Version: 1.0.0 | Published: 8 Oct 2024 | Updated: 229 days ago
Documentation
Associated Media:
Description:
The National Neonatal Research Database is an award-winning resource, a dynamic relational database containing information extracted from the electronic patient records of babies admitted to NHS neonatal units in England, Wales and Scotland (Northern Ireland is currently addressing regulatory requirements for participation). The NNRD-AI is a version of the NNRD curated for machine learning and artificial intelligence applications.
A team led by Professor Neena Modi at the Chelsea and Westminster Hospital campus of Imperial College London established the NNRD in 2007 as a resource to support clinical teams, managers, professional organisations, policy makers, and researchers who wish to evaluate and improve neonatal care and services. Recently, supported by an award from the Medical Research Council, the neonatal team and collaborating data scientists at the Institute for Translational Medicine and Therapeutics, Data Science Group at Imperial College London, created NNRD-AI.
The NNRD-AI is a subset of the full NNRD with around 200 baby variables, 100 daily variables and 450 additional aggregate variables. The guiding principle underpinning the creation of the NNRD-AI is to make available data that requires minimal input from domain experts. Raw electronic patient record data are heavily influenced by the collection process. Additional processing is required to construct higher-order data representations suitable for modelling and application of machine learning/artificial intelligence techniques. In NNRD-AI, data are encoded as readily usable numeric and string variables. Imputation methods, derived from domain knowledge, are utilised to reduce missingness. Out of range values are removed and clinical consistency algorithms applied. A wide range of definitions of complex major neonatal morbidities (e.g. necrotising enterocolitis, bronchopulmonary dysplasia, retinopathy of prematurity), aggregations of daily data and clinically meaningful representations of anthropometric variables and treatments are also available.
Coverage
Spatial:
United Kingdom,England; United Kingdom,Wales; Isle of Man
Typical Age Range:
0-1
Follow Up:
1 - 10 Years
Pathway:
Neonatal unit admission
Provenance
Origin
Purposes:
Care
Sources:
EPR
Collection Situations:
Secondary care - In-patients
Temporal
Accrual Periodicity:
Quarterly
Start Date:
01 January 2007
Time Lag:
2-6 months
Accessibility
Access
Access Rights:
Access Request Cost:
Delivery Lead Time:
Not applicable
Jurisdictions:
GB
Data Controller:
Professor Neena Modi, Imperial College London
Data Processor:
Professor Neena Modi, Imperial College London
Usage
Data Use Limitations:
No restriction
Data Use Requirements:
- Ethics approval required
- Project-specific restrictions
- User-specific restriction
Resource Creators:
We acknowledge the use of the UK National Neonatal Research Database (https://www.imperial.ac.uk/neonatal-data-analysis-unit/neonatal-data-analysis-unit/), established and led by Professor Neena Modi and her research group at Imperial College London, the contribution of neonatal units that collectively form the UK Neonatal Collaborative (https://www.imperial.ac.uk/neonatal-data-analysis-unit/neonatal-data-analysis-unit/contributing-to-the-nnrd/), and their lead clinicians as well as the support of the Imperial BRC and MRC.
Format and Standards
Vocabulary Encoding Schemes:
NHS NATIONAL CODES
Languages:
en
Formats:
csv
Observations
Statistical Population
Population Description
Population Size
Measured Property
Observation Date
Persons
Data on over 1.2 million babies, with approximately 25,000 new infant records added quarterly.
1270000
COUNT
07 November 2022