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Characterization of test positivity among patients with coronavirus disease 2019 (COVID-19) in three electronic health records databases, February–November 2020

BACKGROUND: Monitoring COVID-19 testing volumes and test positivity is an integral part of the response to the pandemic. We described the characteristics of individuals who were tested and tested positive for SARS-CoV-2 during the pre-vaccine phase of the pandemic in the United States (U.S.). METHOD...

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Autores principales: Saunders-Hastings, Patrick, Zhou, Cindy Ke, Hobbi, Shayan, Wong, Hui-Lee, Lloyd, Patricia, Boyd, Eva, Alawar, Nader, Clarke, Tainya C., Beers, Jeff, Burrell, Timothy, Shoaibi, Azadeh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9206507/
https://www.ncbi.nlm.nih.gov/pubmed/35717174
http://dx.doi.org/10.1186/s12889-022-13635-6
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author Saunders-Hastings, Patrick
Zhou, Cindy Ke
Hobbi, Shayan
Wong, Hui-Lee
Lloyd, Patricia
Boyd, Eva
Alawar, Nader
Clarke, Tainya C.
Beers, Jeff
Burrell, Timothy
Shoaibi, Azadeh
author_facet Saunders-Hastings, Patrick
Zhou, Cindy Ke
Hobbi, Shayan
Wong, Hui-Lee
Lloyd, Patricia
Boyd, Eva
Alawar, Nader
Clarke, Tainya C.
Beers, Jeff
Burrell, Timothy
Shoaibi, Azadeh
author_sort Saunders-Hastings, Patrick
collection PubMed
description BACKGROUND: Monitoring COVID-19 testing volumes and test positivity is an integral part of the response to the pandemic. We described the characteristics of individuals who were tested and tested positive for SARS-CoV-2 during the pre-vaccine phase of the pandemic in the United States (U.S.). METHODS: This descriptive study analyzed three U.S. electronic health record (EHR) databases (Explorys, Academic Health System, and OneFlorida) between February and November 2020, identifying patients who received an interpretable nucleic acid amplification test (NAAT) result. Test-level data were used to characterize the settings in which tests were administered. Patient-level data were used to calculate test positivity rates and characterize the demographics, comorbidities, and hospitalization rates of COVID-19-positive patients. RESULTS: Over 40% of tests were conducted in outpatient care settings, with a median time between test order and result of 0–1 day for most settings. Patients tested were mostly female (55.6–57.7%), 18–44 years of age (33.9–41.2%), and Caucasian (44.0–66.7%). The overall test positivity rate was 13.0% in Explorys, 8.0% in Academic Health System, and 8.9% in OneFlorida. The proportion of patients hospitalized within 14 days of a positive COVID-19 NAAT result was 24.2–33.1% across databases, with patients over 75 years demonstrating the highest hospitalization rates (46.7–69.7% of positive tests). CONCLUSIONS: This analysis of COVID-19 testing volume and positivity patterns across three large EHR databases provides insight into the characteristics of COVID-19-tested, COVID-19-test-positive, and hospitalized COVID-19-test-positive patients during the early phase of the pandemic in the U.S. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-022-13635-6.
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spelling pubmed-92065072022-06-20 Characterization of test positivity among patients with coronavirus disease 2019 (COVID-19) in three electronic health records databases, February–November 2020 Saunders-Hastings, Patrick Zhou, Cindy Ke Hobbi, Shayan Wong, Hui-Lee Lloyd, Patricia Boyd, Eva Alawar, Nader Clarke, Tainya C. Beers, Jeff Burrell, Timothy Shoaibi, Azadeh BMC Public Health Research BACKGROUND: Monitoring COVID-19 testing volumes and test positivity is an integral part of the response to the pandemic. We described the characteristics of individuals who were tested and tested positive for SARS-CoV-2 during the pre-vaccine phase of the pandemic in the United States (U.S.). METHODS: This descriptive study analyzed three U.S. electronic health record (EHR) databases (Explorys, Academic Health System, and OneFlorida) between February and November 2020, identifying patients who received an interpretable nucleic acid amplification test (NAAT) result. Test-level data were used to characterize the settings in which tests were administered. Patient-level data were used to calculate test positivity rates and characterize the demographics, comorbidities, and hospitalization rates of COVID-19-positive patients. RESULTS: Over 40% of tests were conducted in outpatient care settings, with a median time between test order and result of 0–1 day for most settings. Patients tested were mostly female (55.6–57.7%), 18–44 years of age (33.9–41.2%), and Caucasian (44.0–66.7%). The overall test positivity rate was 13.0% in Explorys, 8.0% in Academic Health System, and 8.9% in OneFlorida. The proportion of patients hospitalized within 14 days of a positive COVID-19 NAAT result was 24.2–33.1% across databases, with patients over 75 years demonstrating the highest hospitalization rates (46.7–69.7% of positive tests). CONCLUSIONS: This analysis of COVID-19 testing volume and positivity patterns across three large EHR databases provides insight into the characteristics of COVID-19-tested, COVID-19-test-positive, and hospitalized COVID-19-test-positive patients during the early phase of the pandemic in the U.S. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-022-13635-6. BioMed Central 2022-06-18 /pmc/articles/PMC9206507/ /pubmed/35717174 http://dx.doi.org/10.1186/s12889-022-13635-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Saunders-Hastings, Patrick
Zhou, Cindy Ke
Hobbi, Shayan
Wong, Hui-Lee
Lloyd, Patricia
Boyd, Eva
Alawar, Nader
Clarke, Tainya C.
Beers, Jeff
Burrell, Timothy
Shoaibi, Azadeh
Characterization of test positivity among patients with coronavirus disease 2019 (COVID-19) in three electronic health records databases, February–November 2020
title Characterization of test positivity among patients with coronavirus disease 2019 (COVID-19) in three electronic health records databases, February–November 2020
title_full Characterization of test positivity among patients with coronavirus disease 2019 (COVID-19) in three electronic health records databases, February–November 2020
title_fullStr Characterization of test positivity among patients with coronavirus disease 2019 (COVID-19) in three electronic health records databases, February–November 2020
title_full_unstemmed Characterization of test positivity among patients with coronavirus disease 2019 (COVID-19) in three electronic health records databases, February–November 2020
title_short Characterization of test positivity among patients with coronavirus disease 2019 (COVID-19) in three electronic health records databases, February–November 2020
title_sort characterization of test positivity among patients with coronavirus disease 2019 (covid-19) in three electronic health records databases, february–november 2020
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9206507/
https://www.ncbi.nlm.nih.gov/pubmed/35717174
http://dx.doi.org/10.1186/s12889-022-13635-6
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