Employing AI tools to predict features for dental care use in the United States during the global respiratory illness outbreak

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Oral health is strongly associated with overall health. Prior research has demonstrated the benefits of regular dental visits to prevent initiation and progression of systemic diseases such as diabetes and cardiovascular diseases (Macek MD & Tomar SL, 2009;Hardon L, et al., 2023). Prior research has also demonstrated the impacts of dental treatments such as scaling, and root planning on reductions in chronic inflammation which can further help in managing chronic conditions like diabetes (Santas VR et al., 2009). The American Dental Association recommends routine visits to a dentist once or twice a year for children, adults and older adults to manage overall health (1,2). Some individuals may need to visit a dentist more than twice a year to maintain good oral health and overall health (1). Despite these recommendations, access to dental care in the United States (U.S.) has long been a critical public health issue, with only half of the U.S. population over the age of two having ever accessed dental care (3) and 72 million or approximately 27% of adults not having dental insurance (CareQuest Institute of Oral Health, 2025). Moreover, there is socioeconomic gradient in access to oral health in the U.S. (Sanders AE et al., 2006). Increasing levels of income and education are associated with higher frequency of annual dental care visits on a population level. That is, those with higher income and higher education are more likely to have dental insurance which is a key factor for access to routine and timely dentist visits.Additionally, even among those with higher socio-economic status, gaps in oral health and dental care access continue to exist, as these challenges are influences by broader structural issues within the health care system and by factors such as transportation and housing conditions (Broomhead T, Baker SR 2023; Northridge ME et al., 2020).Factors related to low-income status, race, ethnicity, and rural status have further contributed to the lack of, and variability of dental care access thereby contributing to poor oral health outcomes (4,5). Challenges in accessing dental public health services have been associated with the exacerbation of systemic health ailments, including multimorbidity, diabetes, heart and lung disease, dementia, arthritis and complications during pregnancy among ethnically and culturally diverse populations (5)(6)(7). As such, these pronounced disparities in access to, quality of, and affordability of routine primary oral healthcare have impacted a wide range of communities, particularly those with disabilities, dual-eligible, and racial and/or ethnic minority populations who face a greater burden of health disparities (8)(9)(10)(11). In a recent study, those with a low-income status and less than high school education reported higher unmet dental needs than their more affluent and educated counterparts (11). When comparing population groups, Black/African and Hispanic/Latino Americans have reported higher levels of untreated dental disease compared to White Americans (11) In the context of the recent pandemic of 2020-2022, these disparities were further compounded due to urgent oral treatments taking precedence over routine visits (12). This shift resulted in a notable decrease in oral healthcare utilization in the U.S. by 18 million users in the first year of the pandemic, with lasting repercussions and a gradual, slow recovery to prepandemic levels (12). While research has been done on what factors and obstacles in healthcare were associated with barriers to dental visits before 2020 (8)(9)(10)(11), much less has been examined regarding the factors associated with decline in dental care utilization beyond age-related survey stratifications of dental visits during the peak of the global public health crisis in 2021 (12). A study examined dental utilization and oral conditions from 2019-2020 using Electronic Health Records (EHRs) from federally qualified health centers in the U.S. and found visits to dental care providers decreased more in comparison to other health providers during the shelter-in-pace orders during the 2020-2021 (13). Another study found 47% of respondents delayed visiting a dentist for dental check-ups, pain, and for seeking care for planned treatment during the recent pandemic of 2020-2022 (14).Although these studies provided meaningful insights into oral health disparities and access to care issues, the barriers can be further studied by utilizing comprehensive survey datasets and using AI models that would help identify and uncover complex, non-linear relationships between confounding factors that traditional statistical methods may overlook. The statistical methods have been widely used in prior research and limited research has employed Al models on U.S. federal nationally representative survey datasets, a gap we identified. Therefore, to address this gap, our study examines dental care utilization during the second year of the pandemic by applications of multiple AI/ML models to uncover complex, interacting social and health determinants that are not easily captured through traditional statistical approaches.Our aims for this data report were to examine the major contributors that drive oral healthcare visits and identify barriers that have limited access during the pandemic using the nationally representative Medical Expenditure Panel Survey (MEPS). Specifically, the objectives were to (1) demonstrate how Al approaches can be used with nationally representative survey data; (2) provide preliminary findings from multiple Al models regarding top factors associated with dental services utilization in the U.S. using feature importance; and (3) identify to which extent these factors vary across different Al models. To achieve these objectives, multiple AI models were utilized to process and analyze the MEPS dataset. By leveraging AI tools, preliminary findings were identified regarding the top factors for dental visits in the U.S. along with the extent to which these factors vary across AI models.In this data report, we describe the dataset, outline the analytic workflow, and present key modelderived findings rather than developing or testing any causal hypotheses.We used the cross-sectional Medical Expenditure Panel Survey data spanning year 2021.The data report utilizes the nationally representative MEPS, the most comprehensive data collected from American households on healthcare use, costs (including out-of-pockets from self/family, healthcare expenditures and payments to public and private payers), and health insurance coverage in the U.S. MEPS includes information on dental insurance, including on health and dental service use for the American households. Importantly, in recent years MEPS has been oversampling certain population groups and collecting demographic and social factors and satisfaction with care. MEPS has been oversampling Hispanics, Blacks, and Asians, as well as low-income households, to improve the precision and reliability of estimates for these groups. This is because these groups are underrepresented in a standard national sample, and oversampling allows researchers to have a statistically significant sample size for detailed analysis of their healthcare utilization and expenditures. The primary sponsor for MEPS is the For this data report, the MEPS full-year consolidated household file, HC-233, from the 2021 calendar year (the second year of the pandemic) was analyzed. Person-level de-identified fullyear household consolidated file MEPS data on healthcare utilization was used, with a focus on predictive factors. These factors include sociodemographic factors such as age, gender, race/ethnicity, socioeconomic factors such as education, household income, and enabling factors such as dental insurance, health behaviors, such as smoking status for dental visits during 2021.The National Institute on Minority Health and Health Disparities (NIMHD) and the National Institute

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