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Updated: Feb 15, 2026

Accuracy in Dental Medicine, A New Way to Measure Trueness and Precision
Published on: April 29, 2014
A resource reallocation model for school dental screening: taking advantage of teledentistry in low-risk areas
Mohamed Estai1, Stuart M Bunt2, Yogesan Kanagasingam3
1International Research Collaborative-Oral Health and Equity: School of Human Science, University of Western Australia, Crawley, WA, Australia.
Objective:
To estimate the scale of resource transfer that could be achieved by screening low-risk schoolchildren using teledentistry rather than using traditional visual dental examination.
Methods:
This study was based on a previous cost-minimisation study that compared the costs of two dental-screening approaches (visual and teledentistry). The data for the population of children 5-14 years of age was obtained from the Australian Bureau of Statistics and was divided across Australia according to statistical local area (SA2). The cost models (for teledentistry and visual screening) for each SA2 relative to the state, Remoteness Area (RA) and Socio-Economic Index for Area (SEIFA) indexes were estimated. The geographical information system was used to superimpose modelled cost data on the geographical map to provide a visual presentation of the data. Resource transfer scenarios, based on risk minimisation, were then developed and analysed.
Results:
This study demonstrated a suboptimal allocation of dental-care resources, such that children living in high socio-economic areas (major cities) with low disease burdens consuming half of the estimated resources of a universal visual dental screening system. The findings suggest that utilising teledentistry screening for low-risk children has the potential to free up $40 million per annum. Such resources can be reallocated to increase care access and improve the quality of dental services for vulnerable children.
Conclusion:
To reduce inequalities in dental health within a community, scarce health-care resources should be targeted at the population at most risk. These findings can be used to inform policymakers, guide the appropriate distribution of scarce resources and target dental services to benefit high-need children.
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