Evidence map›Paper›PMID 42137000›Full record

ArticlePediatric quality & safety

Ultrasound Image Capture during Central Venous Catheter Insertions: A Quality Improvement Study.

Sam Biniazan, Andrew J Lautz, Marc Mecoli, Erika L Stalets, Matthew W Zackoff

Abstract read
In one paragraph

Article in Pediatric quality & safety. 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
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0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

5 authors.

Sam BiniazanFrom the Division of Critical Care, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio.
Andrew J LautzFrom the Division of Critical Care, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio.
Marc MecoliUniversity of Cincinnati College of Medicine, Cincinnati, Ohio.
Erika L StaletsFrom the Division of Critical Care, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio.
Matthew W ZackoffFrom the Division of Critical Care, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Central venous catheter (CVC) insertion is one of the most common interventions in the pediatric intensive care unit (PICU). Although lifesaving, CVC insertion also carries significant risks of morbidity and mortality-risks that ultrasound guidance can help reduce. This study described a quality improvement initiative aimed at increasing the rate of ultrasound documentation of correct guidewire position before vessel dilation during CVC insertions. Methods: This study developed a novel workflow for capturing images from ultrasound machines used during CVC insertions in a PICU and uploading them into the electronic health record. A specific, measurable, achievable, relevant, time-based aim and key driver diagram guided the interventions. A failure modes and effects analysis identified failure points and informed Plan-Do-Study-Act cycles to increase the rate of successful ultrasound image capture and upload. Results: Between July 1, 2023, and March 31, 2025, critical care fellows and attendings performed 270 new CVC insertions within the PICU. Successful image capture and upload rates reached a monthly high of 64% and a mean completion rate of 58%. The key process metric for placing an electronic health record order required for image upload reached a monthly high of 100% and a mean completion rate of 83%. Conclusions: This study developed and implemented a novel workflow for PICU proceduralists to increase the rate of ultrasound image capture during CVC insertion. Although work continues toward achieving the primary objective, the study provided key insights into the consistent capture of ultrasound images, supporting enhanced safety during CVC insertion.

Identifiers

PMID42137000
PMCPMC13169242

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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.