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Using EHR data to identify coronavirus infections in hospitalized patients: Impact of case definitions on disease surveillance

PURPOSE: To evaluate the number, characteristics, and outcomes of patients identified hospitalized with coronavirus disease 2019 (COVID-19) using two different case definitions. PROCEDURES: Electronic Health Record data were evaluated from patients hospitalized with COVID-19 through May 2020 at 52 h...

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Autores principales: Navar, Ann Marie, Cosmatos, Irene, Purinton, Stacey, Ramsey, Janet L., Taylor, Robert J., Sobel, Rachel E., Barlow, Ginger, Dieck, Gretchen S., Bulgrein, Michael L., Peterson, Eric D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Authors. Published by Elsevier B.V. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9359535/
https://www.ncbi.nlm.nih.gov/pubmed/35988510
http://dx.doi.org/10.1016/j.ijmedinf.2022.104842
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author Navar, Ann Marie
Cosmatos, Irene
Purinton, Stacey
Ramsey, Janet L.
Taylor, Robert J.
Sobel, Rachel E.
Barlow, Ginger
Dieck, Gretchen S.
Bulgrein, Michael L.
Peterson, Eric D.
author_facet Navar, Ann Marie
Cosmatos, Irene
Purinton, Stacey
Ramsey, Janet L.
Taylor, Robert J.
Sobel, Rachel E.
Barlow, Ginger
Dieck, Gretchen S.
Bulgrein, Michael L.
Peterson, Eric D.
author_sort Navar, Ann Marie
collection PubMed
description PURPOSE: To evaluate the number, characteristics, and outcomes of patients identified hospitalized with coronavirus disease 2019 (COVID-19) using two different case definitions. PROCEDURES: Electronic Health Record data were evaluated from patients hospitalized with COVID-19 through May 2020 at 52 health systems across the United States. Characteristics of inpatients with positive laboratory tests for SARS-CoV-2 were compared with those with clinical diagnosis of COVID-19 but without a confirmatory lab result. FINDINGS: Of 14,371 inpatients with COVID-19, 6623 (46.1 %) had a positive laboratory result, and n = 7748 (52.9 %) had only a clinical diagnosis of COVID-19. Compared with clinically diagnosed cases, those with laboratory-confirmed COVID were similar in age and sex, but differed by race, ethnicity, and insurance status. Laboratory-confirmed cases were more likely to receive certain COVID-19 therapies including hydroxychloroquine, anti-IL6 agents and antivirals (p < 0.001). Those with laboratory–confirmed COVID-19 had lower rates of most complications such as myocardial infarction, but higher overall mortality (p < 0.001). CONCLUSION: We observed a two–fold difference in the number of patients hospitalized with COVID-19 depending on whether the case definition required laboratory confirmation. Variations in case definitions also led to differences in cohort characteristics, treatments, and outcomes.
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spelling pubmed-93595352022-08-09 Using EHR data to identify coronavirus infections in hospitalized patients: Impact of case definitions on disease surveillance Navar, Ann Marie Cosmatos, Irene Purinton, Stacey Ramsey, Janet L. Taylor, Robert J. Sobel, Rachel E. Barlow, Ginger Dieck, Gretchen S. Bulgrein, Michael L. Peterson, Eric D. Int J Med Inform Article PURPOSE: To evaluate the number, characteristics, and outcomes of patients identified hospitalized with coronavirus disease 2019 (COVID-19) using two different case definitions. PROCEDURES: Electronic Health Record data were evaluated from patients hospitalized with COVID-19 through May 2020 at 52 health systems across the United States. Characteristics of inpatients with positive laboratory tests for SARS-CoV-2 were compared with those with clinical diagnosis of COVID-19 but without a confirmatory lab result. FINDINGS: Of 14,371 inpatients with COVID-19, 6623 (46.1 %) had a positive laboratory result, and n = 7748 (52.9 %) had only a clinical diagnosis of COVID-19. Compared with clinically diagnosed cases, those with laboratory-confirmed COVID were similar in age and sex, but differed by race, ethnicity, and insurance status. Laboratory-confirmed cases were more likely to receive certain COVID-19 therapies including hydroxychloroquine, anti-IL6 agents and antivirals (p < 0.001). Those with laboratory–confirmed COVID-19 had lower rates of most complications such as myocardial infarction, but higher overall mortality (p < 0.001). CONCLUSION: We observed a two–fold difference in the number of patients hospitalized with COVID-19 depending on whether the case definition required laboratory confirmation. Variations in case definitions also led to differences in cohort characteristics, treatments, and outcomes. The Authors. Published by Elsevier B.V. 2022-10 2022-08-08 /pmc/articles/PMC9359535/ /pubmed/35988510 http://dx.doi.org/10.1016/j.ijmedinf.2022.104842 Text en © 2022 The Authors Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Navar, Ann Marie
Cosmatos, Irene
Purinton, Stacey
Ramsey, Janet L.
Taylor, Robert J.
Sobel, Rachel E.
Barlow, Ginger
Dieck, Gretchen S.
Bulgrein, Michael L.
Peterson, Eric D.
Using EHR data to identify coronavirus infections in hospitalized patients: Impact of case definitions on disease surveillance
title Using EHR data to identify coronavirus infections in hospitalized patients: Impact of case definitions on disease surveillance
title_full Using EHR data to identify coronavirus infections in hospitalized patients: Impact of case definitions on disease surveillance
title_fullStr Using EHR data to identify coronavirus infections in hospitalized patients: Impact of case definitions on disease surveillance
title_full_unstemmed Using EHR data to identify coronavirus infections in hospitalized patients: Impact of case definitions on disease surveillance
title_short Using EHR data to identify coronavirus infections in hospitalized patients: Impact of case definitions on disease surveillance
title_sort using ehr data to identify coronavirus infections in hospitalized patients: impact of case definitions on disease surveillance
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9359535/
https://www.ncbi.nlm.nih.gov/pubmed/35988510
http://dx.doi.org/10.1016/j.ijmedinf.2022.104842
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