Evidence map›Paper›PMID 37250994›Full record

ArticleJournal of clinical and translational science2023

Use of population health data to promote equitable recruitment for a primary care practice implementation trial addressing unhealthy alcohol use.

Alex H Krist, Alison N Huffstetler, Gabriela Villalobos, Michelle S Rockwell, Alicia Richards, Adam Funk, Roy T Sabo, Beth Bortz, Ben Webel, Jong Hyung Lee and 4 more

Abstract read
In one paragraph

Article in Journal of clinical and translational science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Trial
  2. Article
  3. Advancing regulatory science through real-world data and real-world evidence.Journal of clinical and translational science · 2024
    Article
  4. Review
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

14 authors.

Alex H KristDepartment of Family Medicine and Population Health, Virginia Commonwealth University, Richmond, VA, USA.ORCID https://orcid.org/0000-0003-4060-9155
Alison N HuffstetlerDepartment of Family Medicine and Population Health, Virginia Commonwealth University, Richmond, VA, USA.
Gabriela VillalobosDepartment of Family Medicine and Population Health, Virginia Commonwealth University, Richmond, VA, USA.
Michelle S RockwellDepartment of Family & Community Medicine, Virginia Tech Carilion School of Medicine, Roanoke, VA, USA.
Alicia RichardsDepartment of Biostatistics, Virginia Commonwealth University, Richmond, VA, USA.
Adam FunkDepartment of Biostatistics, Virginia Commonwealth University, Richmond, VA, USA.
Roy T SaboWright Center for Clinical and Translational Research, Virginia Commonwealth University, Richmond, VA, USA.
Beth BortzVirginia Center for Health Innovation, Richmond, VA, USA.
Ben WebelDepartment of Family Medicine and Population Health, Virginia Commonwealth University, Richmond, VA, USA.
Jong Hyung LeeDepartment of Family Medicine and Population Health, Virginia Commonwealth University, Richmond, VA, USA.
Kyle RusselVirginia Health Information, Richmond, VA, USA.
Anton KuzelDepartment of Family Medicine and Population Health, Virginia Commonwealth University, Richmond, VA, USA.
Jaqueline B BritzDepartment of Family Medicine and Population Health, Virginia Commonwealth University, Richmond, VA, USA.
F Gerard MoellerWright Center for Clinical and Translational Research, Virginia Commonwealth University, Richmond, VA, USA.

Funding

Wright Regional Center for Clinical and Translational ScienceUM1TR004360 · NCATS · VIRGINIA COMMONWEALTH UNIVERSITY · PI FREDERICK Gerard MOELLER · 2023 to 2026
$16.3M
NCATS NIH HHS UM1 TR004360
6 · The paper itself

Abstract

Background: Recruiting underrepresented people and communities in research is essential for generalizable findings. Ensuring representative participants can be particularly challenging for practice-level dissemination and implementation trials. Novel use of real-world data about practices and the communities they serve could promote more equitable and inclusive recruitment. Methods: We used a comprehensive primary care clinician and practice database, the Virginia All-Payers Claims Database, and the HealthLandscape Virginia mapping tool with community-level socio-ecological information to prospectively inform practice recruitment for a study to help primary care better screen and counsel for unhealthy alcohol use. Throughout recruitment, we measured how similar study practices were to primary care on average, mapped where practices' patients lived, and iteratively adapted our recruitment strategies. Results: In response to practice and community data, we adapted our recruitment strategy three times; first leveraging relationships with residency graduates, then a health system and professional organization approach, followed by a community-targeted approach, and a concluding approach using all three approaches. We enrolled 76 practices whose patients live in 97.3% (1844 of 1907) of Virginia's census tracts. Our overall patient sample had similar demographics to the state for race (21.7% vs 20.0% Black), ethnicity (9.5% vs 10.2% Hispanic), insurance status (6.4% vs 8.0% uninsured), and education (26.0% vs 32.5% high school graduate or less). Each practice recruitment approach uniquely included different communities and patients. Discussion: Data about primary care practices and the communities they serve can prospectively inform research recruitment of practices to yield more representative and inclusive patient cohorts for participation.

Indexed as

equitable recruitmentPreventionprimary carereal-world dataunhealthy alcohol use

Identifiers

PMID37250994
PMCPMC10225269

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.