Evidence map›Paper›PMID 27589942›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2017

iCONCUR: informed consent for clinical data and bio-sample use for research.

Hyeoneui Kim, Elizabeth Bell, Jihoon Kim, Amy Sitapati, Joe Ramsdell, Claudiu Farcas, Dexter Friedman, Stephanie Feudjio Feupe, Lucila Ohno-Machado

Abstract readEvaluation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 3 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

39 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  10. Clinical Research Informatics: a Decade-in-Review.Yearbook of medical informatics · 2024
    Review
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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

9 authors.

Hyeoneui KimDepartment of Biomedical Informatics, University of California, San Diego, USA.
Elizabeth BellDepartment of Biomedical Informatics, University of California, San Diego, USA.
Jihoon KimDepartment of Biomedical Informatics, University of California, San Diego, USA.
Amy SitapatiDepartment of Biomedical Informatics, University of California, San Diego, USA.
Joe RamsdellDepartment of Medicine, University of California, San Diego, USA.
Claudiu FarcasDepartment of Biomedical Informatics, University of California, San Diego, USA.
Dexter FriedmanDepartment of Computer Science and Engineering, University of California San Diego, San Diego, USA.
Stephanie Feudjio FeupeDepartment of Biomedical Informatics, University of California, San Diego, USA.
Lucila Ohno-MachadoDepartment of Biomedical Informatics, University of California, San Diego, USA.

Funding

iCONCUR: informed CONsent for Clinical data and biosample Use for ResearchR01HG008802 · NHGRI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI JIANG, XIAOQIAN, KIM, HYEON-EUI · 2015 to 2017
$1.3M
6 · The paper itself

Abstract

Background: Implementation of patient preferences for use of electronic health records for research has been traditionally limited to identifiable data. Tiered e-consent for use of de-identified data has traditionally been deemed unnecessary or impractical for implementation in clinical settings. Methods: We developed a web-based tiered informed consent tool called informed consent for clinical data and bio-sample use for research (iCONCUR) that honors granular patient preferences for use of electronic health record data in research. We piloted this tool in 4 outpatient clinics of an academic medical center. Results: Of patients offered access to iCONCUR, 394 agreed to participate in this study, among whom 126 patients accessed the website to modify their records according to data category and data recipient. The majority consented to share most of their data and specimens with researchers. Willingness to share was greater among participants from an Human Immunodeficiency Virus (HIV) clinic than those from internal medicine clinics. The number of items declined was higher for for-profit institution recipients. Overall, participants were most willing to share demographics and body measurements and least willing to share family history and financial data. Participants indicated that having granular choices for data sharing was appropriate, and that they liked being informed about who was using their data for what purposes, as well as about outcomes of the research. Conclusion: This study suggests that a tiered electronic informed consent system is a workable solution that respects patient preferences, increases satisfaction, and does not significantly affect participation in research.

Indexed as

Electronic Health RecordsInformed ConsentPatient PreferenceBiomedical ResearchFeasibility StudiesFemaleHumansInformation DisseminationMaleSocioeconomic FactorsEHR data use for researchinformed consenttiered informed consent

Identifiers

PMID27589942
PMCPMC5391727

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.