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Antimicrobial prescribing surveillance data during the COVID-19 pandemic

Population Size

1,602,184

People

Population Size statistic card

Years

2008 - 2021

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 population-level surveillance of therapeutic or preventative antimicrobial interventions of hospitalised COVID-19 patients; including comorbidity data; physiology, blood biomarkers, and outcomes. Longitudinal and individually linked.

Documentation

The use of antimicrobial drugs is linked to antimicrobial resistance which can lead to infections that are harder to treat and may be associated with worse outcomes for the patient.

The use of antibiotics changed in hospital during the different waves of the COVID-19 pandemic, as data was used to assess if antibiotic therapy was associated with better health outcomes for patients with confirmed COVID-19. Looking at changes in health outcomes linked to antibiotic therapy across the whole hospital instead of only patients with COVID-19 over time will help understand if changes to antibiotic use during the pandemic may have had an impact on the risk of antibiotic resistance.

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

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

Scope: Longitudinal and individually linked, so that the preceding and subsequent health journey can be mapped and healthcare utilisation prior to and after admission understood. The dataset includes highly granular patient demographics, co-morbidities taken from ICD-10 and SNOMED-CT codes. Serial, structured data pertaining to process of care (timings, wards and admissions), surgery procedures, microbiology reports, COVID results, prescriptions, drug administered and all outcomes.

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

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

Dataset type

Health and disease, Treatments/Interventions

Dataset sub-type

Therapeutic

Dataset population size

1602184

Keywords

Observations

Observed Node

Disambiguating Description

Measured Value

Measured Property

Observation Date

Persons

1,602,184 spells between 01.12.2008 and 03.07.2021

1602184

Count

20 Jan 2022

Provenance

Purpose of dataset collection

Care

Source of data extraction

EPR

Collection source setting

Secondary care - Accident and Emergency, 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

20/01/2022

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

01/12/2008

End date

02/07/2021

Time lag

Other

Geographic coverage

United Kingdom, England, West Midlands

Minimum age range

15

Maximum age range

110

Follow-up

Other

Accessibility

Language

en

Alignment with standardised data models

LOCAL

Controlled vocabulary

ICD10, OPCS4, LOCAL, NHS NATIONAL CODES

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: Therapeutic


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

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