Incorporating multiple travel modes into a floating catchment area framework to analyse patterns of accessibility to hierarchical healthcare facilities

Introduction: The existing healthcare-services-related literature tends to examine accessibility under a single travel mode, and measurement approaches are remaining limited for several inherent deficiency. This paper proposed a methodological enhancement of the three-step floating catchment area approach. Methods: First, we incorporates real-time travel time and trip distance of private car and public transport obtained from open-source route planning API into model, which aims to differentiate the impact of multiple travel costs on spatial accessibility outcomes; next, an arithmetic mean-based Gaussian weight algorithm was introduced for achieve stable accessibility index; then, exploratory factor analysis was further employed to evaluate healthcare capacity, with the total score as the healthcare supply indicator to calculate the provider-to-population ratios; finally, an empirical study was conducted to verify the model's advantages. We investigate accessibility to three tiers of healthcare facilities (including 22 tertiary hospitals, 88 secondary hospitals, and 55 community healthcare centres), and reveal disparities between supply and demand, via conjoint analysis of the accessibility of facilities and the population density under four associate patterns in the district of Wuhan at community scale (total 830 communities). Results: The results suggest that in terms of travel modes, the travel time and trip distance under the private car mode are shorter than these calculated under the public transport mode. Highly accessible communities are more concentrated in the central urban areas and distributed near a healthcare service centre, and community healthcare center have the greatest accessibility among the three tiers of healthcare. Moreover, statistical analysis highlights that distinct polarized differentiation appears in the number of communities with low and high accessibility, and more than half of the communities have accessibility levels that are inappropriate for their population size. Conclusions: These findings may have important policy implications for health planners and decision-makers who must reasonably allocate public health resources.