key: cord-0787281-9ph7hjye
authors: Bhatt, Ankeet S.; McElrath, Erin E.; Claggett, Brian L.; Bhatt, Deepak L.; Adler, Dale S.; Solomon, Scott D.; Vaduganathan, Muthiah
title: Accuracy of ICD-10 Diagnostic Codes to Identify COVID-19 Among Hospitalized Patients
date: 2021-06-07
journal: J Gen Intern Med
DOI: 10.1007/s11606-021-06936-w
sha: 697a586ad0a5190ef6b9aa06d4d96b9b2b55467f
doc_id: 787281
cord_uid: 9ph7hjye

nan

Health organizations require rapid, reliable access to data on patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). On April 1, 2020, the Centers for Disease Control and Prevention (CDC) introduced a new International Classification of Disease, 10 th revision (ICD-10) code U07.1 (COVID-19, virus identified), 1 together with specific coding guidance regarding its appropriate use. 2 Government agencies, including the Centers for Medicare and Medicaid Services, use ICD-10 data for ascertainment of COVID-19 hospitalizations, 3 though little is known about the reliability of the U07.1 code in identifying disease. We sought to determine the performance characteristics of the ICD-10 code U07.1 for identification of COVID-19 illness in a large multicenter health system.

We identified all inpatient encounters during which ≥1 SARS-CoV-2 reverse transcription polymerase chain reaction (RT-PCR) was performed from April 1 to July 31, 2020, across the Mass General Brigham health system. Patients with ≥1 positive SARS-CoV-2 RT-PCR were denoted to be COVID-19 positive. The agreement between COVID-19 positivity and primary or secondary ICD-10 coding of U07.1 was determined. Performance characteristics (sensitivity, specificity, positive predictive value [PPV] , negative predictive value [NPV] ) for the ICD-10 code U07.1 were reported overall and across major subgroups. Among COVID-19-positive patients, we performed multivariable logistic regression to identify independent predictors of corresponding ICD-10 coding for COVID-19(sensitivity). The Mass General Brigham Institutional Review Board approved the study protocol. Data management and analysis were performed using STATA (College Station, TX).

There were 22,633 patient encounters with a discharge date between April 1, 2020, and July 31, 2020, in which ≥1 SARS-CoV-2 RT-PCR was obtained during admission. Overall, 66.7%, 25.7%, and 7.7% of encounters had 1, 2, and >2 SARS-CoV-2 RT-PCR test(s) performed, respectively (range 1 to 16). Among these encounters, 2210 (9.8%) were determined to be COVID-19 positive. COVID-19 test-positive patients were older (64±18 vs. 60±19 years) and more likely to be men ( (Table 1) . Earlier months in the pandemic were the only significant independent predictors of higher sensitivity of the ICD-10 diagnostic code U07.1 among COVID-19 testpositive patients (Fig. 1 ).

Uniform administrative coding for research, disease tracking, and quality improvement is appealing given its widespread use and ease of interoperability across health systems. Reliance on these administrative data will likely remain important for prior COVID-19 disease identification, particularly given expanding interest in identifying legacy effects and postacute sequelae of SARS-CoV-2 (PASC) infection. However, ICD-10 codes in other clinical settings 4 and for COVID-19related symptoms 5 are known to be subject to misclassification.

We found sensitivity for U07.1 coding among hospitalized patients undergoing SARS-CoV-2 RT-PCR testing was modest, while specificity was high and approached 100% over time. Lack of initial awareness or familiarity with ICD-10 coding for COVID-19, in addition to distinctions between test positivity and clinical disease, may account for lower sensitivity. Lags in coding after hospital discharge and shifts in routine testing practices among hospitalized patients may also partially explain variable sensitivity. The robust specificity of ICD-10 U07.1 coding suggests that claims-based analyses may accurately capture patients with true COVID-19 disease. Epidemiological evaluations relying solely on U07.1 coding, however, may underestimate true disease burden. We acknowledge that SARS-CoV-2 RT-PCR is an imperfect "gold standard" and has itself had variable reported performance. 6 We did not have access to corroborating information from other microbiological assessments or clinical presentations. Until higher fidelity testing is available, these data from a large COVID-19 coronavirus disease 2019, CI confidence interval, ICU intensive care unit, ICD-10 International Classification of Disease, 10 th revision, PPV positive predictive value, NPV negative predictive value, SARS-CoV-2 RT-PCR severe acute respiratory syndrome coronavirus 2 reverse transcription polymerase chain reaction Figure 1 Independent predictors of ICD-10 sensitivity among encounters with ≥1 positive SARS-CoV-2 RT-PCR test. CI, confidence interval; ICD-10, International Classification of Disease, 10 th revision; ICU, intensive care unit; OR, odds ratio; SARS-CoV-2 RT-PCR, severe acute respiratory syndrome coronavirus 2 reverse transcription polymerase chain reaction.

Claggett has received consultancy fees from Boehringer Ingelheim

Society of Cardiovascular Patient Care, TobeSoft; Chair: American Heart Association Quality Oversight Committee; Data Monitoring Committees: Baim Institute for Clinical Research (formerly Harvard Clinical Research Institute, for the PORTICO trial

Level Ex, MJH Life Sciences, Population Health Research Institute (for the COMPASS operations committee, publications committee, steering committee, and USA national co-leader

VA CART Research and Publications Committee (Chair)

Svelte

Solomon has received research grants from Alnylam

Centers for Disease Control and Prevention. New ICD-10-CM code for the 2019 Novel Coronavirus (COVID-19)

Centers for Disease Control and Prevention. ICD-10-CM Official Coding and Reporting Guidelines

Preliminary Medicare COVID-19 Data Snapshot | CMS. Available at

Misclassification of Myocardial Injury as Myocardial Infarction: Implications for Assessing Outcomes in Value-Based Programs

Comparison of international classification of diseases and related health problems, tenth revision codes with electronic medical records among patients with symptoms of coronavirus disease

Interpreting Diagnostic Tests for SARS-CoV-2

and has consulted for Akros, Alnylam, Amgen, Arena, AstraZeneca, Bayer, BMS, Cardior, Cardurion, Corvia, Cytokinetics, Daiichi-Sankyo, Gilead, GSK, Ironwood, Merck, Myokardia, Novartis, Roche, Takeda, Theracos, Quantum Genetics, Cardurion, AoBiome, Janssen, Cardiac Dimensions, Tenaya, Sanofi-Pasteur, Dinaqor, Tremeau, CellProThera, Moderna. Dr. Vaduganathan has received research grant support or served on advisory boards for American Regent, Amgen, AstraZeneca, Bayer AG, Baxter Healthcare, Boehringer Ingelheim, Cytokinetics, Lexicon Pharmaceuticals, and Relypsa, speaker engagements with Novartis and Roche Diagnostics, and participates on clinical endpoint committees for studies sponsored by Galmed and Novartis. All other authors report no relevant disclosures to this work.