Operationalizing the oral health experience is an ongoing effort with various clinical and patient-reported outcomes contributing to such conceptualizations. Computational technology has afforded advances in the ability to model complex interactions between various phenomena and provides an opportunity to reconsider the way oral health is conceptualized. High-dimensional vector space modeling is introduced and discussed as a theoretical way to incorporate all relative features associated with understanding oral health, including clinical, patient-reported, and demographic information. Specifically, a novel application of high-dimensional vector space models is proposed as a vehicle to operationalize the 3P model of oral health. Additionally, this paper outlines how this approach can 1) create more precise, person-level characterizations of oral health
2) track oral health over time, offering greater opportunities for behavioral interventions to prevent, mitigate, or treat the negative impacts of dental, oral, and craniofacial diseases
and 3) offer comparisons to dynamically tuned comparison vectors which can define "good" oral health and quantify disparities and features on which to intervene to mitigate them.