This study aims to address gaps in understanding healthcare accessibility inequality in rural China, where traditional distance-based assessments and urban-centric biases are insufficient. By integrating real-time travel data from Amap and the two-step floating catchment area (2SFCA) method, we conducted a high-resolution (1 km grid) analysis across transportation modes, administrative scales, and time-sensitive populations. Results reveal that driving enables more stable, equitable access (characterized by higher supply–demand ratios and lower variability) than public transport, which distorts ratios due to limited coverage. Accessibility disparities are most pronounced at the county scale, with eastern rural counties (e.g., Yangtze River Delta) showing far higher accessibility (log10(A-value) > 5.0) than remote western counties (log10(A-value) < 1.5). High time-sensitive populations (urgent care) face extreme accessibility gaps, with only 15% of counties providing optimal access. In contrast, low time-sensitive groups benefit from extended travel time thresholds, achieving 62% coverage of optimal access. Targeted interventions—investing in rural high-tier hospitals, enhancing transit frequency, and county-specific policies—are needed to advance health equity. The findings of this study provide the first nationwide high-resolution healthcare accessibility map for rural China, improve assessment accuracy via real-time data, and identify county-level gaps—offering data-driven insights for targeted policies to advance health equity and support rural revitalization.
Gao et al. (Sun,) studied this question.