Background: Accurate referral information is essential to optimize the diagnostic yield of video electroencephalography (VEEG). Incomplete or inaccurate semiology in referral forms can reduce efficiency, increase costs, and delay appropriate treatment. Methods: We conducted a retrospective observational study of 121 patients referred for video EEG monitoring (VEM) at Cairo University Epilepsy Unit between January and December 2019, excluding presurgical evaluations. Referral data, including seizure semiology, suspected seizure type, family history, and imaging, were compared with VEM outcomes. Concordance between referral semiology and electroclinical findings was analyzed. Results: Of 121 referrals, 87 (71.9%) were for seizure type classification, 24 (19.8%) for diagnostic confirmation, 9 (7.4%) for psychogenic non-epileptic seizures (PNES), and 1 (0.8%) for antiseizure drug withdrawal evaluation. Although 111 referrals (91.7%) included semiology, more than half were discordant with VEM results (p < 0.001). Generalized seizures were over-represented in referrals (62.8%) compared with confirmed VEM findings. Overall, 66 records (54.5%) were normal, and 55 (45.5%) abnormal. Latency to first interictal epileptiform discharge (IED) was short (median 7 minutes), with 78.8% occurring within the first 30 minutes. No new discharges were recorded after 2 hours. Conclusion: Referral accuracy significantly impacts the yield of VEM. Inaccurate semiology reporting can misdirect resource allocation and prolong diagnosis. Standardized referral forms, history-taking by specialized epileptologists, and use of home videos are recommended to improve diagnostic efficiency. Tailoring VEM duration to early findings may further optimize cost-effectiveness.