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Deeply phenotyped clinical data for hospitalised Atrial Fibrillation patients

Population Size

48,820

People

Years

2018 - 2022

Associated BioSamples

None/not available

Geographic coverage

United Kingdom

England

Lead time

Not applicable

Summary

Acute presentations of Atrial Fibrillation with hypertension, atherosclerosis or heart valve problems. Granular care pathways. Demography, multi-morbidity, investigations, interventions and treatments. Serial physiology, blood biomarkers, outcomes.

Documentation

Atrial fibrillation (AF) is a condition of the heart where the heart control rhythm changes from the normal sinus mode to a rapid activity. It is an irregular and often very rapid heart rhythm, known as a type of arrhythmia that can lead to thrombotic events and cardiac dysfunction. AF increases the risk of stroke, heart failure and other heart-related complications.

The cause is not fully understood, but it tends to affect certain groups of people, such as older people and people living with long-term (chronic) conditions such as heart disease, high blood pressure or obesity. Congenital heart disease, pericarditis, cardiomyopathy, physical and mental stress, also contribute to disease pathogenesis.

This highly granular dataset includes patient demographics, key lifestyle and underlying health status information, procedures (catheter ablation, electrical cardioversion), medications (beta-blockers, calcium channel blockers, anticoagulants), risk factors and co-morbidities.

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: Thematic dataset of Atrial Fibrillation and Atrial Flutter. 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, attending practitioner change and triage), presenting complaint, assessments, bed moves, consultation, DNAR TEAL, electrocardiogram, events, follow ups, physiology readings (heart rate, BMI, blood pressure, respiratory rate, NEWS2 score, oxygen saturations and clinical frailty scale and others), Lab analysis results (urea, albumin, platelets, potassium, white blood cell count, Covid 19 test and others) microbiology results, procedures, outpatients admissions, surgeries, therapies, ventilation, 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
Cardiovascular
Dataset population size
48,820

Keywords

arrhythmia, atrial fibrillation, High blood pressure, Acute, Heart conditions, Stroke, Heart failure, Cardiomyopathy, Chronic, blood clots, embolisms, beta-blockers, a-fib, anticoagulants, calcium channel blockers, sinus mode, heart condition, rapid heart rhythm, cardioversion, pacemakers

Observations

Observed Node
Disambiguating Description
Measured Value
Measured Property
Observation Date

Persons

48,820 spells diagnosed with atrial fibrillation

48820

Count

06 Jan 2022

Provenance

Purpose of dataset collection
Care
Source of data extraction
EPR
Collection source setting
Secondary care - Accident and Emergency, Secondary care - Outpatients, Secondary care - In-patients
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

06/01/2022

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

01/01/2022

Time lag
Other
Geographic coverage
United Kingdom, England, West Midlands
Maximum age range
150
Follow-up
1 - 10 Years

Accessibility

Language
en
Alignment with standardised data models
LOCAL
Controlled vocabulary
SNOMED CT, OPCS4, ICD10
Format
SQL

Data Access Request

Dataset pipeline status
Available
Time to dataset access
Not applicable
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: Cardiovascular


Collection Sources: No collection sources listed