Alfa Yansane

Dental clinical research: an illustration of the value of standardized diagnostic terms

Abstract Objective Secondary data are a significant resource for in‐depth epidemiologic and public health research. It also allows for effective quality control and clinical outcomes measurement. To illustrate the value of structured diagnostic entry, a use case was developed to quantify adherence to current practice guidelines for managing chronic moderate periodontitis (CMP). Methods Six dental schools using the same electronic health record (EHR) contribute data to a dental data repository (BigMouth) based on the i2b2 data‐warehousing platform. Participating institutions are able to query across the full repository without being able to back trace specific data to its originating institution. At each of the three sites whose data are included in this analysis, the Dental Diagnostic System (DDS) terminology was used to document diagnoses in the clinics. We ran multiple queries against this multi‐institutional database, and the output was validated by manually reviewing a subset of patient charts. Results Over the period under study, 1,866 patients were diagnosed with CMP. Of these, 15 percent received only periodontal prophylaxis treatment, 20 percent received only periodontal maintenance treatment, and only 41 percent received periodontal maintenance treatment in combination with other AAP guideline treatments. Conclusions Our results showed that most patients with CMP were not treated according to the AAP guidelines. On the basis of this use case, we conclude that the availability and habitual use of a structured diagnosis in an EHR allow for the aggregation and secondary analyses of clinical data to support downstream analyses for quality improvement and epidemiological assessments.

Evaluating quality of dental care among patients with diabetes: Adaptation and testing of a dental quality measure in electronic health records

BACKGROUND Patients with diabetes are at increased risk of developing oral complications, and annual dental examinations are an endorsed preventive strategy. The authors evaluated the feasibility and validity of implementing an automated electronic health record (EHR)-based dental quality measure to determine whether patients with diabetes received such evaluations. METHODS The authors selected a Dental Quality Alliance measure developed for claims data and adapted the specifications for EHRs. Automated queries identified patients with diabetes across 4 dental institutions, and the authors manually reviewed a subsample of charts to evaluate query performance. After assessing the initial EHR measure, the authors defined and tested a revised EHR measure to capture better the oral care received by patients with diabetes. RESULTS In the initial and revised measures, the authors used EHR automated queries to identify 12,960 and 13,221 patients with diabetes, respectively, in the reporting year. Variations in the measure scores across sites were greater with the initial measure (range, 36.4-71.3%) than with the revised measure (range, 78.8-88.1%). The automated query performed well (93% or higher) for sensitivity, specificity, and positive and negative predictive values for both measures. CONCLUSIONS The results suggest that an automated EHR-based query can be used successfully to measure the quality of oral health care delivered to patients with diabetes. The authors also found that using the rich data available in EHRs may help estimate the quality of care better than can relying on claims data. PRACTICAL IMPLICATIONS Detailed clinical patient-level data in dental EHRs may be useful to dentists in evaluating the quality of dental care provided to patients with diabetes.

Quantitative evaluation of maxillary alveolar cortical bone thickness and density using computed tomography imaging

Introduction Primary stability is essential to the success of orthodontic mini‐implants (OMIs) and heavily depends on the mechanical retention between OMIs and their supporting bone. Alveolar cortical bone commonly serves as the supporting bone for OMIs during treatment. The purposes of this study were to characterize alveolar cortical bone thickness and density in the maxilla and to explore patient factors that may significantly affect these bone properties. Methods Sixty medical computed tomography scans of the maxilla were analyzed from a selected sample of patients seen at the Radiology Department of Boston Childrens Hospital. Interradicular alveolar bone thickness and density were measured at 2, 4, 6, and 8 mm from the buccal and palatal alveolar bone crests using the Synapse 3D software (version 4.1; FUJIFILM Medical Systems USA, Stamford, Conn). Analyses were conducted with STATA /1C (version 12.0 for Windows; StataCorp, College Station, Tex) using multivariate mixed‐effects regression models and paired t tests. Results Mean age and body mass index of the study sample were 17.88 years and 22.94 kg/m2, respectively. Cortical bone density and thickness significantly increased from the coronal (2 mm) to the apical (8 mm) regions of the alveolar bone (P <0.05). At 8 mm from the alveolar crest, interradicular buccal cortical bone was thickest (1 mm) and densest (1395 Hounsfield units) between the first and second molars. On the palatal side, the thickest bone (1.15 mm) was found between the canine and first premolar; it was similarly densest (1406 Hounsfield units) between the first premolar and canine, and between the first premolar and second premolar interradicular bones. On average, palatal cortical bone was thicker and denser compared with buccal; this difference was statistically significant (P <0.01) in the anterior and middle maxilla, with the anterior maxillary region showing the greatest difference. Female subjects have significantly denser bone compared with male subjects; however, sex is not significantly associated with bone thickness. Body mass index and age are positively associated with bone thickness and density. Radiologic absence of bone was more commonly seen in the anterior maxilla. Conclusions Alveolar bone properties vary in the maxilla in patterns that could guide clinicians in selecting sites best suited for placement of OMIs. HighlightsWe quantified maxillary alveolar cortical bone properties using medical CT.Bone density and thickness increased apically away from the alveolar crest.On average, palatal cortical bone is denser and thicker than buccal bone.Patient factors are significantly associated with bone properties.Patterns exist in the distribution of alveolar bone properties in the maxilla.

Vaccine Hesitancy and Online Information: The Influence of Digital Networks:

Aims. This article analyzes the digital childhood vaccination information network for vaccine-hesitant parents. The goal of this study was to explore the structure and influence of vaccine-hesitant content online by generating a database and network analysis of vaccine-relevant content. Method. We used Media Cloud, a searchable big-data platform of over 550 million stories from 50,000 media sources, for quantitative and qualitative study of an online media sample based on keyword selection. We generated a hyperlink network map and measured indegree centrality of the sources and vaccine sentiment for a random sample of 450 stories. Results. 28,122 publications from 4,817 sources met inclusion criteria. Clustered communities formed based on shared hyperlinks; communities tended to link within, not among, each other. The plurality of information was provaccine (46.44%, 95% confidence interval [39.86%, 53.20%]). The most influential sources were in the health community (National Institutes of Health, Centers for Disease Control and Prevention) or mainstream media (New York Times); some user-generated sources also had strong influence and were provaccine (Wikipedia). The vaccine-hesitant community rarely interacted with provaccine content and simultaneously used primary provaccine content within vaccine-hesitant narratives. Conclusion. The sentiment of the overall conversation was consistent with scientific evidence. These findings demonstrate an online environment where scientific evidence online drives vaccine information outside of the vaccine-hesitant community but is also prominently used and misused within the robust vaccine-hesitant community. Future communication efforts should take current context into account; more information may not prevent vaccine hesitancy.

Feasibility of Electronic Health Record–Based Triggers in Detecting Dental Adverse Events

BACKGROUND We can now quantify and characterize the harm patients suffer in the dental chair by mining data from electronic health records (EHRs). Most dental institutions currently deploy a random audit of charts using locally developed definitions to identify such patient safety incidents. Instead, selection of patient charts using triggers and assessment through calibrated reviewers may more efficiently identify dental adverse events (AEs). OBJECTIVE Our goal was to develop and test EHR-based triggers at four academic institutions and find dental AEs, defined as moderate or severe physical harm due to dental treatment. METHODS We used an iterative and consensus-based process to develop 11 EHR-based triggers to identify dental AEs. Two dental experts at each institution independently reviewed a sample of triggered charts using a common AE definition and classification system. An expert panel provided a second level of review to confirm AEs identified by sites reviewers. We calculated the performance of each trigger and identified strategies for improvement. RESULTS A total of 100 AEs were identified by 10 of the 11 triggers. In 57% of the cases, pain was the most common AE identified, followed by infection and hard tissue damage. Positive predictive value (PPV) for the triggers ranged from 0 to 0.29. The best performing triggers were those developed to identify infections (PPV = 0.29), allergies (PPV = 0.23), failed implants (PPV = 0.21), and nerve injuries (PPV = 0.19). Most AEs (90%) were categorized as temporary moderate-to-severe harm (E2) and the remainder as permanent moderate-to-severe harm (G2). CONCLUSION EHR-based triggers are a promising approach to unearth AEs among dental patients compared with a manual audit of random charts. Data in dental EHRs appear to be sufficiently structured to allow the use of triggers. Pain was the most common AE type followed by infection and hard tissue damage.

Influence of the Posterior Mandible Ridge Morphology on Virtual Implant Planning

PURPOSE The purpose of this study was to examine the anatomy of the mandibular posterior region to develop an anatomical categorization for implant-prosthodontic planning. MATERIALS AND METHODS Using cone beam computed tomography scans, 313 cross-sectional views of edentulous posterior mandibular sites were evaluated with respect to the anatomical ridge morphology. Virtual implant planning was performed, and the need for bone grafting was assessed. The level of complexity for planning implants in those positions was assessed. Sites were classified as straightforward, advanced, or complex sites based on the need for bone grafting. RESULTS Five well-defined cross-sectional configurations were observed: straight (53.6%), oblique (26.2%), s-shape (7.4%), hourglass shape (1.9%), and basal bone (10.8%). There was a statistically significant association between the ridge shape and the feasibility of placing an implant with or without bone grafting; the straight and oblique ridge shapes were more likely to be associated with a favorable anatomy for implant placement. CONCLUSION The ridge shape significantly influenced the ease or difficulty of placing an implant. The s-shape, hourglass, and basal bone posterior mandibular cross-sectional shapes were associated with a higher degree of difficulty.