Travel patterns for government emergency dental care in Australia: a new approach using GIS tools

Abstract

Background: Government subsidized dental care is provided as a community safety-net to complement the private dental sector. The aim of this study was to detail the geographic catchment characteristics of three outer metropolitan government dental clinics. Methods: Three outer metropolitan dental clinics with the greatest number of geocoded triage patients were selected for the study. In total these three facilities had 5742 patients over the 12-week period with 2010 at clinic A, 1278 at clinic B and 2454 at clinic C. Cumulative proportions of patients' residential address locations at distances were calculated; there was close correlation between the three clinics. A best fit curve with a correlation coefficient of 0.998 was developed. Results: In summary, approximately 50% of patients were within 6 km of the clinic and 75% were within 10 km. Conclusions: This study has critical outcomes for the planning of future services in developing a network model for care. The data presented will assist in the development of more evidence-based approaches to planning new service network structures.

Application of geographic information systems and simulation modelling to dental public health: Where next?

“…There have been many GIS‐based studies in dental public health since the 1960s. These have covered a wide range of topics, including: dentist to patient ratios and payments; service usage and access to services and amenities; spatial variations in oral health outcomes; dental workforce numbers and utilization rates; the spatial patterning of dental services; the effects of interventions; and contextual level influences on oral health …”

“…These studies have used many different GIS‐related methods, including: the use of concentric circles, which indicate the radii from a defined point for a certain phenomenon (eg, service coverage); Voronoi polygons, whose boundaries define areas closest to a given point, relative to all other points; the use of Census and deprivation data to distinguish areas based on sociodemographic characteristics; buffer zones used to delineate the coverage areas of services; Euclidean (or straight line) distances between locations; transportation times and station locations; thematic mapping of oral health; point based location data to compare the locations of dental services to social phenomena; human cartograms, which depict geographical areas relative to a given variable other than land mass; geographical data on interventions; and the study of nested geographical data through multilevel modelling …”

“…Such work has allowed researchers and dental public health practitioners to understand the role of spatial variation (or “place”) in: differences in dentist to patient ratios and associated payments; dental service usage by school children; access to dental services; oral cancer; dental trauma; tooth decay; dentist shortages and areas in need of new facilities; dental workforce numbers and potential shortfalls; the clustering of dental services based on location quotients; and the effects of interventions on children's oral health; as well as important contextual level pathways to oral health outcomes and the effects of a number of neighbourhood‐based features …”

“…There have been many GIS-based studies in dental public health since the 1960s. These have covered a wide range of topics, including: dentist to patient ratios and payments 14,15 ; service usage and access to services and amenities 9,[16][17][18][19][20] ; spatial variations in oral health outcomes 10,21,22 ; dental workforce numbers and utilization rates [23][24][25] ; the spatial patterning of dental services [26][27][28][29] ; the effects of interventions 30 ; and contextual level influences on oral health. [31][32][33] These studies have used many different GIS-related methods, including: the use of concentric circles, 14,15 which indicate the radii from a defined point for a certain phenomenon (eg, service coverage); Voronoi polygons, 16 whose boundaries define areas closest to a given point, relative to all other points; the use of Census and deprivation data to distinguish areas based on sociodemographic characteristics [16][17][18][19] ; buffer zones used to delineate the coverage areas of services 18,19 ; Euclidean (or straight line) distances between locations 18 ; transportation times and station locations 26,27 ; thematic mapping of oral health 10,21,22 ; point based location data to compare the locations of dental services to social phenomena 9,[17][18]…”

“…[31][32][33] These studies have used many different GIS-related methods, including: the use of concentric circles, 14,15 which indicate the radii from a defined point for a certain phenomenon (eg, service coverage); Voronoi polygons, 16 whose boundaries define areas closest to a given point, relative to all other points; the use of Census and deprivation data to distinguish areas based on sociodemographic characteristics [16][17][18][19] ; buffer zones used to delineate the coverage areas of services 18,19 ; Euclidean (or straight line) distances between locations 18 ; transportation times and station locations 26,27 ; thematic mapping of oral health 10,21,22 ; point based location data to compare the locations of dental services to social phenomena 9,[17][18][19]28 ; human cartograms, which depict geographical areas relative to a given variable other than land mass 28 ; geographical data on interventions 30 ; and the study of nested geographical data through multilevel modelling. [31][32][33] Such work has allowed researchers and dental public health practitioners to understand the role of spatial variation (or "place") in: differences in dentist to patient ratios and associated payments 14,15 ; dental service usage by school children 16 ; access to dental services 9,[17][18][19]29 ; oral cancer 10 ; dental trauma 21 ; tooth decay 22 ; dentist shortages and areas in need of new facilities 20 ; dental workforce numbers …”