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Evaluation of the clinical application effect of eSource record tools for clinical research

BACKGROUND: Electronic sources (eSources) can improve data quality and reduce clinical trial costs. Our team has developed an innovative eSource record (ESR) system in China. This study aims to evaluate the efficiency, quality, and system performance of the ESR system in data collection and data tra...

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Autores principales: Wang, Bin, Hao, Xinbao, Yan, Xiaoyan, Lai, Junkai, Jin, Feifei, Liao, Xiwen, Xie, Hongju, Yao, Chen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9004184/
https://www.ncbi.nlm.nih.gov/pubmed/35410214
http://dx.doi.org/10.1186/s12911-022-01824-7
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author Wang, Bin
Hao, Xinbao
Yan, Xiaoyan
Lai, Junkai
Jin, Feifei
Liao, Xiwen
Xie, Hongju
Yao, Chen
author_facet Wang, Bin
Hao, Xinbao
Yan, Xiaoyan
Lai, Junkai
Jin, Feifei
Liao, Xiwen
Xie, Hongju
Yao, Chen
author_sort Wang, Bin
collection PubMed
description BACKGROUND: Electronic sources (eSources) can improve data quality and reduce clinical trial costs. Our team has developed an innovative eSource record (ESR) system in China. This study aims to evaluate the efficiency, quality, and system performance of the ESR system in data collection and data transcription. METHODS: The study used time efficiency and data transcription accuracy indicators to compare the eSource and non-eSource data collection workflows in a real-world study (RWS). The two processes are traditional data collection and manual transcription (the non-eSource method) and the ESR-based source data collection and electronic transmission (the eSource method). Through the system usability scale (SUS) and other characteristic evaluation scales (system security, system compatibility, record quality), the participants’ experience of using ESR was evaluated. RESULTS: In terms of the source data collection (the total time required for writing electronic medical records (EMRs)), the ESR system can reduce the time required by 39% on average compared to the EMR system. In terms of data transcription (electronic case report form (eCRF) filling and verification), the ESR can reduce the time required by 80% compared to the non-eSource method (difference: 223 ± 21 s). The ESR accuracy in filling the eCRF field is 96.92%. The SUS score of ESR is 66.9 ± 16.7, which is at the D level and thus very close to the acceptable margin, indicating that optimization work is needed. CONCLUSIONS: This preliminary evaluation shows that in the clinical medical environment, the ESR-based eSource method can improve the efficiency of source data collection and reduce the workload required to complete data transcription. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12911-022-01824-7.
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spelling pubmed-90041842022-04-13 Evaluation of the clinical application effect of eSource record tools for clinical research Wang, Bin Hao, Xinbao Yan, Xiaoyan Lai, Junkai Jin, Feifei Liao, Xiwen Xie, Hongju Yao, Chen BMC Med Inform Decis Mak Research BACKGROUND: Electronic sources (eSources) can improve data quality and reduce clinical trial costs. Our team has developed an innovative eSource record (ESR) system in China. This study aims to evaluate the efficiency, quality, and system performance of the ESR system in data collection and data transcription. METHODS: The study used time efficiency and data transcription accuracy indicators to compare the eSource and non-eSource data collection workflows in a real-world study (RWS). The two processes are traditional data collection and manual transcription (the non-eSource method) and the ESR-based source data collection and electronic transmission (the eSource method). Through the system usability scale (SUS) and other characteristic evaluation scales (system security, system compatibility, record quality), the participants’ experience of using ESR was evaluated. RESULTS: In terms of the source data collection (the total time required for writing electronic medical records (EMRs)), the ESR system can reduce the time required by 39% on average compared to the EMR system. In terms of data transcription (electronic case report form (eCRF) filling and verification), the ESR can reduce the time required by 80% compared to the non-eSource method (difference: 223 ± 21 s). The ESR accuracy in filling the eCRF field is 96.92%. The SUS score of ESR is 66.9 ± 16.7, which is at the D level and thus very close to the acceptable margin, indicating that optimization work is needed. CONCLUSIONS: This preliminary evaluation shows that in the clinical medical environment, the ESR-based eSource method can improve the efficiency of source data collection and reduce the workload required to complete data transcription. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12911-022-01824-7. BioMed Central 2022-04-11 /pmc/articles/PMC9004184/ /pubmed/35410214 http://dx.doi.org/10.1186/s12911-022-01824-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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 Research
Wang, Bin
Hao, Xinbao
Yan, Xiaoyan
Lai, Junkai
Jin, Feifei
Liao, Xiwen
Xie, Hongju
Yao, Chen
Evaluation of the clinical application effect of eSource record tools for clinical research
title Evaluation of the clinical application effect of eSource record tools for clinical research
title_full Evaluation of the clinical application effect of eSource record tools for clinical research
title_fullStr Evaluation of the clinical application effect of eSource record tools for clinical research
title_full_unstemmed Evaluation of the clinical application effect of eSource record tools for clinical research
title_short Evaluation of the clinical application effect of eSource record tools for clinical research
title_sort evaluation of the clinical application effect of esource record tools for clinical research
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9004184/
https://www.ncbi.nlm.nih.gov/pubmed/35410214
http://dx.doi.org/10.1186/s12911-022-01824-7
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