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Synthetic Dataset of Hospital Admissions for Patients with Type 1 and 2 Diabetes

Population Size

159,800

People

Population Size statistic card

Years

2004 - 2022

Years statistic card

Associated BioSamples

None/not available

Associated BioSamples statistic card

Geographic coverage

https://www.geonames.org/2634343/west-midlands.html

Geographic coverage statistic card

Lead time

1-2 months

Lead time statistic card

Summary

A synthetic dataset features patient-level information for 159,800 acute admissions associated with diabetes, including demography, socioeconomic data, co-morbidities, serial acuity and physiology, investigations, medications and outcomes.

Documentation

Type 1 Diabetes is an autoimmune disease impacting on insulin production. Type 2 Diabetes is caused by insulin resistance. Both are chronic conditions associated with serious complications such as heart disease, kidney failure, vision loss, and neuropathy. In the UK, 10% of the NHS budget is spent on managing diabetes. The demand for care is rising, with an increasing number of acute hospital admissions.

This highly granular synthetic dataset represents approximately 159,800 diabetes patients acutely admitted between 2004 and 2022. Data includes demography, socioeconomic status, co-morbidities, “time stamped” serial acuity, physiology and treatments, investigations (structured and unstructured data), hospital care processes, and outcomes.

The dataset was created using the Synthetic Data Vault (SDV) package, specifically employing the GAN synthesizer. The real data was read and pre-processed, ensuring datetime columns were correctly parsed and identifiers were handled as strings. Metadata was defined to capture the schema, specifying field types and primary keys. This metadata guided the synthesizer in understanding the structure of the data. The GAN synthesizer was then fitted to the real data, learning the distributions and dependencies within. After fitting, the synthesizer generated synthetic data that mirrors the statistical properties and relationships of the original dataset.

Geography: This synthetic dataset is based on patient data from the West Midlands. The West Midlands (WM) has a population of 6 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 & > 120 ITU bed capacity.

Data set availability: Data access is available via the PIONEER Hub for projects which will benefit the public or patients. Data access can be provided to NHS, academic, commercial, policy and third sector organisations. Applications from SMEs are welcome. There is a single data access process, with public oversight provided by our public review committee, the Data Trust Committee. Contact pioneer@uhb.nhs.uk or visit www.pioneerdatahub.co.uk for more details.

Available supplementary data: Matched controls; ambulance and community data. Unstructured data (images). We can provide the dataset in OMOP and other common data models and can build different synthetic data to meet bespoke requirements.

Available supplementary support: Analytics, model build, validation & refinement; A.I. support. Data partner support for ETL (extract, transform & load) processes. Bespoke and “off the shelf” Trusted Research Environment (TRE) build and run. Consultancy with clinical, patient & end-user and purchaser access/ support. Support for regulatory requirements. Cohort discovery. Data-driven trials and “fast screen” services to assess population size.

Dataset type

Health and disease, Measurements/Tests, Lifestyle

Dataset sub-type

Not applicable

Dataset population size

159800

Keywords

Observations

Observed Node

Disambiguating Description

Measured Value

Measured Property

Observation Date

Persons

159,800 spells for patients with Diabetes between 01/2004 and 06/2022

159800

Count

06 Nov 2024

Provenance

Purpose of dataset collection

Care

Source of data extraction

Machine generated

Collection source setting

Secondary care - Accident and Emergency

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

02/12/2024

Distribution release date

03/12/2024

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

01/01/2004

End date

01/06/2022

Time lag

Other

Maximum age range

105

Follow-up

1 - 10 Years

Accessibility

Language

en

Alignment with standardised data models

LOCAL

Controlled vocabulary

SNOMED CT, ICD10, OPCS4

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

Data Processor

NOT APPLICABLE

Dataset Types: Health and disease, Measurements/Tests, Lifestyle


Collection Sources: Secondary care - Accident and Emergency

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