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Do International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) codes accurately capture presenting symptoms of fever, cough, and dyspnea among patients being tested for coronavirus disease 2019 (COVID-19)?
In this cohort study, an electronic medical record review of 2201 patients tested for COVID-19 between March 10 and April 6, 2020, found that ICD-10 codes had poor sensitivity and negative predictive value for capturing fever, cough, and dyspnea.
These findings suggest that symptom-specific ICD-10 codes do not accurately capture COVID-19–related symptoms and should not be used to populate symptoms in electronic medical record–based cohorts.
International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) codes are used to characterize coronavirus disease 2019 (COVID-19)–related symptoms. Their accuracy is unknown, which could affect downstream analyses.
To compare the performance of fever-, cough-, and dyspnea-specific ICD-10 codes with medical record review among patients tested for COVID-19.
Design, Setting, and Participants
This cohort study included patients who underwent quantitative reverse transcriptase–polymerase chain reaction testing for severe acute respiratory syndrome coronavirus 2 at University of Utah Health from March 10 to April 6, 2020. Data analysis was performed in April 2020.
Main Outcomes and Measures
The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of ICD-10 codes for fever (R50*), cough (R05*), and dyspnea (R06.0*) were compared with manual medical record review. Performance was calculated overall and stratified by COVID-19 test result, sex, age group (<50, 50-64, and >64 years), and inpatient status. Bootstrapping was used to generate 95% CIs, and Pearson χ2 tests were used to compare different subgroups.
Among 2201 patients tested for COVD-19, the mean (SD) age was 42 (17) years; 1201 (55%) were female, 1569 (71%) were White, and 282 (13%) were Hispanic or Latino. The prevalence of fever was 66% (1444 patients), that of cough was 88% (1930 patients), and that of dyspnea was 64% (1399 patients). For fever, the sensitivity of ICD-10 codes was 0.26 (95% CI, 0.24-0.29), specificity was 0.98 (95% CI, 0.96-0.99), PPV was 0.96 (95% CI, 0.93-0.97), and NPV was 0.41 (95% CI, 0.39-0.43). For cough, the sensitivity of ICD-10 codes was 0.44 (95% CI, 0.42-0.46), specificity was 0.88 (95% CI, 0.84-0.92), PPV was 0.96 (95% CI, 0.95-0.97), and NPV was 0.18 (95% CI, 0.16-0.20). For dyspnea, the sensitivity of ICD-10 codes was 0.24 (95% CI, 0.22-0.26), specificity was 0.97 (95% CI, 0.96-0.98), PPV was 0.93 (95% CI, 0.90-0.96), and NPV was 0.42 (95% CI, 0.40-0.44). ICD-10 code performance was better for inpatients than for outpatients for fever (χ2 = 41.30; P < .001) and dyspnea (χ2 = 14.25; P = .003) but not for cough (χ2 = 5.13; P = .16).
Conclusions and Relevance
These findings suggest that ICD-10 codes lack sensitivity and have poor NPV for symptoms associated with COVID-19. This inaccuracy has implications for any downstream data model, scientific discovery, or surveillance that relies on these codes.
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Accepted for Publication: July 11, 2020.
Published: August 14, 2020. doi:10.1001/jamanetworkopen.2020.17703
Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2020 Crabb BT et al. JAMA Network Open.
Corresponding Author: Rashmee U. Shah, MD, MS, Division of Cardiovascular Medicine, University of Utah School of Medicine, 30 N 1900 E, Room 4A100, Salt Lake City, UT 84132 (firstname.lastname@example.org).
Author Contributions: Mr Crabb and Dr Shah 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: Crabb, West, Brown, Shah.
Acquisition, analysis, or interpretation of data: All authors.
Drafting of the manuscript: Crabb, Martin, West, Brown, Leung, Shah.
Critical revision of the manuscript for important intellectual content: Crabb, Lyons, Bale, Martin, Berger, Mann, West, Peacock, Leung, Shah.
Statistical analysis: Crabb, Martin, Brown, Shah.
Administrative, technical, or material support: Berger, West, Peacock.
Supervision: Crabb, Mann, Leung, Shah.
Conflict of Interest Disclosures: Dr Shah reported receiving honoraria from the American College of Cardiology outside the submitted work. No other disclosures were reported.
Funding/Support: Dr Leung is supported by grant R01AI135114 from the National Institute of Allergy and Infectious Diseases. Dr Shah is supported by grant K08HL136850 from the National Heart Lung and Blood Institute and a donation from Women As One. REDCap, used in this study, is supported by the University of Utah Center for Clinical and Translational Science, with funding in part from the National Center for Research Resources and the National Center for Advancing Translational Sciences (grant 8UL1TR000105, formerly UL1RR025764).
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.
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