In this study, we quantitatively analyzed healthcare accessibility in Asan, Chungcheongnam-do, South Korea, by the enhanced two-step floating catchment area (E2SFCA) method. Healthcare accessibility significantly affects public health and quality of life. However, disparities between urban and rural areas persist. We aimed to evaluate the spatial imbalance in healthcare resources within Asan and to identify medically underserved areas in this study. A node-based road network analysis was conducted to reflect actual resident mobility patterns. We employed the E2SFCA method to compute a healthcare accessibility index and used the Lorenz curve and Gini coefficient to assess the degree of inequality in healthcare accessibility. Subsequently, a cluster analysis using the Louvain algorithm identified 55 communities with similar healthcare accessibility levels. It revealed that urban areas exhibited high healthcare accessibility, whereas peripheral areas had low accessibility. Finally, Getis-Ord statistics were used in a hotspot analysis to identify regions with significantly high and low healthcare accessibility levels. The findings suggest that healthcare accessibility is concentrated in urban areas, whereas peripheral regions lack adequate healthcare services. Compared with conventional grid-based approaches, in this study, we more precisely captured actual movement patterns using a road-network-based accessibility analysis. This enabled a more detailed assessment of the spatial disparities in healthcare accessibility. These findings can be foundational for efficiently allocating healthcare resources and developing public health policies.