From 2SFCA to i2SFCA: integration, derivation and validation

ABSTRACT

Uneven distributions of population and service providers lead to geographic disparity in access for residents and varying workload for staff in facilities. The former can be captured by spatial accessibility in the traditional two-step floating catchment area (2SFCA) method; and the latter can be measured by potential crowdedness in the newly developed inverted 2SFCA (or i2SFCA) method. Residents-based accessibility and facility crowdedness are two sides of the same coin in examining the geographic variability of resource allocation. This short research note derives the formulations of both methods to solidify their theoretical foundation and uses a case study to validate both. By doing so, the 2SFCA and i2SFCA are fully integrated into one conceptual framework, derived with extensions to the Huff model, and validated by empirical data.

KEYWORDS:

• 2-Step floating catchment area (2SFCA) method
• inverted 2-Step floating catchment area (i2SFCA) method
• Huff model
• theoretical foundation

Acknowledgments

Funding from the National Cancer Institute (Grant R21CA212687) is gratefully acknowledged. Points of view or opinions in this article are those of the author and do not necessarily represent the official position or policies of the National Cancer Institute. Technical help from Changzhen Wang in preparing the figures is much appreciated.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1. Note that R² here is 0.62, slightly lower than 0.65 in Figure 7 of Wang (2018). As stated previously, this study defines demand by population instead of patient volume, and the derived crowdedness measure better reflects its essence of ‘potential’ with absence of any knowledge of actual patient visitation data. The reduction in its prediction power from 0.65 to 0.62 is negligible.

Additional information

Funding

This work was supported by the National Cancer Institute [R21CA212687].

Notes on contributors

Fahui Wang

Fahui Wang is Cyril & Tutta Vetter Alumni Professor of Louisiana State University. His research interests focus on GIS, geospatial computational methods, and applications in social sciences, planning and public policy.