Heart, Lung and Circulation

Validation of ICD-10-AM Coding for Myocardial Infarction Subtype in Hospitalisation Data

Published:January 19, 2022DOI:


      International Classification of Disease (ICD) codes are central for identifying myocardial infarction (MI) in administrative hospitalisation data, however validation of MI subtype codes is limited. We measured the sensitivity and specificity of ICD-10-AM (Australian Modification) codes for ST-elevation MI (STEMI) and non-STEMI (NSTEMI).


      A sample of MI admissions was obtained from a dataset containing all MI hospitalisations in Western Australia (WA) for 2003, 2008 and 2013. Clinical data were collected from hospital medical records (n=799 patients). Cases were classified by ICD-10-AM codes for STEMI, NSTEMI and unspecified MI, and compared to clinical classification from review of available electrocardiographs (ECGs) and cardiac biomarkers (n=660). Sensitivity and specificity for ICD-10-AM coding versus clinical classification was measured, stratified by calendar year of discharge.


      The majority of classifiable cases had MI recorded in the principal diagnosis field (STEMI n=293, 84.2%; NSTEMI n=202, 74.3%; unspecified MI n=20, 50.0%). Overall sensitivity of the ICD-10-AM STEMI code was 86.3% (95% CI 81.7–90.0%) and was higher when restricted to MI as a principal versus secondary diagnosis (88.8% vs 66.7%). Comparable values for NSTEMI were 66.7% (95% CI 61.5–71.6%), and 68.8% vs 61.4% respectively. Between 2003 and 2013, sensitivity for both MI subtypes increased: 80.2–89.5% for STEMI, and 51.2–73.8% for NSTEMI. Specificity was high for NSTEMI throughout (88.2% 95% CI 84.1–91.6%), although improving over time for STEMI (68.1–76.4%).


      The sensitivity and specificity of ICD-10-AM codes for MI subtypes in hospitalisation data are generally high, particularly for principal diagnosis cases. However, the temporal improvement in sensitivity in coding of MI subtypes, particularly NSTEMI, may necessitate modification to trend studies using administrative hospitalisation data.


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