BACKGROUND: Periodontitis (PD), a form of gum disease, is a major public health concern as it is globally prevalent and harms both individual quality of life and economic productivity. Global cost in lost productivity is estimated at US$54 billion an

The present study examined the role of age and sex in the outcomes of non-surgical periodontal therapy (NSPT). De-identified demographic and periodontal characteristics of patients who presented for baseline periodontal evaluation, NSPT, and periodontal re-evaluation were abstracted from electronic health records. Independent associations of age and sex with severe periodontitis defined as ≥ 5 mm clinical attachment loss (CAL) and ≥ 6 mm probing depth (PD) were determined using multinomial logistic regression. The null hypothesis was rejected at α < 0.05. A total of 2866 eligible subjects were included in the analysis. Significantly lower odds of CAL ≤ 4 mm than CAL ≥ 5 mm (reference) were observed in adults aged 35–64 (odds ratio, OR, 0.19; 95% confidence interval, CI 0.13, 0.29) and ≥ 65 years (OR 0.13; 95% CI 0.07, 0.25) compared to those aged 18–34 years. Odds of PD < 4 mm versus PD ≥ 6 mm (reference) were lower in adults aged 35–64 years than those aged 18–34 years (OR 0.71; 95% CI 0.55, 0.90) and higher in females compared to males (OR 1.67; 95% CI 1.14, 2.44). These results suggest more compromised post-NSPT outcomes in older adults and males compared to the respective populations and highlight the need for personalized therapeutic strategies in these populations.

Objective: Health education interventions during pregnancy can influence maternal oral health (OH), maternal OH-behaviors and children’s OH. Interventions that can be delivered at anytime and anywhere, for example mobile-health (mHealth) provides an opportunity to address challenges of health education and support activation of women in underserved and rural communities to modify their health behavior. This pilot study was undertaken as a part of a mHealth initiative to determine knowledge, attitudes, and behaviors related to pregnancy and ECC prevention among women attending obstetrics/gynecology (OB/GYN) practices at a large rurally-based clinic. Methods: A cross-sectional survey study was voluntarily engaged by women (n = 191) aged 18 to 59 years attending OB/GYN visits, over a 3-week period from 12/2019 to 1/2020. Survey results were analyzed applying descriptive statistics, X² and Fisher’s Exact tests. The significance level was set at P < .0001 for all analyses. Results: Approximately half of respondents were between 18 and 29 years (53%), had a college degree (55%), and 100% reported cell phone use. Whereas 53% and 31%, respectively, indicated that they were “somewhat” or “very” sure of how to prevent ECC in their children, only 9% recognized evidence of early decay and 30% did not know the purpose of fluoride. Overall, only 27% of participants correctly answered the knowledge-based questions. Further, only 57% reported their provider explained things in a way that was easy to understand. Only 24% reported seeing a dentist during their current pregnancy. Conclusions: Study results suggested potential gaps in knowledge and behaviors related to ECC prevention and provided baseline data to inform future interventions to improve ECC prevention practices. Notably, majority of participants used their cell phones for making medical/dental appointments and reported using their phones to look up health-related information. This demographic represents a potentially receptive target for mHealth approaches to improve understanding of oral health maintenance during pregnancy and ECC prevention.

Background: Physicians and patient-facing caregivers have increasingly used mobile health (mHealth) technologies in the past several years, accelerating during the COVID-19 pandemic. However, barriers and feedback surrounding adoption remain relatively understudied and varied across health systems, particularly in rural areas. Objective: This study aims to identify provider adoption, attitudes, and barriers toward mHealth in a large, multisite, rural US health care system. We investigated (1) mHealth apps that providers use for their own benefit and (2) mHealth apps that a provider uses in conjunction with a patient. Methods: We surveyed all patient-seeing providers within the Marshfield Clinic Health System with a brief, 16-item, web-based survey assessing attitudes toward mHealth, adoption of these technologies, and perceived barriers faced by providers, their peers, and the institution. Survey results were summarized via descriptive statistics, with log-binomial regression and accompanying pairwise analyses, using Kruskal-Wallis and Jonckheere-Terpstra tests for significance, respectively. Respondents were grouped by reported clinical role and specialty. Results: We received a 38% (n/N=916/2410) response rate, with 60.7% (n=556) of those sufficiently complete for analyses. Roughly 54.1% (n=301) of respondents reported mHealth use, primarily around decision-making and supplemental information, with use differing based on provider role and years of experience. Self-reported barriers to using mHealth included a lack of knowledge and time to study mHealth technologies. Providers also reported concerns about patients’ internet access and the complexity of mHealth apps to adequately use mHealth technologies. Providers believed the health system’s barriers were largely privacy, confidentiality, and legal review concerns. Conclusions: These findings echo similar studies in other health systems, surrounding providers’ lack of time and concerns over privacy and confidentiality of patient data. Providers emphasized concerns over the complexity of these technologies for their patients and concerns over patients’ internet access to fully use mHealth in their delivery of care.

Oral cavity cancer (OCC) is associated with high morbidity and mortality rates when diagnosed at late stages. Early detection of increased risk provides an opportunity for implementing prevention strategies surrounding modifiable risk factors and screening to promote early detection and intervention. Historical evidence identified a gap in the training of primary care providers (PCPs) surrounding the examination of the oral cavity. The absence of clinically applicable analytical tools to identify patients with high-risk OCC phenotypes at point-of-care (POC) causes missed opportunities for implementing patient-specific interventional strategies. This study developed an OCC risk assessment tool prototype by applying machine learning (ML) approaches to a rich retrospectively collected data set abstracted from a clinical enterprise data warehouse. We compared the performance of six ML classifiers by applying the 10-fold cross-validation approach. Accuracy, recall, precision, specificity, area under the receiver operating characteristic curve, and recall–precision curves for the derived voting algorithm were: 78%, 64%, 88%, 92%, 0.83, and 0.81, respectively. The performance of two classifiers, multilayer perceptron and AdaBoost, closely mirrored the voting algorithm. Integration of the OCC risk assessment tool developed by clinical informatics application into an electronic health record as a clinical decision support tool can assist PCPs in targeting at-risk patients for personalized interventional care.