Evidence map›Paper›PMID 40052053›Full record

ArticleJournal of clinical and translational science2025

A maturity model for Clinical Trials Management Ecosystem.

Shruti Sehgal, E Chris Pua, Svetlana Rojevsky, Michael J Becich, Joshua Fehrmann, Boyd M Knosp, Adam Wilcox, Jeffery C Talbert, Catherine K Craven, Justin Starren

Abstract read
In one paragraph

Article in Journal of clinical and translational science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Shruti SehgalNorthwestern University Feinberg School of Medicine, Chicago, IL, USA.ORCID https://orcid.org/0000-0001-6352-8628
E Chris PuaVanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA.
Svetlana RojevskyTufts Clinical and Translational Science Institute, Tufts University, Boston, MA, USA.
Michael J BecichDepartment of Biomedical Informatics, School of Medicine, University of Pittsburgh, PA, USA.ORCID https://orcid.org/0000-0001-5998-8074
Joshua FehrmannClinical and Translational Science Institute, University of Minnesota, USA.
Boyd M KnospRoy, J. and Lucille A. Carver College of Medicine and the Institute for Clinical & Translational Science, University of Iowa, Iowa City, IA, USA.ORCID https://orcid.org/0000-0002-3834-3135
Adam WilcoxInstitute for Informatics, Data Science and Biostatistics, Department of Medicine, Washington University in St Louis, St Louis, MO, USA.
Jeffery C TalbertInstitute for Biomedical Informatics, University of Kentucky, Lexington, KY, USA.
Catherine K CravenUniversity of Texas Health Science Center San Antonio, San Antonio, TX, USA.
Justin StarrenUniversity of Arizona, Tucson, AZ, USA.

Funding

Northwestern University Clinical and Translational Science Institute (NUCATS)UL1TR001422 · NCATS · NORTHWESTERN UNIVERSITY AT CHICAGO · PI D'AQUILA, RICHARD · 2015 to 2023
$56.8M
NCATS NIH HHS UL1 TR001422
6 · The paper itself

Abstract

Introduction: Managing clinical trials is a complex process requiring careful integration of human, technology, compliance, and operations for success. We collaborated with experts to develop a multi-axial Clinical Trials Management Ecosystem (CTME) maturity model (MM) to help institutions identify best practices for CTME capabilities. Methods: A working group of research informaticists was established. An online session on maturity models was hosted, followed by a review of the candidate domain axes and finalization of the axes. Next, maturity level attributes were defined for min/max levels (level 1 and level 5) for each axis of the CTME MM, followed by the intermediate levels. A REDCap survey comprising the model's statements was then created, and a subset of working group members tested the model by completing it at their respective institutions. The finalized survey was distributed to all working group members. Results: We developed a CTME MM comprising five maturity levels across 11 axes: study management, regulatory and audit management, financial management, investigational product management, subject identification and recruitment, subject management, data, reporting analytics & dashboard, system integration and interfaces, staff training & personnel management, and organizational maturity and culture. Informaticists at 22 Clinical and Translational Science Award hubs and one other organization self-assessed their institutional CTME maturity. Respondents reported relatively high maturity for study management and investigational product management. The reporting analytics & dashboard axis was the least mature. Conclusion: The CTME MM provides a framework to research organizations to evaluate their current clinical trials management maturity across 11 axes and identify areas for future growth.

Indexed as

clinical and translational researchclinical trialsClinical Trials Management Ecosysteminformaticsmaturity models

Identifiers

PMID40052053
PMCPMC11883580

What Socratic holds

Textmetadata
LicenceCC BY-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 Socratic graph.