Bridging theory and behavior for healthcare accessibility modeling: A mobility-driven revision of the E2SFCA.

Proximity to a healthcare supplier does not necessarily equate to meaningful access to care. Traditional healthcare accessibility models, particularly the Enhanced Two-Step Floating Catchment Area (E2SFCA) method, rely heavily on assumptions of proximity-driven behavior, fixed catchment sizes, and uniform distance decay. These simplifications often overlook the complexities of real-world healthcare-seeking behavior. This study examines the assumptions of the E2SFCA framework by integrating large-scale human mobility data in 2023, which captures anonymized, real-world visitation patterns between neighborhoods and hospitals across Pennsylvania. We revise the E2SFCA model through two key innovations: 1) replacing static catchment thresholds with dynamic, visit-weighted boundaries derived from observed travel behavior, and 2) estimating hospital-specific distance decay functions that better reflect heterogeneous patterns of attraction. These refinements result in accessibility metrics that align more closely with empirical realities. Compared to the traditional model, the revised E2SFCA demonstrates a more meaningful relationship with real-world health outcomes. Specifically, the revised model shows a stronger and statistically significant correlation with household income (r = 0.31, p = 0.011, vs. r = 0.14 in the traditional model) and a more plausible negative association with poor or fair health status (r = -0.12 vs. r = 0.17), aligning with the expectation that better accessibility corresponds to better health outcomes. Additionally, the revised model reveals significantly greater inequality in access that exposes disparities in healthcare accessibility that distance centric approaches tend to obscure. By integrating human mobility data in spatial accessibility modeling, this study offers a more realistic, equitable, and policy-relevant framework for evaluating healthcare access.