A personalized periodontitis risk based on nonimage electronic dental records by machine learning.

Objective: This study aimed to develop a machine-learning (ML) model to predict the risk for Periodontal Disease (PD) based on nonimage electronic dental records (EDRs).

Methods: By using EDRs collected in the BigMouth repository, dental patients from the US were included. Patients were labeled as cases or controls, based on PD diagnosis, treatment and pocketing.

A retrospective analysis of the role of age and sex in outcomes of non-surgical periodontal therapy at a single academic dental center.

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.

Systematically assessing the quality of dental electronic health record data for an investigation into oral health care disparities.

Objectives: This work describes the process by which the quality of electronic health care data for a public health study was determined. The objectives were to adapt, develop, and implement data quality assessments (DQAs) based on the National Institutes of Health Pragmatic Trials Collaboratory (NIHPTC) data quality framework within the three domains of completeness, accuracy, and consistency, for an investigation into oral health care disparities of a preventive care program.

Methods: Electronic health record data for eligible children in a dental accountable care organization of 30 offices, in Oregon, were extracted iteratively from January 1, 2014, through March 31, 2022.

Designing audit and feedback dashboards for dentists to monitor their opioid prescribing.

Background And Objective: Prescription drug abuse is a major factor leading to drug overdose deaths in the US and dentists are one of the leading prescribers of opioid pain medication. Knowing that Audit & Feedback (A&F) dashboards are an effective tool and are used as quality improvement interventions, we aimed to develop such dashboards personalized for dental providers which could allow them to monitor their own opioid prescribing performance.

Methods: In this paper we report on the process for designing the A&F dashboards for dentists which were developed by using an iterative human-centered design process.

BigMouth: development and maintenance of a successful dental data repository.

Few clinical datasets exist in dentistry to conduct secondary research. Hence, a novel dental data repository called BigMouth was developed, which has grown to include 11 academic institutions contributing Electronic Health Record data on over 4.5 million patients.

Assessing the completeness of periodontal disease documentation in the EHR: a first step in measuring the quality of care.

Background: Our objective was to measure the proportion of patients for which comprehensive periodontal charting, periodontal disease risk factors (diabetes status, tobacco use, and oral home care compliance), and periodontal diagnoses were documented in the electronic health record (EHR). We developed an EHR-based quality measure to assess how well four dental institutions documented periodontal disease-related information. An automated database script was developed and implemented in the EHR at each institution.

Measuring sealant placement in children at the dental practice level.

Background: Although sealants are an established and recommended caries-preventive treatment, many children still fail to receive them. In addition, research has shown that existing measures underestimate care by overlooking the sealable potential of teeth before evaluating care. To address this, the authors designed and evaluated 3 novel dental electronic health record-based clinical quality measures that evaluate sealant care only after assessing the sealable potential of teeth.

Investigating Potential Correlations between Endodontic Pathology and Cardiovascular Diseases Using Epidemiological and Genetic Approaches.

Introduction: Apical periodontitis (AP) and cardiovascular diseases (CVDs) are chronic conditions triggered by an inflammatory process and sharing similar pathogeneses and molecular players. Previous studies have suggested that AP may perpetuate a systemic inflammation state and, in turn, contribute to CVD. In this study, we investigated the potential association between endodontic pathology and CVD using epidemiological and genetic approaches.

Tobacco screening and cessation efforts by dental providers: A quality measure evaluation.

Objectives: The purpose of this study was to adapt, test, and evaluate the implementation of a primary care "Preventive care and Screening" meaningful use quality measure for tobacco use, in dental institutions. We determined the percentage of dental patients screened for tobacco use, and the percentage of tobacco users who received cessation counseling.

Methods: We implemented the dental quality measure (DQM), in three dental schools and a large dental accountable care organization.

Assessing the validity of existing dental sealant quality measures.

Background: Although sealants are highly effective in preventing caries in children, placement rates continue to be low. The authors' goals were to implement and assess the performance of 2 existing sealant quality measures against a manual audit of charts at 4 dental institutions and to identify measurement gaps that may be filled by using data from electronic health records.

Methods: The authors evaluated the performance of 2 quality measures designed for claims-based data: the Dental Quality Alliance (DQA) sealant measure, which includes patients at risk of developing elevated caries, and the Oregon Health Authority (OHA) sealant measure (irrespective of caries risk).

Assessment of Diagnosed Temporomandibular Disorders and Orofacial Pain Conditions by Predoctoral Dental Students: A Pilot Study.

Temporomandibular disorders and orofacial pain (TMD/OFP) conditions are challenging to diagnose for predoctoral dental students due to the multifactorial etiology, complexity, and controversial issues surrounding these conditions. The aim of this study was to determine if patients in the clinic of one U.S.