Evidence map›Paper›PMID 39540113›Full record

ArticleJournal of clinical and translational science2024

Implementation of

Carrie Dykes, Cody Gardner, Jack Chang, David Pinto, Karen Wilson, Martin S Zand, Ann Dozier

Abstract read
In one paragraph

Article in Journal of clinical and translational science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. 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

7 authors.

Carrie DykesClinical and Translational Science Institute, School of Medicine and Dentistry, University of Rochester, Rochester, NY, USA.ORCID https://orcid.org/0000-0001-8230-1699
Cody GardnerClinical and Translational Science Institute, School of Medicine and Dentistry, University of Rochester, Rochester, NY, USA.
Jack ChangClinical and Translational Science Institute, School of Medicine and Dentistry, University of Rochester, Rochester, NY, USA.
David PintoClinical and Translational Science Institute, School of Medicine and Dentistry, University of Rochester, Rochester, NY, USA.
Karen WilsonClinical and Translational Science Institute, School of Medicine and Dentistry, University of Rochester, Rochester, NY, USA.
Martin S ZandClinical and Translational Science Institute, School of Medicine and Dentistry, University of Rochester, Rochester, NY, USA.ORCID https://orcid.org/0000-0002-7095-8682
Ann DozierDepartment of Public Health Sciences, School of Medicine and Dentistry, University of Rochester, Rochester, NY, USA.ORCID https://orcid.org/0000-0001-8296-1910

Funding

The University of Rochester's Clinical and Translational Science InstituteUL1TR002001 · NCATS · UNIVERSITY OF ROCHESTER · PI WILSON, KAREN M., ZAND, MARTIN S · 2016 to 2024
$34.6M
NCATS NIH HHS UL1 TR002001
6 · The paper itself

Abstract

Introduction: Recruitment of participants into research studies remains a major concern for investigators. Using clinical teams to identify potentially eligible patients can present a significant barrier. To overcome this, we implemented a process for using our patient portal, called MyChart, as a new institutional recruitment option utilizing our electronic health record's existing functionality. Methods: To streamline the institutional approval process, we established a working group comprised of representatives from human subject protection, information technology, and privacy and vetted our process with many stakeholder groups. Our specific process for study approval is described and started with a consultation with our recruitment and retention function funded through our Clinical and Translational Science Award. Results: The time from consultation to the first message(s) sent ranged from 84 to 442 days and declined slightly over time. The overall patient response rate to MyChart messages about available research studies was 23% with one third of those saying they were interested in learning more. The response rate for Black and Hispanic patients was about 50% that of White patients. Conclusions: Many different types of studies from any medical specialty successfully identified interested patients using this option. Study teams needed support in defining appropriate inclusion/exclusion criteria to identify the relevant population in the electronic health records and they needed assistance writing study descriptions in plain language. Using MyChart for recruitment addressed a critical barrier and opened up the opportunity to provide a full recruitment consultation to identify additional recruitment channels the study teams would not have considered otherwise.

Indexed as

electronic health recordelectronic medical recordpatient portalRecruitmentresponse ratetranslational science barrier

Identifiers

PMID39540113
PMCPMC11557278

What OpenQuestion holds

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LicenceCC BY
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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.