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Utilization of a cloud-based radiology analytics platform to monitor imaging volumes at a large tertiary center
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 fa...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9547187/ https://www.ncbi.nlm.nih.gov/pubmed/36217502 http://dx.doi.org/10.1016/j.ejro.2022.100443 |
_version_ | 1784805208249860096 |
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author | Chu, Stanley Collins, Mitchell Pradella, Maurice Kramer, Martin Davids, Rachel Zimmerman, Mathis Fopma, Sarah Korutz, Alexander Faber, Blair Avery, Ryan Carr, James Allen, Bradley D. Markl, Michael |
author_facet | Chu, Stanley Collins, Mitchell Pradella, Maurice Kramer, Martin Davids, Rachel Zimmerman, Mathis Fopma, Sarah Korutz, Alexander Faber, Blair Avery, Ryan Carr, James Allen, Bradley D. Markl, Michael |
author_sort | Chu, Stanley |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9547187 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-95471872022-10-09 Utilization of a cloud-based radiology analytics platform to monitor imaging volumes at a large tertiary center Chu, Stanley Collins, Mitchell Pradella, Maurice Kramer, Martin Davids, Rachel Zimmerman, Mathis Fopma, Sarah Korutz, Alexander Faber, Blair Avery, Ryan Carr, James Allen, Bradley D. Markl, Michael Eur J Radiol Open Original Article 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. Elsevier 2022-10-05 /pmc/articles/PMC9547187/ /pubmed/36217502 http://dx.doi.org/10.1016/j.ejro.2022.100443 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Original Article Chu, Stanley Collins, Mitchell Pradella, Maurice Kramer, Martin Davids, Rachel Zimmerman, Mathis Fopma, Sarah Korutz, Alexander Faber, Blair Avery, Ryan Carr, James Allen, Bradley D. Markl, Michael Utilization of a cloud-based radiology analytics platform to monitor imaging volumes at a large tertiary center |
title | Utilization of a cloud-based radiology analytics platform to monitor imaging volumes at a large tertiary center |
title_full | Utilization of a cloud-based radiology analytics platform to monitor imaging volumes at a large tertiary center |
title_fullStr | Utilization of a cloud-based radiology analytics platform to monitor imaging volumes at a large tertiary center |
title_full_unstemmed | Utilization of a cloud-based radiology analytics platform to monitor imaging volumes at a large tertiary center |
title_short | Utilization of a cloud-based radiology analytics platform to monitor imaging volumes at a large tertiary center |
title_sort | utilization of a cloud-based radiology analytics platform to monitor imaging volumes at a large tertiary center |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9547187/ https://www.ncbi.nlm.nih.gov/pubmed/36217502 http://dx.doi.org/10.1016/j.ejro.2022.100443 |
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