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AUS-TBI: The Australian Health Informatics Approach to Predict Outcomes and Monitor Intervention Efficacy after Moderate-to-Severe Traumatic Brain Injury

Predicting and optimizing outcomes after traumatic brain injury (TBI) remains a major challenge because of the breadth of injury characteristics and complexity of brain responses. AUS-TBI is a new Australian Government–funded initiative that aims to improve personalized care and treatment for childr...

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Autores principales: Fitzgerald, Melinda, Ponsford, Jennie, Lannin, Natasha A., O'Brien, Terence J., Cameron, Peter, Cooper, D. James, Rushworth, Nick, Gabbe, Belinda
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Mary Ann Liebert, Inc., publishers 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9279124/
https://www.ncbi.nlm.nih.gov/pubmed/35919508
http://dx.doi.org/10.1089/neur.2022.0002
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author Fitzgerald, Melinda
Ponsford, Jennie
Lannin, Natasha A.
O'Brien, Terence J.
Cameron, Peter
Cooper, D. James
Rushworth, Nick
Gabbe, Belinda
author_facet Fitzgerald, Melinda
Ponsford, Jennie
Lannin, Natasha A.
O'Brien, Terence J.
Cameron, Peter
Cooper, D. James
Rushworth, Nick
Gabbe, Belinda
author_sort Fitzgerald, Melinda
collection PubMed
description Predicting and optimizing outcomes after traumatic brain injury (TBI) remains a major challenge because of the breadth of injury characteristics and complexity of brain responses. AUS-TBI is a new Australian Government–funded initiative that aims to improve personalized care and treatment for children and adults who have sustained a TBI. The AUS-TBI team aims to address a number of key knowledge gaps, by designing an approach to bring together data describing psychosocial modulators, social determinants, clinical parameters, imaging data, biomarker profiles, and rehabilitation outcomes in order to assess the influence that they have on long-term outcome. Data management systems will be designed to track a broad range of suitable potential indicators and outcomes, which will be organized to facilitate secure data collection, linkage, storage, curation, management, and analysis. It is believed that these objectives are achievable because of our consortium of highly committed national and international leaders, expert committees, and partner organizations in TBI and health informatics. It is anticipated that the resulting large-scale data resource will facilitate personalization, prediction, and improvement of outcomes post-TBI.
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spelling pubmed-92791242022-08-01 AUS-TBI: The Australian Health Informatics Approach to Predict Outcomes and Monitor Intervention Efficacy after Moderate-to-Severe Traumatic Brain Injury Fitzgerald, Melinda Ponsford, Jennie Lannin, Natasha A. O'Brien, Terence J. Cameron, Peter Cooper, D. James Rushworth, Nick Gabbe, Belinda Neurotrauma Rep Original Article Predicting and optimizing outcomes after traumatic brain injury (TBI) remains a major challenge because of the breadth of injury characteristics and complexity of brain responses. AUS-TBI is a new Australian Government–funded initiative that aims to improve personalized care and treatment for children and adults who have sustained a TBI. The AUS-TBI team aims to address a number of key knowledge gaps, by designing an approach to bring together data describing psychosocial modulators, social determinants, clinical parameters, imaging data, biomarker profiles, and rehabilitation outcomes in order to assess the influence that they have on long-term outcome. Data management systems will be designed to track a broad range of suitable potential indicators and outcomes, which will be organized to facilitate secure data collection, linkage, storage, curation, management, and analysis. It is believed that these objectives are achievable because of our consortium of highly committed national and international leaders, expert committees, and partner organizations in TBI and health informatics. It is anticipated that the resulting large-scale data resource will facilitate personalization, prediction, and improvement of outcomes post-TBI. Mary Ann Liebert, Inc., publishers 2022-06-07 /pmc/articles/PMC9279124/ /pubmed/35919508 http://dx.doi.org/10.1089/neur.2022.0002 Text en © Melinda Fitzgerald et al., 2022; Published by Mary Ann Liebert, Inc. https://creativecommons.org/licenses/by/4.0/This Open Access article is distributed under the terms of the Creative Commons License [CC-BY] (http://creativecommons.org/licenses/by/4.0 (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Fitzgerald, Melinda
Ponsford, Jennie
Lannin, Natasha A.
O'Brien, Terence J.
Cameron, Peter
Cooper, D. James
Rushworth, Nick
Gabbe, Belinda
AUS-TBI: The Australian Health Informatics Approach to Predict Outcomes and Monitor Intervention Efficacy after Moderate-to-Severe Traumatic Brain Injury
title AUS-TBI: The Australian Health Informatics Approach to Predict Outcomes and Monitor Intervention Efficacy after Moderate-to-Severe Traumatic Brain Injury
title_full AUS-TBI: The Australian Health Informatics Approach to Predict Outcomes and Monitor Intervention Efficacy after Moderate-to-Severe Traumatic Brain Injury
title_fullStr AUS-TBI: The Australian Health Informatics Approach to Predict Outcomes and Monitor Intervention Efficacy after Moderate-to-Severe Traumatic Brain Injury
title_full_unstemmed AUS-TBI: The Australian Health Informatics Approach to Predict Outcomes and Monitor Intervention Efficacy after Moderate-to-Severe Traumatic Brain Injury
title_short AUS-TBI: The Australian Health Informatics Approach to Predict Outcomes and Monitor Intervention Efficacy after Moderate-to-Severe Traumatic Brain Injury
title_sort aus-tbi: the australian health informatics approach to predict outcomes and monitor intervention efficacy after moderate-to-severe traumatic brain injury
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9279124/
https://www.ncbi.nlm.nih.gov/pubmed/35919508
http://dx.doi.org/10.1089/neur.2022.0002
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