Imperial College London
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ProfessorVictoriaCornelius

Faculty of Medicine, School of Public Health

Professor in Medical Statistics and Trials Methodology
 
 
 
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Contact

 

+44 (0)20 7594 1218v.cornelius

 
 
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Assistant

 

Mrs Ranjit Rayat +44 (0)20 7594 3445

 
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Location

 

111Stadium HouseWhite City Campus

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Summary

 

Publications

Citation

BibTex format

@article{Cornelius:2018:10.1186/s13063-018-2723-3,
author = {Cornelius, V and McDermott, L and Forster, A and Ashworth, M and Wright, A and Gulliford, M},
doi = {10.1186/s13063-018-2723-3},
journal = {Trials},
title = {Automated recruitment and randomisation for an efficient randomised controlled trial in primary care},
url = {http://dx.doi.org/10.1186/s13063-018-2723-3},
volume = {19},
year = {2018}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Background/aimsUse of electronic health records and information technology to deliver more efficient clinical trials is attracting the attention of research funders and researchers. We report on methodological issues and data quality for a comparison of ‘automated’ and manual (or ‘in-practice’) methods for recruitment and randomisation in a large randomised controlled trial, with individual patient allocation in primary care.MethodsWe conducted a three-arm randomised controlled trial in primary care to evaluate interventions to improve the uptake of invited NHS health checks for cardiovascular risk assessment. Eligible participants were identified using a borough-wide health check management information system. An in-practice recruitment and randomisation method used at 12 general practices required the research team to complete monthly visits to each general practice. For the fully automated method, employed for six general practices, randomisation of eligible participants was performed automatically and remotely using a bespoke algorithm embedded in the health check management information system.ResultsThere were 8588 and 4093 participants recruited for the manual and automated methods, respectively. The in-practice method was ready for implementation 3 months sooner than the automated method and the in-practice method allowed for full control and documentation of the randomisation procedure. However the in-practice approach was labour intensive and the requirement for participant records to be stored locally resulted in the loss of data for 10 practice months. No records for participants allocated using the automated method were lost. A fixed-effects meta-analysis showed that effect estimates for the primary outcome were consistent for the two allocation methods.ConclusionsThis trial demonstrated the feasibility of automated recruitment and randomisation methods into a randomised controlled trial performed in primary care. Future research
AU  - Cornelius,V
AU  - McDermott,L
AU  - Forster,A
AU  - Ashworth,M
AU  - Wright,A
AU  - Gulliford,M
DO  - 10.1186/s13063-018-2723-3
PY  - 2018///
SN  - 1745-6215
TI  - Automated recruitment and randomisation for an efficient randomised controlled trial in primary care
T2  - Trials
UR  - http://dx.doi.org/10.1186/s13063-018-2723-3
UR  - http://hdl.handle.net/10044/1/61058
VL  - 19
ER  -
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