Evidence map›Paper›PMID 29657859›Full record

ArticleJournal of clinical and translational science2017

A survey of practices for the use of electronic health records to support research recruitment.

Jihad S Obeid, Laura M Beskow, Marie Rape, Ramkiran Gouripeddi, R Anthony Black, James J Cimino, Peter J Embi, Chunhua Weng, Rebecca Marnocha, John B Buse

Abstract read
In one paragraph

Article in Journal of clinical and translational science, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed
–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

42 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Transforming research recruitment: Leveraging EHR systems and patient portals.Journal of clinical and translational science · 2025
    Article
  6. Article
  7. Article
  8. Clinical Research Informatics: a Decade-in-Review.Yearbook of medical informatics · 2024
    Review
  9. Article
  10. Article
  11. Observational
  12. Article
  13. Article
  14. Not all phenotypes are created equal: covariates of success in e-phenotype specification.Journal of the American Medical Informatics Association : JAMIA · 2023
    Article
  15. Article
  16. Supporting research, protecting data: one institution's approach to clinical data warehouse governance.Journal of the American Medical Informatics Association : JAMIA · 2022
    Article
  17. An atomic approach to the design and implementation of a research data warehouse.Journal of the American Medical Informatics Association : JAMIA · 2022
    Article
  18. Article
  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

10 authors.

Jihad S ObeidDepartment of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA.ORCID 0000-0002-7193-7779
Laura M BeskowCenter for Biomedical Ethics and Society, Vanderbilt University Medical Center, Nashville, TN, USA.
Marie RapeNC Translational and Clinical Sciences Institute, University of North Carolina School of Medicine, Chapel Hill, NC, USA.
Ramkiran GouripeddiDepartment of Biomedical Informatics, Utah Center for Clinical and Translational Science, University of Utah, Salt Lake City, UT, USA.
R Anthony BlackInstitute of Translational Health Sciences, University of Washington, Seattle, WA, USA.
James J CiminoInformatics Institute, University of Alabama at Birmingham, Birmingham, AL, USA.
Peter J EmbiRegenstrief Institute, Inc., Indiana Clinical and Translational Science Institute, Indiana University, Indianapolis, IN, USA.
Chunhua WengDepartment of Biomedical Informatics, Columbia University, New York, NY, USA.
Rebecca MarnochaInstitute for Clinical and Translational Research, University of Wisconsin, Madison, WI, USA.
John B BuseNC Translational and Clinical Sciences Institute, University of North Carolina School of Medicine, Chapel Hill, NC, USA.

Funding

University of Pittsburgh Clinical and Translational Science InstituteUL1TR001857 · NCATS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI REIS, STEVEN E · 2016 to 2025
$129.3M
UCLA Clinical Translational Science InstituteUL1TR001881 · NCATS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ARLEEN F. BROWN, ARASH NAEIM · 2016 to 2026
$118.1M
Clinical and Translational Science InstituteUL1TR001872 · NCATS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI COLLARD, HAROLD R, JACOBY, VANESSA · 2016 to 2025
$112.1M
Harvard Clinical and Translational Science CenterUL1TR001102 · NCATS · HARVARD MEDICAL SCHOOL · PI NADLER, LEE MARSHALL · 2013 to 2017
$106.2M
Project-005UL1TR001445 · NCATS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI BREDELLA, MIRIAM ANTOINETTE, HOCHMAN, JUDITH S · 2015 to 2025
$103.5M
Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Phenotypic Diversity in COVID-19UL1TR001878 · NCATS · UNIVERSITY OF PENNSYLVANIA · PI FITZGERALD, GARRET A · 2016 to 2025
$102.4M
Transform Dissemination and Implementation Science in CTSA ProgramsUL1TR002319 · NCATS · UNIVERSITY OF WASHINGTON · PI John K. Amory · 2017 to 2026
$100.0M
Clinical and Translational Science AwardUL1TR001873 · NCATS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI REILLY, MUREDACH P · 2016 to 2025
$99.0M
WU INSTITUTE OF CLINICAL AND TRANSLATIONAL SCIENCESUL1TR002345 · NCATS · WASHINGTON UNIVERSITY · PI William G. Powderly · 2017 to 2026
$97.8M
Implementing a Maternal health and PRegnancy Outcomes Vision for Everyone (IMPROVE)UL1TR002378 · NCATS · EMORY UNIVERSITY · PI Andres J Garcia, Elizabeth O. Ofili · 2017 to 2026
$92.1M
UC San Diego Clinical and Translational Research InstituteUL1TR001442 · NCATS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI FIRESTEIN, GARY S, HOGARTH, MICHAEL · 2015 to 2024
$88.3M
NCATS NIH HHS TL1 TR001110NCATS NIH HHS U54 TR000123NCATS NIH HHS U54 TR001356NCATS NIH HHS UL1 TR000001NCATS NIH HHS UL1 TR000039NCATS NIH HHS UL1 TR000058NCATS NIH HHS UL1 TR000114NCATS NIH HHS UL1 TR000135NCATS NIH HHS UL1 TR000371NCATS NIH HHS UL1 TR000423NCATS NIH HHS UL1 TR000427NCATS NIH HHS UL1 TR000430NCATS NIH HHS UL1 TR000433NCATS NIH HHS UL1 TR000439NCATS NIH HHS UL1 TR000445NCATS NIH HHS UL1 TR000448NCATS NIH HHS UL1 TR000454NCATS NIH HHS UL1 TR000457NCATS NIH HHS UL1 TR000460NCATS NIH HHS UL1 TR001064NCATS NIH HHS UL1 TR001067NCATS NIH HHS UL1 TR001070NCATS NIH HHS UL1 TR001073NCATS NIH HHS UL1 TR001079NCATS NIH HHS UL1 TR001082NCATS NIH HHS UL1 TR001085NCATS NIH HHS UL1 TR001086NCATS NIH HHS UL1 TR001102NCATS NIH HHS UL1 TR001105NCATS NIH HHS UL1 TR001108NCATS NIH HHS UL1 TR001111NCATS NIH HHS UL1 TR001114NCATS NIH HHS UL1 TR001117NCATS NIH HHS UL1 TR001120NCATS NIH HHS UL1 TR001409NCATS NIH HHS UL1 TR001412NCATS NIH HHS UL1 TR001414NCATS NIH HHS UL1 TR001417NCATS NIH HHS UL1 TR001420NCATS NIH HHS UL1 TR001422NCATS NIH HHS UL1 TR001425NCATS NIH HHS UL1 TR001427NCATS NIH HHS UL1 TR001430NCATS NIH HHS UL1 TR001433NCATS NIH HHS UL1 TR001436NCATS NIH HHS UL1 TR001439NCATS NIH HHS UL1 TR001442NCATS NIH HHS UL1 TR001445NCATS NIH HHS UL1 TR001449NCATS NIH HHS UL1 TR001450NCATS NIH HHS UL1 TR001453NCATS NIH HHS UL1 TR001855NCATS NIH HHS UL1 TR001857NCATS NIH HHS UL1 TR001860NCATS NIH HHS UL1 TR001863NCATS NIH HHS UL1 TR001866NCATS NIH HHS UL1 TR001872NCATS NIH HHS UL1 TR001873NCATS NIH HHS UL1 TR001876NCATS NIH HHS UL1 TR001878NCATS NIH HHS UL1 TR001881NCATS NIH HHS UL1 TR001998NCATS NIH HHS UL1 TR002001NCATS NIH HHS UL1 TR002003NCATS NIH HHS UL1 TR002014NCATS NIH HHS UL1 TR002240NCATS NIH HHS UL1 TR002319NCATS NIH HHS UL1 TR002345NCATS NIH HHS UL1 TR002369NCATS NIH HHS UL1 TR002378NCATS NIH HHS UL1 TR002384NCATS NIH HHS UL1 TR002489NCATS NIH HHS UL1 TR002538NCRR NIH HHS C06 RR020578
6 · The paper itself

Abstract

Electronic health records (EHRs) provide great promise for identifying cohorts and enhancing research recruitment. Such approaches are sorely needed, but there are few descriptions in the literature of prevailing practices to guide their use. A multidisciplinary workgroup was formed to examine current practices in the use of EHRs in recruitment and to propose future directions. The group surveyed consortium members regarding current practices. Over 98% of the Clinical and Translational Science Award Consortium responded to the survey. Brokered and self-service data warehouse access are in early or full operation at 94% and 92% of institutions, respectively, whereas, EHR alerts to providers and to research teams are at 45% and 48%, respectively, and use of patient portals for research is at 20%. However, these percentages increase significantly to 88% and above if planning and exploratory work were considered cumulatively. For most approaches, implementation reflected perceived demand. Regulatory and workflow processes were similarly varied, and many respondents described substantive restrictions arising from logistical constraints and limitations on collaboration and data sharing. Survey results reflect wide variation in implementation and approach, and point to strong need for comparative research and development of best practices to protect patients and facilitate interinstitutional collaboration and multisite research.

Indexed as

biomedical informaticsclinical researchCTSAElectronic health recordsrecruitment

Identifiers

PMID29657859
PMCPMC5890320

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.