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Coding long COVID: characterizing a new disease through an ICD-10 lens
BACKGROUND: Naming a newly discovered disease is a difficult process; in the context of the COVID-19 pandemic and the existence of post-acute sequelae of SARS-CoV-2 infection (PASC), which includes long COVID, it has proven especially challenging. Disease definitions and assignment of a diagnosis co...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9931566/ https://www.ncbi.nlm.nih.gov/pubmed/36793086 http://dx.doi.org/10.1186/s12916-023-02737-6 |
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author | Pfaff, Emily R. Madlock-Brown, Charisse Baratta, John M. Bhatia, Abhishek Davis, Hannah Girvin, Andrew Hill, Elaine Kelly, Elizabeth Kostka, Kristin Loomba, Johanna McMurry, Julie A. Wong, Rachel Bennett, Tellen D. Moffitt, Richard Chute, Christopher G. Haendel, Melissa |
author_facet | Pfaff, Emily R. Madlock-Brown, Charisse Baratta, John M. Bhatia, Abhishek Davis, Hannah Girvin, Andrew Hill, Elaine Kelly, Elizabeth Kostka, Kristin Loomba, Johanna McMurry, Julie A. Wong, Rachel Bennett, Tellen D. Moffitt, Richard Chute, Christopher G. Haendel, Melissa |
author_sort | Pfaff, Emily R. |
collection | PubMed |
description | BACKGROUND: Naming a newly discovered disease is a difficult process; in the context of the COVID-19 pandemic and the existence of post-acute sequelae of SARS-CoV-2 infection (PASC), which includes long COVID, it has proven especially challenging. Disease definitions and assignment of a diagnosis code are often asynchronous and iterative. The clinical definition and our understanding of the underlying mechanisms of long COVID are still in flux, and the deployment of an ICD-10-CM code for long COVID in the USA took nearly 2 years after patients had begun to describe their condition. Here, we leverage the largest publicly available HIPAA-limited dataset about patients with COVID-19 in the US to examine the heterogeneity of adoption and use of U09.9, the ICD-10-CM code for “Post COVID-19 condition, unspecified.” METHODS: We undertook a number of analyses to characterize the N3C population with a U09.9 diagnosis code (n = 33,782), including assessing person-level demographics and a number of area-level social determinants of health; diagnoses commonly co-occurring with U09.9, clustered using the Louvain algorithm; and quantifying medications and procedures recorded within 60 days of U09.9 diagnosis. We stratified all analyses by age group in order to discern differing patterns of care across the lifespan. RESULTS: We established the diagnoses most commonly co-occurring with U09.9 and algorithmically clustered them into four major categories: cardiopulmonary, neurological, gastrointestinal, and comorbid conditions. Importantly, we discovered that the population of patients diagnosed with U09.9 is demographically skewed toward female, White, non-Hispanic individuals, as well as individuals living in areas with low poverty and low unemployment. Our results also include a characterization of common procedures and medications associated with U09.9-coded patients. CONCLUSIONS: This work offers insight into potential subtypes and current practice patterns around long COVID and speaks to the existence of disparities in the diagnosis of patients with long COVID. This latter finding in particular requires further research and urgent remediation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12916-023-02737-6. |
format | Online Article Text |
id | pubmed-9931566 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-99315662023-02-16 Coding long COVID: characterizing a new disease through an ICD-10 lens Pfaff, Emily R. Madlock-Brown, Charisse Baratta, John M. Bhatia, Abhishek Davis, Hannah Girvin, Andrew Hill, Elaine Kelly, Elizabeth Kostka, Kristin Loomba, Johanna McMurry, Julie A. Wong, Rachel Bennett, Tellen D. Moffitt, Richard Chute, Christopher G. Haendel, Melissa BMC Med Research Article BACKGROUND: Naming a newly discovered disease is a difficult process; in the context of the COVID-19 pandemic and the existence of post-acute sequelae of SARS-CoV-2 infection (PASC), which includes long COVID, it has proven especially challenging. Disease definitions and assignment of a diagnosis code are often asynchronous and iterative. The clinical definition and our understanding of the underlying mechanisms of long COVID are still in flux, and the deployment of an ICD-10-CM code for long COVID in the USA took nearly 2 years after patients had begun to describe their condition. Here, we leverage the largest publicly available HIPAA-limited dataset about patients with COVID-19 in the US to examine the heterogeneity of adoption and use of U09.9, the ICD-10-CM code for “Post COVID-19 condition, unspecified.” METHODS: We undertook a number of analyses to characterize the N3C population with a U09.9 diagnosis code (n = 33,782), including assessing person-level demographics and a number of area-level social determinants of health; diagnoses commonly co-occurring with U09.9, clustered using the Louvain algorithm; and quantifying medications and procedures recorded within 60 days of U09.9 diagnosis. We stratified all analyses by age group in order to discern differing patterns of care across the lifespan. RESULTS: We established the diagnoses most commonly co-occurring with U09.9 and algorithmically clustered them into four major categories: cardiopulmonary, neurological, gastrointestinal, and comorbid conditions. Importantly, we discovered that the population of patients diagnosed with U09.9 is demographically skewed toward female, White, non-Hispanic individuals, as well as individuals living in areas with low poverty and low unemployment. Our results also include a characterization of common procedures and medications associated with U09.9-coded patients. CONCLUSIONS: This work offers insight into potential subtypes and current practice patterns around long COVID and speaks to the existence of disparities in the diagnosis of patients with long COVID. This latter finding in particular requires further research and urgent remediation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12916-023-02737-6. BioMed Central 2023-02-16 /pmc/articles/PMC9931566/ /pubmed/36793086 http://dx.doi.org/10.1186/s12916-023-02737-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Pfaff, Emily R. Madlock-Brown, Charisse Baratta, John M. Bhatia, Abhishek Davis, Hannah Girvin, Andrew Hill, Elaine Kelly, Elizabeth Kostka, Kristin Loomba, Johanna McMurry, Julie A. Wong, Rachel Bennett, Tellen D. Moffitt, Richard Chute, Christopher G. Haendel, Melissa Coding long COVID: characterizing a new disease through an ICD-10 lens |
title | Coding long COVID: characterizing a new disease through an ICD-10 lens |
title_full | Coding long COVID: characterizing a new disease through an ICD-10 lens |
title_fullStr | Coding long COVID: characterizing a new disease through an ICD-10 lens |
title_full_unstemmed | Coding long COVID: characterizing a new disease through an ICD-10 lens |
title_short | Coding long COVID: characterizing a new disease through an ICD-10 lens |
title_sort | coding long covid: characterizing a new disease through an icd-10 lens |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9931566/ https://www.ncbi.nlm.nih.gov/pubmed/36793086 http://dx.doi.org/10.1186/s12916-023-02737-6 |
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