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Automated recruitment and randomisation for an efficient randomised controlled trial in primary care
BACKGROUND/AIMS: Use 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’) me...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6020316/ https://www.ncbi.nlm.nih.gov/pubmed/29945656 http://dx.doi.org/10.1186/s13063-018-2723-3 |
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author | Cornelius, Victoria R. McDermott, Lisa Forster, Alice S. Ashworth, Mark Wright, Alison J. Gulliford, Martin C. |
author_facet | Cornelius, Victoria R. McDermott, Lisa Forster, Alice S. Ashworth, Mark Wright, Alison J. Gulliford, Martin C. |
author_sort | Cornelius, Victoria R. |
collection | PubMed |
description | BACKGROUND/AIMS: Use 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. METHODS: We 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. RESULTS: There 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. CONCLUSIONS: This trial demonstrated the feasibility of automated recruitment and randomisation methods into a randomised controlled trial performed in primary care. Future research should explore the application of these techniques in other clinical contexts and health care settings. TRIAL REGISTRATION: Current Controlled Trials, ID: ISRCTN42856343. Registered on 21 March 2013 ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13063-018-2723-3) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6020316 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-60203162018-07-06 Automated recruitment and randomisation for an efficient randomised controlled trial in primary care Cornelius, Victoria R. McDermott, Lisa Forster, Alice S. Ashworth, Mark Wright, Alison J. Gulliford, Martin C. Trials Research BACKGROUND/AIMS: Use 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. METHODS: We 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. RESULTS: There 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. CONCLUSIONS: This trial demonstrated the feasibility of automated recruitment and randomisation methods into a randomised controlled trial performed in primary care. Future research should explore the application of these techniques in other clinical contexts and health care settings. TRIAL REGISTRATION: Current Controlled Trials, ID: ISRCTN42856343. Registered on 21 March 2013 ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13063-018-2723-3) contains supplementary material, which is available to authorized users. BioMed Central 2018-06-27 /pmc/articles/PMC6020316/ /pubmed/29945656 http://dx.doi.org/10.1186/s13063-018-2723-3 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Cornelius, Victoria R. McDermott, Lisa Forster, Alice S. Ashworth, Mark Wright, Alison J. Gulliford, Martin C. Automated recruitment and randomisation for an efficient randomised controlled trial in primary care |
title | Automated recruitment and randomisation for an efficient randomised controlled trial in primary care |
title_full | Automated recruitment and randomisation for an efficient randomised controlled trial in primary care |
title_fullStr | Automated recruitment and randomisation for an efficient randomised controlled trial in primary care |
title_full_unstemmed | Automated recruitment and randomisation for an efficient randomised controlled trial in primary care |
title_short | Automated recruitment and randomisation for an efficient randomised controlled trial in primary care |
title_sort | automated recruitment and randomisation for an efficient randomised controlled trial in primary care |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6020316/ https://www.ncbi.nlm.nih.gov/pubmed/29945656 http://dx.doi.org/10.1186/s13063-018-2723-3 |
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