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Predicting Expected Organ Donor Numbers in Australian Hospitals Outside of the Donate-Life Network Using the ANZICS Adult Patient Database

BACKGROUND: The majority of organ donations in Australia occur in the DonateLife Network of hospitals, but limited monitoring at other sites may allow donation opportunities to be missed. Our aim was to estimate expected donor numbers using routinely collected data from the Australian and New Zealan...

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Autores principales: O'Brien, Yvette, Chavan, Shaila, Huckson, Sue, Russ, Graeme, Opdam, Helen, Pilcher, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6072376/
https://www.ncbi.nlm.nih.gov/pubmed/29470348
http://dx.doi.org/10.1097/TP.0000000000002111
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author O'Brien, Yvette
Chavan, Shaila
Huckson, Sue
Russ, Graeme
Opdam, Helen
Pilcher, David
author_facet O'Brien, Yvette
Chavan, Shaila
Huckson, Sue
Russ, Graeme
Opdam, Helen
Pilcher, David
author_sort O'Brien, Yvette
collection PubMed
description BACKGROUND: The majority of organ donations in Australia occur in the DonateLife Network of hospitals, but limited monitoring at other sites may allow donation opportunities to be missed. Our aim was to estimate expected donor numbers using routinely collected data from the Australian and New Zealand Intensive Care Society Adult Patient Database and determine whether unrecognized potential donors might exist in non-DonateLife hospitals. METHODS: All deaths at 150 Australian intensive care units (ICUs) contributing to the Australian and New Zealand Intensive Care Society Adult Patient Database were analyzed between January 2010 and December 2015. Donor numbers were extracted from the Australian and New Zealand Organ Donor registry. A univariate linear regression model was developed to estimate expected donor numbers in DonateLife hospitals, then applied to non-DonateLife hospitals. RESULTS: Of 33 614 deaths at 71 DonateLife hospitals, 6835 (20%) met criteria as “ICU deaths potentially suitable to be donors,” and 1992 (6%) were actual donors. There was a consistent relationship between these groups (R(2) = 0.626, P < 0.001) allowing the development of a prediction model which adequately estimated expected donors. Of 8077 deaths in 79 non-DonateLife ICUs, 452 (6%) met criteria as potentially suitable donors. Applying the prediction model developed in DonateLife hospitals, the estimated expected donors in non-DonateLife hospitals was 130. However, there were only 75 actual donors. CONCLUSIONS: It is possible to estimate the expected number of Australian organ donors using routinely collected registry data. These findings suggest that there may be a small but significant pool of underutilized potential donors in non-DonateLife hospitals. This may provide an opportunity to increase donation rates.
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spelling pubmed-60723762018-08-17 Predicting Expected Organ Donor Numbers in Australian Hospitals Outside of the Donate-Life Network Using the ANZICS Adult Patient Database O'Brien, Yvette Chavan, Shaila Huckson, Sue Russ, Graeme Opdam, Helen Pilcher, David Transplantation Original Clinical Science—General BACKGROUND: The majority of organ donations in Australia occur in the DonateLife Network of hospitals, but limited monitoring at other sites may allow donation opportunities to be missed. Our aim was to estimate expected donor numbers using routinely collected data from the Australian and New Zealand Intensive Care Society Adult Patient Database and determine whether unrecognized potential donors might exist in non-DonateLife hospitals. METHODS: All deaths at 150 Australian intensive care units (ICUs) contributing to the Australian and New Zealand Intensive Care Society Adult Patient Database were analyzed between January 2010 and December 2015. Donor numbers were extracted from the Australian and New Zealand Organ Donor registry. A univariate linear regression model was developed to estimate expected donor numbers in DonateLife hospitals, then applied to non-DonateLife hospitals. RESULTS: Of 33 614 deaths at 71 DonateLife hospitals, 6835 (20%) met criteria as “ICU deaths potentially suitable to be donors,” and 1992 (6%) were actual donors. There was a consistent relationship between these groups (R(2) = 0.626, P < 0.001) allowing the development of a prediction model which adequately estimated expected donors. Of 8077 deaths in 79 non-DonateLife ICUs, 452 (6%) met criteria as potentially suitable donors. Applying the prediction model developed in DonateLife hospitals, the estimated expected donors in non-DonateLife hospitals was 130. However, there were only 75 actual donors. CONCLUSIONS: It is possible to estimate the expected number of Australian organ donors using routinely collected registry data. These findings suggest that there may be a small but significant pool of underutilized potential donors in non-DonateLife hospitals. This may provide an opportunity to increase donation rates. Lippincott Williams & Wilkins 2018-08 2018-07-25 /pmc/articles/PMC6072376/ /pubmed/29470348 http://dx.doi.org/10.1097/TP.0000000000002111 Text en Copyright © 2018 The Author(s). Published by Wolters Kluwer Health, Inc. This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND) (http://creativecommons.org/licenses/by-nc-nd/4.0/) , where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.
spellingShingle Original Clinical Science—General
O'Brien, Yvette
Chavan, Shaila
Huckson, Sue
Russ, Graeme
Opdam, Helen
Pilcher, David
Predicting Expected Organ Donor Numbers in Australian Hospitals Outside of the Donate-Life Network Using the ANZICS Adult Patient Database
title Predicting Expected Organ Donor Numbers in Australian Hospitals Outside of the Donate-Life Network Using the ANZICS Adult Patient Database
title_full Predicting Expected Organ Donor Numbers in Australian Hospitals Outside of the Donate-Life Network Using the ANZICS Adult Patient Database
title_fullStr Predicting Expected Organ Donor Numbers in Australian Hospitals Outside of the Donate-Life Network Using the ANZICS Adult Patient Database
title_full_unstemmed Predicting Expected Organ Donor Numbers in Australian Hospitals Outside of the Donate-Life Network Using the ANZICS Adult Patient Database
title_short Predicting Expected Organ Donor Numbers in Australian Hospitals Outside of the Donate-Life Network Using the ANZICS Adult Patient Database
title_sort predicting expected organ donor numbers in australian hospitals outside of the donate-life network using the anzics adult patient database
topic Original Clinical Science—General
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6072376/
https://www.ncbi.nlm.nih.gov/pubmed/29470348
http://dx.doi.org/10.1097/TP.0000000000002111
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