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The acute presentation of pregnant women to non-maternity Emergency departments

Dataset
Version: 1.0.0
Patients admitted with a pregnancy related event. Granular care pathways. Multi-morbidity, investigations, interventions and treatments. Serial physiology, blood biomarkers, physiotherapy, outcome. Deeply phenotyped.

Summary

Citation:
The acute presentation of pregnant women to non-maternity Emergency departments

Documentation

Description:
Each year, there are audits to assess maternal & foetal outcomes across the UK. In 2016-18, 217 women died during or up to six weeks after pregnancy, from causes associated with their pregnancy, among 2,235,159 women giving birth in the UK. 9.7 women per 100k died during pregnancy or up to six weeks after childbirth or the end of pregnancy. There was an increase in the overall maternal death rate in the UK between 2013-15 & 2016-18. Assessors judged that 29% of women who died had good care. However, improvements in care which may have made a difference to the outcome were identified for 51% of women who died. Birmingham has a higher than average maternal & foetal death rate. This dataset includes detailed information about the reasons pregnant women seek acute care, & their care pathways & outcomes. PIONEER geography: The West Midlands (WM) has a population of 5.9m & includes a diverse ethnic, socio-economic mix. There is a higher than average % of minority ethnic groups. WM has the youngest population in the UK with a higher than average birth rate. There are particularly high rates of physical inactivity, obesity, smoking & diabetes. 51.2% of babies born in Birmingham have at least one parent born outside of the UK, this compares with 34.7% for England. Each day >100k people are treated in hospital, see their GP or are cared for by the NHS. EHR: University Hospitals Birmingham NHS Foundation Trust (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 & 100 ITU beds. 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: Pregnant or post-partum women from 2015 onwards who attended A&E in Queen Elizabeth hospital. 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 (including gestation & postpartum period), co-morbidities taken from ICD-10 & SNOMED-CT codes. Serial, structured data pertaining to process of care (admissions, wards, practitioner changes & discharge outcomes), presenting complaints, physiology readings (temperature, blood pressure, NEWS2, SEWS, AVPU), referrals, all prescribed & administered treatments & all outcomes. Available supplementary data: More extensive data including granular serial physiology, bloods, conditions, interventions, treatments. Ambulance, 111, 999 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.
Is Part Of:
NOT APPLICABLE

Coverage

Spatial:
United Kingdom, England, West Midlands
Typical Age Range:
10-55
Follow Up:
OTHER
Physical Sample Availability:
NOT AVAILABLE
Pathway:
The West Midlands (WM) has a population of 5.9 million & includes a diverse ethnic, socio-economic mix. There is a higher than average percentage of minority ethnic groups with Birmingham having a population which is >40% non-white. Birmingham is one of the youngest cities in Europe and has a birth rate that is higher than average (The General Fertility Rate was 69.7 births per thousand population and the Total Fertility Rate was 2.04 children per woman in 2016, both higher than the average for the UK). Unfortunately Birmingham also has a higher than average infant mortality rate and a higher than average incidence of maternal complications. There is social deprivation and Birmingham’s population suffers with particularly high rates of physical inactivity, obesity, smoking & diabetes. There are also high levels of rare diseases, especially immunometabolic conditions. The patients included in this dataset are representative of this diverse population and also include a wide age-range. University Hospitals Birmingham NHS Foundation Trust (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 & 100 ITU beds. 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”. This dataset includes the patient journey from admission to hospital to outcome for pregnant and post-partum patients admitted to a general hospital. The data includes granular demography and co-morbidity, presenting symptoms and diagnoses, serial physiology and blood biomarkers, all investigations, all prescribed and administered treatments and outcomes. It can be supplemented with preceding and following health care contacts, to understand the risk for the acute admission during pregnancy and the subsequent impact on health after discharge. Although primarily secondary care, this dataset can be supplemented with ambulance and primary care data on request. PIONEER can also offer synthetic data, images and access to a secure Trusted Research Environment for analytics and AI. PIONEER can assist with 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.

Provenance

Origin

Purposes:
CARE
Sources:
EPR
Collection Situations:
  • ACCIDENT AND EMERGENCY
  • IN-PATIENTS

Temporal

Accrual Periodicity:
QUARTERLY
Distribution Release Date:
2020-02-17
Start Date:
2015-01-01
End Date:
2020-12-31
Time Lag:
LESS 1 WEEK

Accessibility

Access

Access Service:
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.
Access Request Cost:
www.pioneerdatahub.co.uk/data/data-services-costs/
Delivery Lead Time:
1-2 MONTHS
Jurisdictions:
GB-GBN
Data Controller:
University Hospitals Birmingham NHS Foundation Trust
Data Processor:
NOT APPLICABLE

Usage

Data Use Limitations:
GENERAL RESEARCH USE
Data Use Requirements:
PROJECT SPECIFIC RESTRICTIONS
Resource Creators:
  • This publication uses data from PIONEER
  • an ethically approved database and analytical environment (East Midlands Derby Research Ethics 20/EM/0158)

Format and Standards

Vocabulary Encoding Schemes:
  • ICD10
  • OPCS4
  • SNOMED CT
Conforms To:
LOCAL
Languages:
en
Formats:
SQL

Observations

Statistical Population
Population Description
Population Size
Measured Property
Observation Date
Events
1035 maternity spells in this dataset from 01.01.2015 to 31.12.2020
1035
COUNT
2020-02-17