An Extended Kernel Density Two-Step Floating Catchment Area Method to Analyze Access to Health Care

Abstract

In Portugal the distribution of physicians is considered an appropriate proxy for the distribution of the actual hospital resources and additional information on hospital supply is mostly unavailable, while health care utilization data are also usually absent. A suitable method that can be used to analyze patients' access to hospital health care in countries with such characteristics is the two-step floating catchment area (2SFCA) method, since it requires only the number of physicians to represent supply and the population size to estimate demand. An improved version of the 2SFCA method is the kernel density 2SFCA (KD2SFCA) method. However, this method was not developed to analyze access to health care and it computes scores that express only the spatial access dimensions of proximity and availability. In this paper we present a new method, based on the KD2SFCA method, which improves health care access analysis and better identifies populations that are less empowered to use health care. We adapt the KD2SFCA method for the context of health care access analysis and extend it to capture additional access dimensions. We applied the extended method to the Portuguese hospital health care sector in a case study, and compared its results with those obtained with the KD2SFCA method. Our method was able to improve the identification of the less empowered populations and discovered that they represent 8.1% of the total population, instead of 4.6%, and reside in sixteen of the eighteen Portuguese districts, instead of in thirteen, as identified by the original KD2SFCA method. By improving the KD2SFCA method for the identification of the less empowered populations, our method can be a first step in an endeavor to identify opportunities to increase the health care supply or to redistribute supply resources, with the objective of increasing the access of those deprived populations.

Applying an Extended Kernel Density 4-Step Floating Catchment Area Method to Identify Priority Districts to Promote New Publicly Financed Supply of Gastroenterology Exams

“…This method uses floating catchment areas and computes access scores for small geographic units (Polzin et al, 2014). In 2SFCA-based methods like the EKD2SFCA, the catchment areas are floating areas, because the computation of the scores depends on catchment areas centered on the centroids of each of the small geographic units of the study region.…”

“…The initial catchment d init is used as proposed by , 2009, 2009), Schuurman et al (2010 and Polzin et al (2014Polzin et al ( , 2016, assuming that travel times below a predetermined threshold do not present any sensible proximity impediment to utilization.…”

“…The two indices are first component indices constructed with principal components analysis (PCA), as explained by Polzin et al (2014Polzin et al ( , 2016, following the methodology described by Henry et al (2003), Salmond et al (2006) and Mooi & Sarstedt (2011). The relevant sets of variables were chosen with an iterative approach, following the Kaiser criterion and observing the specific criteria for the Kaiser-Meyer-Olkin (KMO) statistic, the Bartlett's Test of Sphericity, the communalities, and the percentage of the total variance attributed to the first component.…”

“…The EKD4SFCA method provides a combined analysis of competition and access by incorporating the Herfindahl-Hirschman Index (HHI) and a market dominance identification technique in the Extended Kernel Density 2-Step Floating Catchment Area (EKD2SFCA) method (Polzin et al, 2014(Polzin et al, , 2016.…”

Assessment of the walking accessibility of public libraries in Krakow using the E2SFCA approach

“…Thomas (1981 as cited in Polzin et al 2014), there are five different dimensions involved in access: accommodation, affordability, acceptability, accessibility and availability. The two last-mentioned dimensions are spatial dimensions, which will be explained in more detail.…”