DYNAMIC AI: Digital Innovation With Remote Management and Predictive Modelling to Integrate COPD Care With Artificial Intelligence-based Insights: An Acceptability, Feasibility and Safety Study

NCT05914220 | Unknown

• 1 other identifier: INGN20RM641
• Study Type: observational
• Target: 500
• Locations: 1 country
• Sites: 1

Brief Summary

DYNAMIC AI is an MHRA-regulated medical device trial that will examine the feasibility of using AI predictive models within COPD multi-disciplinary team meetings, to allow clinicians to prioritise and optimise COPD management.

Conditions

COPD

Outcome Measures

Primary Outcomes (3)

• Acceptability to patients

  Evaluation of acceptability to patients with COPD of presenting live artificial intelligence-based 12-month mortality risk-prediction score from the LenusCOPD AI insights application, to COPD clinicians' multi-disciplinary team meetings in NHS GG\&C : Evaluation will be based on proportion of patients invited who consent to participate in the DYNAMIC-AI study.

  12 months

• Technical feasibility

  Technical Feasability of presenting live artificial intelligence-based 12-month mortality risk-prediction score from the LenusCOPD AI insights application, to COPD clinicians' multi-disciplinary team meetings in NHS GG\&C: Evaluation of feasibility will be proportion of participants with have adequate source data in LenusCOPD and who have 12-month mortality model-risk scores calculated and presented for MDT review in the AI-insights model app

  12 months

• Safety

  Safety of presenting live artificial intelligence-based 12-month mortality risk-prediction score from the LenusCOPD AI insights application, to COPD clinicians' multi-disciplinary team meetings in NHS GG\&C Evaluation of safety will be based on occurrence of device-related adverse events and from the prospective evaluation of model risk scores - actions of clinicians based on model risk scores and calibration of predicted events : occurred events

  12 months

Secondary Outcomes (4)

• acceptability and technical feasibility experience

  12 months

• Expand dataset for training and validation

  12 months

• Evaluate technical feasibility and descriptive adoption experience

  12 months

• preliminary experience and utility dataset

  12 months

Interventions

AI Insights Application DEVICE

Predictive AI Model Risk score

Eligibility Criteria

• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

People with COPD living within NHS Greater Glasgow and Clyde Health Board

You may qualify if:

• Current active user of NHS Scotland COPD digital service. Resident and under care of NHS GG\&C COPD multidisciplinary team. Consent, access to technology (smartphone, tablet, computer and daily internet access), ability to understand written English and confirmed diagnosis of COPD are requirements for use of the COPD digital service

You may not qualify if:

• Lack of provision of informed consent.

Sponsors & Collaborators

• NHS Greater Glasgow and Clyde: lead
• Lenus Health: collaborator
• University of Glasgow Robertson Centre for Bio Statistics: collaborator

Study Sites (1)

Queen Elizabeth University Hospital

Glasgow, Scotland, G51 4TF, United Kingdom

RECRUITING

MeSH Terms

Conditions

Pulmonary Disease, Chronic Obstructive

Condition Hierarchy (Ancestors)

Lung Diseases, Obstructive; Lung Diseases; Respiratory Tract Diseases; Chronic Disease; Disease Attributes; Pathologic Processes; Pathological Conditions, Signs and Symptoms

Central Study Contacts

Jacqueline Anderson

CONTACT

Jacqueline.Anderson@ggc.scot.nhs.uk

Ruairidh Davison

CONTACT

Ruairidh.Davison@ggc.scot.nhs.uk

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: June 13, 2023
• First Posted: June 22, 2023
• Study Start: April 1, 2023
• Primary Completion: March 31, 2024
• Study Completion: August 31, 2024
• Last Updated: June 22, 2023

Record last verified: 2023-06

Locations

GB (1)