Concordance between ICD-10-AM clinical coding and SARS-CoV-2 PCR testing for COVID-19 in Australian hospitals

Background: The introduction by the World Health Organization of specific International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10) clinical codes for coronavirus disease 2019 (COVID-19) in early 2020 was key to standardising disease reporting and supporting global public health efforts. However, the concordance between these clinical codes and laboratory-confirmed COVID-19 cases based on Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) polymerase chain reaction (PCR) results remains largely unexamined in Australia.
Objective: This study evaluated the concordance between ICD-10 Australian Modification (ICD-10-AM) code U07.1 (COVID-19, virus identified) and SARS-CoV-2 PCR test results in admitted patient records, to improve case identification.
Method: This retrospective study analysed routinely collected electronic medical record data from 13 public hospitals in New South Wales, Australia. Clinical coding of ICD-10-AM U07.1 was assessed using SARS-CoV-2 PCR results as the reference standard. Sensitivity, specificity, positive predictive value and negative predictive value were calculated. A mixed-effects logistic regression model was used to assess diagnostic concordance, adjusting for patient demographics.
Results: Among 25,724 admissions with a SARS-CoV-2 PCR test, 39.4% were confirmed COVID-19 cases based on positive SARS-CoV-2 PCR test results. The ICD-10-AM clinical coding of U07.1 demonstrated excellent accuracy, with a sensitivity of 91.5% (95% CI: 90.8–92.2%) and 94.1% (95% CI: 93.6–94.6%) compared to conventional and rapid PCR-confirmed cases, respectively.
Conclusion: The ICD-10-AM code U07.1 aligns well with SARS-CoV-2 PCR-confirmed cases, supporting its use as a reliable marker for COVID-19 in hospital data for surveillance and research purposes.
Implications for health information management practice: Ongoing improvements in clinical coding practices are necessary to minimise misclassification and enhance accuracy for public health planning.