Factors influencing dentists’ willingness to treat Medicaid-enrolled adolescents

Objectives: To identify factors influencing dentists’ willingness to treat Medicaid-enrolled adolescents with intellectual and developmental disabilities in Washington state. Data sources: Primary data were collected by a survey instrument administered in 2017 to general and pediatric dentists who were Medicaid providers (N = 512). Methods: We administered a 40-item survey, which included 20 hypothetical scenarios involving a 12-year-old Medicaid-enrolled adolescent. Based on the characteristics of the potential patient, dentists were asked to rate their willingness to treat (1 = very likely; 5 = very unlikely). We used conjoint analytic techniques to examine the relative importance of six adolescent- and family-level factors (e.g., severity of intellectual and/or developmental disability [IDD], sugar intake, toothbrushing, caregiver beliefs about fluoride, restorative needs, appointment keeping) and state Medicaid reimbursement level (35 percent, 55 percent, 85 percent of usual, customary, and reasonable amount). Analyses focused on data from 178 dentists with complete and varied responses to the scenarios. Results: The mean age of participants was 53.8 ± 10.5 years and 10.7 percent were pediatric dentists. The holdouts correlation statistics indicated excellent fit for the conjoint model (Pearson’s R = 0.99, P < 0.0001; Kendall’s tau = 0.89, P < 0.0001). Reimbursement level and appointment keeping were the most important factors in dentists’ willingness to treat Medicaid-enrolled adolescents (importance scores of 26.7 and 25.7, respectively). Restorative needs, caregiver beliefs about fluoride, and IDD severity were the next most important (importance scores of 15.4, 10.6, and 8.1, respectively). Sugar intake and toothbrushing behaviors were the least important. Conclusions: Reimbursement and appointment keeping were the most important determinants of dentists’ willingness to treat Medicaid-enrolled adolescents with IDD

The transition from amalgam to other restorative materials in the U.S. predoctoral pediatric dentistry clinics

Increased concerns about the safety of amalgam restorations in children have resulted in many dental schools emphasizing the teaching of alternative dental materials. This study investigated the current teaching of different dental materials for use in posterior teeth in the United States predoctoral pediatric dentistry programs. In 2011, the authors invited the chairs of the predoctoral pediatric dentistry departments in all accredited dental schools at that time (N = 57) to participate in an internet‐based survey. Descriptive statistics were calculated to describe the frequency of using different restorative materials. Regression models were developed to explore the factors related to the use of dental restorations in predoctoral pediatric clinics. Among the 44 dental schools that responded (77% response rate), 74% used amalgam, and 93% used composite in primary posterior teeth. Glass ionomer was used by 61% of the schools in primary posterior teeth. Placing amalgam in primary posterior teeth was associated with programs that treated more 3–5‐year‐old patients (β = .302, p < .043), whereas the use of glass ionomer was associated with having students serving at off‐site satellite dental clinics (β = .015, p < .012). In general, having departments with chairs who had positive attitudes towards Minimal Invasive Dentistry (MID) used composite (β = .091, p < .0001) and glass ionomer (β = 103, p < .0001) more frequently and were less likely to use amalgam (β = −.077, p < .005) in primary posterior teeth. Although teaching MID concepts in predoctoral pediatric clinics in dental schools is increasing, the use of amalgam in posterior primary and permanent teeth is still widely practiced.This project was funded by NIH/NIDC R T32 Grant DEO 14678‐06

Reopening Dental Offices for Routine Care Amid the COVID-19 Pandemic: Report From Palestine

Objectives: This study reports on the readiness of Palestinian dentists to reopen their practices for routine care during the current coronavirus disease 2019 (COVID-19) pandemic. Methods: A cross-sectional study targeted dentists in the West Bank area of Palestine using an online survey during the first 2 weeks of May 2020. Questions mainly asked about dentists’ perception of the risks of COVID-19, readiness to reopen their clinics for routine care, and the level of confidence in dealing with patients suspected of having COVID-19. Results: A total of 488 dentists completed the survey. Almost 60% believed that they were not ready to reopen their practices. Almost 13% had “no confidence” in dealing with patients with COVID-19, while 64% had “little to moderate” confidence. Confidence was correlated negatively with increased fear of becoming infected (r = -0.317, P < .0001) and positively with years of practice (r = 1.7, P < .0001). Dentists who received updated training on infection control or on COVID-19 reported higher levels of confidence (x2 = 53.8, P < .0001, x2 = 26.8, P < .0001, respectively). Although 88% preferred not to treat patients with COVID-19, 40% were willing to provide care to them. Almost 75% reported that they were already facing financial hardships and could not survive financially until the end of the current month. Conclusions: Ethical and financial reasons were the main drivers for dentists in this sample to reopen their practices for routine care. Data from this study highlights the fragility of private dental practice in emergency situations. Ethical, health, and financial challenges that emerged during COVID-19 require dentists to adapt and be better prepared to face future crises.This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sector

Teaching Atraumatic Restorative Treatment in U.S. Dental Schools: A Survey of Predoctoral Pediatric Dentistry Program Directors

The International Dental Federation and World Health Organization have promoted the use of Atraumatic Restorative Treatment (ART) in modern clinical settings worldwide. In the United States, the practice of ART is not believed to be widely used, which may be a result of little attention given to ART training in predoctoral pediatric dentistry curricula in U.S. dental schools. This study investigated the extent of clinical and didactic instruction on ART provided in U.S. dental schools by surveying the predoctoral pediatric dentistry programs in 2010. Of the fifty-seven directors asked to complete the survey, forty-four responded for a response rate of 77 percent. Of these forty-four programs, 66 percent reported providing clinical training on ART, though only 14 percent provide this training often or very often. The types of ART training provided often or very often included interim treatment (18 percent) and single-surface cavities (14 percent) in primary teeth. However, ART was said to be rarely taught as a definitive treatment in permanent teeth (2 percent). Attitude was a major predictor, for clinical training provided and using professional guidelines in treatment decisions were associated with a positive attitude towards ART. These predoctoral pediatric dentistry programs used ART mainly in primary, anterior, and single-surface cavities and as interim treatment. As ART increases access of children to dental care, the incorporation of the ART approach into the curricula of U.S. dental schools should be facilitated by professional organizations.This project was funded by NIH/NIDC R T32 Grant DEO 14678-06

Predicting dentists decisions: a choice-based conjoint analysis of Medicaid participation

Objectives: Private practice dentists are the major source of care for the dental safety net; however, the proportion of dentists who participate in state Medicaid programs is low, often due to poor perceptions of the program’s administration and patient population. Using a discrete choice experiment and a series of hypothetical scenarios, this study evaluated trade-offs dentists make when deciding to accept Medicaid patients. Methods: An online choice-based conjoint survey was sent to 272 general dentists in Iowa. Hypothetical scenarios presented factors at systematically varied levels. The primary determination was whether dentists would accept a new Medicaid patient in each scenario. Using an ecological model of behavior, determining factors were selected from the categories of policy, administration, community, and patient population to estimate dentists’ relative preferences. Results: 62 percent of general dentists responded to the survey. The probability of accepting a new Medicaid patient was highest (81 percent) when reimbursement rates were 85 percent of the dentist’s fees, patients never missed appointments, claims were approved on first submission, and no other practices in the area accepted Medicaid. Although dentists preferred higher reimbursement rates, 56 percent would still accept a new Medicaid patient when reimbursement decreased to 55 percent if they were told that the patient would never miss appointments and claims would be approved on initial submission. Conclusions: This study revealed trade-offs that dentists make when deciding to participate in Medicaid. Findings indicate that states can potentially improve Medicaid participation without changing reimbursement rates by making improvements in claims processing and care coordination to reduce missed appointments.Funding for this project came from an Innovation Fund for Oral Health award from the DentaQuest Foundation (Boston, MA)

Reported Adverse Effects and Attitudes among Arab Populations Following COVID-19 Vaccination: A Large-Scale Multinational Study Implementing Machine Learning Tools in Predicting Post-Vaccination Adverse Effects Based on Predisposing Factors

Background: The unprecedented global spread of coronavirus disease 2019 (COVID-19) has imposed huge challenges on the healthcare facilities, and impacted every aspect of life. This has led to the development of several vaccines against COVID-19 within one year. This study aimed to assess the attitudes and the side effects among Arab communities after receiving a COVID-19 vaccine and use of machine learning (ML) tools to predict post-vaccination side effects based on predisposing factors. Methods: An online-based multinational survey was carried out via social media platforms from June 14 to 31 August 2021, targeting individuals who received at least one dose of a COVID-19 vaccine from 22 Arab countries. Descriptive statistics, correlation, and chi-square tests were used to analyze the data. Moreover, extensive ML tools were utilized to predict 30 post vaccination adverse effects and their severity based on 15 predisposing factors. The importance of distinct predisposing factors in predicting particular side effects was determined using global feature importance employing gradient boost as AutoML. Results: A total of 10,064 participants from 19 Arab countries were included in this study. Around 56% were female and 59% were aged from 20 to 39 years old. A high rate of vaccine hesitancy (51%) was reported among participants. Almost 88% of the participants were vaccinated with one of three COVID-19 vaccines, including Pfizer BioNTech (52.8%), AstraZeneca (20.7%), and Sinopharm (14.2%). About 72% of participants experienced post-vaccination side effects. This study reports statistically significant associations (p < 0.01) between various predisposing factors and post-vaccinations side effects. In terms of predicting post-vaccination side effects, gradient boost, random forest, and XGBoost outperformed other ML methods. The most important predisposing factors for predicting certain side effects (i.e., tiredness, fever, headache, injection site pain and swelling, myalgia, and sleepiness and laziness) were revealed to be the number of doses, gender, type of vaccine, age, and hesitancy to receive a COVID-19 vaccine. Conclusions: The reported side effects following COVID-19 vaccination among Arab populations are usually non-life-threatening; flu-like symptoms and injection site pain. Certain predisposing factors have greater weight and importance as input data in predicting post-vaccination side effects. Based on the most significant input data, ML can also be used to predict these side effects; people with certain predicted side effects may require additional medical attention, or possibly hospitalization