A flow-based statistical model integrating spatial and nonspatial dimensions to measure healthcare access

Abstract

Assessing access to healthcare for an entire healthcare system involves accounting for demand, supply, and geographic variation. In order to capture the interaction between healthcare services and populations, various measures of healthcare access have been utilized, including the popular two-step floating catchment area (2SFCA) method. However, despite the many advantages of 2SFCA, the problems, such as inappropriate assumption of healthcare demand and failure to capture cascading effects across the system have not been satisfactorily addressed. In this paper, a statistical model for evaluating flows of individuals was added to the 2SFCA method (hereafter we refer to it as F2SFCA) in order to overcome limitations associated with its current restriction. The proposed F2SFCA model can incorporate both spatial and nonspatial dimensions and thus synthesizes them into one framework. Moreover, the proposed F2SFCA model can be easily adapted to measure access for different types of individuals, over different service provider types, or with capacity constraints in a healthcare system. We implemented the proposed model in a case study assessing access to healthcare for the elderly in Taipei City, Taiwan, and compared the weaknesses and strengths to the 2SFCA method and its variations.

Keywords: Accessibility; F2SFCA; GIS; Potential access; Spatial interaction model.