Spatial Accessibility
2023-7-18
Spatial accessibility in suboptimally configured health care systems: A modified two-step floating catchment area (M2SFCA) metric
This paper examines limitations in current methods for measuring spatial accessibility to healthcare and proposes a new approach to account for suboptimal configurations of facilities.
Abstract:
The floating catchment area (FCA) family of metrics employ principles from gravity-based models to incorporate supply, demand, and distance in their characterization of the spatial accessibility of health care resources. Unlike traditional gravity models, the FCA metrics provide an output in highly interpretable container-like units (e.g., physicians per person). This work explores two significant issues related to FCA metrics. First, the Three Step Floating Catchment Area is critically examined. Next, the research shows that all FCA metrics contain an underlying assumption that supply locations are optimally configured to meet the needs of the population within the system. Because truly optimal configurations are highly unlikely in real-world health care systems, a modified two-step floating catchment area (M2SFCA) metric is offered to address this issue. The M2SFCA is built upon previous FCA metrics, but allows for spatial accessibility to be discounted as a result of the suboptimal configuration of health care facilities within the system. The utility of the new metric is demonstrated through simulated data examples and a case study exploring acute care hospitals in Michigan.
Summary:
Summary:
- Study examines methods for measuring spatial accessibility to healthcare
- Reviews Floating Catchment Area (FCA) metrics like 2SFCA and E2SFCA
- Critically examines 3SFCA method which accounts for competition between facilities
- Finds 3SFCA can overestimate and underestimate spatial accessibility
- Current FCA methods assume optimal configuration of facilities
- This can lead to overestimation of spatial accessibility
- Proposes Modified 2SFCA (M2SFCA) to account for suboptimal configurations
- M2SFCA incorporates both relative and absolute distances
- Applied less accessible opportunities are discounted in M2SFCA
- Simulated and case study data show M2SFCA differences from E2SFCA
- M2SFCA provides more nuanced measure of spatial accessibility
Study questions and answers:
| Study Question | Answer |
|---|---|
| What is the main limitation of current FCA methods? | They assume an optimal configuration of facilities |
| How does 3SFCA account for competition between facilities? | Uses a selection weight to allocate demand |
| What are two impacts of the 3SFCA competition factor? | Can over and underestimate spatial accessibility |
| What are the two distance factors incorporated in M2SFCA? | Relative and absolute distances |
| How does M2SFCA improve on current FCA methods? | Accounts for suboptimal configurations, provides more nuanced measure |
| What data did the author use to demonstrate M2SFCA? | Simulated data and Michigan hospital case study |