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The carbon footprint of hospital diagnostic imaging in Australia

BACKGROUND: Pathology testing and diagnostic imaging together contribute 9% of healthcare's carbon footprint. Whilst the carbon footprint of pathology testing has been undertaken, to date, the carbon footprint of the four most common imaging modalities is unclear. METHODS: We performed a prospe...

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Autores principales: McAlister, Scott, McGain, Forbes, Petersen, Matilde, Story, David, Charlesworth, Kate, Ison, Glenn, Barratt, Alexandra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9079346/
https://www.ncbi.nlm.nih.gov/pubmed/35538935
http://dx.doi.org/10.1016/j.lanwpc.2022.100459
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author McAlister, Scott
McGain, Forbes
Petersen, Matilde
Story, David
Charlesworth, Kate
Ison, Glenn
Barratt, Alexandra
author_facet McAlister, Scott
McGain, Forbes
Petersen, Matilde
Story, David
Charlesworth, Kate
Ison, Glenn
Barratt, Alexandra
author_sort McAlister, Scott
collection PubMed
description BACKGROUND: Pathology testing and diagnostic imaging together contribute 9% of healthcare's carbon footprint. Whilst the carbon footprint of pathology testing has been undertaken, to date, the carbon footprint of the four most common imaging modalities is unclear. METHODS: We performed a prospective life cycle assessment at two Australian university-affiliated health services of five imaging modalities: chest X-ray (CXR), mobile chest X-ray (MCXR), computerised tomography (CT), magnetic resonance imaging (MRI) and ultrasound (US). We included scanner electricity use and all consumables and associated waste, including bedding, imaging contrast, and gloves. Analysis was performed using both attributional and consequential life cycle assessment methods. The primary outcome was the greenhouse gas footprint, measured in carbon dioxide equivalent (CO(2)e) emissions. FINDINGS: Mean CO(2)e emissions were 17·5 kg/scan for MRI; 9·2 kg/scan for CT; 0·8 kg/scan for CXR; 0·5 kg/scan for MCXR; and 0·5 kg/scan for US. Emissions from scanners from standby energy were substantial. When expressed as emissions per additional scan (results of consequential analysis) impacts were lower: 1·1 kg/scan for MRI; 1·1 kg/scan for CT; 0·6 kg/scan for CXR; 0·1 kg/scan for MCXR; and 0·1 kg/scan for US, due to emissions from standby power being excluded. INTERPRETATION: Clinicians and administrators can reduce carbon emissions from diagnostic imaging, firstly by reducing the ordering of unnecessary imaging, or by ordering low-impact imaging (X-ray and US) in place of high-impact MRI and CT when clinically appropriate to do so. Secondly, whenever possible, scanners should be turned off to reduce emissions from standby power. Thirdly, ensuring high utilisation rates for scanners both reduces the time they spend in standby, and apportions the impacts of the reduced standby power of a greater number of scans. This therefore reduces the impact on any individual scan, maximising resource efficiency. FUNDING: Healthy Urban Environments (HUE) Collaboratory of the Maridulu Budyari Gumal Sydney Partnership for Health, Education, Research and Enterprise MBG SPHERE. The National Health and Medical Research Council (NHMRC) PhD scholarship
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spelling pubmed-90793462022-05-09 The carbon footprint of hospital diagnostic imaging in Australia McAlister, Scott McGain, Forbes Petersen, Matilde Story, David Charlesworth, Kate Ison, Glenn Barratt, Alexandra Lancet Reg Health West Pac Articles BACKGROUND: Pathology testing and diagnostic imaging together contribute 9% of healthcare's carbon footprint. Whilst the carbon footprint of pathology testing has been undertaken, to date, the carbon footprint of the four most common imaging modalities is unclear. METHODS: We performed a prospective life cycle assessment at two Australian university-affiliated health services of five imaging modalities: chest X-ray (CXR), mobile chest X-ray (MCXR), computerised tomography (CT), magnetic resonance imaging (MRI) and ultrasound (US). We included scanner electricity use and all consumables and associated waste, including bedding, imaging contrast, and gloves. Analysis was performed using both attributional and consequential life cycle assessment methods. The primary outcome was the greenhouse gas footprint, measured in carbon dioxide equivalent (CO(2)e) emissions. FINDINGS: Mean CO(2)e emissions were 17·5 kg/scan for MRI; 9·2 kg/scan for CT; 0·8 kg/scan for CXR; 0·5 kg/scan for MCXR; and 0·5 kg/scan for US. Emissions from scanners from standby energy were substantial. When expressed as emissions per additional scan (results of consequential analysis) impacts were lower: 1·1 kg/scan for MRI; 1·1 kg/scan for CT; 0·6 kg/scan for CXR; 0·1 kg/scan for MCXR; and 0·1 kg/scan for US, due to emissions from standby power being excluded. INTERPRETATION: Clinicians and administrators can reduce carbon emissions from diagnostic imaging, firstly by reducing the ordering of unnecessary imaging, or by ordering low-impact imaging (X-ray and US) in place of high-impact MRI and CT when clinically appropriate to do so. Secondly, whenever possible, scanners should be turned off to reduce emissions from standby power. Thirdly, ensuring high utilisation rates for scanners both reduces the time they spend in standby, and apportions the impacts of the reduced standby power of a greater number of scans. This therefore reduces the impact on any individual scan, maximising resource efficiency. FUNDING: Healthy Urban Environments (HUE) Collaboratory of the Maridulu Budyari Gumal Sydney Partnership for Health, Education, Research and Enterprise MBG SPHERE. The National Health and Medical Research Council (NHMRC) PhD scholarship Elsevier 2022-05-03 /pmc/articles/PMC9079346/ /pubmed/35538935 http://dx.doi.org/10.1016/j.lanwpc.2022.100459 Text en © 2022 The Author(s) 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 Articles
McAlister, Scott
McGain, Forbes
Petersen, Matilde
Story, David
Charlesworth, Kate
Ison, Glenn
Barratt, Alexandra
The carbon footprint of hospital diagnostic imaging in Australia
title The carbon footprint of hospital diagnostic imaging in Australia
title_full The carbon footprint of hospital diagnostic imaging in Australia
title_fullStr The carbon footprint of hospital diagnostic imaging in Australia
title_full_unstemmed The carbon footprint of hospital diagnostic imaging in Australia
title_short The carbon footprint of hospital diagnostic imaging in Australia
title_sort carbon footprint of hospital diagnostic imaging in australia
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9079346/
https://www.ncbi.nlm.nih.gov/pubmed/35538935
http://dx.doi.org/10.1016/j.lanwpc.2022.100459
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