Impact of traffic on the spatiotemporal variations of spatial accessibility of emergency medical services in inner-city Shanghai

Hu, Wenyan; Tan, Jinfeng; Li, Mengya; Wang, Jun; Wang, Fahui

doi:10.1177/2399808318809711

Cited by 20 publications

(29 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Residences are adopted here to represent the scenes (i.e. patient origins), which is a common option in assessing potential spatial access to EMS in the lack of real EMS run data [2,17,33]. The data used in this research consist of 1,172 local communities (often called Shequ in China), 41 EMS stations and 53 definitive care facilities (equivalent to hospitals in Wuhan).…”

Section: Study Area and Datamentioning

confidence: 99%

“…All three aforementioned types of methods have been widely adopted to measure healthcare access in a variety of contexts (e.g. [5,7,17,38]).…”

mentioning

confidence: 99%

“…[20]), or by using transportation simulation models (e.g. [17]) that fail to capture the variations in travel time resulting from real traffic conditions which undoubtedly is crucial to EMS. Whilst distance is constant, the time taken to cover it is clearly and heavily influenced by traffic levels and speed which have extreme diurnal variation.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Spatiotemporal access to emergency medical services in Wuhan, China: accounting for scene and transport time intervals

et al. 2020

View full text Add to dashboard Cite

Background Access as a primary indicator of Emergency Medical Service (EMS) efficiency has been widely studied over the last few decades. Most previous studies considered one-way trips, either getting ambulances to patients or transporting patients to hospitals. This research assesses spatiotemporal access to EMS at the shequ (the smallest administrative unit) level in Wuhan, China, attempting to fill a gap in literature by considering and comparing both trips in the evaluation of EMS access. Methods Two spatiotemporal access measures are adopted here: the proximity-based travel time obtained from online map services and the enhanced two-step floating catchment area (E-2SFCA) which is a gravity-based model. First, the travel time is calculated for the two trips involved in one EMS journey: one is from the nearest EMS station to the scene (i.e. scene time interval (STI)) and the other is from the scene to the nearest hospital (i.e. transport time interval (TTI)). Then, the predicted travel time is incorporated into the E-2SFCA model to calculate the access measure considering the availability of the service provider as well as the population in need. For both access measures, the calculation is implemented for peak hours and off-peak hours. Results Both methods showed a marked decrease in EMS access during peak traffic hours, and differences in spatial patterns of ambulance and hospital access. About 73.9% of shequs can receive an ambulance or get to the nearest hospital within 10 min during off-peak periods, and this proportion decreases to about 45.5% for peak periods. Most shequs with good ambulance access but poor hospital access are in the south of the study area. In general, the central areas have better ambulance, hospital and overall access than peripheral areas, particularly during off-peak periods. Conclusions In addition to the impact of peak traffic periods on EMS access, we found that good ambulance access does not necessarily guarantee good hospital access nor the overall access, and vice versa.

show abstract

Section: Study Area and Datamentioning

confidence: 99%

“…All three aforementioned types of methods have been widely adopted to measure healthcare access in a variety of contexts (e.g. [5,7,17,38]).…”

mentioning

confidence: 99%

See 1 more Smart Citation

Spatiotemporal access to emergency medical services in Wuhan, China: accounting for scene and transport time intervals

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Traditional studies look towards subjectively choosing specific travel modes (F. Wang, 2012), but an increasing number of scholars have begun to improve accessibility models considering the influence of different transport modes (Dony, Delmelle, & Delmelle, 2015). Travel impedance data can be accessed from open data sources (García-Albertos, Picornell, Salas-Olmedo, & Gutiérrez, 2018;Weiss et al, 2018), including individual trip survey data (Mao & Nekorchuk, 2013), web mapping service (Google Maps (Dony et al, 2015), Baidu Maps (Tao, Yao, Kong, Duan, & Li, 2018), Amap Maps (Zhou, Ding, Wu, Huang, & Hu, 2019)) and location-based social media data (T. Zhang et al, 2018), which enable advancements in revealing the characteristics of human activities (Huang, Levinson, Wang, Zhou, & Wang, 2018;Y. Liu et al, 2015;Xu et al, 2016).…”

Section: Residential Transport Mode Choices With Multimodal Transportmentioning

confidence: 99%

“…Xia et al, 2019). Spatiotemporal accessibility (STA), as one of the foremost directions of accessibility research, takes into account space and time indicators to evaluate the effectiveness of public services, including healthcare services (T. Xia et al, 2019), social amenities (Widener, Farber, Neutens, & Horner, 2015), and emergency services (Wenyan Hu, Tan, Li, Wang, & Wang, 2018).…”

Section: Introductionmentioning

confidence: 99%

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

Zhou¹,

Li²,

Chen³

et al. 2020

Preprint

View full text Add to dashboard Cite

Background: Healthcare accessibility research is developing towards a focus on multimodal transport modes (MTM) and spatiotemporal variation. Dynamic traffic conditions lead residents to make distinct traveling decisions in different timepoints, which has an impact on the spatiotemporal accessibility of healthcare. Pediatric clinic services (PCS) are one of the typical healthcare services that require a diagnosis through a professional physician clinic.Results: This paper aims to examine a methodological framework for the spatiotemporal accessibility of PCS (STA-PCS) and obtains its spatiotemporal variation characteristics. We design a spatial time impedance of multimodal transport modes (STI-MTM) model, which considers residential transport mode choices and adopt a gravity model based on web mapping data and population spatial distribution data to measure STA-PCS. We selected Nanjing, China, as the study area to estimate the STA-PCS value at four timepoints. The results indicate that the spatial aggregate of PCS is evident, and dynamic traffic factors influence the volatility of STA-PCS.Conclusions: This work holds pragmatic implications for policymakers on the STA-PCS considered travel characteristics based on georeferenced social media data.

show abstract

Time-varying spatial accessibility of primary healthcare services based on spatiotemporal variations in demand, supply, and traffic conditions: A case study of Seoul, South Korea

Kim

KWON

2022

Journal of Transport & Health

View full text Add to dashboard Cite

Impact of traffic on the spatiotemporal variations of spatial accessibility of emergency medical services in inner-city Shanghai

Cited by 20 publications

References 27 publications

Spatiotemporal access to emergency medical services in Wuhan, China: accounting for scene and transport time intervals

Spatiotemporal access to emergency medical services in Wuhan, China: accounting for scene and transport time intervals

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

Time-varying spatial accessibility of primary healthcare services based on spatiotemporal variations in demand, supply, and traffic conditions: A case study of Seoul, South Korea

Contact Info

Product

Resources

About