Evaluation of healthcare inequity for older adults: A spatio-temporal perspective. (December 2020)

• Record Type: Journal Article
• Authors: Chen, Guangping; Wang, Cassandra C.; Jin, Pingbin; Xia, Bingyan; Xiao, Liang; Chen, Siyun; Luo, Jing
• Is Part Of: Journal of transport & health. Volume 19(2020)
• Publication Date: 2020-12
• Subjects: Healthcare inequity -- Accessibility -- Older adults -- Gaussian 2SFCA method -- Real-time speed data; Transportation -- Health aspects -- Periodicals; Transportation -- Periodicals; Public Health -- Periodicals; Noise, Transportation -- Periodicals; Air Pollutants -- Periodicals; 388
• DOI: 10.1016/j.jth.2020.100911
• Languages: English
• ISSNs: 2214-1405

Abstract

Abstract: Introduction: Population aging raises many fundamental questions for public health policymakers, one of which is how to address the inequity of medical services for older adults. Geographic information systems (GIS)-based accessibility has been widely employed to measure the inequity of access to healthcare facilities. However, the focus in literature lies generally on spatial patterns; few accessibility studies have focused on temporal inequity. This study focuses on the disparity of the elderly's healthcare inequity (EHI) in both spatial and temporal dimensions. Methods: EHI is measured by the elderly's medical services accessibility (EMSA) scores. Based on a road network analysis with real-time traffic data acquired by a Python-based web crawler, a Gaussian two-step floating catchment area (2SFCA) method is employed to calculate EMSA scores. Sensitivity analysis is presented for three threshold times (i.e., 5, 15, and 30 min) and different intervals of a time of day (TOD) period. Results: In the temporal patterns, the average EMSA ( EMSA-avg ) scores of daily variations vary from 0.0262 to 0.0556 at t 0 = 5 min, from 0.0704 to 0.1073 at t 0 = 15 min, and from 0.1734 to 0.2223 at t 0 = 30 min. Meanwhile, three "low value intervals (LVIs)" exist in TOD period. In the spatial patterns, the areas with frequent traffic congestions or no nearby hospitals are characterized by low-level accessibility for the 5 min catchment, while the same level areas for the 30 min are far from the city centre and equipped with inconvenient public transportation. Conclusions: The findings may help the policymakers in planning the medical service resources for the growing aging population and providing caregivers information for a timely and effective medical treatment. Highlights: We estimated the elderly's healthcare inequity (EHI) in both spatial and temporal dimensions. Real-time road speed data is firstly employed to calculate the temporal elderly's medical services accessibility (EMSA) scores. The EMSA scores were measured with the Gaussian two-step floating catchment area (2SFCA) method. A detailed analysis on the daily variations of EMSA. Public policy implications on improving the delivery of healthcare services for elderly people and reducing EHI has been proposed.