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Alcohol genome-wide association studies (GWASs) have generally focused on alcohol consumption and alcohol use disorder (AUD); few have examined habitual drinking behaviors like maximum habitual alcohol intake (MaxAlc).To identify genetic loci associated with MaxAlc and to elucidate the genetic architecture across alcohol traits.This MaxAlc genetic association study was performed among Million Veteran Program participants enrolled from January 10, 2011, to September 30, 2020. Ancestry-specific GWASs were conducted in participants with European (n = 218 623) and African (n = 29 132) ancestry, then meta-analyzed (N = 247 755). Linkage-disequilibrium score regression was used to estimate single nucleotide variant (SNV)-heritability and genetic correlations (rg) with other alcohol and psychiatric traits. Genomic structural equation modeling (gSEM) was used to evaluate genetic associations between MaxAlc and other alcohol traits. Mendelian randomization was used to examine potential causal relationships between MaxAlc and liver enzyme levels. MTAG (multitrait analysis of GWAS) was used to analyze MaxAlc and problematic alcohol use (PAU) jointly.Genetic associations.MaxAlc was defined from the following survey item: "in a typical month, what is/was the largest number of drinks of alcohol you may have had in one day?" with ordinal responses from 0 to 15 or more drinks.GWASs were conducted on sample sizes of as many as 247 455 US veterans. Participants were 92.68% male and had mean (SD) age of 65.92 (11.70) years. The MaxAlc GWAS resulted in 15 genome-wide significant loci. Top associations in European-ancestry and African-ancestry participants were with known functional variants in the ADH1B gene, namely rs1229984 (P = 3.12 × 10-101) and rs2066702 (P = 6.30 × 10-17), respectively. Novel associations were also found. SNV-heritability was 6.65% (SE, 0.41) in European-ancestry participants and 3.42% (SE, 1.46) in African-ancestry participants. MaxAlc was positively correlated with PAU (rg = 0.79; P = 3.95 × 10-149) and AUD (rg = 0.76; P = 1.26 × 10-127) and had negative rg with the UK Biobank "alcohol usually taken with meals" (rg = -0.53; P = 1.40 × 10-50). For psychiatric traits, MaxAlc had the strongest genetic correlation with suicide attempt (rg = 0.40; P = 3.02 × 10-21). gSEM supported a 2-factor model with MaxAlc loading on a factor with PAU and AUD and other alcohol consumption measures loading on a separate factor. Mendelian randomization supported an association between MaxAlc and the liver enzyme gamma-glutamyltransferase (β = 0.012; P = 2.66 × 10-10). MaxAlc MTAG resulted in 31 genome-wide significant loci.The findings suggest that MaxAlc closely aligns genetically with PAU traits. This study improves understanding of the mechanisms associated with normative alcohol consumption vs problematic habitual use and AUD as well as how MaxAlc relates to psychiatric and medical conditions genetically and biologically.

Background Dentists strive to provide safe and effective oral healthcare. However, some patients may encounter an adverse event (AE) defined as "unnecessary harm due to dental treatment." In this research, we propose and evaluate two systems for categorizing the type and severity of AEs encountered at the dental office. Methods Several existing medical AE type and severity classification systems were reviewed and adapted for dentistry. Using data collected in previous work, two initial dental AE type and severity classification systems were developed. Eight independent reviewers performed focused chart reviews, and AEs identified were used to evaluate and modify these newly developed classifications. Results A total of 958 charts were independently reviewed. Among the reviewed charts, 118 prospective AEs were found and 101 (85.6%) were verified as AEs through a consensus process. At the end of the study, a final AE type classification comprising 12 categories, and an AE severity classification comprising 7 categories emerged. Pain and infection were the most common AE types representing 73% of the cases reviewed (56% and 17%, respectively) and 88% were found to cause temporary, moderate to severe harm to the patient. Conclusions Adverse events found during the chart review process were successfully classified using the novel dental AE type and severity classifications. Understanding the type of AEs and their severity are important steps if we are to learn from and prevent patient harm in the dental office.

Large-scale multi-ethnic cohorts offer unprecedented opportunities to elucidate the genetic factors influencing complex traits related to health and disease among minority populations. At the same time, the genetic diversity in these cohorts presents new challenges for analysis and interpretation. We consider the utility of race and/or ethnicity categories in genome-wide association studies (GWASs) of multi-ethnic cohorts. We demonstrate that race/ethnicity information enhances the ability to understand population-specific genetic architecture. To address the practical issue that self-identified racial/ethnic information may be incomplete, we propose a machine learning algorithm that produces a surrogate variable, termed HARE. We use height as a model trait to demonstrate the utility of HARE and ethnicity-specific GWASs.

ObjectiveTo develop an empirically derived taxonomy of clinical decision support (CDS) alert malfunctions.Materials and MethodsWe identified CDS alert malfunctions using a mix of qualitative and quantitative methods: (1) site visits with interviews of chief medical informatics officers, CDS developers, clinical leaders, and CDS end users; (2) surveys of chief medical informatics officers; (3) analysis of CDS firing rates; and (4) analysis of CDS overrides. We used a multi-round, manual, iterative card sort to develop a multi-axial, empirically derived taxonomy of CDS malfunctions.ResultsWe analyzed 68 CDS alert malfunction cases from 14 sites across the United States with diverse electronic health record systems. Four primary axes emerged: the cause of the malfunction, its mode of discovery, when it began, and how it affected rule firing. Build errors, conceptualization errors, and the introduction of new concepts or terms were the most frequent causes. User reports were the predominant mode of discovery. Many malfunctions within our database caused rules to fire for patients for whom they should not have (false positives), but the reverse (false negatives) was also common.DiscussionAcross organizations and electronic health record systems, similar malfunction patterns recurred. Challenges included updates to code sets and values, software issues at the time of system upgrades, difficulties with migration of CDS content between computing environments, and the challenge of correctly conceptualizing and building CDS.ConclusionCDS alert malfunctions are frequent. The empirically derived taxonomy formalizes the common recurring issues that cause these malfunctions, helping CDS developers anticipate and prevent CDS malfunctions before they occur or detect and resolve them expediently.

Diagnosis at the edges of our knowledge calls upon clinicians to be data driven, cross-disciplinary, and collaborative in unprecedented ways. Exact disease recognition, an element of the concept of precision in medicine, requires new infrastructure that spans geography, institutional boundaries, and the divide between clinical care and research. The National Institutes of Health (NIH) Common Fund supports the Undiagnosed Diseases Network (UDN) as an exemplar of this model of precise diagnosis. Its goals are to forge a strategy to accelerate the diagnosis of rare or previously unrecognized diseases, to improve recommendations for clinical management, and to advance research, especially into disease mechanisms. The network will achieve these objectives by evaluating patients with undiagnosed diseases, fostering a breadth of expert collaborations, determining best practices for translating the strategy into medical centers nationwide, and sharing findings, data, specimens, and approaches with the scientific and medical communities. Building the UDN has already brought insights to human and medical geneticists. The initial focus has been on data sharing, establishing common protocols for institutional review boards and data sharing, creating protocols for referring and evaluating patients, and providing DNA sequencing, metabolomic analysis, and functional studies in model organisms. By extending this precision diagnostic model nationally, we strive to meld clinical and research objectives, improve patient outcomes, and contribute to medical science.

Whole-exome sequencing (WES) has increasingly enabled new pathogenic gene variant identification for undiagnosed neurodevelopmental disorders and provided insights into both gene function and disease biology. Here, we describe seven children with a neurodevelopmental disorder characterized by microcephaly, profound developmental delays and/or intellectual disability, cataracts, severe epilepsy including infantile spasms, irritability, failure to thrive, and stereotypic hand movements. Brain imaging in these individuals reveals delay in myelination and cerebral atrophy. We observe an identical recurrent de novo heterozygous c.892C>T (p.Arg298Trp) variant in the nucleus accumbens associated 1 ( NACC1 ) gene in seven affected individuals. One of the seven individuals is mosaic for this variant. NACC1 encodes a transcriptional repressor implicated in gene expression and has not previously been associated with germline disorders. The probability of finding the same missense NACC1 variant by chance in 7 out of 17,228 individuals who underwent WES for diagnoses of neurodevelopmental phenotypes is extremely small and achieves genome-wide significance (p = 1.25 × 10 −14 ). Selective constraint against missense variants in NACC1 makes this excess of an identical missense variant in all seven individuals more remarkable. Our findings are consistent with a germline recurrent mutational hotspot associated with an allele-specific neurodevelopmental phenotype in NACC1 .

Early B cell factor 3 (EBF3) is a member of the highly evolutionarily conserved Collier/Olf/EBF (COE) family of transcription factors. Prior studies on invertebrate and vertebrate animals have shown that EBF3 homologs are essential for survival and that loss-of-function mutations are associated with a range of nervous system developmental defects, including perturbation of neuronal development and migration. Interestingly, aristaless-related homeobox (ARX), a homeobox-containing transcription factor critical for the regulation of nervous system development, transcriptionally represses EBF3 expression. However, human neurodevelopmental disorders related to EBF3 have not been reported. Here, we describe three individuals who are affected by global developmental delay, intellectual disability, and expressive speech disorder and carry de novo variants in EBF3. Associated features seen in these individuals include congenital hypotonia, structural CNS malformations, ataxia, and genitourinary abnormalities. The de novo variants affect a single conserved residue in a zinc finger motif crucial for DNA binding and are deleterious in a fly model. Our findings indicate that mutations in EBF3 cause a genetic neurodevelopmental syndrome and suggest that loss of EBF3 function might mediate a subset of neurologic phenotypes shared by ARX-related disorders, including intellectual disability, abnormal genitalia, and structural CNS malformations.

Objective To illustrate ways in which clinical decision support systems (CDSSs) malfunction and identify patterns of such malfunctions.Materials and Methods We identified and investigated several CDSS malfunctions at Brigham and Women’s Hospital and present them as a case series. We also conducted a preliminary survey of Chief Medical Information Officers to assess the frequency of such malfunctions.Results We identified four CDSS malfunctions at Brigham and Women’s Hospital: (1) an alert for monitoring thyroid function in patients receiving amiodarone stopped working when an internal identifier for amiodarone was changed in another system; (2) an alert for lead screening for children stopped working when the rule was inadvertently edited; (3) a software upgrade of the electronic health record software caused numerous spurious alerts to fire; and (4) a malfunction in an external drug classification system caused an alert to inappropriately suggest antiplatelet drugs, such as aspirin, for patients already taking one. We found that 93% of the Chief Medical Information Officers who responded to our survey had experienced at least one CDSS malfunction, and two-thirds experienced malfunctions at least annually.Discussion CDSS malfunctions are widespread and often persist for long periods. The failure of alerts to fire is particularly difficult to detect. A range of causes, including changes in codes and fields, software upgrades, inadvertent disabling or editing of rules, and malfunctions of external systems commonly contribute to CDSS malfunctions, and current approaches for preventing and detecting such malfunctions are inadequate.Conclusion CDSS malfunctions occur commonly and often go undetected. Better methods are needed to prevent and detect these malfunctions.

In recent years, there has been an increase in research studies highlighting patients' experiences of adverse events (AEs) as well as the role of patients in promoting safety. The primary goal of the study was to assess the prevalence of dental AEs (DAEs) among dental patients in South Africa and its associated factors. The integration of the patient perspective into dental patient safety research will enhance our collective understanding of DAEs.We conducted a cross-sectional study of adult patients at a large dental academic institution in South Africa from May to June 2015, evaluating their previous experiences of DAEs at any dental clinic in South Africa. Descriptive statistics and bivariate and multivariate analyses were performed to identify the factors associated with an increased likelihood of experiencing a DAE.A total of 440 questionnaires were returned during the 6-week study period (response rate = 97.8%). Overall, 45.5% of participants reported experiencing one or more DAEs. Two hundred participants reported a total of 717 DAEs giving us a lifetime prevalence of 1.6 DAEs per respondent. Our results suggest that respondents who were younger (18-24 y), from high-income families (R150,000 or US $9200), dissatisfied with their last dental visit and oral health had an increased likelihood of reporting a previous experience of a DAE.This study provides an insight into the nature of information that can be gleaned from dental patients regarding safety and helps lay the foundation for patient involvement in patient safety reporting.

PurposeTo describe examples of missed pathogenic variants on whole-exome sequencing (WES) and the importance of deep phenotyping for further diagnostic testing.MethodsGuided by phenotypic information, three children with negative WES underwent targeted single-gene testing.ResultsIndividual 1 had a clinical diagnosis consistent with infantile systemic hyalinosis, although WES and a next-generation sequencing (NGS)-based ANTXR2 test were negative. Sanger sequencing of ANTXR2 revealed a homozygous single base pair insertion, previously missed by the WES variant caller software. Individual 2 had neurodevelopmental regression and cerebellar atrophy, with no diagnosis on WES. New clinical findings prompted Sanger sequencing and copy number testing of PLA2G6. A novel homozygous deletion of the noncoding exon 1 (not included in the WES capture kit) was detected, with extension into the promoter, confirming the clinical suspicion of infantile neuroaxonal dystrophy. Individual 3 had progressive ataxia, spasticity, and magnetic resonance image changes of vanishing white matter leukoencephalopathy. An NGS leukodystrophy gene panel and WES showed a heterozygous pathogenic variant in EIF2B5; no deletions/duplications were detected. Sanger sequencing of EIF2B5 showed a frameshift indel, probably missed owing to failure of alignment.ConclusionThese cases illustrate potential pitfalls of WES/NGS testing and the importance of phenotype-guided molecular testing in yielding diagnoses.

One major challenge encountered with interpreting human genetic variants is the limited understanding of the functional impact of genetic alterations on biological processes. Furthermore, there remains an unmet demand for an efficient survey of the wealth of information on human homologs in model organisms across numerous databases. To efficiently assess the large volume of publically available information, it is important to provide a concise summary of the most relevant information in a rapid user-friendly format. To this end, we created MARRVEL (model organism aggregated resources for rare variant exploration). MARRVEL is a publicly available website that integrates information from six human genetic databases and seven model organism databases. For any given variant or gene, MARRVEL displays information from OMIM, ExAC, ClinVar, Geno2MP, DGV, and DECIPHER. Importantly, it curates model organism-specific databases to concurrently display a concise summary regarding the human gene homologs in budding and fission yeast, worm, fly, fish, mouse, and rat on a single webpage. Experiment-based information on tissue expression, protein subcellular localization, biological process, and molecular function for the human gene and homologs in the seven model organisms are arranged into a concise output. Hence, rather than visiting multiple separate databases for variant and gene analysis, users can obtain important information by searching once through MARRVEL. Altogether, MARRVEL dramatically improves efficiency and accessibility to data collection and facilitates analysis of human genes and variants by cross-disciplinary integration of 18 million records available in public databases to facilitate clinical diagnosis and basic research.

Standardized dental diagnostic terminologies (SDDxTs) were introduced decades ago. Their use has been on the rise, accompanying the adoption of electronic health records (EHRs). One of the most broadly used terminologies is the Dental Diagnostic System (DDS). Our aim was to assess the adoption of SDDxTs by US dental schools by using the Rogers diffusion of innovations framework, focusing on the DDS.The authors electronically surveyed clinic deans in all US dental schools (n = 61) to determine use of an EHR and SDDxT, perceived barriers to adoption of an SDDxT, and the effect of implementing an SDDxT on clinical productivity.The response rate was 57%. Of the 35 responses, 91% reported using an EHR to document patient care, with 84% using axiUm; 41% used the DDS. Fifty-four percent of those who did not use an SDDxT had considered adopting the DDS, but 38% had not, citing barriers such as complexity and compatibility.Adoption of an SDDxT, particularly the DDS, is on the rise. Nevertheless, a large number of institutions are in the Rogers late majority and laggards categories with respect to adoption. Several factors may discourage adoption, including the inability to try out the terminology on a small scale, poor usability within the EHR, the fact that it would be a cultural shift in practice, and a perception of unclear benefits. However, the consolidation of the DDS and American Dental Association terminology efforts stands to encourage adoption.The successful adoption of dental innovation depends not only on the intrinsic merit of the innovation, as some useful innovations do not achieve widespread traction. As such, it is important for health care providers to understand how to disseminate their ideas in order to ensure traction and widespread adoption.

Whether and how to return individual genetic results to study participants is among the most contentious policy issues in contemporary genomic research.We surveyed corresponding authors of genome-wide association studies, identified through the National Human Genome Research Institute's Catalog of Published Genome-Wide Association Studies, to describe the experiences and attitudes of these stakeholders.Of 357 corresponding authors, 200 (56%) responded. One hundred twenty-six (63%) had been responsible for primary data and sample collection, whereas 74 (37%) had performed secondary analyses. Only 7 (4%) had returned individual results within their index genome-wide association studies. Most (69%) believed that return of results to individual participants was warranted under at least some circumstances. Most respondents identified a desire to benefit participants' health (63%) and respect for participants' desire for information (57%) as major motivations for returning results. Most also identified uncertain clinical utility (76%), the possibility that participants will misunderstand results (74%), the potential for emotional harm (61%), the need to ensure access to trained clinicians (59%), and the potential for loss of confidentiality (51%) as major barriers to return of results.Investigators have limited experience returning individual results from genome-scale research, yet most are motivated to do so in at least some circumstances.

Although standardized terminologies such as the International Classification of Diseases have been in use in medicine for over a century, efforts in the dental profession to standardize dental diagnostic terms have not achieved widespread acceptance. To address this gap, a standardized dental diagnostic terminology, the EZCodes, was developed in 2009. Fifteen dental education institutions in the United States and Europe have implemented the EZCodes dental diagnostic terminology. This article reports on the utilization and valid entry of the EZCodes at three of the dental schools that have adopted this standardized dental diagnostic terminology. Electronic data on the use of procedure codes with diagnostic terms from the three schools over a period from July 2010 to June 2011 were aggregated. The diagnostic term and procedure code pairs were adjudicated by three calibrated dentists. Analyses were conducted to gain insight into the utilization and valid entry of the EZCodes diagnostic terminology in the one-year period. Error proportions in the entry of diagnostic term (and by diagnostic category) were also computed. In the twelve-month period, 29,965 diagnostic terms and 249,411 procedure codes were entered at the three institutions resulting in a utilization proportion of 12 percent. Caries and periodontics were the most frequently used categories. More than 1,000 of the available 1,321 diagnostic terms were never used. Overall, 60.5 percent of the EZCodes entries were found to be valid. The results demonstrate low utilization of EZCodes in an electronic health record and raise the need for specific training of dental providers on the importance of using dental diagnostic terminology and specifically how to use the terms in the electronic record. These findings will serve to increase the use/correct use of the EZCodes dental diagnostic terminology and ultimately create a reliable platform for undertaking clinical, outcomes, and quality improvement-related research.

Background Although some patients experience adverse events (AEs) resulting in harm caused by treatments in dentistry, few published reports have detailed how dental providers describe these events. Understanding how dental treatment professionals view AEs is essential to building a safer environment in dental practice. Methods The authors interviewed dental professionals and domain experts through focus groups and in-depth interviews and asked them to identify the types of AEs that may occur in dental settings. Results The initial interview and focus group findings yielded 1,514 items that included both causes and AEs. In total, 632 causes were coded into 1 of the 8 categories of the Eindhoven classification, and 882 AEs were coded into 12 categories of a newly developed dental AE classification. Interrater reliability was moderate among coders. The list was reanalyzed, and duplicate items were removed leaving a total of 747 unique AEs and 540 causes. The most frequently identified AE types were "aspiration and ingestion" at 14% (n = 142), "wrong-site, wrong-procedure, wrong-patient errors" at 13%, "hard-tissue damage" at 13%, and "soft-tissue damage" at 12%. Conclusions Dental providers identified a large and diverse list of AEs. These events ranged from "death due to cardiac arrest" to "jaw fatigue from lengthy procedures." Practical Implications Identifying threats to patient safety is a key element of improving dental patient safety. An inventory of dental AEs underpins efforts to track, prevent, and mitigate these events.

Introduction The inability of some seriously and chronically ill individuals to receive a definitive diagnosis represents an unmet medical need. In 2008, the NIH Undiagnosed Diseases Program (UDP) was established to provide answers to patients with mysterious conditions that long eluded diagnosis and to advance medical knowledge. Patients admitted to the NIH UDP undergo a five-day hospitalization, facilitating highly collaborative clinical evaluations and a detailed, standardized documentation of the individual's phenotype. Bedside and bench investigations are tightly coupled. Genetic studies include commercially available testing, single nucleotide polymorphism microarray analysis, and family exomic sequencing studies. Selected gene variants are evaluated by collaborators using informatics, in vitro cell studies, and functional assays in model systems (fly, zebrafish, worm, or mouse). Insights from the UDP In seven years, the UDP received 2954 complete applications and evaluated 863 individuals. Nine vignettes (two unpublished) illustrate the relevance of an undiagnosed diseases program to complex and common disorders, the coincidence of multiple rare single gene disorders in individual patients, newly recognized mechanisms of disease, and the application of precision medicine to patient care. Conclusions The UDP provides examples of the benefits expected to accrue with the recent launch of a national Undiagnosed Diseases Network (UDN). The UDN should accelerate rare disease diagnosis and new disease discovery, enhance the likelihood of diagnosing known diseases in patients with uncommon phenotypes, improve management strategies, and advance medical research.

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.

A person's right to access his or her protected health information is a core feature of the U.S. Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule. If the information is stored electronically, covered entities must be able to provide patients with some type of machine-readable, electronic copy of their data. The aim of this study was to understand how academic dental institutions execute the Privacy Rule's right of access in the context of electronic health records (EHRs). A validated electronic survey was distributed to the clinical deans of 62 U.S. dental schools during a two-month period in 2014. The response rate to the survey was 53.2% (N=33). However, three surveys were partially completed, and of the 30 completed surveys, the 24 respondents who reported using axiUm as the EHR at their dental school clinic were the ones on which the results were based (38.7% of total schools at the time). Of the responses analyzed, 86% agreed that clinical modules should be considered part of a patient's dental record, and all agreed that student teaching-related modules should not. Great variability existed among these clinical deans as to whether administrative and financial modules should be considered part of a patient record. When patients request their records, close to 50% of responding schools provide the information exclusively on paper. This study found variation among dental schools in their implementation of the Privacy Rule right of access, and although all the respondents had adopted EHRs, a large number return records in paper format.

BackgroundThe authors conducted a study to determine the frequency and type of adverse events (AEs) associated with dental devices reported to the Food and Drug Administration Manufacturer and User Facility Device Experience (MAUDE) database.MethodsThe authors downloaded and reviewed the dental device-related AEs reported to MAUDE from January 1, 1996, through December 31,2011.ResultsMAUDE received a total of 1,978,056 reports between January 1, 1996, and December 31, 2011. Among these reports, 28,046 (1.4%) AE reports were associated with dental devices. Within the dental AE reports that had event type information, 17,261 reported injuries, 7,777 reported device malfunctions, and 66 reported deaths. Among the 66 entries classified as death reports, 52 reported a death in the description; the remaining were either misclassified or lacked sufficient information in the report to determine whether a death had occurred. Of the dental device-associated AEs, 53.5% pertained to endosseous implants.ConclusionsA plethora of devices are used in dental care. To achieve Element 1 of Agency for Healthcare Research and Quality's Patient Safety Initiative, clinicians and researchers must be able to monitor the safety of dental devices. Although MAUDE was identified by the authors as essentially the sole source of this valuable information on adverse events, their investigations led them to conclude that MAUDE had substantial limitations that prevent it from being the broad-based patient safety sentinel the profession requires.Practical implicationsAs potential contributors to MAUDE, dental care teams play a key role in improving the profession's access to information about the safety of dental devices.

Background Errors are commonplace in health care, including dentistry. It is imperative for dental professionals to intercept errors before they lead to an adverse event and to mitigate their effects when an adverse event occurs. This requires a systematic approach at both the profession level, encapsulated in the Agency for Healthcare Research and Quality’s patient safety initiative framework, as well as at the practice level, in which crew resource management is a tested paradigm. Supporting patient safety at both the profession and dental practice levels relies on understanding the types and causes of errors, which have not been well studied. Methods The authors performed a retrospective review of dental adverse events reported in the literature. Electronic bibliographic databases were searched, and data were extracted on background characteristics, incident description, case characteristics, clinic setting where adverse event originated, phase of patient care that adverse event was detected, proximal cause, type of patient harm, degree of harm, and recovery actions. Results The authors identified 182 publications (containing 270 cases) through their search. Delayed treatment, unnecessary treatment, or disease progression after misdiagnosis was the largest type of harm reported. Of the reviewed cases, 24.4% of those patients involved in an adverse event experienced permanent harm. One of every 10 case reports reviewed (11.1%) reported that the adverse event resulted in the death of the affected patient. Conclusions Published case reports provide a window into understanding the nature and extent of dental adverse events; however, the overall dearth of publications on adverse events in the dental literature points to the need for more study. Practical Implications Siloed and incomplete contributions to dentistry’s understanding of adverse events in the dental office are threats to dental patients’ safety. Publishing more, and more comprehensive, case reports on adverse events is recommended for dental practitioners.

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 health records (EHRs) at four dental schools participating in the Consortium of Oral Health Research and Informatics. A multi-stakeholder committee developed a data governance framework that encouraged data sharing while allowing control of contributed data. We adopted the i2b2 data warehousing platform and mapped data from each institution to a common reference terminology. We realized that dental EHRs urgently need to adopt common terminologies. While all used the same treatment code set, only three of the four sites used a common diagnostic terminology, and there were wide discrepancies in how medical and dental histories were documented. BigMouth was successfully launched in August 2012 with data on 1.1 million patients, and made available to users at the contributing institutions.

It is with great interest that we read Dr. Christman and colleagues' article, “Designing a Safety Checklist for Dental Implant Placement: A Delphi Study” (JADA 2014;145[2]:131-140), which described the development of a checklist to standardize the process of dental implant placement. Although the concern for preventing patient harm is fundamental to the practice of medicine, the 2000 publication of “To Err Is Human: Building a Safer Health System,”1 by the Committee on Quality of Health Care in America of the Institute of Medicine, catalyzed a patient safety and quality revolution. Against this backdrop, checklists have emerged as practical and effective tools for realizing a safer health care environment. Checklists support team members by presenting critical tasks as a list, a format that simplifies understanding and recall of information. Long used in aviation, checklists increasingly are being relied on in medicine to reduce the occurrence of errors of omission, create reliable evaluations, and improve quality and use of best practices.2 Dentistry has lagged behind in the attention paid to safety, and the use of checklists within the dental world is almost nonexistent. Dr. Christman and colleagues' work, therefore, is an encouraging step forward. As the authors suggest, it is critical to test the safety checklist in a clinical environment to establish its functionality and compatibility with task execution. Beyond that, regardless of the systematic approach used in the design of this checklist, perhaps the most important determinant of its success will be how it is implemented.3 Target users must have a full understanding of the purpose of the checklist, and they must be trained in how to use it.3 Usefulness of the checklist also requires support of all staff, dedicated champions and endorsement by clinic leaders. Along the same lines, we have been fortunate to obtain a grant (1R21DE023408-01A1) from the National Institute of Dental and Craniofacial Research titled “Improving the Quality of Dental Care by Implementing a Clinician Checklist.” In a pilot work, we observed that a record of fundamental tasks that directly affect the quality of dental care (such as updating the medical history and medication history) often is missing from patient records. This implies that although most dental care providers agree on what constitutes basic best practices, they often fail to complete and/or document the associated tasks. We are developing a checklist that will be implemented to support clinical dental team members in consistently performing and documenting these tasks. Again, we are excited that momentum is being generated regarding the topic of patient safety in dentistry. We congratulate Dr. Christman and colleagues for their pioneering work and look forward to learning about the quality improvement that accompanies the implementation of this implant checklist.

There is a dearth of knowledge about the type and frequency of adverse events (AEs) in dentistry. Current approaches to obtaining information rely on reviews of randomly selected records, which may not be the most efficient or effective methodology.Inspired by the Institute for Healthcare Improvement's (IHI) global and outpatient trigger tools, which identifies records with characteristics ("triggers") that are associated with AEs, the authors created the dental clinic trigger tool. The triggers included procedures for incision and drainage, failed implants and selected treatment patterns. The authors ran the trigger tool against six months of electronic health records data and compared its performance with that of a review of 50 randomly selected patient records.In total, 315 records were triggered, 158 (50 percent) of which were positive for one or more AEs; 17 (34 percent) of the 50 randomly selected records were positive for at least one AE. The authors assigned each AE an IHI severity ranking. Most AEs caused temporary harm, but nine were considered to have caused permanent harm according to a modified IHI severity ranking.The study results demonstrate the promise of a directed records review approach, as the dental clinic trigger tool was more effective in identifying AEs than was a review of randomly selected records.All dental practices should proactively monitor the safety of the care they provide. Use of the trigger tool will help make this process more efficient and effective.

To document how race and ethnicity are identified, categorized, and utilized in contemporary dental public health literature.Two researchers independently performed a literature review of all articles in Community Dentistry and Oral Epidemiology and the Journal of Public Health Dentistry over a 5-year period (2004-2009). Articles pertaining to the study of US-based populations with any mention of race or ethnicity were included. The following data were abstracted from each article:( a) how each article broadly described race and/or ethnicity; (b) the terms used to specifically define the races and/or ethnicities captured; (c) the location of any mention of the concept of race and/or ethnicity; (d) the stated purpose for including race and/or ethnicity concepts; (e) the stated analytic use of race and/or ethnicity concepts; and (f) the stated method used to assess race and/or ethnicity concepts.Overall, race and/or ethnicity concepts were most commonly referred to within the text of the results section. Fifty percent of articles did not state their purpose for including race and/or ethnicity concepts within their studies, while 34.3 percent omitted stating their analytic use of these concepts. When assessing these concepts, 41.4 percent relied upon subject self-report.These data showed that there was inconsistent documentation of how race and ethnicity was measured. While race and ethnicity are important measures for public health studies and are frequently reported in dental public health research, there is no clear system for classifying these measures.

Background— Many different genetic and clinical factors have been identified as causes or contributors to atherosclerosis. We present a model of preclinical atherosclerosis based on genetic and clinical data that predicts the presence of coronary artery calcification in healthy Americans of European descent 45 to 84 years of age in the Multi-Ethnic Study of Atherosclerosis (MESA). Methods and Results— We assessed 712 individuals for the presence or absence of coronary artery calcification and assessed their genotypes for 2882 single-nucleotide polymorphisms. With the use of these single-nucleotide polymorphisms and relevant clinical data, a Bayesian network that predicts the presence of coronary calcification was constructed. The model contained 13 single-nucleotide polymorphisms (from genes AGTR1, ALOX15, INSR, PRKAB1, IL1R2, ESR2, KCNK1, FBLN5, PPARA, VEGFA, PON1, TDRD6, PLA2G7, and 1 ancestry informative marker) and 5 clinical variables (sex, age, weight, smoking, and diabetes mellitus) and achieved 85% predictive accuracy, as measured by area under the receiver operating characteristic curve. This is a significant ( P Conclusions— We present an investigation of joint genetic and clinical factors associated with atherosclerosis that shows predictive results for both cases, as well as enhanced performance for their combination.

Cardioembolic stroke is a complex disease resulting from the interaction of numerous factors. Using data from Genes Affecting Stroke Risk and Outcome Study (GASROS), we show that a multivariate predictive model built using Bayesian networks is able to achieve a predictive accuracy of 86% on the fitted values as computed by the area under the receiver operating characteristic curve relative to that of the individual single nucleotide polymorphism with the highest prognostic performance (area under the receiver operating characteristic curve=60%).

Individuals’ dependence on nicotine, primarily through cigarette smoking, is a major source of morbidity and mortality worldwide. Many smokers attempt but fail to quit smoking, motivating researchers to identify the origins of this dependence. Because of the known heritability of nicotine-dependence phenotypes, considerable interest has been focused on discovering the genetic factors underpinning the trait. This goal, however, is not easily attained: no single factor is likely to explain any great proportion of dependence because nicotine dependence is thought to be a complex trait (i.e., the result of many interacting factors). Genomewide association studies are powerful tools in the search for the genomic bases of complex traits, and in this context, novel candidate genes have been identified through single nucleotide polymorphism (SNP) association analyses. Beyond association, however, genetic data can be used to generate predictive models of nicotine dependence. As expected in the context of a complex trait, individual SNPs fail to accurately predict nicotine dependence, demanding the use of multivariate models. Standard approaches, such as logistic regression, are unable to consider large numbers of SNPs given existing sample sizes. However, using Bayesian networks, one can overcome these limitations to generate a multivariate predictive model, which has markedly enhanced predictive accuracy on fitted values relative to that of individual SNPs. This approach, combined with the data being generated by genomewide association studies, promises to shed new light on the common, complex trait nicotine dependence.