Evidence map›Paper›PMID 42839354›Full record

ArticleClinical and translational science2026

Protocol Deviations at an Academic Clinical Research Unit: Insights and Strategies for Prevention.

Maran Subramain, Patrick Ten Eyck, Kristy Mahan, Jackline Wangui, Kimberly Sprenger, Donald G McCloud, John M Buatti, Alejandro P Comellas

Abstract read
In one paragraph

Article in Clinical and translational science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Maran SubramainInstitute for Clinical and Translational Science, University of Iowa, Iowa City, Iowa, USA.ORCID https://orcid.org/0000-0002-1482-8226
Patrick Ten EyckInstitute for Clinical and Translational Science, University of Iowa, Iowa City, Iowa, USA.ORCID https://orcid.org/0000-0002-5041-0708
Kristy MahanInstitute for Clinical and Translational Science, University of Iowa, Iowa City, Iowa, USA.
Jackline WanguiInstitute for Clinical and Translational Science, University of Iowa, Iowa City, Iowa, USA.
Kimberly SprengerInstitute for Clinical and Translational Science, University of Iowa, Iowa City, Iowa, USA.
Donald G McCloudWestern Michigan University, Kalamazoo, Michigan, USA.
John M BuattiDepartment of Radiation Oncology, University of Iowa, Iowa City, Iowa, USA.ORCID https://orcid.org/0000-0001-8499-3721
Alejandro P ComellasInstitute for Clinical and Translational Science, University of Iowa, Iowa City, Iowa, USA.ORCID https://orcid.org/0000-0003-1521-7520

Funding

University of Iowa Institute for Clinical and Translational ScienceUM1TR004403 · NCATS · UNIVERSITY OF IOWA · PI Marlan R Hansen, Patricia Winokur · 2023 to 2026
$16.1M
National Center for Advancing Translational Sciences of the National Institutes of Health (NCATS) UM1TR004403NCATS NIH HHS UM1 TR004403
6 · The paper itself

Abstract

Protocol deviations threaten data integrity, regulatory compliance, and participant safety in clinical trials. Despite their prevalence, few longitudinal studies have characterized deviation patterns and described quality improvement strategies within clinical research units (CRUs). This descriptive longitudinal quality improvement study analyzed protocol deviations and prevented incidents reported at the University of Iowa CRU from June 17, 2020, through December 31, 2024. Events were captured via online survey and classified using a five-grade severity scale. Pearson's chi-square tests assessed associations between event characteristics and outcomes. During the survey data-collection period, 11,581 CRU visits were recorded. Overall, 261 events were reported, including 100 incidents prevented before becoming protocol deviations and 68 confirmed protocol deviations; 93 events preceded systematic collection of the prevented/resulted classification. Grade 1 was the most frequently selected severity classification (126 of 178 severity-grade selections; 70.8%). The laboratory (60.2%) and study setup (33.7%) were the most frequent event contexts. Among events with a prevented/resulted classification, Grade 1 events were more frequently prevented than Grade 2-5 events (71.8% vs. 25.0%; p < 0.0001). Quality improvement strategies implemented during the observation period included dedicated study liaisons, standardized start-up checklists, increased staffing, and structured communication processes. Lower-severity events were more frequently prevented before resulting in protocol deviations. These findings identify operational contexts and event characteristics that may inform proactive, systems-based approaches to deviation prevention in CRUs.

Indexed as

Academic Medical CentersBiomedical ResearchClinical ProtocolsQuality ImprovementAcademiaHumansIowaLongitudinal StudiesResearch DesignSurveys and Questionnairesclinical and translational science award (CTSA)clinical research unitsclinical trialscontinuous quality improvement (CQI)protocol deviations

Identifiers

PMID42839354
PMCPMC13642981

What OpenQuestion holds

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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.