Trends in Emergency Neurosurgical Workload: Evidence From a Tertiary Center.

Background Emergency neurosurgical referrals are a leading driver of on-call workload and unplanned admissions. Tracking their volume and case-mix supports safe staffing, imaging capacity, and bed planning across regional networks. The study included all emergency referrals made to the department between 2020 and 2022. Methodology Patient data were individually extracted from a prospectively maintained local database. The initial step involved a de-duplication process, ensuring the dataset represented unique patient referrals for each year under consideration. The subsequent phase involved a nuanced categorization strategy to distinctly identify new case referrals against follow-ups. An advanced synonym recognition approach was adopted to include a range of terms and related clinical conditions, ensuring robust and inclusive data categorization. The data were analyzed in R Studio using negative binomial regression (monthly call counts, adjusted for seasonality), quasi-Poisson regression (sensitivity analysis of annual totals), the Kruskal-Wallis test (nonparametric comparison of monthly counts across years), Kendall's τ trend test (monotonic trend in annual counts), and logistic regression (odds of out-of-hours (OOH) vs. in-hours (InH) calls, adjusted for month). Results The data revealed a progressive increase in calls to the neurosurgical registrar, from 5,435 in 2016 to 9,567 in 2021 and 9,279 in 2022 (quasi-Poisson incidence rate ratio (IRR), 1.08 per year; 95% confidence interval (CI), 1.06-1.11;