Coding Long COVID: Characterizing a new disease through an ICD-10 lens https://www.medrxiv.org/content/10.1101/2022.04.18.22273968v1
Now published. Coding long COVID: characterizing a new disease through an ICD-10 lens 2023 Pfaff et al Abstract 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. Open access, https://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-023-02737-6
"Our diagnosis clusters suggest that long COVID is not a single phenotype, but rather a collection of sub-phenotypes that may benefit from different diagnostics and treatments. Each of these clusters contains conditions and symptoms reported in existing long COVID literature [34], clearly suggests that the definition of long COVID is more expansive than lingering respiratory symptoms [35], and illustrates that long COVID can manifest differently among patients in different age groups. Notably, among the conditions represented in our clusters, six have overlap with the eight conditions identified in another recent large-scale EHR analysis as high confidence for association with PASC, suggesting the particular importance of those conditions: anosmia/dysgeusia, chronic fatigue syndrome, chest pain, palpitations, shortness of breath, and type 2 diabetes [36]. "
"Also noteworthy is the fact that the neurological cluster appears more prominently in younger groups, especially patients 21–45 years of age. Of particular note is the appearance of myalgic encephalomyelitis (listed in Systematized Nomenclature of Medicine – Clinical Terms (SNOMED CT) as “chronic fatigue syndrome,” a non-preferred term)—a disease which parallels long COVID in many ways [37,38,39]—in the neurological cluster across all age groups, suggesting not only frequent co-occurrence with a U09.9 diagnosis, but also co-occurrence with other neurological symptoms. The cluster differences we see among age groups make a case for age stratification when studying U09.9, and long COVID in general. Regardless, given long COVID’s heterogeneity in presentation, course, and outcome, the clustering of symptoms may prove informative for future development of classification and diagnostic criteria"
Looks like dysautonomia is not being coded properly. They note neurological symptoms but most don't seem to be recorded. It's pretty much the easiest and most obvious one. Very long way to go still. Not sure if an error, misinterpretation of a change reflected elsewhere or something else, but: https://twitter.com/user/status/1626604410192158721
How is Long Covid being coded on Snowmed in the UK currently? Has it been placed under post viral conditions like ME or elsewhere? I heard the DWP were categorising it as mental health and wondered on what basis that was happening....?! (and how they were classing ME in the same scenarios)
