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Introduction\ud The urgent and emergency care system (UEC) is struggling with increased demand, some of which is clinically unnecessary. Patients suffering suspected seizures commonly present to emergency departments, but most seizures are self-limiting and have low risk of short-term adverse outcomes. We aimed to investigate the flow of suspected seizure patients through the UEC system using datalinkage to facilitate development of new models of care.\ud \ud Methods\ud We used a two-stage process of deterministic linking to perform a cross-sectional analysis of data from adults in a large region in England (population 5.4 million) during 2014. The core dataset\ud comprised a total of 739,436 ambulance emergency incidents, 1,033,778 ED attendances and 362,358 admissions.\ud \ud Results\ud A high proportion of cases were successfully linked (86.9% ED-inpatient, 77.7% ED-ambulance). Suspected seizures represented 2.8% of all ambulance service incidents. 61.7% of these incidents led to dispatch of a rapid-response ambulance (8 minutes) and 72.1% were conveyed to hospital. 37 patients died before being conveyed to hospital and 24 died in the ED (total 61; 0.3%). The in-patient death rate was 0.4%. Suspected seizures represented 0.71% of ED attendances, 89.8% of these\ud arrived by emergency ambulance, 45.4% were admitted and 44.5% of these admissions lasted under 48 hours.\ud \ud Conclusions\ud This study confirms previously published data from smaller unlinked datasets, validating the linkage method, and provides new data for suspected seizures. There are significant barriers to realising the full potential of data-linkage. Collaborative action is needed to create facilitative governance frameworks and improve data quality and analytical capacity.