A multi-modal relative spatial access assessment approach to measure spatial accessibility to primary care providers

Abstract

Two-step floating catchment area (2SFCA) methods that account for multiple transportation modes provide more realistic accessibility representation than single-mode methods. However, the use of the impedance coefficient in an impedance function (e.g., Gaussian function) introduces uncertainty to 2SFCA results. This paper proposes an enhancement to the multi-modal 2SFCA methods through incorporating the concept of a spatial access ratio (SPAR) for spatial access measurement. SPAR is the ratio of a given place’s access score to the mean of all access scores in the study area. An empirical study on spatial access to primary care physicians (PCPs) in the city of Albuquerque, NM, USA was conducted to evaluate the effectiveness of SPAR in addressing uncertainty introduced by the choice of the impedance coefficient in the classic Gaussian impedance function. We used ESRI StreetMap Premium and General Transit Specification Feed (GTFS) data to calculate the travel time to PCPs by car and bus. We first generated two spatial access scores—using different catchment sizes for car and bus, respectively—for each demanding population location: an accessibility score for car drivers and an accessibility score for bus riders. We then computed three corresponding spatial access ratios of the above scores for each population location. Sensitivity analysis results suggest that the spatial access scores vary significantly when using different impedance coefficients (p < 0.05); while SPAR remains stable (p = 1). Results from this paper suggest that a spatial access ratio can significantly reduce impedance coefficient-related uncertainties in multi-modal 2SFCA methods.

Measuring spatiotemporal accessibility for pediatric clinical services with multimodal transport modes: an exploratory analysis in Nanjing, China

“…Xia et al, 2019), and mental health in childhood and adolescence (Nordbø, Nordh, Raanaas, & Aamodt, 2018). Because primary healthcare is closely related to life, relatively inexpensive, and easily delivered, primary care has received extensive attention (Lin et al, 2018). The other burgeoning thread of research has shifted the focus to accessibility measures for different age groups, for example, highlighting age level differences, like children and older people (Neutens, 2015).…”

“…Also, scholars pay attention to the impact of dynamic environmental changes on the spatiotemporal accessibility, such as the daily food and transportation environments affect grocery store accessibility (Widener et al, 2017), temporal variability accessibility to supermarkets (Farber, Morang, & Widener, 2014;Widener et al, 2015). In the perspective of the STA of health research, more comprehensive accessibility measures, including integrating time and transport modes from open data (Tenkanen, Saarsalmi, Järv, Salonen, & Toivonen, 2016), multi-temporal transport network models (Tomasiello, Giannotti, Arbex, & Davis, 2019), and multi-modal relative spatial access assessment approach (Lin et al, 2018), is becoming an important development branch of dynamic environment changes on the spatiotemporal accessibility. Considering the sociality of healthcare services, our STA research focuses on place-based STA measurements based on residents' mobility and timepoints variance.…”

“…Additionally, web mapping platforms have integrated multiple traffic factors, including fundamental traffic flow principles and historical traffic data, through large-scale users' behavior data based on mobile apps (Pilkington et al, 2018) and record realistic MTM information (Järv et al, 2018). Based on the travel impedance data considered in the MTM, many new accessibility models have been developed, such as multimodal 2SFCA (Mao & Nekorchuk, 2013), a variable-width floating catchment area model (Dony et al, 2015), multimodal 2SFCA incorporating the spatial access ratio (Lin et al, 2018), and multimodal accessibility-based equity assessment (Tahmasbi et al, 2019).…”

“…Models of the accessibility of urban facilities, as potential opportunities for the spatial interaction of geographical entities, are widely used in geography, urban studies, and transportation research (Batty, 2013;Kwan, Richardson, Wang, & Zhou, 2015). As the traffic system has become comprehensive, healthcare accessibility research based on human mobility has become more complicated (Lin, Wan, Sheets, Gong, & Davies, 2018;Pan et al, 2018;T. Xia et al, 2019).…”

Two-Step Floating Catchment Area Model-Based Evaluation of Community Care Facilities’ Spatial Accessibility in Xi’an, China

“…Tseng et al (2018) applied spatial analysis techniques, such as hot-spot analysis and the enhanced two-step floating catchment area (E2SFCA) method, to examine Taiwan’s distribution of the aging population of each village [ 60 ]. The 2SFCA model is also constantly being studied [ 61 , 62 , 63 ]. The research of Chen X et al (2019) shows that on a small scale analysis (e.g., the community level), the catchment size is the most critical model component; on a large scale analysis (e.g., statewide), the distance decay function is of elevated importance [ 61 ].…”