Yuan Yannan, Mei Yun, Zhao Shuhua, Dai Shenglong, Liu Xiaohong, Sun Xiaojing, Fu Zhiying, Zhou Liheng, Ai Jie, Ma Liheng, Jiang Min
Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), National Drug Clinical Trial Center, Peking University Cancer Hospital & Institute, Beijing, China.
Yidu Tech Inc, Beijing, China.
JMIR Med Inform. 2024 Jun 27;12:e52934. doi: 10.2196/52934.
The traditional clinical trial data collection process requires a clinical research coordinator who is authorized by the investigators to read from the hospital's electronic medical record. Using electronic source data opens a new path to extract patients' data from electronic health records (EHRs) and transfer them directly to an electronic data capture (EDC) system; this method is often referred to as eSource. eSource technology in a clinical trial data flow can improve data quality without compromising timeliness. At the same time, improved data collection efficiency reduces clinical trial costs.
This study aims to explore how to extract clinical trial-related data from hospital EHR systems, transform the data into a format required by the EDC system, and transfer it into sponsors' environments, and to evaluate the transferred data sets to validate the availability, completeness, and accuracy of building an eSource dataflow.
A prospective clinical trial study registered on the Drug Clinical Trial Registration and Information Disclosure Platform was selected, and the following data modules were extracted from the structured data of 4 case report forms: demographics, vital signs, local laboratory data, and concomitant medications. The extracted data was mapped and transformed, deidentified, and transferred to the sponsor's environment. Data validation was performed based on availability, completeness, and accuracy.
In a secure and controlled data environment, clinical trial data was successfully transferred from a hospital EHR to the sponsor's environment with 100% transcriptional accuracy, but the availability and completeness of the data could be improved.
Data availability was low due to some required fields in the EDC system not being available directly in the EHR. Some data is also still in an unstructured or paper-based format. The top-level design of the eSource technology and the construction of hospital electronic data standards should help lay a foundation for a full electronic data flow from EHRs to EDC systems in the future.
传统的临床试验数据收集过程需要一名经研究者授权的临床研究协调员从医院电子病历中读取数据。使用电子源数据开辟了一条从电子健康记录（EHR）中提取患者数据并将其直接传输到电子数据采集（EDC）系统的新途径；这种方法通常被称为电子源。临床试验数据流中的电子源技术可以提高数据质量而不影响及时性。同时，提高数据收集效率可降低临床试验成本。
本研究旨在探索如何从医院EHR系统中提取与临床试验相关的数据，将数据转换为EDC系统所需的格式，并将其传输到申办方的环境中，以及评估传输的数据集以验证构建电子源数据流的可用性、完整性和准确性。
选取在药物临床试验登记与信息公示平台注册的一项前瞻性临床试验研究，从4份病例报告表的结构化数据中提取以下数据模块：人口统计学信息、生命体征、当地实验室数据和伴随用药。对提取的数据进行映射、转换、去识别处理，并传输到申办方的环境中。基于可用性、完整性和准确性进行数据验证。
在安全可控的数据环境中，临床试验数据成功从医院EHR传输到申办方的环境中，转录准确率达100%，但数据的可用性和完整性有待提高。
由于EDC系统中的一些必填字段在EHR中无法直接获取，导致数据可用性较低。一些数据仍处于非结构化或纸质格式。电子源技术的顶层设计和医院电子数据标准的构建应有助于为未来从EHR到EDC系统的全电子数据流奠定基础。
