A5018847156- Dental Health and Care Utilization
- Dental Radiography and Imaging
- Oral microbiology and periodontitis research
- Data Quality and Management
- Electronic Health Records Systems
- Medical Coding and Health Information
- Biomedical Text Mining and Ontologies
- Artificial Intelligence in Healthcare
- Endodontics and Root Canal Treatments
- Opioid Use Disorder Treatment
- AI in cancer detection
- Medical Malpractice and Liability Issues
- Patient Safety and Medication Errors
- Dental Anxiety and Anesthesia Techniques
- Oropharyngeal Anatomy and Pathologies
- Pharmaceutical Practices and Patient Outcomes
- Smoking Behavior and Cessation
- Orthodontics and Dentofacial Orthopedics
- Clinical Reasoning and Diagnostic Skills
- Patient Satisfaction in Healthcare
- Antibiotic Use and Resistance
- Oral Health Pathology and Treatment
- Temporomandibular Joint Disorders
- Dental Research and COVID-19
- HIV/AIDS oral health manifestations
The University of Texas Health Science Center at Houston
2012-2025
Willamette University
2017
The University of Texas at Austin
2016
Few oral health databases are available for research and the advancement of evidence-based dentistry. In this work we developed a centralized data repository derived from electronic records (EHRs) at four dental schools participating in Consortium Oral Health Research Informatics. A multi-stakeholder committee governance framework that encouraged sharing while allowing control contributed data. We adopted i2b2 warehousing platform mapped each institution to common reference terminology....
Few clinical datasets exist in dentistry to conduct secondary research. Hence, a novel dental data repository called BigMouth was developed, which has grown include 11 academic institutions contributing Electronic Health Record on over 4.5 million patients. The primary purpose for is serve as high-quality resource rapidly conducting oral health-related allows assessing the health status of diverse US patient population; provides rationale and evidence new care delivery modes; embraces...
Abstract The present study examined the role of age and sex in outcomes non-surgical periodontal therapy (NSPT). De-identified demographic characteristics patients who presented for baseline evaluation, NSPT, re-evaluation were abstracted from electronic health records. Independent associations with severe periodontitis defined as ≥ 5 mm clinical attachment loss (CAL) 6 probing depth (PD) determined using multinomial logistic regression. null hypothesis was rejected at α < 0.05. A total...
Introduction: In the United States, dentists are one of leading prescribers opioids and antibiotics. Because dental schools training grounds for future dentists, it is crucial to understand how prescribing has changed why these medications being prescribed in academic settings. Objectives: The objective this research was describe trends factors associated with opioid antibiotic medication at US institutions between 2011 2020. Methods: Data from electronic records collected through BigMouth...
Introduction: Oral health mirrors systemic health; yet, few clinics worldwide provide dental care as part of primary medical care, nor are records commonly integrated with records. Objectives: To determine the degree to which misreporting underlying conditions poses problems for clinicians, we assessed 2 common conditions—hypertension and diabetes—at time examination assessment. Methods: Using comparative chart analysis, analyzed a diverse group patients previously seen at University Texas...
Background: Patients may be inadvertently harmed while undergoing dental treatments. To improve care, we must first determine the types and frequency of harms that patients experience, but identifying cases harm is not always straightforward for practices. Mining data from electronic health records a promising means efficiently detecting possible adverse events (AEs). Methods: We developed 7 triggers (electronic record based) to flag patient charts contain distinct common AEs. These were...
A learning health system (LHS) is a in which patients and clinicians work together to choose care on the basis of best evidence drive discovery as natural outgrowth every clinical encounter ensure right at time. An LHS for dentistry now feasible, an increased number oral encounters are captured electronic records (EHRs). The authors used EHRs data track periodontal outcomes 3 large dental institutions. 2 interest were new periodontitis case (for who had not received diagnosis previously)...
Abstract Objectives The purpose of this study was to adapt, test, and evaluate the implementation a primary care “Preventive Screening” meaningful use quality measure for tobacco use, in dental institutions. We determined percentage patients screened users who received cessation counseling. Methods implemented (DQM), three schools large accountable organization. An automated electronic health record (EHR) query identified 18 years older were one or more times within 24 months, counseling...
Temporomandibular disorders and orofacial pain (TMD/OFP) conditions are challenging to diagnose for predoctoral dental students due the multifactorial etiology, complexity, controversial issues surrounding these conditions. The aim of this study was determine if patients in clinic one U.S. school reported existing signs symptoms TMD/OFP, whether diagnosed condition based on symptoms, then treated. a retrospective analysis electronic health record data over three‐year period. results showed...
Abstract Background Longitudinal patient level data available in the electronic health record (EHR) allows for development, implementation, and validations of dental quality measures (eMeasures). Objective We report feasibility validity implementing two eMeasures. The eMeasures determined proportion patients receiving a caries risk assessment (eCRA) corresponding appropriate risk-based preventative treatments at elevated (appropriateness care [eAoC]) academic institutions one accountable...
Our objective was to measure the proportion of patients for which comprehensive periodontal charting, disease risk factors (diabetes status, tobacco use, and oral home care compliance), diagnoses were documented in electronic health record (EHR). We developed an EHR-based quality assess how well four dental institutions disease-related information. An automated database script implemented EHR at each institution. The validated by comparing findings from with a manual review charts.The...
This study aimed to develop a machine-learning model predict the risk for Periodontal Disease (PD) based on nonimage electronic dental records (EDRs).
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, authors designed evaluated 3 novel dental electronic health record-based clinical quality evaluate sealant only after assessing teeth. Measure I recorded proportion patients with who received sealants. II had...
Abstract Objectives This work describes the process by which quality of electronic health care data for a public study was determined. The objectives were to adapt, develop, and implement assessments ( DQAs ) based on National Institutes Health Pragmatic Trials Collaboratory NIHPTC framework within three domains completeness, accuracy, consistency, an investigation into oral disparities preventive program. Methods Electronic record eligible children in dental accountable organization 30...
Abstract Background: Our objective was to measure the proportion of patients for which comprehensive periodontal charting, disease risk factors (diabetes status, tobacco use, and oral home care compliance), diagnoses were documented in electronic health record (EHR). We developed an EHR-based quality assess how well four dental institutions disease-related information. An automated database script implemented EHR at each institution. The validated by comparing findings from with a manual...
Objective This study assessed contributing factors associated with dental adverse events (AEs). Methods Seven electronic health record–based triggers were deployed identifying potential AEs at 2 institutions. From 4106 flagged charts, reviewers examined 439 charts selected randomly to identify and classify using our AE type severity classification systems. Based on information captured in the record, we analyzed harmful assess factors; defined as those that resulted temporary moderate severe...