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Abstract
Background
Socioeconomically disadvantaged children are disproportionately affected by oral disease. Mobile dental services help underserved communities overcome barriers to accessing health care, including time, geography, and trust. The NSW Health Primary School Mobile Dental Program (PSMDP) is designed to provide diagnostic and preventive dental services to children at their schools. The PSMDP is mainly targeted toward high-risk children and priority populations. This study aims to evaluate the program’s performance across five local health districts (LHDs) where the program is being implemented.
Methods
The evaluation will use routinely collected administrative data, along with other program-specific data sources, from the district public oral health services to conduct a statistical analysis that determines the reach and uptake of the program, its effectiveness, and the associated costs and cost-consequences. The PSMDP evaluation program utilises data from Electronic Dental Records (EDRs) and other data sources, including patient demographics, service mix, general health, oral health clinical data and risk factor information. The overall design includes cross-sectional and longitudinal components. The design combines comprehensive output monitoring across the five participating LHDs and investigates the associations between socio-demographic factors, service patterns and health outcomes. Time series analysis using difference-in-difference estimation will be conducted across the four years of the program, involving services, risk factors, and health outcomes. Comparison groups will be identified via propensity matching across the five participating LHDs. An economic analysis will estimate the costs and cost-consequences for children who participate in the program versus the comparison group.
Discussion
The use of EDRs for oral health services evaluation research is a relatively new approach, and the evaluation works within the limitations and strengths of utilising administrative datasets. The study will also provide avenues to improve the quality of data collected and system-level improvements to better enable future services to be aligned with disease prevalence and population needs.
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