ArticleNPJ digital medicine2024
Next-generation study databases require FAIR, EHR-integrated, and scalable Electronic Data Capture for medical documentation and decision support.
Article in NPJ digital medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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Who cites it
14 citing papers in PubMed, 25 citations in OpenAlex.
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- Psychosocial risk screening in the inpatient care of physically ill patients: study protocol for a feasibility study.BMJ open · 2026Article
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- Glucagon-like Peptide-1 Receptor Agonists and Risk of Pneumonia and Postprocedure Hospitalization Among Patients Undergoing Gastrointestinal Endoscopy.Gastro hep advances · 2026Article
- Patient-reported outcomes - the missing link to advancing light chain (AL) amyloidosis clinical research.Blood reviews · 2025Review
- Design and implementation of a natural language processing system at the point of care: MiADE (medical information AI data extractor).BMC medical informatics and decision making · 2025Article
- Medical researchers' perception of sharing of metadata from case report forms.Learning health systems · 2025Article
- AI Mapping of In-House Codes to LOINC Codes Using Laboratory Test Results Excluding Test Names: Toward International Sharing of Medical Data.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2025Article
- The double-edged sword of nutraceuticals: comprehensive review of protective agents and their hidden risks.Frontiers in nutrition · 2025Review
- Review
- Single source - triple flow: Structured electronic data capture for pancreatic surgery patients.Digital healthArticle
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Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Structured patient data play a key role in all types of clinical research. They are often collected in study databases for research purposes. In order to describe characteristics of a next-generation study database and assess the feasibility of its implementation a proof-of-concept study in a German university hospital was performed. Key characteristics identified include FAIR access to electronic case report forms (eCRF), regulatory compliant Electronic Data Capture (EDC), an EDC with electronic health record (EHR) integration, scalable EDC for medical documentation, patient generated data, and clinical decision support. In a local case study, we then successfully implemented a next-generation study database for 19 EDC systems (n = 2217 patients) that linked to i.s.h.med (Oracle Cerner) with the local EDC system called OpenEDC. Desiderata of next-generation study databases for patient data were identified from ongoing local clinical study projects in 11 clinical departments at Heidelberg University Hospital, Germany, a major tertiary referral hospital. We compiled and analyzed feature and functionality requests submitted to the OpenEDC team between May 2021 and July 2023. Next-generation study databases are technically and clinically feasible. Further research is needed to evaluate if our approach is feasible in a multi-center setting as well.
Identifiers
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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.