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

Please always quote using this URN: urn:nbn:de:bvb:20-opus-261228
  • 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 arePurpose 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.show moreshow less

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Metadaten
Author: S. RauchORCiD, H. Taubenböck, C. Knopp, J. Rauh
URN:urn:nbn:de:bvb:20-opus-261228
Document Type:Journal article
Faculties:Philosophische Fakultät (Histor., philolog., Kultur- und geograph. Wissensch.) / Institut für Geographie und Geologie
Language:English
Parent Title (English):International Journal of Health Geographics
Year of Completion:2021
Volume:20
Article Number:31
Source:International Journal of Health Geographics (2021) 20:31. https://doi.org/10.1186/s12942-021-00284-y
DOI:https://doi.org/10.1186/s12942-021-00284-y
Dewey Decimal Classification:9 Geschichte und Geografie / 91 Geografie, Reisen / 910 Geografie, Reisen
Tag:accessibility analysis; high resolution population data; public health
Release Date:2022/04/07
Open-Access-Publikationsfonds / Förderzeitraum 2021
Licence (German):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International