Characterization of Post–COVID-19 Definitions and Clinical Coding Practices: Longitudinal Study

Post-COVID-19 condition (colloquially known as "long COVID-19") characterized as postacute sequelae of SARS-CoV-2 has no universal clinical case definition. Recent efforts have focused on understanding long COVID-19 symptoms, and electronic health record (EHR) data provide a unique resourc...

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Published inOnline journal of public health informatics Vol. 16; p. e53445
Main Authors Maripuri, Monika, Dey, Andrew, Honerlaw, Jacqueline, Hong, Chuan, Ho, Yuk-Lam, Tanukonda, Vidisha, Chen, Alicia W, Panickan, Vidul Ayakulangara, Wang, Xuan, Zhang, Harrison G, Yang, Doris, Samayamuthu, Malarkodi Jebathilagam, Morris, Michele, Visweswaran, Shyam, Beaulieu-Jones, Brendin, Ramoni, Rachel, Muralidhar, Sumitra, Gaziano, J Michael, Liao, Katherine, Xia, Zongqi, Brat, Gabriel A, Cai, Tianxi, Cho, Kelly
Format Journal Article
LanguageEnglish
Published Canada JMIR Publications 03.05.2024
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Online AccessGet full text
ISSN1947-2579
1947-2579
DOI10.2196/53445

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Abstract Post-COVID-19 condition (colloquially known as "long COVID-19") characterized as postacute sequelae of SARS-CoV-2 has no universal clinical case definition. Recent efforts have focused on understanding long COVID-19 symptoms, and electronic health record (EHR) data provide a unique resource for understanding this condition. The introduction of the International Classification of Diseases, Tenth Revision (ICD-10) code U09.9 for "Post COVID-19 condition, unspecified" to identify patients with long COVID-19 has provided a method of evaluating this condition in EHRs; however, the accuracy of this code is unclear. This study aimed to characterize the utility and accuracy of the U09.9 code across 3 health care systems-the Veterans Health Administration, the Beth Israel Deaconess Medical Center, and the University of Pittsburgh Medical Center-against patients identified with long COVID-19 via a chart review by operationalizing the World Health Organization (WHO) and Centers for Disease Control and Prevention (CDC) definitions. Patients who were COVID-19 positive with either a U07.1 ICD-10 code or positive polymerase chain reaction test within these health care systems were identified for chart review. Among this cohort, we sampled patients based on two approaches: (1) with a U09.9 code and (2) without a U09.9 code but with a new onset long COVID-19-related ICD-10 code, which allows us to assess the sensitivity of the U09.9 code. To operationalize the long COVID-19 definition based on health agency guidelines, symptoms were grouped into a "core" cluster of 11 commonly reported symptoms among patients with long COVID-19 and an extended cluster that captured all other symptoms by disease domain. Patients having ≥2 symptoms persisting for ≥60 days that were new onset after their COVID-19 infection, with ≥1 symptom in the core cluster, were labeled as having long COVID-19 per chart review. The code's performance was compared across 3 health care systems and across different time periods of the pandemic. Overall, 900 patient charts were reviewed across 3 health care systems. The prevalence of long COVID-19 among the cohort with the U09.9 ICD-10 code based on the operationalized WHO definition was between 23.2% and 62.4% across these health care systems. We also evaluated a less stringent version of the WHO definition and the CDC definition and observed an increase in the prevalence of long COVID-19 at all 3 health care systems. This is one of the first studies to evaluate the U09.9 code against a clinical case definition for long COVID-19, as well as the first to apply this definition to EHR data using a chart review approach on a nationwide cohort across multiple health care systems. This chart review approach can be implemented at other EHR systems to further evaluate the utility and performance of the U09.9 code.
AbstractList BackgroundPost–COVID-19 condition (colloquially known as “long COVID-19”) characterized as postacute sequelae of SARS-CoV-2 has no universal clinical case definition. Recent efforts have focused on understanding long COVID-19 symptoms, and electronic health record (EHR) data provide a unique resource for understanding this condition. The introduction of the International Classification of Diseases, Tenth Revision (ICD-10) code U09.9 for “Post COVID-19 condition, unspecified” to identify patients with long COVID-19 has provided a method of evaluating this condition in EHRs; however, the accuracy of this code is unclear. ObjectiveThis study aimed to characterize the utility and accuracy of the U09.9 code across 3 health care systems—the Veterans Health Administration, the Beth Israel Deaconess Medical Center, and the University of Pittsburgh Medical Center—against patients identified with long COVID-19 via a chart review by operationalizing the World Health Organization (WHO) and Centers for Disease Control and Prevention (CDC) definitions. MethodsPatients who were COVID-19 positive with either a U07.1 ICD-10 code or positive polymerase chain reaction test within these health care systems were identified for chart review. Among this cohort, we sampled patients based on two approaches: (1) with a U09.9 code and (2) without a U09.9 code but with a new onset long COVID-19–related ICD-10 code, which allows us to assess the sensitivity of the U09.9 code. To operationalize the long COVID-19 definition based on health agency guidelines, symptoms were grouped into a “core” cluster of 11 commonly reported symptoms among patients with long COVID-19 and an extended cluster that captured all other symptoms by disease domain. Patients having ≥2 symptoms persisting for ≥60 days that were new onset after their COVID-19 infection, with ≥1 symptom in the core cluster, were labeled as having long COVID-19 per chart review. The code’s performance was compared across 3 health care systems and across different time periods of the pandemic. ResultsOverall, 900 patient charts were reviewed across 3 health care systems. The prevalence of long COVID-19 among the cohort with the U09.9 ICD-10 code based on the operationalized WHO definition was between 23.2% and 62.4% across these health care systems. We also evaluated a less stringent version of the WHO definition and the CDC definition and observed an increase in the prevalence of long COVID-19 at all 3 health care systems. ConclusionsThis is one of the first studies to evaluate the U09.9 code against a clinical case definition for long COVID-19, as well as the first to apply this definition to EHR data using a chart review approach on a nationwide cohort across multiple health care systems. This chart review approach can be implemented at other EHR systems to further evaluate the utility and performance of the U09.9 code.
Post-COVID-19 condition (colloquially known as "long COVID-19") characterized as postacute sequelae of SARS-CoV-2 has no universal clinical case definition. Recent efforts have focused on understanding long COVID-19 symptoms, and electronic health record (EHR) data provide a unique resource for understanding this condition. The introduction of the International Classification of Diseases, Tenth Revision (ICD-10) code U09.9 for "Post COVID-19 condition, unspecified" to identify patients with long COVID-19 has provided a method of evaluating this condition in EHRs; however, the accuracy of this code is unclear. This study aimed to characterize the utility and accuracy of the U09.9 code across 3 health care systems-the Veterans Health Administration, the Beth Israel Deaconess Medical Center, and the University of Pittsburgh Medical Center-against patients identified with long COVID-19 via a chart review by operationalizing the World Health Organization (WHO) and Centers for Disease Control and Prevention (CDC) definitions. Patients who were COVID-19 positive with either a U07.1 ICD-10 code or positive polymerase chain reaction test within these health care systems were identified for chart review. Among this cohort, we sampled patients based on two approaches: (1) with a U09.9 code and (2) without a U09.9 code but with a new onset long COVID-19-related ICD-10 code, which allows us to assess the sensitivity of the U09.9 code. To operationalize the long COVID-19 definition based on health agency guidelines, symptoms were grouped into a "core" cluster of 11 commonly reported symptoms among patients with long COVID-19 and an extended cluster that captured all other symptoms by disease domain. Patients having ≥2 symptoms persisting for ≥60 days that were new onset after their COVID-19 infection, with ≥1 symptom in the core cluster, were labeled as having long COVID-19 per chart review. The code's performance was compared across 3 health care systems and across different time periods of the pandemic. Overall, 900 patient charts were reviewed across 3 health care systems. The prevalence of long COVID-19 among the cohort with the U09.9 ICD-10 code based on the operationalized WHO definition was between 23.2% and 62.4% across these health care systems. We also evaluated a less stringent version of the WHO definition and the CDC definition and observed an increase in the prevalence of long COVID-19 at all 3 health care systems. This is one of the first studies to evaluate the U09.9 code against a clinical case definition for long COVID-19, as well as the first to apply this definition to EHR data using a chart review approach on a nationwide cohort across multiple health care systems. This chart review approach can be implemented at other EHR systems to further evaluate the utility and performance of the U09.9 code.
Post-COVID-19 condition (colloquially known as "long COVID-19") characterized as postacute sequelae of SARS-CoV-2 has no universal clinical case definition. Recent efforts have focused on understanding long COVID-19 symptoms, and electronic health record (EHR) data provide a unique resource for understanding this condition. The introduction of the International Classification of Diseases, Tenth Revision (ICD-10) code U09.9 for "Post COVID-19 condition, unspecified" to identify patients with long COVID-19 has provided a method of evaluating this condition in EHRs; however, the accuracy of this code is unclear.BACKGROUNDPost-COVID-19 condition (colloquially known as "long COVID-19") characterized as postacute sequelae of SARS-CoV-2 has no universal clinical case definition. Recent efforts have focused on understanding long COVID-19 symptoms, and electronic health record (EHR) data provide a unique resource for understanding this condition. The introduction of the International Classification of Diseases, Tenth Revision (ICD-10) code U09.9 for "Post COVID-19 condition, unspecified" to identify patients with long COVID-19 has provided a method of evaluating this condition in EHRs; however, the accuracy of this code is unclear.This study aimed to characterize the utility and accuracy of the U09.9 code across 3 health care systems-the Veterans Health Administration, the Beth Israel Deaconess Medical Center, and the University of Pittsburgh Medical Center-against patients identified with long COVID-19 via a chart review by operationalizing the World Health Organization (WHO) and Centers for Disease Control and Prevention (CDC) definitions.OBJECTIVEThis study aimed to characterize the utility and accuracy of the U09.9 code across 3 health care systems-the Veterans Health Administration, the Beth Israel Deaconess Medical Center, and the University of Pittsburgh Medical Center-against patients identified with long COVID-19 via a chart review by operationalizing the World Health Organization (WHO) and Centers for Disease Control and Prevention (CDC) definitions.Patients who were COVID-19 positive with either a U07.1 ICD-10 code or positive polymerase chain reaction test within these health care systems were identified for chart review. Among this cohort, we sampled patients based on two approaches: (1) with a U09.9 code and (2) without a U09.9 code but with a new onset long COVID-19-related ICD-10 code, which allows us to assess the sensitivity of the U09.9 code. To operationalize the long COVID-19 definition based on health agency guidelines, symptoms were grouped into a "core" cluster of 11 commonly reported symptoms among patients with long COVID-19 and an extended cluster that captured all other symptoms by disease domain. Patients having ≥2 symptoms persisting for ≥60 days that were new onset after their COVID-19 infection, with ≥1 symptom in the core cluster, were labeled as having long COVID-19 per chart review. The code's performance was compared across 3 health care systems and across different time periods of the pandemic.METHODSPatients who were COVID-19 positive with either a U07.1 ICD-10 code or positive polymerase chain reaction test within these health care systems were identified for chart review. Among this cohort, we sampled patients based on two approaches: (1) with a U09.9 code and (2) without a U09.9 code but with a new onset long COVID-19-related ICD-10 code, which allows us to assess the sensitivity of the U09.9 code. To operationalize the long COVID-19 definition based on health agency guidelines, symptoms were grouped into a "core" cluster of 11 commonly reported symptoms among patients with long COVID-19 and an extended cluster that captured all other symptoms by disease domain. Patients having ≥2 symptoms persisting for ≥60 days that were new onset after their COVID-19 infection, with ≥1 symptom in the core cluster, were labeled as having long COVID-19 per chart review. The code's performance was compared across 3 health care systems and across different time periods of the pandemic.Overall, 900 patient charts were reviewed across 3 health care systems. The prevalence of long COVID-19 among the cohort with the U09.9 ICD-10 code based on the operationalized WHO definition was between 23.2% and 62.4% across these health care systems. We also evaluated a less stringent version of the WHO definition and the CDC definition and observed an increase in the prevalence of long COVID-19 at all 3 health care systems.RESULTSOverall, 900 patient charts were reviewed across 3 health care systems. The prevalence of long COVID-19 among the cohort with the U09.9 ICD-10 code based on the operationalized WHO definition was between 23.2% and 62.4% across these health care systems. We also evaluated a less stringent version of the WHO definition and the CDC definition and observed an increase in the prevalence of long COVID-19 at all 3 health care systems.This is one of the first studies to evaluate the U09.9 code against a clinical case definition for long COVID-19, as well as the first to apply this definition to EHR data using a chart review approach on a nationwide cohort across multiple health care systems. This chart review approach can be implemented at other EHR systems to further evaluate the utility and performance of the U09.9 code.CONCLUSIONSThis is one of the first studies to evaluate the U09.9 code against a clinical case definition for long COVID-19, as well as the first to apply this definition to EHR data using a chart review approach on a nationwide cohort across multiple health care systems. This chart review approach can be implemented at other EHR systems to further evaluate the utility and performance of the U09.9 code.
Author Ho, Yuk-Lam
Xia, Zongqi
Cho, Kelly
Wang, Xuan
Gaziano, J Michael
Yang, Doris
Dey, Andrew
Hong, Chuan
Ramoni, Rachel
Zhang, Harrison G
Visweswaran, Shyam
Muralidhar, Sumitra
Samayamuthu, Malarkodi Jebathilagam
Brat, Gabriel A
Cai, Tianxi
Maripuri, Monika
Beaulieu-Jones, Brendin
Liao, Katherine
Panickan, Vidul Ayakulangara
Chen, Alicia W
Honerlaw, Jacqueline
Tanukonda, Vidisha
Morris, Michele
AuthorAffiliation 9 Department of Surgery Beth Israel Deaconess Medical Center Boston, MA United States
5 Office of Research and Development US Department of Veterans Affairs Washington, DC United States
7 Division of Rheumatology, Inflammation, and Immunity Brigham and Women's Hospital Boston, MA United States
3 Department of Population Health Sciences University of Utah Salt Lake City, UT United States
4 Department of Biomedical Informatics University of Pittsburgh Pittsburgh, PA United States
1 Veterans Affairs Boston Healthcare System Boston, MA United States
8 Department of Neurology University of Pittsburgh Pittsburgh, PA United States
2 Department of Biomedical Informatics Harvard Medical School Boston, MA United States
6 Division of Aging, Department of Medicine Mass General Brigham Harvard Medical School Boston, MA United States
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BackLink https://www.ncbi.nlm.nih.gov/pubmed/38700929$$D View this record in MEDLINE/PubMed
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ContentType Journal Article
Copyright Monika Maripuri, Andrew Dey, Jacqueline Honerlaw, Chuan Hong, Yuk-Lam Ho, Vidisha Tanukonda, Alicia W Chen, Vidul Ayakulangara Panickan, Xuan Wang, Harrison G Zhang, Doris Yang, Malarkodi Jebathilagam Samayamuthu, Michele Morris, Shyam Visweswaran, Brendin Beaulieu-Jones, Rachel Ramoni, Sumitra Muralidhar, J Michael Gaziano, Katherine Liao, Zongqi Xia, Gabriel A Brat, Tianxi Cai, Kelly Cho. Originally published in the Online Journal of Public Health Informatics (https://ojphi.jmir.org/), 03.05.2024.
Monika Maripuri, Andrew Dey, Jacqueline Honerlaw, Chuan Hong, Yuk-Lam Ho, Vidisha Tanukonda, Alicia W Chen, Vidul Ayakulangara Panickan, Xuan Wang, Harrison G Zhang, Doris Yang, Malarkodi Jebathilagam Samayamuthu, Michele Morris, Shyam Visweswaran, Brendin Beaulieu-Jones, Rachel Ramoni, Sumitra Muralidhar, J Michael Gaziano, Katherine Liao, Zongqi Xia, Gabriel A Brat, Tianxi Cai, Kelly Cho. Originally published in the Online Journal of Public Health Informatics (https://ojphi.jmir.org/), 03.05.2024. 2024
Copyright_xml – notice: Monika Maripuri, Andrew Dey, Jacqueline Honerlaw, Chuan Hong, Yuk-Lam Ho, Vidisha Tanukonda, Alicia W Chen, Vidul Ayakulangara Panickan, Xuan Wang, Harrison G Zhang, Doris Yang, Malarkodi Jebathilagam Samayamuthu, Michele Morris, Shyam Visweswaran, Brendin Beaulieu-Jones, Rachel Ramoni, Sumitra Muralidhar, J Michael Gaziano, Katherine Liao, Zongqi Xia, Gabriel A Brat, Tianxi Cai, Kelly Cho. Originally published in the Online Journal of Public Health Informatics (https://ojphi.jmir.org/), 03.05.2024.
– notice: Monika Maripuri, Andrew Dey, Jacqueline Honerlaw, Chuan Hong, Yuk-Lam Ho, Vidisha Tanukonda, Alicia W Chen, Vidul Ayakulangara Panickan, Xuan Wang, Harrison G Zhang, Doris Yang, Malarkodi Jebathilagam Samayamuthu, Michele Morris, Shyam Visweswaran, Brendin Beaulieu-Jones, Rachel Ramoni, Sumitra Muralidhar, J Michael Gaziano, Katherine Liao, Zongqi Xia, Gabriel A Brat, Tianxi Cai, Kelly Cho. Originally published in the Online Journal of Public Health Informatics (https://ojphi.jmir.org/), 03.05.2024. 2024
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Keywords COVID-19
International Classification of Diseases
algorithm validation
postacute sequelae of SARS-CoV-2
veterans
PASC
U09.9 ICD-10 code
long COVID-19
electronic health records
chart review
Language English
License Monika Maripuri, Andrew Dey, Jacqueline Honerlaw, Chuan Hong, Yuk-Lam Ho, Vidisha Tanukonda, Alicia W Chen, Vidul Ayakulangara Panickan, Xuan Wang, Harrison G Zhang, Doris Yang, Malarkodi Jebathilagam Samayamuthu, Michele Morris, Shyam Visweswaran, Brendin Beaulieu-Jones, Rachel Ramoni, Sumitra Muralidhar, J Michael Gaziano, Katherine Liao, Zongqi Xia, Gabriel A Brat, Tianxi Cai, Kelly Cho. Originally published in the Online Journal of Public Health Informatics (https://ojphi.jmir.org/), 03.05.2024.
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 use, distribution, and reproduction in any medium, provided the original work, first published in the Online Journal of Public Health Informatics, is properly cited. The complete bibliographic information, a link to the original publication on https://ojphi.jmir.org/, as well as this copyright and license information must be included.
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Snippet Post-COVID-19 condition (colloquially known as "long COVID-19") characterized as postacute sequelae of SARS-CoV-2 has no universal clinical case definition....
BackgroundPost–COVID-19 condition (colloquially known as “long COVID-19”) characterized as postacute sequelae of SARS-CoV-2 has no universal clinical case...
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Title Characterization of Post–COVID-19 Definitions and Clinical Coding Practices: Longitudinal Study
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