Automated EHR score to predict COVID-19 outcomes at US Department of Veterans Affairs

The sudden emergence of COVID-19 has brought significant challenges to the care of Veterans. An improved ability to predict a patient’s clinical course would facilitate optimal care decisions, resource allocation, family counseling, and strategies for safely easing distancing restrictions. The Care...

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Autores principales: Osborne, Thomas F., Veigulis, Zachary P., Arreola, David M., Röösli, Eliane, Curtin, Catherine M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7384633/
https://www.ncbi.nlm.nih.gov/pubmed/32716922
http://dx.doi.org/10.1371/journal.pone.0236554
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author Osborne, Thomas F.
Veigulis, Zachary P.
Arreola, David M.
Röösli, Eliane
Curtin, Catherine M.
author_facet Osborne, Thomas F.
Veigulis, Zachary P.
Arreola, David M.
Röösli, Eliane
Curtin, Catherine M.
author_sort Osborne, Thomas F.
collection PubMed
description The sudden emergence of COVID-19 has brought significant challenges to the care of Veterans. An improved ability to predict a patient’s clinical course would facilitate optimal care decisions, resource allocation, family counseling, and strategies for safely easing distancing restrictions. The Care Assessment Need (CAN) score is an existing risk assessment tool within the Veterans Health Administration (VA), and produces a score from 0 to 99, with a higher score correlating to a greater risk. The model was originally designed for the nonacute outpatient setting and is automatically calculated from structured data variables in the electronic health record. This multisite retrospective study of 6591 Veterans diagnosed with COVID-19 from March 2, 2020 to May 26, 2020 was designed to assess the utility of repurposing the CAN score as objective and automated risk assessment tool to promptly enhance clinical decision making for Veterans diagnosed with COVID-19. We performed bivariate analyses on the dichotomized CAN 1-year mortality score (high vs. low risk) and each patient outcome using Chi-square tests of independence. Logistic regression models using the continuous CAN score were fit to assess its predictive power for outcomes of interest. Results demonstrated that a CAN score greater than 50 was significantly associated with the following outcomes after positive COVID-19 test: hospital admission (OR 4.6), prolonged hospital stay (OR 4.5), ICU admission (3.1), prolonged ICU stay (OR 2.9), mechanical ventilation (OR 2.6), and mortality (OR 7.2). Repurposing the CAN score offers an efficient way to risk-stratify COVID-19 Veterans. As a result of the compelling statistical results, and automation, this tool is well positioned for broad use across the VA to enhance clinical decision-making.
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spelling pubmed-73846332020-08-05 Automated EHR score to predict COVID-19 outcomes at US Department of Veterans Affairs Osborne, Thomas F. Veigulis, Zachary P. Arreola, David M. Röösli, Eliane Curtin, Catherine M. PLoS One Research Article The sudden emergence of COVID-19 has brought significant challenges to the care of Veterans. An improved ability to predict a patient’s clinical course would facilitate optimal care decisions, resource allocation, family counseling, and strategies for safely easing distancing restrictions. The Care Assessment Need (CAN) score is an existing risk assessment tool within the Veterans Health Administration (VA), and produces a score from 0 to 99, with a higher score correlating to a greater risk. The model was originally designed for the nonacute outpatient setting and is automatically calculated from structured data variables in the electronic health record. This multisite retrospective study of 6591 Veterans diagnosed with COVID-19 from March 2, 2020 to May 26, 2020 was designed to assess the utility of repurposing the CAN score as objective and automated risk assessment tool to promptly enhance clinical decision making for Veterans diagnosed with COVID-19. We performed bivariate analyses on the dichotomized CAN 1-year mortality score (high vs. low risk) and each patient outcome using Chi-square tests of independence. Logistic regression models using the continuous CAN score were fit to assess its predictive power for outcomes of interest. Results demonstrated that a CAN score greater than 50 was significantly associated with the following outcomes after positive COVID-19 test: hospital admission (OR 4.6), prolonged hospital stay (OR 4.5), ICU admission (3.1), prolonged ICU stay (OR 2.9), mechanical ventilation (OR 2.6), and mortality (OR 7.2). Repurposing the CAN score offers an efficient way to risk-stratify COVID-19 Veterans. As a result of the compelling statistical results, and automation, this tool is well positioned for broad use across the VA to enhance clinical decision-making. Public Library of Science 2020-07-27 /pmc/articles/PMC7384633/ /pubmed/32716922 http://dx.doi.org/10.1371/journal.pone.0236554 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication.
spellingShingle Research Article
Osborne, Thomas F.
Veigulis, Zachary P.
Arreola, David M.
Röösli, Eliane
Curtin, Catherine M.
Automated EHR score to predict COVID-19 outcomes at US Department of Veterans Affairs
title Automated EHR score to predict COVID-19 outcomes at US Department of Veterans Affairs
title_full Automated EHR score to predict COVID-19 outcomes at US Department of Veterans Affairs
title_fullStr Automated EHR score to predict COVID-19 outcomes at US Department of Veterans Affairs
title_full_unstemmed Automated EHR score to predict COVID-19 outcomes at US Department of Veterans Affairs
title_short Automated EHR score to predict COVID-19 outcomes at US Department of Veterans Affairs
title_sort automated ehr score to predict covid-19 outcomes at us department of veterans affairs
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7384633/
https://www.ncbi.nlm.nih.gov/pubmed/32716922
http://dx.doi.org/10.1371/journal.pone.0236554
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