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Using electronic patient records to assess the effect of a complex antenatal intervention in a cluster randomised controlled trial—data management experience from the DESiGN Trial team

BACKGROUND: The use of electronic patient records for assessing outcomes in clinical trials is a methodological strategy intended to drive faster and more cost-efficient acquisition of results. The aim of this manuscript was to outline the data collection and management considerations of a maternity...

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Autores principales: Relph, Sophie, Elstad, Maria, Coker, Bolaji, Vieira, Matias C., Moitt, Natalie, Gutierrez, Walter Muruet, Khalil, Asma, Sandall, Jane, Copas, Andrew, Lawlor, Deborah A., Pasupathy, Dharmintra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7941939/
https://www.ncbi.nlm.nih.gov/pubmed/33685512
http://dx.doi.org/10.1186/s13063-021-05141-8
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author Relph, Sophie
Elstad, Maria
Coker, Bolaji
Vieira, Matias C.
Moitt, Natalie
Gutierrez, Walter Muruet
Khalil, Asma
Sandall, Jane
Copas, Andrew
Lawlor, Deborah A.
Pasupathy, Dharmintra
author_facet Relph, Sophie
Elstad, Maria
Coker, Bolaji
Vieira, Matias C.
Moitt, Natalie
Gutierrez, Walter Muruet
Khalil, Asma
Sandall, Jane
Copas, Andrew
Lawlor, Deborah A.
Pasupathy, Dharmintra
author_sort Relph, Sophie
collection PubMed
description BACKGROUND: The use of electronic patient records for assessing outcomes in clinical trials is a methodological strategy intended to drive faster and more cost-efficient acquisition of results. The aim of this manuscript was to outline the data collection and management considerations of a maternity and perinatal clinical trial using data from electronic patient records, exemplifying the DESiGN Trial as a case study. METHODS: The DESiGN Trial is a cluster randomised control trial assessing the effect of a complex intervention versus standard care for identifying small for gestational age foetuses. Data on maternal/perinatal characteristics and outcomes including infants admitted to neonatal care, parameters from foetal ultrasound and details of hospital activity for health-economic evaluation were collected at two time points from four types of electronic patient records held in 22 different electronic record systems at the 13 research clusters. Data were pseudonymised on site using a bespoke Microsoft Excel macro and securely transferred to the central data store. Data quality checks were undertaken. Rules for data harmonisation of the raw data were developed and a data dictionary produced, along with rules and assumptions for data linkage of the datasets. The dictionary included descriptions of the rationale and assumptions for data harmonisation and quality checks. RESULTS: Data were collected on 182,052 babies from 178,350 pregnancies in 165,397 unique women. Data availability and completeness varied across research sites; each of eight variables which were key to calculation of the primary outcome were completely missing in median 3 (range 1–4) clusters at the time of the first data download. This improved by the second data download following clarification of instructions to the research sites (each of the eight key variables were completely missing in median 1 (range 0–1) cluster at the second time point). Common data management challenges were harmonising a single variable from multiple sources and categorising free-text data, solutions were developed for this trial. CONCLUSIONS: Conduct of clinical trials which use electronic patient records for the assessment of outcomes can be time and cost-effective but still requires appropriate time and resources to maximise data quality. A difficulty for pregnancy and perinatal research in the UK is the wide variety of different systems used to collect patient data across maternity units. In this manuscript, we describe how we managed this and provide a detailed data dictionary covering the harmonisation of variable names and values that will be helpful for other researchers working with these data. TRIAL REGISTRATION: Primary registry and trial identifying number: ISRCTN 67698474. Registered on 02/11/16. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13063-021-05141-8.
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spelling pubmed-79419392021-03-09 Using electronic patient records to assess the effect of a complex antenatal intervention in a cluster randomised controlled trial—data management experience from the DESiGN Trial team Relph, Sophie Elstad, Maria Coker, Bolaji Vieira, Matias C. Moitt, Natalie Gutierrez, Walter Muruet Khalil, Asma Sandall, Jane Copas, Andrew Lawlor, Deborah A. Pasupathy, Dharmintra Trials Methodology BACKGROUND: The use of electronic patient records for assessing outcomes in clinical trials is a methodological strategy intended to drive faster and more cost-efficient acquisition of results. The aim of this manuscript was to outline the data collection and management considerations of a maternity and perinatal clinical trial using data from electronic patient records, exemplifying the DESiGN Trial as a case study. METHODS: The DESiGN Trial is a cluster randomised control trial assessing the effect of a complex intervention versus standard care for identifying small for gestational age foetuses. Data on maternal/perinatal characteristics and outcomes including infants admitted to neonatal care, parameters from foetal ultrasound and details of hospital activity for health-economic evaluation were collected at two time points from four types of electronic patient records held in 22 different electronic record systems at the 13 research clusters. Data were pseudonymised on site using a bespoke Microsoft Excel macro and securely transferred to the central data store. Data quality checks were undertaken. Rules for data harmonisation of the raw data were developed and a data dictionary produced, along with rules and assumptions for data linkage of the datasets. The dictionary included descriptions of the rationale and assumptions for data harmonisation and quality checks. RESULTS: Data were collected on 182,052 babies from 178,350 pregnancies in 165,397 unique women. Data availability and completeness varied across research sites; each of eight variables which were key to calculation of the primary outcome were completely missing in median 3 (range 1–4) clusters at the time of the first data download. This improved by the second data download following clarification of instructions to the research sites (each of the eight key variables were completely missing in median 1 (range 0–1) cluster at the second time point). Common data management challenges were harmonising a single variable from multiple sources and categorising free-text data, solutions were developed for this trial. CONCLUSIONS: Conduct of clinical trials which use electronic patient records for the assessment of outcomes can be time and cost-effective but still requires appropriate time and resources to maximise data quality. A difficulty for pregnancy and perinatal research in the UK is the wide variety of different systems used to collect patient data across maternity units. In this manuscript, we describe how we managed this and provide a detailed data dictionary covering the harmonisation of variable names and values that will be helpful for other researchers working with these data. TRIAL REGISTRATION: Primary registry and trial identifying number: ISRCTN 67698474. Registered on 02/11/16. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13063-021-05141-8. BioMed Central 2021-03-08 /pmc/articles/PMC7941939/ /pubmed/33685512 http://dx.doi.org/10.1186/s13063-021-05141-8 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.
spellingShingle Methodology
Relph, Sophie
Elstad, Maria
Coker, Bolaji
Vieira, Matias C.
Moitt, Natalie
Gutierrez, Walter Muruet
Khalil, Asma
Sandall, Jane
Copas, Andrew
Lawlor, Deborah A.
Pasupathy, Dharmintra
Using electronic patient records to assess the effect of a complex antenatal intervention in a cluster randomised controlled trial—data management experience from the DESiGN Trial team
title Using electronic patient records to assess the effect of a complex antenatal intervention in a cluster randomised controlled trial—data management experience from the DESiGN Trial team
title_full Using electronic patient records to assess the effect of a complex antenatal intervention in a cluster randomised controlled trial—data management experience from the DESiGN Trial team
title_fullStr Using electronic patient records to assess the effect of a complex antenatal intervention in a cluster randomised controlled trial—data management experience from the DESiGN Trial team
title_full_unstemmed Using electronic patient records to assess the effect of a complex antenatal intervention in a cluster randomised controlled trial—data management experience from the DESiGN Trial team
title_short Using electronic patient records to assess the effect of a complex antenatal intervention in a cluster randomised controlled trial—data management experience from the DESiGN Trial team
title_sort using electronic patient records to assess the effect of a complex antenatal intervention in a cluster randomised controlled trial—data management experience from the design trial team
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7941939/
https://www.ncbi.nlm.nih.gov/pubmed/33685512
http://dx.doi.org/10.1186/s13063-021-05141-8
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