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Granular ICU data focussing on the impact of lactate readings on outcomes

Population Size

12,369

People

Population Size statistic card

Years

2018 - 2020

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

A granular dataset of over 12,000 ICU admissions with lactate reading from 01/01/2018 to 31/12/2020 (pre-COVID). Detailed patient flow through the hospital providing severity, demographics, multi-morbidity, interventions, treatments and outcomes.

Documentation

Lactate is a chemical produced by the body as cells consume energy - in times of stress more lactate is produced. In the past, we thought that lactate was just a waste product, but more recently we have learned that lactate has an important role to play in the body.

People suffering from certain severe illnesses may have a high ‘lactate’ level in their blood. This is particularly common in the following:

Severe infections which the body cannot properly control (sepsis)

People who have sustained severe injuries (traumatic injury)

People who are critically unwell with other illnesses (needing treatment in an intensive care unit)

Some patients will develop a high lactate level when they are in hospital. Doctors recognise that this indicates the patient is becoming more unwell, but it is often challenging to know exactly what is causing the lactate level to be raised.

Raised lactate level has been associated with worse outcome in other syndromes, including major trauma and undifferentiated critical illness; however healthy individuals may generate very high lactate levels during strenuous exercise from which they recover without any harm. It is unclear whether lactate in itself is harmful to patients. This dataset provides unique insight into the potential role of lactate as not only a biomarker but a therapeutic target in acute illness.

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, admissions, wards), presenting complaint, physiology readings (BMI, temperature and weight), Sample analysis results (blood sodium level, lactate, haemoglobin, oxygen saturations, and others) drug administered and all outcomes.

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 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

Metabolic and endocrine

Dataset population size

12369

Keywords

Observations

Observed Node

Disambiguating Description

Measured Value

Measured Property

Observation Date

Persons

12,369 ICU admissions with lactate reading from 01/01/2018 to 31/12/2020

12369

Count

25 Nov 2021

Provenance

Purpose of dataset collection

Care

Source of data extraction

EPR

Collection source setting

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

25/11/2021

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

28/12/2020

Time lag

Other

Geographic coverage

United Kingdom, England, West Midlands

Minimum age range

19

Maximum age range

105

Follow-up

Other

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: Metabolic and endocrine


Collection Sources: Secondary care - In-patients

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