NHS Lothian

Small Business Research Initiative Grant

DL_2024_060

Chronic obstructive pulmonary disease (COPD) is a common lung condition, often caused by smoking. Patients living with COPD may suffer from shortness of breath and this can worsen unpredictably in flare-ups known as exacerbations. These often require hospital care. COPD is the commonest cause of emergency attendance to the hospital with breathlessness, and the third commonest cause of death worldwide. We plan to use health data from deidentified people with COPD to find risk factors for these exacerbations and other harmful outcomes including death. This will include using machine learning techniques, where advanced computers look for patterns in records that might otherwise be missed. Our aim is to create a new prediction tool that could be used to target care to patients identified at risk of deterioration. This project is a continuation of DL_2022_024 and involves new project partners in NHS Lothian to quickly move developments from this project into patient care.

Chronic Obstructive Pulmonary Disease (COPD) is the commonest cause of respiratory emergencies to the hospital and the third commonest cause of mortality worldwide. We know there are thousands of people living with COPD in the region, but we currently do not systematically use data to understand or improve their outcomes. For example, comparing current prescribing patterns against best-practice guidelines could help identify the numbers of patients in whom medications could be optimised. We will apply techniques of advanced machine learning to identify patterns in COPD patients who have more frequent harmful outcomes, such as unplanned hospital admissions. This will be used to develop a tool to predict and present a COPD patient’s risk of these outcomes, and so identify those who may benefit from earlier intervention by clinical teams. This innovation project is a continuation of DL_2022_024 being delivered in partnership with NHS Lothian to develop live clinical dashboards to target better care to COPD patients at the highest risk of harm. We believe this work is of high potential benefit to many patients living with COPD, with a clear route for translation into direct clinical care of patients in the region. This will hopefully in future also help us predict who’s at most risk of developing severe COPD, from a predictive algorithm to help address risk factors in that “at risk” cohort.

Public Health Research

21/10/2024

Personally Identifiable

Release