Evidence map›Paper›PMID 27311638›Full record

ArticleClinical trials (London, England)2016

Improving the value of clinical research through the use of Common Data Elements.

Jerry Sheehan, Steven Hirschfeld, Erin Foster, Udi Ghitza, Kerry Goetz, Joanna Karpinski, Lisa Lang, Richard P Moser, Joanne Odenkirchen, Dianne Reeves and 3 more

Abstract read
In one paragraph

Article in Clinical trials (London, England), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 85 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
85citing papers in PubMed, 5 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

85 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
  2. Addressing Systematic Missing Data in the Context of Causally Interpretable Meta-analysis.Prevention science : the official journal of the Society for Prevention Research · 2023
    Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Completeness of Common Data Elements for Breast Cancer Clinical Trials in Observational Databases.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2026
    Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Common data elements for food allergy clinical trials: an overview.Current opinion in allergy and clinical immunology · 2025
    Review

25 more citing papers are in PubMed but not listed here.

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

13 authors.

Jerry SheehanNational Library of Medicine, National Institutes of Health, Bethesda, MD, USA.
Steven HirschfeldEunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA.
Erin FosterNational Library of Medicine, National Institutes of Health, Bethesda, MD, USA.
Udi GhitzaNational Institute on Drug Abuse, National Institutes of Health, Bethesda, MD, USA.
Kerry GoetzNational Eye Institute, National Institutes of Health, Bethesda, MD, USA.
Joanna KarpinskiNational Library of Medicine, National Institutes of Health, Bethesda, MD, USA.
Lisa LangNational Library of Medicine, National Institutes of Health, Bethesda, MD, USA.
Richard P MoserNational Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Joanne OdenkirchenNational Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.
Dianne ReevesNational Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Yaffa RubinsteinNational Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, MD, USA.
Ellen WernerNational Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA.
Michael HuertaNational Library of Medicine, National Institutes of Health, Bethesda, MD, USA mike.huerta@nih.hhs.gov.

Funding

Intramural NIH HHS Z99 HD999999
6 · The paper itself

Abstract

The use of Common Data Elements can facilitate cross-study comparisons, data aggregation, and meta-analyses; simplify training and operations; improve overall efficiency; promote interoperability between different systems; and improve the quality of data collection. A Common Data Element is a combination of a precisely defined question (variable) paired with a specified set of responses to the question that is common to multiple datasets or used across different studies. Common Data Elements, especially when they conform to accepted standards, are identified by research communities from variable sets currently in use or are newly developed to address a designated data need. There are no formal international specifications governing the construction or use of Common Data Elements. Consequently, Common Data Elements tend to be made available by research communities on an empiric basis. Some limitations of Common Data Elements are that there may still be differences across studies in the interpretation and implementation of the Common Data Elements, variable validity in different populations, and inhibition by some existing research practices and the use of legacy data systems. Current National Institutes of Health efforts to support Common Data Element use are linked to the strengthening of National Institutes of Health Data Sharing policies and the investments in data repositories. Initiatives include cross-domain and domain-specific resources, construction of a Common Data Element Portal, and establishment of trans-National Institutes of Health working groups to address technical and implementation topics. The National Institutes of Health is seeking to lower the barriers to Common Data Element use through greater awareness and encourage the culture change necessary for their uptake and use. As National Institutes of Health, other agencies, professional societies, patient registries, and advocacy groups continue efforts to develop and promote the responsible use of Common Data Elements, particularly if linked to accepted data standards and terminologies, continued engagement with and feedback from the research community will remain important.

Indexed as

Biomedical ResearchCommon Data ElementsInformation DisseminationData CollectionHumansNational Institutes of Health (U.S.)United StatesCommon Data Elementsdata collectiondata sharingdata standardsinteroperability

Identifiers

PMID27311638
PMCPMC5133155

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.