Measuring Accessibility of Healthcare Facilities for Populations with Multiple Transportation Modes Considering Residential Transportation Mode Choice

Abstract

Accessibility research of healthcare facilities is developing towards multiple transportation modes (MTM), which are influenced by residential transportation choices and preferences. Due to differences in travel impact factors such as traffic conditions, origin location, distance to the destination, and economic cost, residents’ daily travel presents different residential transportation mode choices (RTMC). The purpose of our study was to measure the spatial accessibility of healthcare facilities based on MTM considering RTMC (MTM-RTMC). We selected the gravity two-step floating catchment area method (G2SFCA) as a fundamental model. Through the single transportation mode (STM), MTM, and MTM-RTMC, three aspects used to illustrate and redesign the G2SFCA, we obtained the MTM-RTMC G2SFCA model that integrates RTMC probabilities and the travel friction coefficient. We selected Nanjing as the experimental area, used route planning data of four modes (including driving, walking, public transportation, and bicycling) from a web mapping platform, and applied the three models to pediatric clinic services to measure accessibility. The results show that the MTM-RTMC mechanism is to make up for the traditional estimation of accessibility, which loses sight of the influence of residential transportation choices. The MTM-RTMC mechanism that provides a more realistic and reliable way can generalize to major accessibility models and offers preferable guidance for policymakers.

Disparities in Geographical Access to Hospitals in Portugal

“…This paper will focus on the two spatial dimensions from Penchansky and Thomas' approach and the two first components referred by Geurs and Wee. In this way, the study will consider the relationship between three factors, their spatial distribution and their characteristics: (a) how far people live from healthcare services and are willing to travel, (b) how well transport provides links to the healthcare services, and (c) how long it takes to travel to such services [16][17][18][19][20][21][22].…”

“…The third parameter considers the way geographic accessibility between the residential area and the public service is measured. According to the literature, the five most commonly used measures are: (1) the distance/time to the service [102]; (2) the number of services within n meters or minutes [101]; (3) the mean distance/time to the n closest services [30]; (4) the gravity model [103,104]; (5) the two-step floating catchment area methods and those derived from them [18,20,21,24,85,103,[105][106][107][108]. Among these, the last two are relatively popular methods for measuring spatial equity [18,82,109].…”

Use of 2SFCA Method to Identify and Analyze Spatial Access Disparities to Healthcare in Jeddah, Saudi Arabia

“…This will contribute to mitigating spatial inequity in access to healthcare. There are several studies such as Mao and Nekorchuk [66] and Zhou et al [67] that used multiple transportation modes to measure spatial accessibility to healthcare. Accordingly, decision makers should formulate intervention priorities aimed at improving the public transportation system in Jeddah, which contributes to facilitating access to healthcare services at the right time, especially for those who do not have cars.…”

AMORE Project: Integrated knowledge translation and geospatial analysis to improve travel times to health services (accessibility) and health equity in Cali, Colombia: a proof of concept using mixed-methods research

“…(1,2,(58)(59)(60) It is common knowledge that travel times can change substantially with traffic congestion, but this consideration is missing from many origin-destination studies guiding urban planning (61)(62)(63)(64)(65)(66)(67)(68)(69). Mobility surveys seldom delve into the health equity implications of accessibility to health services, let alone look into disaggregated data to enhance understanding of the populations being left out, so as to better understand the health service seeking behaviors, out of pocket expenditures, or direct payments required to reach health services (19).…”

“…Mobility surveys seldom delve into the health equity implications of accessibility to health services, let alone look into disaggregated data to enhance understanding of the populations being left out, so as to better understand the health service seeking behaviors, out of pocket expenditures, or direct payments required to reach health services (19). The emergence of new digital technologies and data sources presents an opportunity for innovations addressing such shortcomings (1,2,59,60,70). A first prototype of the AMORE Platform was developed and tested between June and August of 2020.…”