RECEIVER: Digital Service Model for Chronic Obstructive Pulmonary Disease (COPD)
|ClinicalTrials.gov Identifier: NCT04240353|
Recruitment Status : Recruiting
First Posted : January 27, 2020
Last Update Posted : January 27, 2020
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 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 services|
|Study Type :||Observational|
|Estimated Enrollment :||400 participants|
|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|
Patients with high-risk COPD receiving guideline-based COPD care, support for COPD self-management and support of the use of home NIV treatment via regular engagement with a digital health service model
Other: COPD digital services
Use of COPD digital services to record patient symptoms, integrate physiology monitoring, communicate with the clinical team and track interaction
- Successful engagement [ Time Frame: 1 year ]Proportion of enrolled patients successfully engaged with the digital service model as measured by the number of hospital admissions per year
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT04240353
|Contact: Anna Taylor, BSc (Hons) MB ChB||0141 451 email@example.com|
|Contact: Chris Carlinfirstname.lastname@example.org|
|Queen Elizabeth University Hospital||Recruiting|
|Glasgow, Scotland, United Kingdom, G51 4TF|
|Contact: Chris Carlin 01414516088 Christopher.Carlin@ggc.scot.nhs.uk|
|Contact: Jacqueline Anderson 01414516088 Jacqueline.Anderson@ggc.scot.nhs.uk|
|Principal Investigator: Chris Carlin|
|Sub-Investigator: Anna Taylor|
|Principal Investigator:||Chris Carlin||NHS Greater Glasgow and Clyde|