Evidence map›Paper›PMID 40170025›Full record

ArticleBMC medical informatics and decision making2025

Reusing data from HL7 CDA-based shared EHR systems for clinical trial conduct: a method for analyzing feasibility.

Georg Duftschmid, Florian Katsch, Gabriela Ciortuz, Dipak Kalra, Christoph Rinner

Abstract read
In one paragraph

Article in BMC medical informatics and decision making, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Georg DuftschmidCenter for Medical Data Science (CEDAS), Medical University of Vienna, Spitalgasse 23, Vienna, 1090, Austria. georg.duftschmid@muv.ac.at.
Florian KatschCenter for Medical Data Science (CEDAS), Medical University of Vienna, Spitalgasse 23, Vienna, 1090, Austria.
Gabriela CiortuzInstitute of Medical Informatics, University of Luebeck, Lübeck, Germany.
Dipak KalraEuropean Institute for Innovation through Health Data (i~HD), University College of London, London, UK.
Christoph RinnerCenter for Medical Data Science (CEDAS), Medical University of Vienna, Spitalgasse 23, Vienna, 1090, Austria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundElectronic health record (EHR) systems have been shown to represent a valuable source of data reuse in the design and conduct of clinical trials. Earlier work has mostly focused on institutional EHR systems. Shared EHR systems have been neglected so far, even though they are highly prevalent today and their characteristics (integrated data across a patient's care providers, standardized information model) make them attractive for the task. However, as they typically focus on a limited data set for the most common care situations, it remains unclear, whether shared EHR systems actually cover the data elements required for clinical trial conduct. In this paper we present a method, which allows shared EHR systems to be analyzed in this regard.

methodsWe focus on shared EHR systems using HL7 CDA as this is currently the most-widely used content standard. For the data elements that are commonly used in clinical trials we refer to the EHR4CR reference list. The latter is semiautomatically mapped to the EHR system's information model using the open source tool ART-DECOR. For the final automatic analysis of the mappings, another open source tool is provided.

resultsA stepwise approach was developed to analyze HL7 CDA-based shared EHR systems for their coverage of data elements that are relevant for clinical trials. All tools used in this work as well as all mappings are publicly accessible to make the method reusable and the results reproducible. We applied our approach to the Austrian nation-wide EHR system ELGA and showed that the latter allows the recording of 88% of all EHR4CR data elements, 77% in structured format.

conclusionsOur method allows HL7 CDA-based shared EHR systems to be easily analyzed to what extent their content could be reused in the context of clinical trials. The results for ELGA indicate that it has a substantial corresponding potential. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

Clinical Trials as TopicElectronic Health RecordsHealth Level SevenFeasibility StudiesHumansClinical trialsData collectionData modelsElectronic medical records

Identifiers

PMID40170025
PMCPMC11963467

What Socratic holds

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LicenceCC BY
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Registered trials

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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 Socratic graph.