TY - JOUR
T1 - Leveraging a health information exchange for analyses of COVID-19 outcomes including an example application using smoking history and mortality
AU - Tortolero, Guillermo A.
AU - Brown, Michael R.
AU - Sharma, Shreela V.
AU - de Oliveira Otto, Marcia C.
AU - Yamal, Jose Miguel
AU - Aguilar, David
AU - Gunther, Matt D.
AU - Mofleh, Dania I.
AU - Harris, Rachel D.
AU - John, Jemima C.
AU - de Vries, Paul S.
AU - Ramphul, Ryan
AU - Serbo, Dritana Marko
AU - Kiger, Jennifer
AU - Banerjee, Deborah
AU - Bonvino, Nick
AU - Merchant, Angela
AU - Clifford, Warren
AU - Mikhail, Jenny
AU - Xu, Hua
AU - Murphy, Robert E.
AU - Wei, Qiang
AU - Vahidy, Farhaan S.
AU - Morrison, Alanna C.
AU - Boerwinkle, Eric
N1 - Publisher Copyright:
Copyright: © 2021 Tortolero et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2021/6
Y1 - 2021/6
N2 - 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 12th, 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.
AB - 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 12th, 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.
KW - Age Factors
KW - COVID-19/mortality
KW - Cohort Studies
KW - Comorbidity
KW - Ethnic Groups
KW - Health Information Exchange/statistics & numerical data
KW - Healthcare Disparities
KW - Hospitalization
KW - Humans
KW - Pandemics
KW - Prospective Studies
KW - Retrospective Studies
KW - Risk Factors
KW - SARS-CoV-2/metabolism
KW - Sex Factors
KW - Smoking
KW - Texas
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U2 - 10.1371/journal.pone.0247235
DO - 10.1371/journal.pone.0247235
M3 - Article
C2 - 34081724
AN - SCOPUS:85107379870
SN - 1932-6203
VL - 16
SP - e0247235
JO - PLoS ONE
JF - PLoS ONE
IS - 6 June
M1 - e0247235
ER -