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Purpose <p>We aimed to test associations of participant-reported Long COVID symptom interference with life activities with Long COVID symptoms, presence of U09.9 Long COVID diagnosis code, demographics, and clinical factors. In a subgroup, we documented coding related to Long COVID and post-exertional malaise in the electronic medical record (EMR).</p> Methods <p>Using a cross-sectional analysis (<i>n</i> = 205) of participant data from a Long COVID survey, we tested associations with Chi-square, Fisher’s exact, or Fisher-Freeman-Halton exact statistical tests and Independent Samples T-tests.</p> Results <p>Participants were predominately female (67%) with a mean age of 50.9 years. Participants were White (50.0%), African American (47.5%), and Asian (2.5%); 1.5% reported Hispanic ethnicity. 41% of participants reported high Long COVID symptom interference with life activities. Participants who were older (<i>p</i>=.028), were female (<i>p</i>=.002), were obese (<i>p</i>=.049), had worse general health (<i>p</i>&lt;.001), worse physical health (<i>p</i>&lt;.001), had worse mental health (<i>p</i>&lt;.001), and had U09.9 diagnosis (<i>p</i>&lt;.001) were more likely to experience high symptom interference. Among participants with high symptom interference, there were no significant associations with U09.9 diagnosis code. EMR sub-analysis (<i>n</i> = 100) revealed that among participants that reported high symptom interference (<i>n</i> = 39), 64% (<i>n</i> = 25) had a code related to Long COVID.</p> Conclusion <p>Although we found discrepancies between self-reported measures and EMR coding, we did not find evidence of demographic biases in diagnosis among participants with high symptom interference.</p> Clinical trial number <p>Not applicable.</p>

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Differences in diagnostic coding in long COVID: sociodemographic and symptom interference factors

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月7日

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  • Jasmine K. Vickers,
  • Emily B. Levitan,
  • Carrie R. Howell,
  • Aoyjai P. Montgomery,
  • Raymond Jones,
  • Frances E. Lund,
  • Nathan Erdmann

摘要

Purpose

We aimed to test associations of participant-reported Long COVID symptom interference with life activities with Long COVID symptoms, presence of U09.9 Long COVID diagnosis code, demographics, and clinical factors. In a subgroup, we documented coding related to Long COVID and post-exertional malaise in the electronic medical record (EMR).

Methods

Using a cross-sectional analysis (n = 205) of participant data from a Long COVID survey, we tested associations with Chi-square, Fisher’s exact, or Fisher-Freeman-Halton exact statistical tests and Independent Samples T-tests.

Results

Participants were predominately female (67%) with a mean age of 50.9 years. Participants were White (50.0%), African American (47.5%), and Asian (2.5%); 1.5% reported Hispanic ethnicity. 41% of participants reported high Long COVID symptom interference with life activities. Participants who were older (p=.028), were female (p=.002), were obese (p=.049), had worse general health (p<.001), worse physical health (p<.001), had worse mental health (p<.001), and had U09.9 diagnosis (p<.001) were more likely to experience high symptom interference. Among participants with high symptom interference, there were no significant associations with U09.9 diagnosis code. EMR sub-analysis (n = 100) revealed that among participants that reported high symptom interference (n = 39), 64% (n = 25) had a code related to Long COVID.

Conclusion

Although we found discrepancies between self-reported measures and EMR coding, we did not find evidence of demographic biases in diagnosis among participants with high symptom interference.

Clinical trial number

Not applicable.