CHARE-GD I Subproject 1: Cross-Border Health Data Compass as a Basis for Comparative Studies
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CHARE-GD I Subproject 1: Cross-Border Health Data Compass as a Basis for Comparative Studies
Background of the project
The quality and availability of patient care in the healthcare system in both Germany and the Netherlands varies from region to region. These regional differences in care, together with demographic, socio-economic and natural conditions, overlap with the organisation of two different national healthcare systems to form a complex overall situation. Are there differences in the quality of healthcare between rural and urban regions in the two countries? What is the potential of cross-border care for underserved areas? In order for researchers to answer these and other questions, small-scale data and suitable methods are required. The project aims to lay these foundations.
Investigation of the location typification of hospitals by zones of potential accessibility.
Are there differences in the quality of health care between rural and urban regions? To answer this question, a differentiation of the location of health care facilities is essential. A large part of the relevant literature uses the spatial typology of the “Bundesinstituts für Bau-, Stadt- und Raumforschung“ (BBSR, Federal Institute for Research on Building, Urban Affairs and Spatial Development) for this purpose. The present work looks at the population structures in the catchment areas of German hospitals by means of the BBSR spatial types. The analysis of the potential catchment areas indicates that the classification of BBSR location types can only be used to a limited extent in the context of health care research in peripheral regions.
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You can find this study here: https://gispoint.de/fileadmin/user_upload/paper_gis_open/AGIT_2022/537728011.pdf
Specht, Sebastian; Schnack, Helge; Krauskopf, Jan Elmar; Hein, Andreas (2022) Untersuchung der Lage-Typisierung von Krankenhäusern durch Zonen potenzieller Erreichbarkeit. In: AGIT ‒ Journal für Angewandte Geoinformatik, 8-2022. doi.org/10.14627/537728011