Key result
Pairing stroke codes with same-day brain imaging achieves 90% accuracy in identifying acute cerebrovascular disease.
Why the study?
Validation of stroke diagnostic code accuracy in hospital-based cancer registries using electronic medical records in Japan was needed to ensure research reliability.
Does combining clinical examination data with diagnostic codes improve the accuracy of stroke identification in electronic medical records of cancer patients?
Observational (n=25,827)
No
Does combining clinical examination data with diagnostic codes improve the accuracy of stroke identification in electronic medical records of cancer patients?
Absolute Event Rate: 90% vs 22%
Combining stroke diagnostic codes with brain imaging data significantly improves the accuracy of identifying acute cerebrovascular events in electronic medical records compared to using diagnostic codes alone.
Supports refined EMR stroke phenotyping in cancer patients; leaves open prospective validation before wider adoption.
BACKGROUND: This study aimed to validate an algorithm that determines stroke diagnostic code accuracy, in a hospital-based cancer registry, using electronic medical records (EMRs) in Japan. METHODS: The subjects were 27,932 patients enrolled in the hospital-based cancer registry of Osaka University Hospital, between January 1, 2007 and December 31, 2015. The ICD-10 (international classification of diseases, 10th revision) diagnostic codes for stroke were extracted from the EMR database. Specifically, subarachnoid hemorrhage (I60); intracerebral hemorrhage (I61); cerebral infarction (I63); and other transient cerebral ischemic attacks and related syndromes and transient cerebral ischemic attack (unspecified) (G458 and G459), respectively. Diagnostic codes, both "definite" and "suspected," and brain imaging information were extracted from the database. We set the algorithm with the combination of the diagnostic code and/or the brain imaging information, and manually reviewed the presence or absence of the acute cerebrovascular disease with medical charts. RESULTS: A total of 2654 diagnostic codes, 1991 "definite" and 663 "suspected," were identified. After excluding duplicates, the numbers of "definite" and "suspected" diagnostic codes were 912 and 228, respectively. The proportion of the presence of the disease in the "definite" diagnostic code was 22%; this raised 51% with the combination of the diagnostic code and the use of brain imaging information. When adding the interval of when brain imaging was performed (within 30 days and within 1 day) to the diagnostic code, the proportion increased to 84% and 90%, respectively. In the algorithm of "definite" diagnostic code, history of stroke was the most common in the diagnostic code, but in the algorithm of "definite" diagnostic code and the use of brain imaging within 1 day, stroke mimics was the most frequent. CONCLUSIONS: Combining the diagnostic code and clinical examination improved the proportion of the presence of disease in the diagnostic code and achieved appropriate accuracy for research. Clinical research using EMRs require outcome validation prior to conducting a study.
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Gon et al. (2017) conducted an observational in Stroke in cancer patients (n=25,827). Combination of diagnostic code and brain imaging vs. Diagnostic code alone was evaluated on Proportion of the presence of acute cerebrovascular disease (diagnostic accuracy). Combining a 'definite' stroke diagnostic code with brain imaging performed within 1 day of diagnosis improved the accuracy of identifying true acute cerebrovascular disease from 22% to 90%.
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