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Introduction: Accurate surveillance of TIA is important for monitoring disease burden and evaluating temporal trends. Passive surveillance is a time and cost-effective method to identify TIA using administrative data. Although TIA is primarily managed in the emergency department (ED) without admission to hospital, prior administrative data validation studies have mainly evaluated inpatient databases. We determined the validity of the ICD-10 codes to identify TIA in an ED administrative database.Methods: The study population was obtained from two ongoing studies on the diagnosis of TIA and minor stroke versus stroke mimic. Stroke mimics were actively recruited. Patients enrolled between December 1st 2013 and October 30th 2015 with an ED visit were included in the current study. ED discharge diagnoses were obtained from the National Ambulatory Care Reporting System database. We determined the sensitivity, specificity, and positive predictive value (PPV) of the ICD-10 TIA codes by using two reference standards: 1) the ED chart abstraction and 2) the 90-day final diagnosis, both adjudicated by stroke neurologists. Different case definition algorithms were tested.Results: We included 417 patients. ED adjudication showed 163 (39.1%) TIA, 155 (37.2%) ischemic stroke, and 99 (23.7%) stroke mimics. The most restrictive algorithm, defined as a TIA code in the main position had the lowest sensitivity (36.8%), but highest specificity (92.5%) and PPV (76.0%). The most inclusive algorithm, defined as a TIA code in any positions with and without query prefix had the highest sensitivity (63.8%), but lowest specificity (81.5%) and PPV (68.9%). Comparing the final 90-day diagnosis with coding showed similar results.Conclusions: TIA can be identified with high specificity, but low sensitivity from ED discharge diagnoses. By including patients with stroke mimics, we determined both the false positive and negative rates, allowing for the calculation of sensitivity and specificity. We used two reference standards to verify the accuracy of administrative data. Future studies are necessary to understand the reasons for the low sensitivity of administrative data for TIA and whether the miscoded patients are systematically different from the accurately coded ones.