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An ordinal severity scale for COVID-19 retrospective studies using Electronic Health Record data
OBJECTIVES: Although the World Health Organization (WHO) Clinical Progression Scale for COVID-19 is useful in prospective clinical trials, it cannot be effectively used with retrospective Electronic Health Record (EHR) datasets. Modifying the existing WHO Clinical Progression Scale, we developed an...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9278199/ https://www.ncbi.nlm.nih.gov/pubmed/35911666 http://dx.doi.org/10.1093/jamiaopen/ooac066 |
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author | Khodaverdi, Maryam Price, Bradley S Porterfield, J Zachary Bunnell, H Timothy Vest, Michael T Anzalone, Alfred Jerrod Harper, Jeremy Kimble, Wes D Moradi, Hamidreza Hendricks, Brian Santangelo, Susan L Hodder, Sally L |
author_facet | Khodaverdi, Maryam Price, Bradley S Porterfield, J Zachary Bunnell, H Timothy Vest, Michael T Anzalone, Alfred Jerrod Harper, Jeremy Kimble, Wes D Moradi, Hamidreza Hendricks, Brian Santangelo, Susan L Hodder, Sally L |
author_sort | Khodaverdi, Maryam |
collection | PubMed |
description | OBJECTIVES: Although the World Health Organization (WHO) Clinical Progression Scale for COVID-19 is useful in prospective clinical trials, it cannot be effectively used with retrospective Electronic Health Record (EHR) datasets. Modifying the existing WHO Clinical Progression Scale, we developed an ordinal severity scale (OS) and assessed its usefulness in the analyses of COVID-19 patient outcomes using retrospective EHR data. MATERIALS AND METHODS: An OS was developed to assign COVID-19 disease severity using the Observational Medical Outcomes Partnership common data model within the National COVID Cohort Collaborative (N3C) data enclave. We then evaluated usefulness of the developed OS using heterogenous EHR data from January 2020 to October 2021 submitted to N3C by 63 healthcare organizations across the United States. Principal component analysis (PCA) was employed to characterize changes in disease severity among patients during the 28-day period following COVID-19 diagnosis. RESULTS: The data set used in this analysis consists of 2 880 456 patients. PCA of the day-to-day variation in OS levels over the totality of the 28-day period revealed contrasting patterns of variation in disease severity within the first and second 14 days and illustrated the importance of evaluation over the full 28-day period. DISCUSSION: An OS with well-defined, robust features, based on discrete EHR data elements, is useful for assessments of COVID-19 patient outcomes, providing insights on the progression of COVID-19 disease severity over time. CONCLUSIONS: The OS provides a framework that can facilitate better understanding of the course of acute COVID-19, informing clinical decision-making and resource allocation. |
format | Online Article Text |
id | pubmed-9278199 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-92781992022-07-18 An ordinal severity scale for COVID-19 retrospective studies using Electronic Health Record data Khodaverdi, Maryam Price, Bradley S Porterfield, J Zachary Bunnell, H Timothy Vest, Michael T Anzalone, Alfred Jerrod Harper, Jeremy Kimble, Wes D Moradi, Hamidreza Hendricks, Brian Santangelo, Susan L Hodder, Sally L JAMIA Open Research and Applications OBJECTIVES: Although the World Health Organization (WHO) Clinical Progression Scale for COVID-19 is useful in prospective clinical trials, it cannot be effectively used with retrospective Electronic Health Record (EHR) datasets. Modifying the existing WHO Clinical Progression Scale, we developed an ordinal severity scale (OS) and assessed its usefulness in the analyses of COVID-19 patient outcomes using retrospective EHR data. MATERIALS AND METHODS: An OS was developed to assign COVID-19 disease severity using the Observational Medical Outcomes Partnership common data model within the National COVID Cohort Collaborative (N3C) data enclave. We then evaluated usefulness of the developed OS using heterogenous EHR data from January 2020 to October 2021 submitted to N3C by 63 healthcare organizations across the United States. Principal component analysis (PCA) was employed to characterize changes in disease severity among patients during the 28-day period following COVID-19 diagnosis. RESULTS: The data set used in this analysis consists of 2 880 456 patients. PCA of the day-to-day variation in OS levels over the totality of the 28-day period revealed contrasting patterns of variation in disease severity within the first and second 14 days and illustrated the importance of evaluation over the full 28-day period. DISCUSSION: An OS with well-defined, robust features, based on discrete EHR data elements, is useful for assessments of COVID-19 patient outcomes, providing insights on the progression of COVID-19 disease severity over time. CONCLUSIONS: The OS provides a framework that can facilitate better understanding of the course of acute COVID-19, informing clinical decision-making and resource allocation. Oxford University Press 2022-07-09 /pmc/articles/PMC9278199/ /pubmed/35911666 http://dx.doi.org/10.1093/jamiaopen/ooac066 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of the American Medical Informatics Association. 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 reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research and Applications Khodaverdi, Maryam Price, Bradley S Porterfield, J Zachary Bunnell, H Timothy Vest, Michael T Anzalone, Alfred Jerrod Harper, Jeremy Kimble, Wes D Moradi, Hamidreza Hendricks, Brian Santangelo, Susan L Hodder, Sally L An ordinal severity scale for COVID-19 retrospective studies using Electronic Health Record data |
title | An ordinal severity scale for COVID-19 retrospective studies using Electronic Health Record data |
title_full | An ordinal severity scale for COVID-19 retrospective studies using Electronic Health Record data |
title_fullStr | An ordinal severity scale for COVID-19 retrospective studies using Electronic Health Record data |
title_full_unstemmed | An ordinal severity scale for COVID-19 retrospective studies using Electronic Health Record data |
title_short | An ordinal severity scale for COVID-19 retrospective studies using Electronic Health Record data |
title_sort | ordinal severity scale for covid-19 retrospective studies using electronic health record data |
topic | Research and Applications |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9278199/ https://www.ncbi.nlm.nih.gov/pubmed/35911666 http://dx.doi.org/10.1093/jamiaopen/ooac066 |
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