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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.
  • Tortolero GA; School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, United States of America.
  • Brown MR; School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, United States of America.
  • Sharma SV; School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, United States of America.
  • de Oliveira Otto MC; School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, United States of America.
  • Yamal JM; School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, United States of America.
  • Aguilar D; School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, United States of America.
  • Gunther MD; School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, United States of America.
  • Mofleh DI; School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, United States of America.
  • Harris RD; School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, United States of America.
  • John JC; School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, United States of America.
  • de Vries PS; School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, United States of America.
  • Ramphul R; School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, United States of America.
  • Serbo DM; School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, United States of America.
  • Kiger J; Harris County Public Health, Houston Texas, United States of America.
  • Banerjee D; City of Houston Health Department, Houston, Texas, United States of America.
  • Bonvino N; Greater Houston Healthconnect, Houston, Texas, United States of America.
  • Merchant A; Greater Houston Healthconnect, Houston, Texas, United States of America.
  • Clifford W; Greater Houston Healthconnect, Houston, Texas, United States of America.
  • Mikhail J; Greater Houston Healthconnect, Houston, Texas, United States of America.
  • Xu H; School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX, United States of America.
  • Murphy RE; School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX, United States of America.
  • Wei Q; School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX, United States of America.
  • Vahidy FS; Center for Outcomes Research, Houston Methodist, Houston, Texas, United States of America.
  • Morrison AC; School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, United States of America.
  • Boerwinkle E; School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, United States of America.
PLoS One ; 16(6): e0247235, 2021.
Article in English | MEDLINE | ID: covidwho-1256018
ABSTRACT
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.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Health Information Exchange / COVID-19 Type of study: Cohort study / Observational study / Prognostic study / Randomized controlled trials Limits: Humans Country/Region as subject: North America Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2021 Document Type: Article Affiliation country: Journal.pone.0247235

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Health Information Exchange / COVID-19 Type of study: Cohort study / Observational study / Prognostic study / Randomized controlled trials Limits: Humans Country/Region as subject: North America Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2021 Document Type: Article Affiliation country: Journal.pone.0247235