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Leveraging a health information exchange for analyses of COVID-19 outcomes including an example application using smoking history and mortality

Understanding sociodemographic, behavioral, clinical, and laboratory risk factors in patients diagnosed with COVID-19 is critically important, and requires building large and diverse COVID-19 cohorts with both retrospective information and prospective follow-up. A large Health Information Exchange (...

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Autores principales: Tortolero, Guillermo A., Brown, Michael R., Sharma, Shreela V., de Oliveira Otto, Marcia C., Yamal, Jose-Miguel, Aguilar, David, Gunther, Matt D., Mofleh, Dania I., Harris, Rachel D., John, Jemima C., de Vries, Paul S., Ramphul, Ryan, Serbo, Dritana Marko, Kiger, Jennifer, Banerjee, Deborah, Bonvino, Nick, Merchant, Angela, Clifford, Warren, Mikhail, Jenny, Xu, Hua, Murphy, Robert E., Wei, Qiang, Vahidy, Farhaan S., Morrison, Alanna C., Boerwinkle, Eric
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8174716/
https://www.ncbi.nlm.nih.gov/pubmed/34081724
http://dx.doi.org/10.1371/journal.pone.0247235
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author Tortolero, Guillermo A.
Brown, Michael R.
Sharma, Shreela V.
de Oliveira Otto, Marcia C.
Yamal, Jose-Miguel
Aguilar, David
Gunther, Matt D.
Mofleh, Dania I.
Harris, Rachel D.
John, Jemima C.
de Vries, Paul S.
Ramphul, Ryan
Serbo, Dritana Marko
Kiger, Jennifer
Banerjee, Deborah
Bonvino, Nick
Merchant, Angela
Clifford, Warren
Mikhail, Jenny
Xu, Hua
Murphy, Robert E.
Wei, Qiang
Vahidy, Farhaan S.
Morrison, Alanna C.
Boerwinkle, Eric
author_facet Tortolero, Guillermo A.
Brown, Michael R.
Sharma, Shreela V.
de Oliveira Otto, Marcia C.
Yamal, Jose-Miguel
Aguilar, David
Gunther, Matt D.
Mofleh, Dania I.
Harris, Rachel D.
John, Jemima C.
de Vries, Paul S.
Ramphul, Ryan
Serbo, Dritana Marko
Kiger, Jennifer
Banerjee, Deborah
Bonvino, Nick
Merchant, Angela
Clifford, Warren
Mikhail, Jenny
Xu, Hua
Murphy, Robert E.
Wei, Qiang
Vahidy, Farhaan S.
Morrison, Alanna C.
Boerwinkle, Eric
author_sort Tortolero, Guillermo A.
collection PubMed
description Understanding sociodemographic, behavioral, clinical, and laboratory risk factors in patients diagnosed with COVID-19 is critically important, and requires building large and diverse COVID-19 cohorts with both retrospective information and prospective follow-up. A large Health Information Exchange (HIE) in Southeast Texas, which assembles and shares electronic health information among providers to facilitate patient care, was leveraged to identify COVID-19 patients, create a cohort, and identify risk factors for both favorable and unfavorable outcomes. The initial sample consists of 8,874 COVID-19 patients ascertained from the pandemic’s onset to June 12(th), 2020 and was created for the analyses shown here. We gathered demographic, lifestyle, laboratory, and clinical data from patient’s encounters across the healthcare system. Tobacco use history was examined as a potential risk factor for COVID-19 fatality along with age, gender, race/ethnicity, body mass index (BMI), and number of comorbidities. Of the 8,874 patients included in the cohort, 475 died from COVID-19. Of the 5,356 patients who had information on history of tobacco use, over 26% were current or former tobacco users. Multivariable logistic regression showed that the odds of COVID-19 fatality increased among those who were older (odds ratio = 1.07, 95% CI 1.06, 1.08), male (1.91, 95% CI 1.58, 2.31), and had a history of tobacco use (2.45, 95% CI 1.93, 3.11). History of tobacco use remained significantly associated (1.65, 95% CI 1.27, 2.13) with COVID-19 fatality after adjusting for age, gender, and race/ethnicity. This effort demonstrates the impact of having an HIE to rapidly identify a cohort, aggregate sociodemographic, behavioral, clinical and laboratory data across disparate healthcare providers electronic health record (HER) systems, and follow the cohort over time. These HIE capabilities enable clinical specialists and epidemiologists to conduct outcomes analyses during the current COVID-19 pandemic and beyond. Tobacco use appears to be an important risk factor for COVID-19 related death.
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spelling pubmed-81747162021-06-14 Leveraging a health information exchange for analyses of COVID-19 outcomes including an example application using smoking history and mortality Tortolero, Guillermo A. Brown, Michael R. Sharma, Shreela V. de Oliveira Otto, Marcia C. Yamal, Jose-Miguel Aguilar, David Gunther, Matt D. Mofleh, Dania I. Harris, Rachel D. John, Jemima C. de Vries, Paul S. Ramphul, Ryan Serbo, Dritana Marko Kiger, Jennifer Banerjee, Deborah Bonvino, Nick Merchant, Angela Clifford, Warren Mikhail, Jenny Xu, Hua Murphy, Robert E. Wei, Qiang Vahidy, Farhaan S. Morrison, Alanna C. Boerwinkle, Eric PLoS One Research Article Understanding sociodemographic, behavioral, clinical, and laboratory risk factors in patients diagnosed with COVID-19 is critically important, and requires building large and diverse COVID-19 cohorts with both retrospective information and prospective follow-up. A large Health Information Exchange (HIE) in Southeast Texas, which assembles and shares electronic health information among providers to facilitate patient care, was leveraged to identify COVID-19 patients, create a cohort, and identify risk factors for both favorable and unfavorable outcomes. The initial sample consists of 8,874 COVID-19 patients ascertained from the pandemic’s onset to June 12(th), 2020 and was created for the analyses shown here. We gathered demographic, lifestyle, laboratory, and clinical data from patient’s encounters across the healthcare system. Tobacco use history was examined as a potential risk factor for COVID-19 fatality along with age, gender, race/ethnicity, body mass index (BMI), and number of comorbidities. Of the 8,874 patients included in the cohort, 475 died from COVID-19. Of the 5,356 patients who had information on history of tobacco use, over 26% were current or former tobacco users. Multivariable logistic regression showed that the odds of COVID-19 fatality increased among those who were older (odds ratio = 1.07, 95% CI 1.06, 1.08), male (1.91, 95% CI 1.58, 2.31), and had a history of tobacco use (2.45, 95% CI 1.93, 3.11). History of tobacco use remained significantly associated (1.65, 95% CI 1.27, 2.13) with COVID-19 fatality after adjusting for age, gender, and race/ethnicity. This effort demonstrates the impact of having an HIE to rapidly identify a cohort, aggregate sociodemographic, behavioral, clinical and laboratory data across disparate healthcare providers electronic health record (HER) systems, and follow the cohort over time. These HIE capabilities enable clinical specialists and epidemiologists to conduct outcomes analyses during the current COVID-19 pandemic and beyond. Tobacco use appears to be an important risk factor for COVID-19 related death. Public Library of Science 2021-06-03 /pmc/articles/PMC8174716/ /pubmed/34081724 http://dx.doi.org/10.1371/journal.pone.0247235 Text en © 2021 Tortolero et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Tortolero, Guillermo A.
Brown, Michael R.
Sharma, Shreela V.
de Oliveira Otto, Marcia C.
Yamal, Jose-Miguel
Aguilar, David
Gunther, Matt D.
Mofleh, Dania I.
Harris, Rachel D.
John, Jemima C.
de Vries, Paul S.
Ramphul, Ryan
Serbo, Dritana Marko
Kiger, Jennifer
Banerjee, Deborah
Bonvino, Nick
Merchant, Angela
Clifford, Warren
Mikhail, Jenny
Xu, Hua
Murphy, Robert E.
Wei, Qiang
Vahidy, Farhaan S.
Morrison, Alanna C.
Boerwinkle, Eric
Leveraging a health information exchange for analyses of COVID-19 outcomes including an example application using smoking history and mortality
title Leveraging a health information exchange for analyses of COVID-19 outcomes including an example application using smoking history and mortality
title_full Leveraging a health information exchange for analyses of COVID-19 outcomes including an example application using smoking history and mortality
title_fullStr Leveraging a health information exchange for analyses of COVID-19 outcomes including an example application using smoking history and mortality
title_full_unstemmed Leveraging a health information exchange for analyses of COVID-19 outcomes including an example application using smoking history and mortality
title_short Leveraging a health information exchange for analyses of COVID-19 outcomes including an example application using smoking history and mortality
title_sort leveraging a health information exchange for analyses of covid-19 outcomes including an example application using smoking history and mortality
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8174716/
https://www.ncbi.nlm.nih.gov/pubmed/34081724
http://dx.doi.org/10.1371/journal.pone.0247235
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