Risk and space: modelling the accessibility of stroke centers using day- & nighttime population distribution and different transportation scenarios

Abstract

Purpose Rapid accessibility of (intensive) medical care can make the difference between life and death. Initial care in case of strokes is highly dependent on the location of the patient and the traffic situation for supply vehicles. In this methodologically oriented paper we want to determine the inequivalence of the risks in this respect. Methods Using GIS we calculate the driving time between Stroke Units in the district of Münster, Germany for the population distribution at day- & nighttime. Eight different speed scenarios are considered. In order to gain the highest possible spatial resolution, we disaggregate reported population counts from administrative units with respect to a variety of factors onto building level. Results The overall accessibility of urban areas is better than in less urban districts using the base scenario. In that scenario 6.5% of the population at daytime and 6.8% at nighttime cannot be reached within a 30-min limit for the first care. Assuming a worse traffic situation, which is realistic at daytime, 18.1% of the population fail the proposed limit. Conclusions In general, we reveal inequivalence of the risks in case of a stroke depending on locations and times of the day. The ability to drive at high average speeds is a crucial factor in emergency care. Further important factors are the different population distribution at day and night and the locations of health care facilities. With the increasing centralization of hospital locations, rural residents in particular will face a worse accessibility situation.

Access to paediatric oncology centres in Switzerland: Disparities across rural–urban and Swiss‐foreigners cohorts

“…To create the routable network, we used an approach for OpenStreetMap data, based on maximum speeds ( V max ) and surrounding population density (Bundesinstitut für Bau‐ Stadt‐ und Raumforschung im Bundesamt für Bauwesen und Raumordnung, 2019 ; Rauch et al, 2021 ). OSM has large gaps in the presentation of V max in Switzerland (approx.…”

“…First, we compared access in rural, intermediate and urban areas, as categorised by the Swiss Federal Statistical Office (2014). Second, we compared Swiss citizens' versus foreign residents' access to PPCs.To create the routable network, we used an approach for Open-StreetMap data, based on maximum speeds (V max ) and surrounding population density (Bundesinstitut für Bau-Stadt-und Raumforschung im Bundesamt für Bauwesen und Raumordnung, 2019;Rauch et al, 2021). OSM has large gaps in the presentation of V max in Switzerland (approx.…”

Potential crowdedness of mechanical thrombectomy and cerebral infarction mortality in Japan: Application of inverted two-step floating catchment area method

“…A variety of studies have indicated options to shorten the time from stroke onset to reperfusion, such as cooperative method (9), workflows in hospitals (10,11), rapid diagnoses (12), and public awareness campaigns (13). However, infrastructure and human resources such as spatial accessibility (14)(15)(16), facilities (i.e., the number of beds, equipment), and human resources (17) are critical. Optimization of supply against demand is a crucial issue because the allocation of facilities and human resources affects the onset-to-reperfusion time in stroke.…”

An equity and efficiency integrated grid-to-level 2SFCA approach: spatial accessibility of multilevel healthcare

“…Meanwhile, classic 2SFCA models have not taken the universal coverage of multilevel healthcare in a large region and extreme long-distance healthcare seeking behavior into account because of the limitation of the inefficient repetitive computing. Moreover, different modes of transportation have gained the attention of many scholars, but the estimation of hospitalization time based on assumed speeds would still bias accessibility, especially in densely populated areas [ 32 ]. How to integrate real-time travel distances into 2SFCA algorithm models and calculate the corresponding hospitalizing weight in further experimental studies is still in process [ 23 ].…”