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

• ClinicalTrials.gov Identifier: NCT04240353
• Recruitment Status: Unknown
• First Posted: January 27, 2020
• Last Update Posted: February 3, 2021
• Sponsor: NHS Greater Glasgow and Clyde
• Collaborator: University of Glasgow
• Information provided by (Responsible Party): NHS Greater Glasgow and Clyde

Study Description

Brief Summary:

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.

Condition or disease	Intervention/treatment
Chronic Obstructive Pulmonary Disease	Other: COPD digital support service

Detailed Description:

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.

Study Design

• Study Type: Observational
• Estimated Enrollment: 400 participants
• Observational Model: Cohort
• Time Perspective: Prospective
• Official Title: Remote-management of COPD: Evaluating Implementation of Digital Innovations to Enable Routine Care
• Actual Study Start Date: August 1, 2018
• Estimated Primary Completion Date: July 31, 2021
• Estimated Study Completion Date: July 31, 2021

Groups and Cohorts

Group/Cohort	Intervention/treatment
COPD group; 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; Use of COPD digital services to record patient symptoms, integrate physiology monitoring, communicate with the clinical team and track interaction; Other Name: Lenus Health COPD

Outcome Measures

Primary Outcome Measures :

1. Patient utilisation of digital service [ Time Frame: 24 months (12 months recruiting) ]
   Proportion of enrolled high-risk COPD patients successfully utilising remote-management in a digital service model

Secondary Outcome Measures :

1. Clinical outcomes [ Time Frame: 24 months (12 months recruiting) ]
   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
2. Clinical service outcomes [ Time Frame: 24 months (12 months recruiting) ]
   Impact of digital service model on clinical service outcomes including number, nature and complexity of reviews for remotely managed NIV and supported self management.
3. Machine-learning analyses [ Time Frame: 24 months (12 months recruiting) ]
   Machine-learning supported exploratory analyses of associations and relative predictive importance of electronic health record, patient-reported outcomes, wearables physiology and NIV parameters
4. Patient-centred outcomes [ Time Frame: 24 months (12 months recruiting) ]
   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.
5. Healthcare cost analyses of digital service model [ Time Frame: 24 months (12 months recruiting) ]
   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

Eligibility Criteria

• Ages Eligible for Study: 18 Years to 100 Years (Adult, Older Adult)
• Sexes Eligible for Study: All
• Accepts Healthy Volunteers: No
• Sampling Method: Non-Probability Sample

Study Population

Patients with high risk COPD presenting to secondary care with COPD exacerbation or persisting hypercapnic respiratory failure (requiring home NIV)

Criteria

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

Contacts and Locations

Locations

United Kingdom

Queen Elizabeth University Hospital

Glasgow, Scotland, United Kingdom, G51 4TF

Sponsors and Collaborators

NHS Greater Glasgow and Clyde

University of Glasgow

Investigators

• Principal Investigator: Chris Carlin; NHS Greater Glasgow and Clyde

More Information

Publications automatically indexed to this study by ClinicalTrials.gov Identifier (NCT Number):

Taylor A, Lowe DJ, McDowell G, Lua S, Burns S, McGinness P, Carlin CM. Remote-Management of COPD: Evaluating the Implementation of Digital Innovation to Enable Routine Care (RECEIVER): the protocol for a feasibility and service adoption observational cohort study. BMJ Open Respir Res. 2021 Aug;8(1):e000905. doi: 10.1136/bmjresp-2021-000905.

• Responsible Party: NHS Greater Glasgow and Clyde
• ClinicalTrials.gov Identifier: NCT04240353
• Other Study ID Numbers: INGN18RM173
• First Posted: January 27, 2020
• Last Update Posted: February 3, 2021
• Last Verified: February 2021

Individual Participant Data (IPD) Sharing Statement:

• Plan to Share IPD: No

• Studies a U.S. FDA-regulated Drug Product: No
• Studies a U.S. FDA-regulated Device Product: No

Additional relevant MeSH terms:

Lung Diseases; Lung Diseases, Obstructive; Pulmonary Disease, Chronic Obstructive; Respiratory Tract Diseases; Chronic Disease; Disease Attributes; Pathologic Processes