ArticleJournal of dental research2025
System Dynamics Modeling of Caries Severity States in Long-Term Care.
Article in Journal of dental research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
8 authors.
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Abstract
Dental caries among long-term care (LTC) residents is a persistent and complex problem driven by social and structural factors. Systems thinking may be useful in considering novel approaches to reducing disease. This study aimed to develop a system dynamics model to simulate the progression of dentate older adults in LTC through caries severity states and estimate the effects of 3 intervention scenarios on the progression of caries: preventive topical fluoride (TF), arrest of caries with silver diamine fluoride (SDF), and a combination of TF and SDF. Dentate older adults in LTC were categorized into 4 caries severity states by their number of untreated carious lesions. The model assumed that changes in severity states were consistent with incidence rates reported in the literature and available billing data for dental care and that individuals move in and out of the system by entering and exiting the facility or experiencing edentulism. For all scenarios, the proportion of dentate older adults in LTC with 1 or more untreated lesions stays stable, the distribution of disease shifts from a high severity state, and the system approaches equilibrium after 4 y. The TF intervention predicts minimal impacts on decreasing the proportion of dentate older adults with 1 or more untreated lesions (2.5% decrease), while the SDF intervention and the combination interventions were most disruptive. There was a 29.6% and 33.6% decrease, respectively. Given the specific population dynamics in LTC, these findings suggest that long-term (greater than 4 y) interventions should be designed to address both the management of existing lesions and their incidence. This system dynamics model allows researchers to render institution-specific data points from LTCs to estimate the effects of proposed interventions at the respective site.
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