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Infectious Diseases

Use of and Comorbidities Associated With Diagnostic Codes for COVID-19 in US Health Insurance Claims

Educational Objective
To identify the key insights or developments described in this article

1 Credit CME

JAMA Network Open

Published Online: September 8, 2021

Research Letter

Article Information and Disclosures

Kai-Cheng Yang, MS¹;

Byungkyu Lee, PhD²;

Yong-Yeol Ahn, PhD¹;

Brea L. Perry, PhD²

Author Affiliations

¹Luddy School of Informatics, Computing, and Engineering, Indiana University-Bloomington, Bloomington
²Department of Sociology, Indiana University-Bloomington, Bloomington

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Accurate identification of COVID-19 diagnosis in patient medical records is essential for studies using administrative data to examine morbidity, mortality, and risk factors associated with COVID-19.¹ Before April 1, 2020, the Centers for Disease Control and Prevention suggested using the existing International Statistical Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) code B97.29 (other coronavirus as the cause of diseases classified elsewhere) as the primary diagnostic code for patients infected with COVID-19.² On April 1, 2020, a new code U07.1 (2019-nCoV acute respiratory disease) was added to ICD-10-CM³ and was rapidly adopted by hospitals.⁴ Our study examined how nonhospital and hospital health care professionals have used these diagnostic codes in practice using a national medical claims data set in the US. We analyzed the comorbidities associated with COVID-19 diagnosis to assess the specificity of the legacy code and the importance of using both codes.

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Article Information

Accepted for Publication: July 8, 2021.

Published: September 8, 2021. doi:10.1001/jamanetworkopen.2021.24643

Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2021 Yang KC et al. JAMA Network Open.

Corresponding Author: Brea L. Perry, PhD, Department of Sociology, Indiana University-Bloomington, 1020 E Kirkwood Ave, 767 Ballantine Hall, Bloomington, IN 47405 (blperry@indiana.edu).

Author Contributions: Mr Yang and Dr Perry had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Yang, Lee, Ahn.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Yang.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Yang.

Obtained funding: Ahn, Perry.

Administrative, technical, or material support: Yang, Ahn, Perry.

Supervision: Ahn, Perry.

Conflict of Interest Disclosures: None reported.

Funding/Support: This research was funded by grant R01 DA039928 from the National Institute on Drug Abuse (Dr Perry).

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: The findings and conclusions in this study are those of the authors and do not necessarily represent the official position of the National Institute on Drug Abuse.

Additional Contributions: We thank Kosali Simon, PhD, and the College of Arts and Sciences at Indiana University-Bloomington for their support. They did not receive financial compensation for their contribution.

References

Schwab P , Mehrjou A , Parbhoo S , et al. Real-time prediction of COVID-19 related mortality using electronic health records. Nat Commun. 2021;12(1):1058. doi:10.1038/s41467-020-20816-7 PubMed Google Scholar Crossref

Centers for Disease Control and Prevention. ICD-10-CM official coding guidelines—supplement coding encounters related to COVID-19 coronavirus outbreak. February 20, 2020. Accessed October 9, 2020. https://www.cdc.gov/nchs/data/icd/ICD-10-CM-Official-Coding-Gudance-Interim-Advice-coronavirus-feb-20-2020.pdf

Centers for Disease Control and Prevention. ICD-10-CM official coding and reporting guidelines: April 1, 2020 through September 30, 2020. Accessed October 9, 2020. https://www.cdc.gov/nchs/data/icd/COVID-19-guidelines-final.pdf

Kadri SS , Gundrum J , Warner S , et al. Uptake and accuracy of the diagnosis code for COVID-19 among US hospitalizations. JAMA. 2020;324(24):2553-2554. doi:10.1001/jama.2020.20323 PubMed Google Scholar Crossref

Wallace PJ , Shah ND , Dennen T , Bleicher PA , Crown WH . Optum Labs: building a novel node in the learning health care system. Health Aff (Millwood). 2014;33(7):1187-1194. doi:10.1377/hlthaff.2014.0038 PubMed Google Scholar Crossref

Ogrinc G , Davies L , Goodman D , Batalden P , Davidoff F , Stevens D . SQUIRE 2.0 (Standards for Quality Improvement Reporting Excellence): revised publication guidelines from a detailed consensus process. BMJ Qual Saf. 2016;25(12):986-992. doi:10.1136/bmjqs-2015-004411 PubMed Google Scholar Crossref

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Credit Designation Statement: The American Medical Association designates this Journal-based CME activity activity for a maximum of 1.00  AMA PRA Category 1 Credit(s)™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

Successful completion of this CME activity, which includes participation in the evaluation component, enables the participant to earn up to:

1.00 Medical Knowledge MOC points in the American Board of Internal Medicine's (ABIM) Maintenance of Certification (MOC) program;;
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1.00 Lifelong Learning points in the American Board of Pathology’s (ABPath) Continuing Certification program; and
1.00 credit toward the CME [and Self-Assessment requirements] of the American Board of Surgery’s Continuous Certification program

It is the CME activity provider's responsibility to submit participant completion information to ACCME for the purpose of granting MOC credit.