Coding Long COVID: Characterizing a new disease through an ICD-10 lens [preprint]
Authors
Pfaff, Emily RMadlock-Brown, Charisse
Baratta, John M
Bhatia, Abhishek
Davis, Hannah
Girvin, Andrew
Hill, Elaine
Kelly, Liz
Kostka, Kristin
Loomba, Johanna
McMurry, Julie A
Wong, Rachel
Bennett, Tellen D
Moffitt, Richard
Chute, Christopher G
Haendel, Melissa
UMass Chan Affiliations
Center for Clinical and Translational ScienceDocument Type
PreprintPublication Date
2022-09-02
Metadata
Show full item recordAbstract
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 US took nearly two 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 = 21,072), 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, high education, and high access to medical care. 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.Source
Pfaff ER, Madlock-Brown C, Baratta JM, Bhatia A, Davis H, Girvin A, Hill E, Kelly L, Kostka K, Loomba J, McMurry JA, Wong R, Bennett TD, Moffitt R, Chute CG, Haendel M; N3C Consortium; RECOVER Consortium. Coding Long COVID: Characterizing a new disease through an ICD-10 lens. medRxiv [Preprint]. 2022 Sep 2:2022.04.18.22273968. doi: 10.1101/2022.04.18.22273968. Update in: BMC Med. 2023 Feb 16;21(1):58. PMID: 36093345; PMCID: PMC9460974.DOI
10.1101/2022.04.18.22273968Permanent Link to this Item
http://hdl.handle.net/20.500.14038/52088PubMed ID
36093345Notes
This article is a preprint. Preprints are preliminary reports of work that have not been certified by peer review.Funding and Acknowledgements
The UMass Center for Clinical and Translational Science (UMCCTS), UL1TR001453, provided data for this study.Related Resources
Now published in BMC Medicine doi: 10.1186/s12916-023-02737-6.Rights
The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.Distribution License
http://creativecommons.org/licenses/by-nc-nd/4.0/ae974a485f413a2113503eed53cd6c53
10.1101/2022.04.18.22273968
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Except where otherwise noted, this item's license is described as The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.