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

Authors :
Bin Wang
Xinbao Hao
Xiaoyan Yan
Junkai Lai
Feifei Jin
Xiwen Liao
Hongju Xie
Chen Yao
Source :
BMC Medical Informatics and Decision Making, Vol 22, Iss 1, Pp 1-11 (2022)
Publication Year :
2022
Publisher :
BMC, 2022.

Abstract

Abstract 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.

Details

Language :
English
ISSN :
14726947
Volume :
22
Issue :
1
Database :
Directory of Open Access Journals
Journal :
BMC Medical Informatics and Decision Making
Publication Type :
Academic Journal
Accession number :
edsdoj.39c554002e0f41528ed430d41ae05f42
Document Type :
article
Full Text :
https://doi.org/10.1186/s12911-022-01824-7