INTRODUCTION: Patients with stroke are often selected for epidemiological reporting and research using ICD-9-CM (ICD-9) diagnostic codes. This study addresses the accuracy of these codes in identifying patients with stroke. METHODS: A sample of 279 patients with new stroke and 392 non-stroke (no evidence of new stroke) patients were identified by medical record review from 11 Veterans Affairs Medical Centers. Administrative records containing ICD-9-CM diagnoses were matched with this sample. Coding sensitivity and specificity were determined using individual ICD-9 codes and two coding algorithms. RESULTS: Significant variation was found in the accuracy of cerebrovascular ICD-9-CM codes in identifying patients diagnosed with stroke. Two coding algorithms were identified with the following performance statistics based on the sampled populations: 1) 91-percent sensitivity, 40-percent specificity; and 2) 54-percent sensitivity, 87-percent specificity. DISCUSSION/ CONCLUSIONS: Variability in identifying patients with stroke using ICD-9 codes has been reported in the literature and confirmed. Two coding algorithms for maximizing sensitivity or specificity are proposed. Caution is urged when using ICD-9-coded administrative data to identify patients with stroke.
INTRODUCTION:Patients with stroke are often selected for epidemiological reporting and research using ICD-9-CM (ICD-9) diagnostic codes. This study addresses the accuracy of these codes in identifying patients with stroke. METHODS: A sample of 279 patients with new stroke and 392 non-stroke (no evidence of new stroke) patients were identified by medical record review from 11 Veterans Affairs Medical Centers. Administrative records containing ICD-9-CM diagnoses were matched with this sample. Coding sensitivity and specificity were determined using individual ICD-9 codes and two coding algorithms. RESULTS: Significant variation was found in the accuracy of cerebrovascular ICD-9-CM codes in identifying patients diagnosed with stroke. Two coding algorithms were identified with the following performance statistics based on the sampled populations: 1) 91-percent sensitivity, 40-percent specificity; and 2) 54-percent sensitivity, 87-percent specificity. DISCUSSION/ CONCLUSIONS: Variability in identifying patients with stroke using ICD-9 codes has been reported in the literature and confirmed. Two coding algorithms for maximizing sensitivity or specificity are proposed. Caution is urged when using ICD-9-coded administrative data to identify patients with stroke.
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