Towards a smart healthy city: A generalised flow-based 2SFCA method for incorporating actual mobility data in healthcare accessibility evaluation

Abstract

Worldwide efforts have been made to prioritise equal access to hospitals, given its importance to health equality and the necessity of building healthy cities in the post-pandemic society. As the most used spatial accessibility technique to identify the under-served areas, however, the two-step floating catchment area (2SFCA) method was criticised for adopting presumed parameters that might lead to biased and misleading results. With the increasing availability of urban mobility data, it is now possible to incorporate people's actual service-seeking behaviour into the methodological framework of the classic 2SFCA. In this regard, this study proposes a Generalised Flow-based 2SFCA (GF2SFCA) method, which builds upon the demand-driven characteristic of healthcare facilities and utilises underlying patterns in geographical flow data to adaptively measure hospitals' influential range, distance-decay effect, and attractiveness. Specifically, two new indicators, namely, the global popularity index and local preference index, are proposed to synthetically evaluate hospital attraction from the perspective of actual healthcare demand, taking into account visitation counts, travel distance, and the collective preference of communities associated with a hospital. While alleviating certain subjectivity caused by parameters pre-selection, the GF2SFCA framework helps evaluate healthcare accessibility precisely. The experimental results, using Wuhan, China as a case study, confirmed the effectiveness of the proposed framework in producing realistic estimations and demonstrated its robustness to the potential uncertainty in mobility data. The data-driven property of GF2SFCA also allows for practical implementation in various contexts, which would benefit the survey of regional healthcare equality and its dynamics.