Many patients admitted to hospital have multiple long-term conditions (MLTCs), also known as multimorbidity. Despite this, care delivery in hospital is designed for the treatment of single conditions. Often, the care of patients with multimorbidity can be unsatisfactory, inefficient and expensive.

Chronic Obstructive Pulmonary Disease (COPD) is associated with a high burden of co-morbidities which tend to co-exist in specific disease clusters. Recognising their presence enables holistic patient management, but also offers opportunities to identify common biological mechanisms across diseases which might be therapeutically targetable.

The most common comorbidities in COPD include cardiovascular disease, diabetes, depression and osteoporosis. Often presentations are badged as exacerbations and alternative causes of breathlessness are missed.

This dataset includes 846 patients with COPD admitted to hospital. The infographic includes data from 01/01/2018 to 31/12/2018, but data is available from the past 10 years+. Data includes detailed demography, presenting symptoms, co-morbidities, admission diagnosis, laboratory tests, serial physiology, prescribed and administered drugs, use of non-invasive and invasive ventilation, and outcomes. Data can be matched to lung function for a proportion of patients.

PIONEER geography: The West Midlands (WM) has a population of 5.9 million & includes a diverse ethnic & socio-economic mix.

UHB is one of the largest NHS Trusts in England, providing direct acute services & specialist care across four hospital sites, with 2.2 million patient episodes per year, 2750 beds & an expanded 250 ITU bed capacity during COVID. UHB runs a fully electronic healthcare record (EHR) (PICS Birmingham Systems), a shared primary & secondary care record (Your Care Connected) & a patient portal “My Health”.

Scope: All patients admitted to hospital for COPD exacerbations. Longitudinal & individually linked, so that the preceding & subsequent health journey can be mapped & healthcare utilisation prior to & after admission understood. The dataset includes highly granular patient demographics, co-morbidities taken from ICD-10 & SNOMED-CT codes. Serial, structured data pertaining to process of care (timings, admissions, wards), presenting complaint, physiology readings (temperature, BMI, blood pressure, respiratory rate, NEWS2 score, oxygen saturations and others), Sample analysis results (urea, albumin, platelets, white blood cells and others) drug administered and all outcomes. Linked images available (radiographs, CT scans, MRI).

Available supplementary data: Matched controls ambulance, OMOP data, synthetic data.

Available supplementary support: Analytics, Model build, validation & refinement A.I. Data partner support for ETL (extract, transform & load) process, Clinical expertise, Patient & end-user access, Purchaser access, Regulatory requirements, Data-driven trials, “fast screen” services.