Data Flow Construction and Quality Evaluation of Electronic Source Data in Clinical Trials: Pilot Study Based on Hospital Electronic Medical Records in China

Background: The traditional clinical trial data collection process requires a Clinical Research Coordinator (CRC) who is authorized by the investigators to read from the hospital electronic medical record. Using electronic source data opens a new path to extract subjects' data from EHR and transfer directly to EDC (often the method is referred to as eSource ).The eSource technology in clinical trial data flow can improve data quality without compromising timeliness. At the same time, improved data collection efficiency reduces clinical trial costs. Objective: Explore how to extract clinical trial-related data from hospital electronic health record system (EHR), transform the data into an electronic data capture system (EDC) required format, and transfer it into sponsor's environment. Evaluate the transferred datasets to validate the availability, completeness, and accuracy of building eSource dataflow. Methods: A prospective clinical trial study registered on the "Drug Clinical Trial Registration and Information Disclosure Platform (http://www.chinadrugtrials.org.cn/) " was selected, and the production data environment of EHR relied on to extract the structured data of four Case Report Form(CRF) data modules: demographics, vital signs, local laboratory, and concomitant medications from EHR. Extracted data was mapped & transformed, de-identified, and transferred to the sponsor’s environments. Data validation was performed based on availability, completeness and accuracy. Results: In a secure and controlled data environment, clinical trial data was successfully transferred from a hospital EHR to sponsor's environment with 100% transcriptional accuracy, but availability and completeness could be improved. Conclusions: Data availability is low due to some fields required in EDC not being available directly in the EHR. Concurrently, some data is still in unstructured data format and paper-based medical record data, therefore data completeness in the EHR is low. The top-level design of eSource and the construction of hospital electronic data standards should help lay a foundation for full electronic data flow from EHR to EDC in future.