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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.

Relph, S; Elstad, M; Coker, B; Vieira, MC; Moitt, N; Gutierrez, WM; Khalil, A; Sandall, J; Copas, A; Lawlor, DA; et al. Relph, S; Elstad, M; Coker, B; Vieira, MC; Moitt, N; Gutierrez, WM; Khalil, A; Sandall, J; Copas, A; Lawlor, DA; Pasupathy, D; DESIGN Trial team (2021) 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. Trials, 22 (1). p. 195. ISSN 1745-6215 https://doi.org/10.1186/s13063-021-05141-8
SGUL Authors: Khalil, Asma

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Abstract

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.

Item Type: Article
Additional Information: © The Author(s). 2021 Open Access This 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 obtainpermission 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.
Keywords: Cluster randomised trial, Data linkage, Data management, Electronic patient records, Maternal, Methodology, Perinatal, General & Internal Medicine, 1102 Cardiorespiratory Medicine and Haematology, 1103 Clinical Sciences, Cardiovascular System & Hematology
SGUL Research Institute / Research Centre: Academic Structure > Molecular and Clinical Sciences Research Institute (MCS)
Journal or Publication Title: Trials
ISSN: 1745-6215
Language: eng
Dates:
DateEvent
8 March 2021Published
19 February 2021Accepted
Publisher License: Creative Commons: Attribution 4.0
Projects:
Project IDFunderFunder ID
N/ATommy's Baby CharityUNSPECIFIED
MAJ150704Guy's and St Thomas' Charityhttp://dx.doi.org/10.13039/501100000380
RG1011/16Stillborn and Neonatal Death CharityUNSPECIFIED
NF-SI-0611-10196National Institute for Health Researchhttp://dx.doi.org/10.13039/501100000272
9571/13-2CAPESUNSPECIFIED
PubMed ID: 33685512
Go to PubMed abstract
URI: https://openaccess.sgul.ac.uk/id/eprint/113059
Publisher's version: https://doi.org/10.1186/s13063-021-05141-8

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