Evidence map›Paper›PMID 36217502›Full record

ArticleEuropean journal of radiology open2022

Utilization of a cloud-based radiology analytics platform to monitor imaging volumes at a large tertiary center.

Stanley Chu, Mitchell Collins, Maurice Pradella, Martin Kramer, Rachel Davids, Mathis Zimmerman, Sarah Fopma, Alexander Korutz, Blair Faber, Ryan Avery and 3 more

Abstract read
In one paragraph

Article in European journal of radiology open, 2022. 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

13 authors.

Stanley ChuDepartment of Radiology, Northwestern University, 737 N Michigan Ave, Suite 1600, Chicago, IL 60611, United States.
Mitchell CollinsDepartment of Radiology, Northwestern University, 737 N Michigan Ave, Suite 1600, Chicago, IL 60611, United States.
Maurice PradellaDepartment of Radiology, Northwestern University, 737 N Michigan Ave, Suite 1600, Chicago, IL 60611, United States.
Martin KramerSiemens Healthineers, Henkestr. 127, 91052 Erlangen, Federal Republic of Germany.
Rachel DavidsDepartment of Radiology, Northwestern University, 737 N Michigan Ave, Suite 1600, Chicago, IL 60611, United States.
Mathis ZimmermanSiemens Healthineers, Henkestr. 127, 91052 Erlangen, Federal Republic of Germany.
Sarah FopmaDepartment of Radiology, Northwestern University, 737 N Michigan Ave, Suite 1600, Chicago, IL 60611, United States.
Alexander KorutzDepartment of Radiology, Northwestern University, 737 N Michigan Ave, Suite 1600, Chicago, IL 60611, United States.
Blair FaberDepartment of Radiology, Northwestern University, 737 N Michigan Ave, Suite 1600, Chicago, IL 60611, United States.
Ryan AveryDepartment of Radiology, Northwestern University, 737 N Michigan Ave, Suite 1600, Chicago, IL 60611, United States.
James CarrDepartment of Radiology, Northwestern University, 737 N Michigan Ave, Suite 1600, Chicago, IL 60611, United States.
Bradley D AllenDepartment of Radiology, Northwestern University, 737 N Michigan Ave, Suite 1600, Chicago, IL 60611, United States.
Michael MarklDepartment of Radiology, Northwestern University, 737 N Michigan Ave, Suite 1600, Chicago, IL 60611, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rationale and objective: In this study, we evaluate the ability of a novel cloud-based radiology analytics platform to continuously monitor imaging volumes at a large tertiary center following institutional protocol and policy changes. Materials and methods: We evaluated response to environmental factors through the lens of the COVID-19 pandemic. Analysis involved 11 CT/18 MR imaging systems at a large tertiary center. A vendor neutral, cloud-based analytics tool (CBRAP) was used to retrospectively collect information via DICOM headers on imaging exams between Oct. 2019 to Aug. 2021. Exams were stratified by modality (CT or MRI) and organized by body region. Pre-pandemic scan volumes (Oct 2019-Feb. 2010) were compared with volumes during/after two waves of COVID-19 in Illinois (Mar. to May 2020 & Oct. to Dec. 2020) using a t-test or Mann-Whitney U test. Results: The CBRAP was able to analyze 169,530 CT and 110,837 MR images, providing a detailed snapshot of baseline and post-pandemic CT and MR imaging across the radiology enterprise at our tertiary center. The CBRAP allowed for further subdivision in its reporting, showing monthly trends in average scan volumes specifically in the head, abdomen, spine, MSK, thorax, neck, GU system, or breast. Conclusion: The CBRAP retrieved data for 300,000 + imaging exams across multiple modalities at a large tertiary center in a highly populated, urban environment. The ability to analyze large imaging volumes across multiple waves of COVID-19 and evaluate quality-improvement endeavors/imaging protocol changes displays the usefulness of the CBRAP as an advanced imaging analytics tool.

Indexed as

CBRAP, Cloud-based analytics toolCloud-based analyticsComputed tomographyCOVID-19CT, Computed tomographyGU, GenitourinaryHEENT, Head, eyes, ear, nose, throatMagnetic resonance imagingMRI, Magnetic resonance imagingMSK, MusculoskeletalProcess improvement

Identifiers

PMID36217502
PMCPMC9547187

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.