Evidence map›Paper›PMID 24410735›Full record

ArticleTrials2014

A European inventory of common electronic health record data elements for clinical trial feasibility.

Justin Doods, Florence Botteri, Martin Dugas, Fleur Fritz, EHR4CR WP7

Abstract readMulticenter Study
In one paragraph

Article in Trials, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing 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

27 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Clinical Research Informatics: a Decade-in-Review.Yearbook of medical informatics · 2024
    Review
  8. Parsing Clinical Trial Eligibility Criteria for Cohort Query by a Multi-Input Multi-Output Sequence Labeling Model.Proceedings. IEEE International Conference on Bioinformatics and Biomedicine · 2023
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Identification of Common Data Elements from Pivotal FDA Trials.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2020
    Article
  16. Review
  17. A conceptual framework for evaluating data suitability for observational studies.Journal of the American Medical Informatics Association : JAMIA · 2018
    Article
  18. Electronic health records to facilitate clinical research.Clinical research in cardiology : official journal of the German Cardiac Society · 2017
    Review
  19. Article
  20. Article
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.

Justin Doods
Florence Botteri
Martin Dugas
Fleur FritzInstitute of Medical Informatics, University Münster, Albert-Schweitzer-Campus 1/A11, D-48149 Münster, Germany. Fleur.Fritz@uni-muenster.de.
EHR4CR WP7

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundClinical studies are a necessity for new medications and therapies. Many studies, however, struggle to meet their recruitment numbers in time or have problems in meeting them at all. With increasing numbers of electronic health records (EHRs) in hospitals, huge databanks emerge that could be utilized to support research. The Innovative Medicine Initiative (IMI) funded project 'Electronic Health Records for Clinical Research' (EHR4CR) created a standardized and homogenous inventory of data elements to support research by utilizing EHRs. Our aim was to develop a Data Inventory that contains elements required for site feasibility analysis.

methodsThe Data Inventory was created in an iterative, consensus driven approach, by a group of up to 30 people consisting of pharmaceutical experts and informatics specialists. An initial list was subsequently expanded by data elements of simplified eligibility criteria from clinical trial protocols. Each element was manually reviewed by pharmaceutical experts and standard definitions were identified and added. To verify their availability, data exports of the source systems at eleven university hospitals throughout Europe were conducted and evaluated.

resultsThe Data Inventory consists of 75 data elements that, on the one hand are frequently used in clinical studies, and on the other hand are available in European EHR systems. Rankings of data elements were created from the results of the data exports. In addition a sub-list was created with 21 data elements that were separated from the Data Inventory because of their low usage in routine documentation.

conclusionThe data elements in the Data Inventory were identified with the knowledge of domain experts from pharmaceutical companies. Currently, not all information that is frequently used in site feasibility is documented in routine patient care.

Indexed as

Data MiningElectronic Health RecordsMedical InformaticsResearch DesignClinical Trials as TopicEuropeFeasibility StudiesHospitals, UniversityHumansPatient SelectionSample Size

Identifiers

PMID24410735
PMCPMC3895709

What OpenQuestion 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 OpenQuestion graph.