and whether it benefits them. We are concerned that offering healthcare digitally could disadvantage some people, particularly older people or people from Black and Minority Ethnic or socially disadvantaged backgrounds. We need to find out whether this happens and how to avoid it. We will find out what the costs are of delivering a service this way._x000D_ _x000D_ We will do this by developing the digital tool, using it in the NHS, and collecting data from patients and clinicians who use it. We will collect quantitative data (numbers) on the proportion of eligible patients who use the tool, whether disadvantaged people are less likely to use it, how their symptoms change over time, and costs of delivering the service. We will interview patients and clinicians to find out what they like and dislike about the service, so we can improve it. _x000D_ _x000D_ Our team includes clinicians (chest specialists, physiotherapists, dieticians, psychologists, GPs), computer scientists, health researchers and a private company that is used to developing digital tools for use in the NHS. Between us we have all the necessary expertise and experience to develop this tool, get it into use across the NHS, and evaluate its impact on the target population. The learning will inform use of digital tools for other conditions in the NHS and internationally

Lay abstract: Background: Covid-19 had affected nearly 300,000 patients in the UK by 6/7/20. Many remain symptomatic with breathlessness, fatigue and anxiety for weeks or months. These symptoms can be improved with rehabilitation, but traditional, face-to-face models of service delivery will struggle to cope with these large numbers of patients. A digital approach is likely to be needed, but there are numerous challenges with this approach, including failures of implementation; anxieties around the digital divide / health inequalities; and concerns around low engagement with such programmes._x000D_ _x000D_ Aim: to refine, deploy and evaluate a digitally-mediated, remote, supported rehabilitation programme for patients affected by Covid-19._x000D_ _x000D_ Methods: We will combine research methods common to engineering and computer science (focused on developing a product that is safe, stable and meets user requirements) with those familiar to biomedical and health service researchers (focused on effectiveness and population impact). Thus we will apply the Medical Research Council (MRC) Framework for development and evaluation of complex interventions (Phases 1, 2 and 4), User-Centred Design (UCD) and the ISO 9241 Human-Computer Interaction (HCI) Lifecycle for intervention development. Behavioural theory and behaviour change techniques will inform content and delivery; Normalisation Process Theory will inform implementation. Evaluation will use mixed methods, combining qualitative (interviews with clinician and patient users) and quantitative data. Quantitative data will include referral, registration, and usage rates, demographic and clinical characteristics of patients, and patient reported outcomes for breathlessness (MRC dyspnoea and Dyspnoea 12 scales); fatigue (FACIT-F); anxiety (GAD-7) and nutrition (MUST). _x000D_ _x000D_ Outputs: (i) A digital health intervention (DHI) to support post-Covid rehabilitation; (ii) the DHI can be easily modified to support rehab and self-management in other conditions; (iii) generalizable learning on digital health, including: overcoming the digital divide; using AI to improve engagement; implementing DHI into routine clinical practice; enabling efficient review of large numbers of patients; costs and resources needed for sustainable digitally-mediated care; and appropriate funding models. _x000D_ _x000D_ Dissemination and Implementation: The DHI will be available for use across the NHS; transfer of knowledge will be facilitated through the AHSN and ARC networks as we are supported by UCLP, ARC North Thames and NHS Innovation Accelerator, and underpinned by academic peer-reviewed publications, supported by targeted media and social-media activity. _x000D_ _x000D_ Team expertise: We combine outstanding clinical expertise (chest medicine, rehabilitation, physiotherapy, dietetics, clinical psychology, GPs) with world-leading academic experts in digital health, computer science, behavioural science, implementation science, sociology, statistics and health economics and a commercial provider experienced in working with the NHS.

Research activity codes: 8.1 ORGANISATION AND DELIVERY OF SERVICES
Health categories: INFECTION