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The impact of multimorbidity on care pathways during COPD hospitalisations

Population Size

846

People

Population Size statistic card

Years

2018 - 2018

Years statistic card

Associated BioSamples

None/not available

Associated BioSamples statistic card

Geographic coverage

United Kingdom

England

Geographic coverage statistic card

Lead time

1-2 months

Lead time statistic card

Summary

Deeply phenotyped data on patients hospitalised with COPD with and without other conditions to map pathways and outcomes. Granular multi-morbidity data, investigations, investigations and treatments. Serial physiology, laboratory results, outcomes.

Documentation

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.

Dataset type

Health and disease, Treatments/Interventions

Dataset sub-type

Respiratory

Dataset population size

846

Keywords

Observations

Observed Node

Disambiguating Description

Measured Value

Measured Property

Observation Date

Persons

846 admissions of worsening COPD between 01-01-2018 to 31-12-2018

846

Count

17 Dec 2021

Provenance

Purpose of dataset collection

Care

Source of data extraction

EPR

Collection source setting

Secondary care - Accident and Emergency, Secondary care - In-patients, Secondary care - Outpatients

Patient pathway description

Data is representative of the multi-ethnicity population within the West Midlands (42% non white). Data includes all patients admitted during this timeframe, with National data Opt Outs applied, and therefore is representative of admissions to secondary care. Data focuses on in-patient stay in hospital during the acute episode but can be supplemented on request to include previous and subsequent hospital contacts (including outpatient appointments) and ambulance, 111, 999 data.

Image contrast

Not stated

Biological sample availability

None/not available

Structural Metadata

Details

Publishing frequency

Quarterly

Version

1.0.0

Modified

08/10/2024

Distribution release date

17/12/2021

Citation Requirements

This publication uses data from PIONEER, an ethically approved database and analytical environment (East Midlands Derby Research Ethics 20/EM/0158)

Coverage

Start date

01/01/2018

End date

31/12/2018

Time lag

Other

Geographic coverage

United Kingdom, England, West Midlands

Minimum age range

20

Maximum age range

95

Follow-up

1 - 10 Years

Accessibility

Language

en

Alignment with standardised data models

LOCAL

Controlled vocabulary

SNOMED CT, ICD10

Format

SQL

Data Access Request

Dataset pipeline status

Available

Time to dataset access

1-2 months

Access request cost

www.pioneerdatahub.co.uk/data/data-services-costs/

Access method category

TRE/SDE

Access service description

Trusted Research Environments (TRE) are built using Microsoft Azure services and hosted in the UK to provide research teams a safe, secure and agile environment which allows users to quickly analyse, interpret and form an enriched view of primary care information through a range of integrated datasets.

Health data collated from multiple sources is ingested into a secure data lake which will then allow subsets of data to be made available to research teams on approval of a data request. Once approved a customer specific TRE is made available with a standard set of leading analytical tools from Microsoft including Azure Databricks, Azure Machine Learning, Azure SQL and Azure Synapse (for large-scale data warehouses). Specific tools can be provided at an additional cost over the standard platform data access charge and the PIONEER team will work with you to determine your exact needs.

Access to the TRE is managed using the latest virtual desktop technology to provide a safe and secure end-user experience. By utilising leading edge design PIONEER are able to create TREs rapidly to enable us to service any customer requirement.

Jurisdiction

GB-ENG

Data use limitation

General research use

Data use requirements

Project-specific restrictions

Data Controller

University Hospitals Birmingham NHS Foundation Trust

Dataset Types: Health and disease, Treatments/Interventions

Dataset Sub-types: Respiratory


Collection Sources: Secondary care - Accident and Emergency, Secondary care - In-patients, Secondary care - Outpatients

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