Validity of international classification of disease codes to identify ischemic stroke and intracranial hemorrhage among individuals with associated diagnosis of atrial fibrillation.

Academic Article


  • BACKGROUND: Because of its association with death and disability, stroke is a focus of outcomes in atrial fibrillation (AF) research. International Classification of Disease-Ninth Revision (ICD-9) edition codes are commonly used to identify stroke in research, particularly in large administrative data. We sought to assess the validity of ICD-9 codes in stroke case ascertainment and for AF across 3 institutions. METHODS AND RESULTS: Participating centers included Boston Medical Center (safety net hospital), Geisinger Health System (rural Pennsylvania), and the University of Alabama (academic center in the southeastern stroke belt). ICD-9 codes for ischemic stroke (433-434, 436) and intracranial hemorrhage (430-432) identified 1812 stroke cases with an associated code for AF (427.31) from 2006 to 2010. Cases were vetted through chart review with final adjudication by a stroke neurologist. Review considered 94.2% of ICD-9 identified stroke cases valid with decreased accuracy for concurrent AF diagnosis (82.28%) and stroke attributable to AF (72.8%). Among events with "without infarction" modifiers, 7.2% were valid strokes. ICD-9 stroke code accuracy did not differ by stroke type or site. Stroke code 434 displayed higher accuracy than 433 (94.4% versus 85.2%; P<0.01), and primary stroke codes were more accurate than nonprimary codes (97.2% versus 83.7%; P<0.0001). CONCLUSIONS: Using ICD-9 stroke and AF codes to identify patients with stroke plus AF resulted in inaccuracies. Given the expanded financial and policy implications of patient-oriented research, conclusions derived solely from administrative data without validation of outcome events should be interpreted with caution.
  • Authors


  • International Classification of Disease codes, atrial fibrillation, intracranial hemorrhages, stroke, Aged, Aged, 80 and over, Atrial Fibrillation, Brain Ischemia, Data Mining, Databases, Factual, Female, Humans, International Classification of Diseases, Intracranial Hemorrhages, Male, Medical Records, Middle Aged, Predictive Value of Tests, Reproducibility of Results, Stroke, United States
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    Author List

  • Thigpen JL; Dillon C; Forster KB; Henault L; Quinn EK; Tripodis Y; Berger PB; Hylek EM; Limdi NA
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  • 8
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  • 8
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  • 1