Current Attitudes Toward Neuroanatomy: A Comparative Cross-Sectional Survey of Neurosurgeons from the United Kingdom and Worldwide.

OBJECTIVE: How attitudes toward neuroanatomy and preferences of studying resources vary among neurosurgeons is unknown. The impact of the coronavirus disease 2019 (COVID-19) pandemic on anatomy learning habits is also yet to be elucidated. In this study, we explore these objectives, to guide the development of future neurosurgeon-tailored anatomy education and resources. METHODS: This was a 2-stage, cross-sectional study design comprising a local pilot survey followed by a structured 17-item questionnaire, distributed to both neurosurgical trainees and consultants. Grade and nationality differences in sentiment agreement were statistically compared. RESULTS: A total of 365 responses were received from 32 countries (overall response rate, 23.2%). Neuroanatomy is highly regarded among most neurosurgeons and takes a central role in their professional identity. Yet, 69% of neurosurgeons wanted to spend more time learning. Common study prompts included perceived operative complexity, lack of familiarity and teaching. Financial barriers and motivation were obstacles limiting neuroanatomy learning, more so among trainee neurosurgeons, with personal commitment barriers significantly varying with geographic location. Surgical relevance, accessibility, and image quality were important factors when selecting anatomy resources, with cost and up-to-datedness being important for juniors. The COVID-19 pandemic saw a shift toward virtual resources, particularly affecting United Kingdom-based trainees. CONCLUSIONS: Although neuroanatomy is well regarded, barriers exist that impede further neuroanatomy learning. Neurosurgical training programs should tailor anatomy education according to the seniority and background of their residents. Furthermore, resources that are surgically relevant and accessible and are of high image quality are more likely to be better used.

Analyzing historical and future acute neurosurgical demand using an AI-enabled predictive dashboard.

Characterizing acute service demand is critical for neurosurgery and other emergency-dominant specialties in order to dynamically distribute resources and ensure timely access to treatment. This is especially important in the post-Covid 19 pandemic period, when healthcare centers are grappling with a record backlog of pending surgical procedures and rising acute referral numbers. Healthcare dashboards are well-placed to analyze this data, making key information about service and clinical outcomes available to staff in an easy-to-understand format. However, they typically provide insights based on inference rather than prediction, limiting their operational utility. We retrospectively analyzed and prospectively forecasted acute neurosurgical referrals, based on 10,033 referrals made to a large volume tertiary neurosciences center in London, U.K., from the start of the Covid-19 pandemic lockdown period until October 2021 through the use of a novel AI-enabled predictive dashboard. As anticipated, weekly referral volumes significantly increased during this period, largely owing to an increase in spinal referrals (p < 0.05). Applying validated time-series forecasting methods, we found that referrals were projected to increase beyond this time-point, with Prophet demonstrating the best test and computational performance. Using a mixed-methods approach, we determined that a dashboard approach was usable, feasible, and acceptable among key stakeholders.