PURPOSE:To evaluate the relationship between receipt of a 5,000 ppm sodium fluoride dentifrice prescription and time to first dental restoration in a population of older adults. METHODS:Electronic dental records of patients aged ≥ 65 years who received a caries risk assessment at their initial comprehensive examination between 2009 and 2019 were analyzed to assess differences in the time to first restoration between patients who received a 5,000 ppm sodium fluoride dentifrice prescription and those who did not. Multivariable Cox regression was used to evaluate the time to first restoration after the caries risk assessment, controlling for covariates of interest. RESULTS:The dataset included 3,741 participants, of whom 48% were women and 77% were self-pay. In the final multivariable Cox regression model generated using the Bayesian Information Criterion for variable selection, having a 5,000 ppm sodium fluoride dentifrice prescription within 14 days after the caries risk assessment (HR 1.16, 95% CI 1.00-1.36), having 5 or more teeth with caries (HR 1.30, 95% CI 1.18-1.45), not having a dental home (HR 1.29, 95% CI 1.16-1.44), and eating > 3 snacks per day (HR 1.23, 95% CI 1.10-1.39), were the most important predictors of a faster time to first restoration. CONCLUSION:This study identified having a prescription for high-fluoride dentifrice, number of teeth with caries, not having a dental home, and eating > 3 snacks per day as being associated with greater hazard of first restoration among older adult patients seeking comprehensive care in a dental school clinic.

PURPOSE/OBJECTIVES:To compare characteristics of patients seeking comprehensive versus urgent care at a university dental school clinic, particularly regarding self-reported history of primary care provider (PCP) visits in the previous year. METHODS:In this retrospective chart review, electronic data were collected from patients seen at the admissions clinic between 2016 and 2021. Patients were dichotomized based on their choice of comprehensive care (CC) versus urgent care (UC). Univariate, bivariate, and multivariable statistical analyses were conducted. RESULTS:Among approximately 28,000 patients, 57% sought CC while 43% sought UC. From 2016 to 2021, the proportion of patients seeking CC increased steadily from 52% to 63%. In multivariable analyses comparing patients who chose CC versus UC, the variables most strongly associated with being in the UC group were: not having seen a PCP in the year prior to the dental appointment (OR = 1.67, 95% CI = 1.52-1.83), being 25-44 years old (OR = 1.21, 95% CI = 1.08-1.36), being self-pay (OR = 1.41, 95% CI = 1.27-1.57), having blood pressure values in the prehypertensive, Hypertensive I, or Hypertensive II stage (OR = 1.25, 1.47, 2.05 respectively; 95% CI = 1.13-1.38, 1.28-1.68, 1.52-2.76, respectively), and being obese Class III (OR = 1.46, 95% CI = 1.25-1.70). CONCLUSIONS:Patients who sought urgent care were more likely to report not having seen a PCP in the previous year compared to patients who chose CC, after controlling for important confounding variables. Possible clinical and educational implications are discussed.

Introduction and aims Healthcare access in low- and middle-income countries (LMICs) is constrained by structural and socio-cultural barriers, including language. Oral health, despite its importance to general health, is often overlooked in universal health coverage efforts. The Oral Health Impact Profile (OHIP-5) is a brief patient-reported outcome measure (PROM) for oral health–related quality of life (OHRQoL) but has not been adapted into indigenous Nigerian languages. This study aimed to translate and evaluate the Yoruba version (OHIP-5Yor), assess its psychometric performance using both English and Yoruba administrations, and explore its relevance for improving patient-centred oral healthcare access in LMICs. Methods A cross-sectional survey of 143 adults was conducted at two dental centres in Ibadan, Nigeria. The OHIP-5 was translated using a forward–backward approach with pilot testing. Psychometric evaluation included internal consistency, inter-item correlation, convergent validity, and confirmatory factor analysis. Results Of the 143 participants, 52 completed the Yoruba version and 91 the English version. The mean OHIP-5 score was 6.6 ± 4.3. The instrument showed acceptable internal consistency (Cronbach’s α = 0.67) and supportive construct validity. Structural validity indices, however, indicated that the factorial structure requires further evaluation in larger and more diverse samples. Conclusions The findings provide preliminary support for the reliability and validity of the OHIP-5Yor as a culturally adapted tool for assessing OHRQoL among Nigerian adult dental patients. Beyond psychometric evaluation, the instrument may help address an important equity gap by enabling non-English speakers to participate more fully in oral health assessment, thereby supporting patient–clinician communication and highlighting unmet needs. Incorporation of such tools into routine care and public health surveillance represents a potential, scalable approach to strengthening oral healthcare access in low- and middle-income countries (LMICs). Clinical relevance The OHIP-5Yor enables brief, culturally appropriate assessment of patient-perceived oral health impacts and may support more equitable oral healthcare delivery in multilingual settings.

BACKGROUND:Smokeless tobacco (SLT) use is a major public health problem in many parts of the world, including India. Despite this, smokeless tobacco often doesn't receive enough attention. The aim of this study was to assess the pH, moisture, nicotine levels, and warning labels on smokeless tobacco products sold in Pondicherry, India. METHODS AND MATERIAL:Ten SLT samples, procured despite the ban in Pondicherry, were analysed. The selection criteria were based on availability, reflecting the diverse range of SLT products. pH levels, moisture content, and nicotine concentrations were measured using validated analytical methods recommended by World Health Organization (WHO). Warning labels were evaluated for compliance with regulatory standards. STATISTICAL ANALYSIS:Descriptive statistics were used. Pearson's correlation test was employed to examine the relationship between pH, moisture, and amount of nicotine. A P value of <0.05 was considered significant. RESULTS:The pH values of the SLT samples ranged from 5.09 to 10.46. Moisture content varied significantly, with percentages from 5.48% to 33.44%. Nicotine concentrations ranged from 0.63 mg/g to 35.74 mg/g. A moderate positive correlation was found between moisture content and nicotine levels (r = 0.672, P < 0.05), while a strong negative correlation was observed between pH and nicotine content (r = -0.849, P < 0.01). The analysis of warning labels revealed inconsistent adherence to regulatory standards, with many packages lacking comprehensive health warnings. CONCLUSION:The pH, moisture, and nicotine content of the products varied widely among the products. The warning signs were only present in the English language.

Purpose: This study aimed to investigate the predictors of survival of non-occlusal non-incisal glass-ionomer restorations as a surrogate for root surface restorations among older adults. Methods: In a retrospective cohort analysis using the University of Iowa College of Dentistry electronic dental records, we included 721 patients aged 65+whoreceived 2+surface non-occlusal non-incisal glass ionomer restorations placed from January 2005 - December 2011. Restorations were followed until September2017 or until they were deemed to have failed. Results: At baseline, participants' mean age was 77.6 +/- 8.2 years, and 45.8%were females. Most patients were self-pay (65.2%). Most restorations were placed by residents and dental students (82.7%) and included only two surfaces (95.6%).About half (49.1%) failed during follow-up, with a median survival time of3.7 years. The time ratio for lower incisors compared to other teeth was 0.6(p=.006), for three-and-four-surface restorations compared to two was 0.7(p=.007), for faculty as providers compared to residents and students was 1.4(p=.039), and for the Geriatric & Special Needs Clinic compared to others was 0.8 (p=.013). Time ratios less than one indicate association with shorter durations for restorations, and time ratios greater than one indicate association with longer durations for restorations. Conclusion: Tooth type, number of restored surfaces, provider type, and clinic were all significant factors associated with survival of these restorations.

Objectives To predict the dental caries outcomes in young adults from a set of longitudinally-obtained predictor variables and identify the most important predictors using machine learning techniques.Methods This study was conducted using the Iowa Fluoride Study dataset. The predictor variables - sex, mother's education, family income, composite socio-economic status (SES), caries experience at ages 9, 13, and 17, and the cumulative estimates of risk and protective factors, including fluoride, dietary, and behavioral variables from ages 5-9, 9-13, 13-17, and 17-23 were used to predict the age 23 D2+MFS count. The following machine learning models (LASSO regression, generalized boosting machines (GBM), negative binomial (NegGLM), and extreme gradient boosting models (XGBOOST)) were compared under 5-fold cross validation with nested resampling techniques.Results The prevalence of cavitated level caries experience at age 23 (mean D2+MFS count) was 4.75. The predictive analysis found LASSO to be the best performing model (compared to GBM, NegGLM, and XGBOOST), with a root mean square error (RMSE) of 0.70, and coefficient of determination (R2) of 0.44. After dichotomization of the predicted and observed values of the LASSO regression, the classification results showed accuracy, precision, recall, and ROC AUC of 83.7%, 85.9%, 93.1%, 68.2%, respectively. Previous caries experience at age 13 and age 17 and sugar-sweetened beverages intakes at age 13 and age 17 were found to be the four most important predictors of cavitated caries count at age 23.Conclusion Our machine learning model showed high accuracy and precision in the prediction of caries in young adults from a longitudinally-obtained predictor variables. Our model could, in the future, after further development and validation with other diverse population data, be used by public health specialists and policy-makers as a screening tool to identify the risk of caries in young adults and apply more targeted interventions. However, data from a more diverse population are needed to improve the quality and generalizability of caries prediction.

Objectives This study investigates longevity of glass ionomer restorations in an older adult population. Methods This was a retrospective study based on clinical records. Patient records for 3,665 restorations in 1,777 adults 65 or older who had received a restoration between 12th July 2016 and 20th October 2022 were extracted from the electronic dental records system of the University of Iowa College of Dentistry and Dental Clinics. The data were analyzed to determine the influence of patient factors and restorative material on restoration longevity. Single variable and multiple variable survival models were created. Results Many variables that showed a statistically significant influence on restoration longevity in the single variable survival models and did not show such an influence in the multivariable model, indicating the effect of these variables is explained when other factors are controlled for. In particular, patient age at the time of restoration showed no significant influence in the multivariable model, and no medical factor had a statistically significant influence. The restorative material did show a significant influence in the multivariable model; using the resin-modified glass ionomer restorative (Fuji II LC) as a reference, the conventional glass ionomer restorative (Fuji IX) had a hazard ratio of 2.0 (p = 0.011), and the coated-conventional glass ionomer restorative (Equia) had a hazard ratio of 2.8 (p < 0.001). Significance Resin-modified glass ionomer restorations may have superior longevity for older adults than conventional and coated-conventional glass ionomer restorations.

AIMS:Edentulism is an incapacitating condition, and its prevalence is unequal among different population groups in the United States (US) despite its declining prevalence. This study aimed to investigate the current prevalence, apply Machine Learning (ML) Algorithms to investigate factors associated with complete tooth loss among older US adults, and compare the performance of the models.METHODS:The cross-sectional 2020 Behavioral Risk Factor Surveillance System (BRFSS) data was used to evaluate the prevalence and factors associated with edentulism. ML models were developed to identify factors associated with edentulism utilizing seven ML algorithms. The performance of these models was compared using the area under the receiver operating characteristic curve (AUC).RESULTS:An overall prevalence of 11.9% was reported. The AdaBoost algorithm (AUC = 84.9%) showed the best performance. Analysis showed that the last dental visit, educational attainment, smoking, difficulty walking, and general health status were among the top factors associated with complete edentulism.CONCLUSION:Findings from our study support the declining prevalence of complete edentulism in older adults in the US and show that it is possible to develop a high-performing ML model to investigate the most important factors associated with edentulism using nationally representative data.

Objective:To determine the dental caries trajectories over the life course (from age 9 to 23) using an unsupervised machine learning approach.Methods:This is a longitudinal study of caries trajectories over a life course using data from 1,382 individuals from the Iowa Fluoride Study birth cohort. The trajectory analysis of caries in the permanent dentition at ages 9, 13, 17 and 23 was performed using the unsupervised machine learning algorithm known as K-means for Longitudinal Data (KmL), a k-means based clustering algorithm implemented in R specifically designed for analyzing longitudinal data. The trajectory grouping was performed by assessing the distances of the individual trajectories from the centroid and the prediction of the "best" partition was performed based on the Calinsky & Harabatz criterion. The number of cluster partitions assessed was 2 to 6. The number of re-runs with different starting conditions for each number of clusters was 20.Results:The trajectory analysis identified three trajectory groups with 70.5%, 21.1%, and 8.4% of participants in the low, medium, and high caries trajectory groups, respectively. The mean D2+MFS counts of the low caries trajectory groups at ages 9, 13, 17, and 23 were 0.23, 0.37, 1.10, and 1.56, respectively. The mean D2+MFS counts of the medium caries trajectory groups at ages 9, 13, 17, and 23 were 0.92, 2.09, 6.24, and 9.55, respectively. The mean D2+MFS counts of the high caries trajectory groups at ages 9, 13, 17, and 23 were 1.49, 4.80, 12.91, and 22.52, respectively. There were steeper increases in the D2+MFS scores of the three trajectory groups between age 13 and 17, with less steep but also strongly positive slopes from age 17 to 23, suggesting that the period from age 13 to 17 is the highest risk period.Conclusion:There was an increase in the trajectory slopes after age 13 which might be due to changes in risk factors. The next step in this study will be to identify those factors that predict trajectory group membership by modeling their relationships using supervised machine learning techniques.

A multisystem phenotype with the Triad of bodily pain, psychological distress, and sleep disturbance was found to have high risk for developing initial onset of painful temporomandibular disorders (TMDs) in the multicenter Orofacial Pain: Prospective Evaluation and Risk Assessment dataset. In this study, we systemically examined phenotypic characteristics and explored potential pathophysiology in quantitative sensory testing and autonomic nervous system domains in this multisystem Triad phenotype. Secondary analysis was performed on 1199 non-Triad and 154 Triad TMD-free Orofacial Pain: Prospective Evaluation and Risk Assessment enrollees at baseline. Results indicated that before developing TMDs, the Triad phenotype demonstrated both orofacial and systemic signs and symptoms that can only be captured through multisystem assessment. In addition, we found significantly lower resting heart rate variability and higher resting heart rate in the Triad phenotype as compared with the non-Triad group. However, pain sensitivity measured by quantitative sensory testing was not different between groups. These findings highlight the importance of whole-person multisystem assessment at the stage before developing complex pain conditions, such as TMDs, and suggest that, in addition to a "tissue damage monitor," pain should be considered in a broader context, such as a component within a "distress monitoring system" at the whole-person level when multisystem issues copresent. Therefore, the presence or absence of multisystem issues may carry critical information when searching for disease mechanisms and developing mechanism-based intervention and prevention strategies for TMDs and related pain conditions. Cardiovascular autonomic function should be further researched when multisystem issues copresent before developing TMDs.

BACKGROUND:Nursing home (NH) residents seek care at dental offices, yet many of them are at the end of life. The uncertain life expectancy further complicates the care of NH residents. This study aimed to develop and validate a Nursing Home Mortality Index (NHMI) to identify NH residents in the last year of life.METHODS:Logistic modeling was used to develop predictive models for death within 1 year after initial appointment by utilizing the new patient examination data and mortality data of 903 Minnesota NH residents. The final model was selected based on areas under the curve (AUC) and then validated using data from 586 Iowa NH residents. Based on the final model, the NHMI was developed with the estimated 1-year mortality for the low, medium and high risk group.RESULTS:One-year mortalities were 21% and 26% in the development and validation cohorts, respectively. Predictors included age, gender, communication capacity, physical mobility, congestive heart failure, peripheral vascular disease, cancer, cerebrovascular disease, chronic renal disease and liver disease. AUCs for the development and validation models were 0.73 and 0.68, respectively. For the validation cohort, the sensitivity and specificity were 0.79 and 0.53, respectively. The estimated 1-year mortality risks for three risk groups were 0%-10%, 11%-19%, and ≥20%, respectively CONCLUSION: The high mortality rate of NH residents following a dental exam highlighted a need to incorporate patients' prognoses in treatment planning along with normative needs and patients' preferences. The NHMI provides a practical way to guide treatment decisions for end-of-life NH residents.

Developing measurements for assessing oral health-related quality of life (OHRQoL) in children presents unique challenges.Oral health is greatly influenced by age, resulting in notable differences in OHRQoL between children and adults.While numerous tools exist for measuring adult OHRQoL, this complexity hinders the creation of suitable measurement instruments tailored to children and adolescents.However, developing instruments specifically for these younger populations enables researchers to pinpoint and explore OHRQoL factors unique to them, such as self-image, social acceptance, and the school environment.This paper aims to provide a concise overview of instruments designed to assess the OHRQoL in children.

We consider a regression modeling of the quantiles of residual life, remaining lifetime at a specific time. We propose a smoothed induced version of the existing non-smooth estimating equations approaches for estimating regression parameters. The proposed estimating equations are smooth in regression parameters, so solutions can be readily obtained via standard numerical algorithms. Moreover, the smoothness in the proposed estimating equations enables one to obtain a robust sandwich-type covariance estimator of regression estimators aided by an efficient resampling method. To handle data subject to right censoring, the inverse probability of censoring distribution is used as a weight. The consistency and asymptotic normality of the proposed estimator are established. Extensive simulation studies are conducted to validate the proposed estimator’s performance in various finite samples settings. We apply the proposed method to dental study data evaluating the longevity of dental restorations.

AIMTo assess the association between receipt of different types of dental procedures and mortality among nursing home residents.METHODS AND RESULTSBetween June 2006 and March 2008, 535 nursing home residents received a health screening assessment and were offered comprehensive dental care. Death certificate data were obtained in September 2013 and multivariable regression models were generated to assess the effect of dental procedures delivered after the screening assessment on mortality, adjusting for demographic and health-related covariates. Residents had a mean age of 85.2 years at baseline and approximately 30% were edentulous. About two-thirds received at least one dental procedure, and about 88% had died, between the screening date and the end of follow-up. Among dentate residents, after adjustment for relevant covariates, for each one-unit increase in the number of intervals during which they received at least one preventive dental procedure there was a 13% decrease in mortality (HR = 0.87, 95% CI = 0.78-0.98) at any given time, while for prosthetic dental procedures there was a 16% decrease in mortality (HR = 0.84, 95% CI = 0.72-0.97). Among edentulous residents, only prosthetic procedures were analyzed, and they were not significantly associated with mortality.CONCLUSIONAmong dentate institutionalized elderly, receipt of preventive or prosthetic dental procedures was associated with decreased mortality.

OBJECTIVE:To evaluate the influence of surgery start time (SST) and other patient- and therapy-related variables on the risk for early implant failure (EIF) in an academic setting.MATERIAL AND METHODS:Data were extracted from the electronic health records of 61 patients who had at least one EIF and 140 age- and gender-matched, randomly selected, non-EIF controls. Bivariate and multivariable analyses were performed to identify relevant associations between EIF and different variables, such as SST.RESULTS:Incidence of EIF was not significantly associated with SST (HR: 1.9 for afternoon implant placement, 95% CI: 0.9-3.9; p = .105). Other factors that were associated with a significantly increased risk for EIF in a multivariable model were pre-placement ridge augmentation (HR: 7.5, 95% CI: 2.2-25.1; p = .001), intra-operative complications (HR: 5.9, 95% CI: 2.2-16.3; p < .001), simultaneous soft tissue grafting (HR: 5.03, 95% CI: 1.3-19.5; p = .020), simultaneous bone grafting (HR: 3.7, 95% CI: 1.6-8.8; p = .002), and placement with sedation (HR: 3.4, 95% CI: 1.5-7.5; p = .002).CONCLUSIONS:While SST was not associated with the occurrence of EIF in our cohort, other variables, such as ridge augmentation prior to implant placement, simultaneous bone or soft tissue grafting, intra-operative complications, implant placement with sedation, and number of implants in the oral cavity, were associated with an increased risk for this adverse event.

Purpose/aim: To analyze potential factors associated with levels of selected oral pathogens, as well as total aerobic bacterial species, among nursing home residents. Materials and methods: Nursing home residents were divided into three groups (G1 included people with teeth but no dentures, G2 included people with teeth and dentures, and G3 included people with no teeth and with dentures). All participants had microbiological samples collected from their oral cavity and dentures. Counts of total aerobic bacterial species, Porphyromonas gingivalis, Fusobacterium nucleatum, Actinomyces viscosus, Aggregatibacter actinomycetemcomitans, and Candida albicans were compared among groups using the Wilcoxon rank sum test. A multivariate analysis was also performed to control other available covariates. Results: Bivariate analysis revealed significant differences among the groups, and multivariate analysis showed that sex, the presence of natural teeth, denture wearing, oral hygiene indices, and systemic health conditions were associated with bacterial and Candida albicans log counts. Conclusions: Presence of natural teeth and denture wearing, as well as oral hygiene, sex and systemic health conditions were associated with bacterial and Candida albicans log counts among nursing home residents.

BACKGROUND:Temporomandibular disorders (TMD) risk assessment is difficult in general dentistry owing to the complexity of multifactorial risk contributions and the lack of standardized education. The authors explored a health history-based chairside risk assessment.METHODS:Secondary data analysis was performed on the Orofacial Pain: Prospective Evaluation and Risk Assessment data set. Potential demographic, systemic, and local risk contributors were conceptualized into 10 risk categories. Multivariate Cox proportional hazards modeling with backward selection was applied. Variables with P values < .05 were kept in each successive model.RESULTS:The analysis included data from 2,737 participants. The final model indicated that people with any psychological conditions, pain disorders, sleep disorders, or orofacial symptoms were at elevated risks of developing first-onset TMD. Results of post hoc analysis showed the coexistence of conditions from multiple body systems conferred greater risk of developing TMD.CONCLUSIONS:Coexisting conditions and symptoms from multiple body systems substantially increase the risk of developing TMD pain. Therefore, multisystem risk assessment and interprofessional collaborations are important for the prevention of TMD.PRACTICAL IMPLICATIONS:Dentists should include psychological conditions, pain disorders, sleep disorders, and orofacial symptoms when assessing patients' risk of developing TMD pain.

PURPOSE/AIM To investigate factors associated with self-reported dry mouth (xerostomia) among older adults seeking dental care at a University clinic. MATERIALS AND METHODS A query was performed in the electronic records database and de-identified data were collected from patients aged 65 + recorded on the date that the initial health history was entered. Among these patients, data about patients' medications, gender, age, BMI, tobacco use, alcohol addiction, diabetes, heart disease, joint replacement, allergies to medications, hypertension, and mental disorders were obtained. Evaluation of potential risk factors for dry mouth was performed using univariate and multivariable logistic regression analyzes (alpha = 0.05). RESULTS A total of 11,061 subjects were included in the analysis, 51.5% of whom were women. The mean age in years was 74.2 ± 7.0, the median number of medications was 7 (IQR = 4-11), and 38.5% of the participants reported dry mouth. The multivariable logistic regression analysis revealed that the odds of xerostomia for subjects who took 11 +, 7-10, or 4-6 medications were 3.34, 2.07, or 1.38 times those of subjects who had took 0-3 medications, respectively. CONCLUSION Number of medications showed a strong and dose-dependent association with xerostomia.

Background A key challenge for improving the quality of health care is to be able to use a common framework to work with patient information acquired in any of the health and life science disciplines. Patient information collected during dental care exposes many of the challenges that confront a wider scale approach. For example, to improve the quality of dental care, we must be able to collect and analyze data about dental procedures from multiple practices. However, a number of challenges make doing so difficult. First, dental electronic health record (EHR) information is often stored in complex relational databases that are poorly documented. Second, there is not a commonly accepted and implemented database schema for dental EHR systems. Third, integrative work that attempts to bridge dentistry and other settings in healthcare is made difficult by the disconnect between representations of medical information within dental and other disciplines’ EHR systems. As dentistry increasingly concerns itself with the general health of a patient, for example in increased efforts to monitor heart health and systemic disease, the impact of this disconnect becomes more and more severe. To demonstrate how to address these problems, we have developed the open-source Oral Health and Disease Ontology (OHD) and our instance-based representation as a framework for dental and medical health care information. We envision a time when medical record systems use a common data back end that would make interoperating trivial and obviate the need for a dedicated messaging framework to move data between systems. The OHD is not yet complete. It includes enough to be useful and to demonstrate how it is constructed. We demonstrate its utility in an analysis of longevity of dental restorations. Our first narrow use case provides a prototype, and is intended demonstrate a prospective design for a principled data backend that can be used consistently and encompass both dental and medical information in a single framework. Results The OHD contains over 1900 classes and 59 relationships. Most of the classes and relationships were imported from existing OBO Foundry ontologies. Using the LSW2 ( LISP Semantic Web ) software library, we translated data from a dental practice’s EHR system into a corresponding Web Ontology Language (OWL) representation based on the OHD framework. The OWL representation was then loaded into a triple store, and as a proof of concept, we addressed a question of clinical relevance – a survival analysis of the longevity of resin filling restorations. We provide queries using SPARQL and statistical analysis code in R to demonstrate how to perform clinical research using a framework such as the OHD, and we compare our results with previous studies. Conclusions This proof-of-concept project translated data from a single practice. By using dental practice data, we demonstrate that the OHD and the instance-based approach are sufficient to represent data generated in real-world, routine clinical settings. While the OHD is applicable to integration of data from multiple practices with different dental EHR systems, we intend our work to be understood as a prospective design for EHR data storage that would simplify medical informatics. The system has well-understood semantics because of our use of BFO-based realist ontology and its representation in OWL. The data model is a well-defined web standard.