Routine Data Analyses for Estimating the Caries Treatment Experience of Children

Abstract

Oral health surveys are considered the gold standard for assessing the caries experience of children. Analyses of routine data offer additional opportunities not yet fully explored. This study aimed at estimating the caries treatment experience by mining an insurance claims database. Comprehensive claims data sets were extracted from the data warehouse of a major health insurance company (BARMER, Germany). A surrogate variable for caries experience was formed that reflected the proportion of children without any former potentially caries-related treatment (filling, root canal treatment, and extraction) at ages from 1 to 14 years. The statistical calculations were based on Kaplan-Meier survival analyses. The evaluation for the permanent dentition comprised N = 593,330 children at 6 years and N = 114,568 at 12 years. At 12 years of age, 66.8% had not yet experienced potentially caries-related treatments. This value hints at a significantly higher caries experience at 12 years compared to available epidemiological data. For the deciduous dentition, the respective rates were 74.0% at 6 years and 45.8% at 10 years. Although various sources of bias have to be taken into account, the potential of routine data mining is evident. The approach is supplemental to oral health surveys. It can be useful in coming closer to reality when estimating the caries experience of children. From our results, we conclude that the oral health of up to 14-year-olds in Germany remains in urgent need of improvement.