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Background The underrepresentation of acute psychiatric settings in epilepsy research presents a barrier to delivering equitable healthcare for people with comorbid epilepsy and severe mental illness. The treatment of epilepsy in this patient group presents challenges, including diagnostic uncertainty, pharmacological complexity, and a lack of integrated specialist care. We aimed to report the lifetime prevalence of epilepsy among people receiving acute psychiatric inpatient care and examine the sociodemographic and clinical characteristics influencing their treatment outcomes.Methods We analysed electronic patient records from South London and Maudsley NHS Foundation Trust to estimate the lifetime prevalence of epilepsy in a retrospective cohort of 9,237 individuals admitted to psychiatric inpatient wards between 2015 and 2019. Hospital and national databases were used to examine patient characteristics, including sociodemographic variables, antiseizure medication prescription patterns, and engagement with specialist neurology services. Kaplan-Meier and Cox regression analyses were conducted to identify predictors of all-cause mortality in individuals with epilepsy and a comparator cohort of 8,857 patients without epilepsy.Results The lifetime prevalence of epilepsy in this population was 3% (95% CI: 2.65 to 3.36). Among individuals with epilepsy, 64.1% were prescribed two or more antiseizure medications, while only 32.6% received specialist neurology input in the year before and after their most recent admission. Additionally, 72.8% lived in areas with high levels of socioeconomic deprivation. Adjusting for clinical and demographic covariates, the presence of epilepsy was associated with a 43% increased risk of mortality in this population (HR = 1.43, 95% CI: 1.08–1.90, p = 0.01).Conclusions Epilepsy has an elevated prevalence and is a significant predictor of mortality among people receiving acute psychiatric inpatient care. Low rates of specialist neurology input and treatment complexity highlight an urgent need for interdisciplinary collaboration and systemic changes in care pathways. Risk prediction models and tailored interventions to improve both service provision and patient engagement could reduce preventable deaths in this vulnerable population.