MedTrace Logo

Predict&Prevent: Use of a Personalised Early Warning Decision Support System to Predict and Prevent Acute Exacerbations of COPD

NCT04136418 · Status: UNKNOWN · Phase: NA · Type: INTERVENTIONAL · Enrollment: 384

Last updated 2022-11-01

No results posted yet for this study

Summary

COPD is a common complex disease with debilitating breathlessness; mortality and reduced quality of life, accelerated by frequent lung attacks (exacerbations). Changes in breathlessness, cough and/or sputum production often change before exacerbations but patients cannot judge the importance of such changes so they remain unreported and untreated. Remote monitoring systems have been developed but none have yet convincingly shown the ability to identify these early changes of an exacerbation and how severe they can be.

This study asks if a smart digital health intervention (COPDPredict™) can be used by both COPD patients and clinicians to improve self-management, predict lung attacks early, intervene promptly, and avoid hospitalisation.

COPDPredict™ consists of a patient-facing App and clinician-facing smart early warning decision support system. It collects and processes information to determine a patient's health through a combination of wellbeing scores, lung function and biomarker measurements. This information is combined to generate personalised lung health profiles. As each patient is monitored over time, the system detects changes from an individual's 'usual health' and indicates the likelihood of imminent exacerbation of COPD. When this happens, alerts are sent to both the individual and the clinician, with instructions to the patient on what actions to take. Any advice from clinicians can be exchanged via the App's secure messaging facility. If patients have followed the action plan but fail to improve or if an episode triggers an 'at high risk alert', clinicians are further prompted to case manage and intervene with escalated treatment, including home visits, if necessary.

The COPDPredict™ intervention aims to assist patients and clinicians in preventing clinical deterioration from COPD exacerbations with prompt appropriate intervention.

This study will randomise 384 patients who have frequent exacerbations, from hospitals in the West Midlands, to either (1) standard self-management plan (SSMP) with rescue medication (RM), or (2) COPDPredict™ and RM.

Conditions

Interventions

DEVICE

COPDPredict mobile App

An App on a mobile device is used by the patient to track the status of their COPD and inform the patient's care team

OTHER

Usual care

Patients self-manage their COPD using prescribed medication in accordance with basic guidance information

Sponsors & Collaborators

  • University Hospitals of North Midlands NHS Trust

    collaborator OTHER

  • University of Birmingham

    lead OTHER

Study Design

Allocation
RANDOMIZED
Purpose
PREVENTION
Masking
NONE
Model
PARALLEL

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2020-10-07
Primary Completion
2023-03-31
Completion
2023-03-31

Countries

  • United Kingdom

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04136418 on ClinicalTrials.gov