Imperial College London
Alternate

ProfessorStephenBrett

Faculty of Medicine, Department of Surgery & Cancer

Professor of Critical Care
 
 
 
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Contact

 

+44 (0)20 3313 4521stephen.brett Website

 
 
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Location

 

Hammersmith House 570Hammersmith HospitalHammersmith Campus

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Summary

 

Publications

Citation

BibTex format

@article{Harris:2018:10.1016/j.ijmedinf.2018.01.006,
author = {Harris, S and Shi, S and Brealey, D and MacCallum, NS and Denaxas, S and Perez-Suarez, D and Ercole, A and Watkinson, P and Jones, A and Ashworth, S and Beale, R and Young, D and Brett, S and Singer, M},
doi = {10.1016/j.ijmedinf.2018.01.006},
journal = {International Journal of Medical Informatics},
pages = {82--89},
title = {Critical Care Health Informatics Collaborative (CCHIC): data, tools and methods for reproducible research: a multi-centre UK intensive care database},
url = {http://dx.doi.org/10.1016/j.ijmedinf.2018.01.006},
volume = {112},
year = {2018}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - To build and curate a linkable multi-centre database of high resolution longitudinal electronic health records (EHR) from adult Intensive Care Units (ICU). To develop a set of open-source tools to make these data ‘research ready’ while protecting patient's privacy with a particular focus on anonymisation. Materials and methods: We developed a scalable EHR processing pipeline for extracting, linking, normalising and curating and anonymising EHR data. Patient and public involvement was sought from the outset, and approval to hold these data was granted by the NHS Health Research Authority's Confidentiality Advisory Group (CAG). The data are held in a certified Data Safe Haven. We followed sustainable software development principles throughout, and defined and populated a common data model that links to other clinical areas. Results: Longitudinal EHR data were loaded into the CCHIC database from eleven adult ICUs at 5 UK teaching hospitals. From January 2014 to January 2017, this amounted to 21,930 and admissions (18,074 unique patients). Typical admissions have 70 data-items pertaining to admission and discharge, and a median of 1030 (IQR 481–2335) time-varying measures. Training datasets were made available through virtual machine images emulating the data processing environment. An open source R package, cleanEHR, was developed and released that transforms the data into a square table readily analysable by most statistical packages. A simple language agnostic configuration file will allow the user to select and clean variables, and impute missing data. An audit trail makes clear the provenance of the data at all times. Discussion: Making health care data available for research is problematic. CCHIC is a unique multi-centre longitudinal and linkable resource that prioritises patient privacy through the highest standards of data security, but also provides tools to clean, organise, and anonymise the data. We believe the development of such tools are
AU  - Harris,S
AU  - Shi,S
AU  - Brealey,D
AU  - MacCallum,NS
AU  - Denaxas,S
AU  - Perez-Suarez,D
AU  - Ercole,A
AU  - Watkinson,P
AU  - Jones,A
AU  - Ashworth,S
AU  - Beale,R
AU  - Young,D
AU  - Brett,S
AU  - Singer,M
DO  - 10.1016/j.ijmedinf.2018.01.006
EP  - 89
PY  - 2018///
SN  - 1386-5056
SP  - 82
TI  - Critical Care Health Informatics Collaborative (CCHIC): data, tools and methods for reproducible research: a multi-centre UK intensive care database
T2  - International Journal of Medical Informatics
UR  - http://dx.doi.org/10.1016/j.ijmedinf.2018.01.006
UR  - http://hdl.handle.net/10044/1/57363
VL  - 112
ER  -
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