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Impact of changing case definitions for coronavirus disease 2019 (COVID-19) hospitalization on pandemic metrics

Published online by Cambridge University Press:  13 March 2023

Claire N. Shappell Open the ORCID record for Claire N. Shappell [Opens in a new window] ,
Michael Klompas Open the ORCID record for Michael Klompas [Opens in a new window] ,
Christina Chan Open the ORCID record for Christina Chan [Opens in a new window] ,
Tom Chen Open the ORCID record for Tom Chen [Opens in a new window]  and
Chanu Rhee Open the ORCID record for Chanu Rhee [Opens in a new window]
Claire N. Shappell*
Affiliation:
Department of Population Medicine, Harvard Medical School/Harvard Pilgrim Health Care Institute, Boston, Massachusetts Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
Michael Klompas
Affiliation:
Department of Population Medicine, Harvard Medical School/Harvard Pilgrim Health Care Institute, Boston, Massachusetts Division of Infectious Diseases, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
Christina Chan
Affiliation:
Department of Population Medicine, Harvard Medical School/Harvard Pilgrim Health Care Institute, Boston, Massachusetts
Tom Chen
Affiliation:
Department of Population Medicine, Harvard Medical School/Harvard Pilgrim Health Care Institute, Boston, Massachusetts
Chanu Rhee
Affiliation:
Department of Population Medicine, Harvard Medical School/Harvard Pilgrim Health Care Institute, Boston, Massachusetts Division of Infectious Diseases, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
*
Author for correspondence: Claire N. Shappell, E-mail: [email protected]
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Abstract

Objective:

To examine the impact of commonly used case definitions for coronavirus disease 2019 (COVID-19) hospitalizations on case counts and outcomes.

Design, patients, and setting:

Retrospective analysis of all adults hospitalized between March 1, 2020, and March 1, 2022, at 5 Massachusetts acute-care hospitals.

Interventions:

We applied 6 commonly used definitions of COVID-19 hospitalization: positive severe acute respiratory coronavirus virus 2 (SARS-CoV-2) polymerase chain reaction (PCR) assay within 14 days of admission, PCR plus dexamethasone administration, PCR plus remdesivir, PCR plus hypoxemia, institutional COVID-19 flag, or COVID-19 International Classification of Disease, Tenth Revision (ICD-10) codes. Outcomes included case counts and in-hospital mortality. Overall, 100 PCR-positive cases were reviewed to determine each definition’s accuracy for distinguishing primary or contributing versus incidental COVID-19 hospitalizations.

Results:

Of 306,387 hospital encounters, 15,436 (5.0%) met the PCR-based definition. COVID-19 hospitalization counts varied substantially between definitions: 4,628 (1.5% of all encounters) for PCR plus dexamethasone, 5,757 (1.9%) for PCR plus remdesivir, 11,801 (3.9%) for PCR plus hypoxemia, 15,673 (5.1%) for institutional flags, and 15,868 (5.2%) for ICD-10 codes. Definitions requiring dexamethasone, hypoxemia, or remdesivir selected sicker patients compared to PCR alone (mortality rates 12.2%, 10.7%, and 8.8% vs 8.3%, respectively). Definitions requiring PCR plus remdesivir or dexamethasone did not detect a reduction in in-hospital mortality associated with the SARS-CoV-2 Omicron variant. ICD-10 codes had the highest sensitivity (98.4%) but low specificity (39.5%) for distinguishing primary or contributing versus incidental COVID-19 hospitalizations. PCR plus dexamethasone had the highest specificity (92.1%) but low sensitivity (35.5%).

Conclusions:

Commonly used definitions for COVID-19 hospitalizations generate variable case counts and outcomes and differentiate poorly between primary or contributing versus incidental COVID-19 hospitalizations. Surveillance definitions that better capture and delineate COVID-19–associated hospitalizations are needed.

Type
Original Article
Information
Infection Control & Hospital Epidemiology , Volume 44 , Issue 9 , September 2023 , pp. 1458 - 1466
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Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of The Society for Healthcare Epidemiology of America

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