ArticleJournal of the Society for Clinical Data Management2025
Automating Data Entry from Electronic Health Record to Electronic Data Capture Using a Trusted Cloud-Based Application in Multisite Cancer Clinical Trials.
Article in Journal of the Society for Clinical Data Management, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Advancing Clinical Trial Efficiency and Data Accuracy through Direct EHR-to-EDC Integration.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2026Article
- Advances in nanotechnology-enabled adjuvants for peptide-based cancer vaccines.Nano research · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
18 authors.
Funding
Abstract
Introduction: For more than two decades, researchers have sought to develop and to improve technologies to seamlessly move data from electronic health record (EHR) systems to study forms in electronic data capture (EDC) systems. The goal is to utilize advancing technology to improve study data accuracy and quality while decreasing the burden of data collection on busy clinical research professionals. Objectives: This report discusses findings from the SWOG Cancer Research Network's use of a secure and trusted third-party cloud-based application as a technology link between EHR databases and the clinical trial EDC application. The objectives are to ease the burden on site staff and improve data accuracy and completeness. Methods: Three SWOG sites used a cloud-based EHR-to-EDC application to enter study data for two follow-up tumor assessment case report forms for six patients each. This software-assisted method was compared to manual medical record abstraction. Time savings, error rate, and interrater reliability were measured. Results: A comparison of the two methods demonstrated substantial time savings and improvements in data quality. This is especially true for data fields that can be automatically captured using the application for clinical trials using the software-assisted approach. Conclusions: Using a secure and trusted cloud-based application to access the EHR to assist in data collection for clinical trials resulted in welcome time savings for clinical research professionals and higher data accuracy.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.