Automated data transmission can be expected to reduce effort and save resources and costs while ensuring high data quality. It addresses feasibility, connectivity, and system compatibility of currently used PMSs in health care and clinical research and is therefore directly applicable.Ĭonclusions: This use case demonstrates that secure, consistent, and automated end-to-end data transmission from the treating physician to the regulatory authority is feasible. Results: This model for automated data transfer bridges the current gap between clinical practice data capture at the point of care and the data sets required by regulatory agencies it also enables automated EHR2EDC data transfer in compliance with the General Data Protection Regulation (GDPR). Of these, 5 forms with 185 variables contain 67 automatically transferable variables (67/274, 24% of all variables and 67/185, 36% of eligible variables). The electronic case report form (eCRF) contains 13 forms with 274 variables. EHR2EDC synchronization occurs automatically overnight, and real-time updates can be initiated manually following each data entry in the EHR. From there, data are automatically transferred to the validated AlcedisTRIAL EDC system (Alcedis GmbH) for data collection and management. Methods: The SaniQ software platform (Qurasoft GmbH) is already used to extract and harmonize predefined variables from electronic medical records of different Compu Group Medical–hosted PMSs. This required addressing aspects of data security, as well as the lack of compatibility between EHR health care data and the data quality required in EDC systems for clinical research. Objective: We aimed to develop a model for automated data transfer as part of an observational study that allows data of sufficient quality to be captured at the point of care, extracted from various PMSs, and automatically transferred to electronic case report forms in EDC systems. Data quality for research purposes within EDC systems must meet the requirements of regulatory authorities for standardized submission of clinical trial data and safety reports. Automated digital transfer from EHRs to EDC systems (EHR2EDC) would enable more accurate and efficient data capture but has so far encountered technological barriers primarily related to data format and the technological environment: in Germany, health care data are collected at the point of care in a variety of often individualized practice management systems (PMSs), most of them not interoperable. Online Journal of Public Health InformaticsĮmail: Data transfer between electronic health records (EHRs) at the point of care and electronic data capture (EDC) systems for clinical research is still mainly carried out manually, which is error-prone as well as cost- and time-intensive.Asian/Pacific Island Nursing Journal 12 articles.JMIR Bioinformatics and Biotechnology 37 articles.JMIR Biomedical Engineering 69 articles. Journal of Participatory Medicine 80 articles.JMIR Perioperative Medicine 92 articles.JMIR Rehabilitation and Assistive Technologies 214 articles.
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