|Publication type:||Conference paper|
|Type of review:||Peer review (abstract)|
|Title:||A three-step floating catchment area method to quantify the spatial accessibility of healthcare facilities for citizens|
|Conference details:||15th biennal NECTAR Conference, Helsinki, Finland, 5-7 June 2019|
|Subjects:||Health care; Spatial accessibility; Spatial distribution; Land use; Floating catchment area; Health care services|
|Subject (DDC):||362: Health and social services|
|Abstract:||The provision of good health care services to citizens is of increasing importance to improve their health and well-being. These services include, amongst others, general practitioners, specialists and ambulant or stationary hospital facilities. Besides the quality of the facilities itself (personnel, equipment), their supply (e.g. capacity) and proximity (temporal/spatial) are key for patients. Spatial accessibility is a well-established concept that combines the above factors, i.e. land-use components (supply, demand) and transport components (e.g. travel times) in an integrated way. When it comes to health care accessibility, models that take into account both supply and potential demand, i.e. competition, are of growing interest, both in academia and practice. The supply-side comprehends e.g. the available capacity of a facility, whereas the demand consists of the number of people in an area which (potentially) might use this facility. The proximity to facilities is usually captured by some mode-specific deterrence function that depends on travel time and calibration parameters. In this paper, a method to assess the spatial accessibility of health care services with competing facilities will be outlined. The model belongs to the family of so-called FCA models (Floating Catchment Areas), which considers the potential demand by facility-specific catchment areas. The output is, unlike in standard gravity models, well interpretable (e.g. in terms of physicians per person) and communicable. Hence it shall provide a transparent basis for decision-makers. We demonstrate the applicability of our approach by some examples of health care services using real-world data for selected urban areas in Northern Switzerland. The main focus is here to determine areas that are under- or over-supplied. Together with other information, the knowledge of such critical areas together with the extent of differences might help to develop appropriate policies to reduce inequalities and of improving the well-being of the citizens.|
|Fulltext version:||Published version|
|License (according to publishing contract):||Not specified|
|Departement:||School of Engineering|
|Organisational Unit:||Institute of Data Analysis and Process Design (IDP)|
|Appears in collections:||Publikationen School of Engineering|
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