RECEIVER: Digital Service Model for Chronic Obstructive Pulmonary Disease (COPD)

Study Overview
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Brief Summary
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Chronic obstructive pulmonary disease (COPD) is a serious but treatable chronic health condition. Optimised management improves symptoms, complications, quality of life and survival. Disease exacerbations, which have adverse outcomes and often trigger hospital admissions, underpin the rising costs of managing COPD (projected increase in the United Kingdom (UK) to £2.3bn by 2030). The costs and care-quality gap of COPD exacerbations, coupled with the global rising prevalence present a major healthcare challenge. This study proposal, which has been developed in partnership with patients, clinicians, enterprise and government representation is to conduct an implementation and effectiveness observational cohort study to establish a continuous and preventative digital health service model for COPD. The implementation proposals comprise: - Establishing a digital resource for high-risk COPD patients which contains symptom diaries (structured patient reported outcome questionnaires), integrates physiology monitoring (FitBit and home NIV therapy data), enables asynchronous communication with clinical team, supports COPD self-management and tracks interaction with the service (for endpoint analyses). Establishing a cloud-based clinical COPD dashboard which will integrate background electronic health record data, core COPD clinical dataset, patient-reported outcomes, physiology and therapy data and patient messaging to provide clinical decision support and practice-efficiencies, enhancing delivery of guideline-based COPD care. Use the acquired dataset to explore feasibility and accuracy of machine-learned predictive modelling risk scores, via cloud-based infrastructure, which will be for future prospective clinical trial. Our primary endpoint for the effectiveness evaluation is number of patients screened and recruited who successfully utilise and engage with this RECEIVER clinical service. The implementation components of the project will be iterated during the study, based on patient and clinical user experience and engagement. Secondary endpoints include a number of specified clinical outcomes, clinical service outcomes, machine-learning supported exploratory analyses, patient-centred outcomes and healthcare cost analyses.

Detailed Description
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Patients will be screened from emergency attendance or admission at South and North Sector (Queen Elizabeth University Hospital, and Glasgow Royal Infirmary) and from referrals to the COPD clinical team at these sites. Patients meeting inclusion criteria will be approached and offered enrolment to the study. Recruitment and consent timings will be individualised to be most efficient and least burdensome for patients. For some patients it will be appropriate to do this immediately to avoid burden of repeated attendances; for some patients, delay and consideration may be appropriate; for some patients the enrolment and engagement may be a staged process (consent at time of hospital attendance, study commence at follow up home or clinic visit etc). Patients recruited will receive support information and assistance with login setups for the digital service components. Literature with frequently asked questions (FAQs), and team contacts for service support are available for throughout the study. Patients enrolled will be asked, and prompted with text notifications, to complete daily short structured COPD symptom questionnaire. There are a small number of additional questions on a weekly basis, with quality of life questions completed once every 28 days. Patients recruited will have a Fitbit wristband wearable to monitor physiology. Patients with hypercapnic respiratory failure will additionally be on home non-invasive ventilation (NIV) treatment - this is part of their routine clinical care rather than a study intervention. However, the study patient resource and messaging system will be used to gather information and support this treatment. Selected patients, who are recruited during hospital admission or attendance and will be attending outpatient clinic follow up, will undergo exploratory physiology measurements - parasternal electromyography (EMG) (similar to electrocardiography (ECG) recording, takes  20 minutes with breathing manoeuvres), oscillometry (a breathing test involving 10 resting non-effortful breaths blown into the medical device), home pollution monitoring (a pack which rests in patients bedroom +/- tube placed outside house) for 7 days - alongside routine clinical care at baseline and 3 monthly intervals. Patients will have linked access from the patient resource to curated information about COPD diagnosis, and all aspects of management. Specific prompts about management - e.g. timing to make appointment for annual flu vaccination - will be provided through platform-text notifications. Self-management content of the resource will potentially be further developed over iterations within the study; any change in content of patient materials would be advised as a protocol amendment. Patients will be able to message the clinical team using the patient portal. This supplements existing availability of answer phone contact details provided as part of routine clinical care. Automatic messages will notify patients that this is not for emergency contact, and that replies should be expected within Mon-Fri working hours, by next working day. This messaging system will be used to support self management, home oxygen and home NIV treatment initiation and monitoring, and practical aspects such as appointment scheduling and equipment consumable replenishment. The clinical team will be able to access the data from the patients symptom diaries, wearable and NIV physiology directly - asynchronously, rather than delayed acquisition of this data at a clinical contact. This data visualisation will support routine clinical care, and better inform unscheduled advice contacts from patients (e.g. help determine significance of apparent worsening symptoms). This data will be subject to machine-learning analysis, which will evaluate secondary endpoints, as per protocol.

Official Title
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Remote-management of COPD: Evaluating Implementation of Digital Innovations to Enable Routine Care

Conditions
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Chronic Obstructive Pulmonary Disease

Intervention / Treatment
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* Other: COPD digital support service


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: confirmed diagnosis of chronic obstructive pulmonary disease, established pre-screening or at screening, defined as per Global Initiative for Chronic Obstructive Lung Disease (GOLD) 2019 guidelines home non-invasive ventilation cohort: hypercapnic respiratory failure and/or sleep-disordered breathing meeting established criteria for provision of home NIV exacerbation cohort: recent presentation to secondary care with exacerbation of COPD, defined as per GOLD 2019 guidelines patient or close-contact has access to smartphone, tablet or daily home computer web-browser informed consent ≥18 years of age Exclusion Criteria: inability to comprehend informed consent communication barrier precluding use of COPD digital service

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 100 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| COPD group<br>Patients with high-risk COPD with recent exacerbation requiring hospitalisation (within last 12 months) or hypercapnia respiratory failure and/or sleep disordered breathing meeting criteria for provision of home NIV. | Other: COPD digital support service<br>* Use of COPD digital services to record patient symptoms, integrate physiology monitoring, communicate with the clinical team and track interaction<br>* Other names: Lenus Health COPD;|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Patient utilisation of digital service | Proportion of enrolled high-risk COPD patients successfully utilising remote-management in a digital service model | 24 months (12 months recruiting) | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Clinical outcomes | Impact of digitally-enabled remote management on clinical outcomes including COPD exacerbations, unscheduled care contact, hospitalisation and occupied bed days, compared to historical and contemporary SafeHaven cohort (electronic health care record dataset) cohorts | 24 months (12 months recruiting) | 
| Clinical service outcomes | Impact of digital service model on clinical service outcomes including number, nature and complexity of reviews for remotely managed NIV and supported self management. | 24 months (12 months recruiting) | 
| Machine-learning analyses | Machine-learning supported exploratory analyses of associations and relative predictive importance of electronic health record, patient-reported outcomes, wearables physiology and NIV parameters | 24 months (12 months recruiting) | 
| Patient-centred outcomes | Impact of digital service on patient-centred outcomes including health related quality of life (EQ5-D) at baseline and monthly during study and qualitative user research with semi-structured user experience interviews. | 24 months (12 months recruiting) | 
| Healthcare cost analyses of digital service model | Assessment of healthcare costs associated with the digital service model including development and installation costs, recurring costs, and projected direct/indirect costs savings compared to previous service model | 24 months (12 months recruiting) |