Abstract
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.
Original language | English |
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Article number | ooac066 |
Journal | JAMIA Open |
Volume | 5 |
Issue number | 3 |
DOIs | |
State | Published - Oct 1 2022 |
Bibliographical note
Publisher Copyright:© 2022 The Author(s).
Funding
The analyses described in publication were conducted with data accessed through the NCATS N3C Data Enclave and supported by NCATS U24 TR002306. This research was possible because of the patients whose information is included within the data from participating organizations. The N3C Consortium Collaborators are as follows: Christopher G. Chute, DrPH'Schools of Medicine, Public Health, and Nursing, Johns Hopkins University, Baltimore, MD; Melissa A. Haendel, PhD'Center for Health AI, University of Colorado Anschutz Medical Campus, Aurora, CO; and Anita Walden, MS'Center for Health AI, University of Colorado Anschutz Medical Campus, Aurora, CO; the authorship was determined using ICMJE recommendations.
Funders | Funder number |
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DrPH'Schools of Medicine, Public Health, and Nursing | |
National Center for Advancing Translational Sciences (NCATS) | U24 TR002306 |
The Johns Hopkins University |
Keywords
- COVID-19 ordinal scale
- Electronic Health Record
- N3C
- National COVID Cohort Collaborative
ASJC Scopus subject areas
- Health Informatics