Optimising COPD Care Pathways through EHR Integration, Risk Stratification, and Data Strategy Alignment

Lay Description

Aims

1) Inform regional and national practitioners and policy makers about the benefits of integrated Respiratory Hubs for Chronic Obstructive Pulmonary Disease (COPD) care.

2) Explore advanced AI approaches to risk stratification of COPD patients in primary care.

Objectives & plan of investigation

1) Identify and curate clinical datasets from provider service’s Electronic Health Records (EHRs) across the pathway for COPD care.

2) Develop harmonised coding set/key terms for COPD care- diagnosis, treatment, and outcomes including future risk profile.

3) Analyse factors which predict poor clinical outcome (future exacerbation risk, ED attendance and hospital admission) to create risk stratification models for targeted clinical interventions.

4) Develop novel stratification approaches to identify rising risk COPD patients in primary care using Natural Language Processing Models (NLP) and ML validated against conventional coding and hospital outcomes.

5) Provide a blueprint for integrating COPD pathway data to inform national rollout of the HDRUK support Respiratory Data Strategy.

Public Benefit Statement

Anticipated value of the project:

For Patients

• Earlier identification of those at risk of COPD exacerbations (getting worse), enabling timely and targeted interventions.
• More personalised care, reducing unnecessary admissions to hospital and improving quality of life.
• Fairer, more consistent treatment through standardised coding and joined up care pathways.

For the NHS:

• Fewer emergency attendances and admissions, reducing pressure on hospitals and costs.
• Better use of clinical time and resources through integrated EHRs and risk prediction tools.
• A scalable blueprint to inform the wider UK Respiratory Data Strategy and strengthen national respiratory care.