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. The measure was validated by comparing the findings from the measure with a manual review of charts. RESULTS: The overall measure scores varied significantly across the four institutions (institution 1 = 20.47%, institution 2 = 0.97%, institution 3 = 22.27% institution 4 = 99.49%, p-value < 0.0001). The largest gaps in documentation were related to periodontal diagnoses and capturing oral homecare compliance. A random sample of 1224 charts were manually reviewed and showed excellent validity when compared with the data generated from the EHR-based measure (Sensitivity, Specificity, PPV, and NPV > 80%). CONCLUSION: Our results demonstrate the feasibility of developing automated data extraction scripts using structured data from EHRs, and successfully implementing these to identify and measure the periodontal documentation completeness within and across different dental institutions.

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. The null hypothesis was rejected at α < 0.05. A total of 2866 eligible subjects were included in the analysis. Significantly lower odds of CAL ≤ 4 mm than CAL ≥ 5 mm (reference) were observed in adults aged 35-64 (odds ratio, OR, 0.19; 95% confidence interval, CI 0.13, 0.29) and ≥ 65 years (OR 0.13; 95% CI 0.07, 0.25) compared to those aged 18-34 years. Odds of PD < 4 mm versus PD ≥ 6 mm (reference) were lower in adults aged 35-64 years than those aged 18-34 years (OR 0.71; 95% CI 0.55, 0.90) and higher in females compared to males (OR 1.67; 95% CI 1.14, 2.44). These results suggest more compromised post-NSPT outcomes in older adults and males compared to the respective populations and highlight the need for personalized therapeutic strategies in these populations.

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. Baseline eligibility criteria included: children ages 0-18 with a baseline examination, Oregon home address, and either Medicaid or commercial dental benefits at least once between 2014 and 2108. Using the NIHPTC framework as a guide, DQAs were conducted throughout data element identification, extraction, staging, profiling, review, and documentation. RESULTS: The data set included 91,487 subjects, 11 data tables comprising 75 data variables (columns), with a total of 6,861,525 data elements. Data completeness was 97.2%, the accuracy of EHR data elements in extracts was 100%, and consistency between offices was strong; 29 of 30 offices within 2 standard deviations of the mean (s = 94%). CONCLUSIONS: The NIHPTC framework proved to be a useful approach, to identify, document, and characterize the dataset. The concepts of completeness, accuracy, and consistency were adapted by the multidisciplinary research team and the overall quality of the data are demonstrated to be of high quality.

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. The results obtained from each iteration were used to enrich the information needs analyses, provide function testing, and guide the design decisions of the next iteration. RESULTS: Engaging dentists in the development and refinement of the dashboards while using the think-aloud protocol for user-testing, provided rapid feedback and identified areas that were confusing and needed either a redesign or additional explanatory content. The final version of dashboards consisted of displaying necessary information through easy to interpret visualizations and interactive features. These included providing access to current national and organizational prescribing guidelines, displaying changes in individual prescribing behavior over time, comparing individual prescribing rate to peer group rate and target rate, displaying procedure specific prescribing, integrating patient reported post-operative dental pain experience and providing navigation and interpretation tips for users. The dashboards were easy to learn and understand for the dentists and were deemed as worth using often in dental practice. CONCLUSION: Our research was able to demonstrate the creation of useful and usable A&F dashboards using data from electronic dental records and patient surveys, for dentists to effectively monitor their opioid prescribing behavior. Efficacy of the dashboards will be tested in future work.

Identifying Contributing Factors Associated With Dental Adverse Events Through a Pragmatic Electronic Health Record-Based Root Cause Analysis.

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 dental institutions. From 4106 flagged charts, 2 reviewers examined 439 charts selected randomly to identify and classify AEs using our dental AE type and severity classification systems. Based on information captured in the electronic health record, we analyzed harmful AEs to assess potential contributing factors; harmful AEs were defined as those that resulted in temporary moderate to severe harm, required hospitalization, or resulted in permanent moderate to severe harm. We classified potential contributing factors according to (1) who was involved (person), (2) what were they doing (tasks), (3) what tools/technologies were they using (tools/technologies), (4) where did the event take place (environment), (5) what organizational conditions contributed to the event? (organization), (6) patient (including parents), and (7) professional-professional collaboration. A blinded panel of dental experts conducted a second review to confirm the presence of an AE. RESULTS: Fifty-nine cases had 1 or more harmful AEs. Pain occurred most frequently (27.1%), followed by nerve injury (16.9%), hard tissue injury (15.2%), and soft tissue injury (15.2%). Forty percent of the cases were classified as "temporary not moderate to severe harm." Person (training, supervision, and fatigue) was the most common contributing factor (31.5%), followed by patient (noncompliance, unsafe practices at home, low health literacy, 17.1%), and professional-professional collaboration (15.3%). CONCLUSIONS: Pain was the most common harmful AE identified. Person, patient, and professional-professional collaboration were the most frequently assessed factors associated with harmful AEs.

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. The primary purpose for BigMouth is to serve as a high-quality resource for rapidly conducting oral health-related research. BigMouth allows for assessing the oral health status of a diverse US patient population; provides rationale and evidence for new oral health care delivery modes; and embraces the specific oral health research education mission. A data governance framework that encouraged data sharing while controlling contributed data was initially developed. This transformed over time into a mature framework, including a fee schedule for data requests and allowing access to researchers from noncontributing institutions. Adoption of BigMouth helps to foster new collaborations between clinical, epidemiological, statistical, and informatics experts and provides an additional venue for professional development.

Translating periodontal data to knowledge in a learning health system.

BACKGROUND: A learning health system (LHS) is a health system in which patients and clinicians work together to choose care on the basis of best evidence and to drive discovery as a natural outgrowth of every clinical encounter to ensure the right care at the right time. An LHS for dentistry is now feasible, as an increased number of oral health care encounters are captured in electronic health records (EHRs). METHODS: The authors used EHRs data to track periodontal health outcomes at 3 large dental institutions. The 2 outcomes of interest were a new periodontitis case (for patients who had not received a diagnosis of periodontitis previously) and tooth loss due to progression of periodontal disease. RESULTS: The authors assessed a total of 494,272 examinations (new periodontitis outcome: n = 168,442; new tooth loss outcome: n = 325,830), representing a total of 194,984 patients. Dynamic dashboards displaying performance on both measures over time allow users to compare demographic and risk factors for patients. The incidence of new periodontitis and tooth loss was 4.3% and 1.2%, respectively. CONCLUSIONS: Periodontal disease, diagnosis, prevention, and treatment are particularly well suited for an LHS model. The results showed the feasibility of automated extraction and interpretation of critical data elements from the EHRs. The 2 outcome measures are being implemented as part of a dental LHS. The authors are using this knowledge to target the main drivers of poorer periodontal outcomes in a specific patient population, and they continue to use clinical health data for the purpose of learning and improvement. PRACTICAL IMPLICATIONS: Dental institutions of any size can conduct contemporaneous self-evaluation and immediately implement targeted strategies to improve oral health outcomes.

Caries Risk Documentation And Prevention: eMeasures For Dental Electronic Health Records.

BACKGROUND: Longitudinal patient level data available in the electronic health record (EHR) allows for the development, implementation, and validations of dental quality measures (eMeasures). OBJECTIVE: We report the feasibility and validity of implementing two eMeasures. The eMeasures determined the proportion of patients receiving a caries risk assessment (eCRA) and corresponding appropriate risk-based preventative treatments for patients at elevated risk of caries (appropriateness of care [eAoC]) in two academic institutions and one accountable care organization, in the 2019 reporting year. METHODS: Both eMeasures define the numerator and denominator beginning at the patient level, populations' specifications, and validated the automated queries. For eCRA, patients who completed a comprehensive or periodic oral evaluation formed the denominator, and patients of any age who received a CRA formed the numerator. The eAoC evaluated the proportion of patients at elevated caries risk who received the corresponding appropriate risk-based preventative treatments. RESULTS: EHR automated queries identified in three sites 269,536 patients who met the inclusion criteria for receiving a CRA. The overall proportion of patients who received a CRA was 94.4% (eCRA). In eAoC, patients at elevated caries risk levels (moderate, high, or extreme) received fluoride preventive treatment ranging from 56 to 93.8%. For patients at high and extreme risk, antimicrobials were prescribed more frequently site 3 (80.6%) than sites 2 (16.7%) and 1 (2.9%). CONCLUSION: Patient-level data available in the EHRs can be used to implement process-of-care dental eCRA and AoC, eAoC measures identify gaps in clinical practice. EHR-based measures can be useful in improving delivery of evidence-based preventative treatments to reduce risk, prevent tooth decay, and improve oral health.

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. METHODS: Measure I recorded the proportion of patients with sealable teeth who received sealants. Measure II recorded the proportion of patients who had at least 1 of their sealable teeth sealed. Measure III recorded the proportion of patients who received sealant on all of their sealable teeth. RESULTS: On average, 48.1% of 6- through 9-year-old children received 1 or more sealants compared with 32.4% of 10- through 14-year-olds (measure I). The average measure score decreased for patients who received sealants for at least 1 of their sealable teeth (measure II) (43.2% for 6- through 9-year-olds and 28.4% for 10- through 14-year-olds). Fewer children received sealants on all eligible teeth (measure III) (35.5% of 6- through 9-year-olds and 21% of 10- through 14-year-olds received sealant on all eligible teeth). Among the 48.5% who were at elevated caries risk, the sealant rates were higher across all 3 measures. CONCLUSIONS: A valid and actionable practice-based sealant electronic measure that evaluates sealant treatment among the eligible population, both at the patient level and the tooth level, has been developed. PRACTICAL IMPLICATIONS: The measure developed in this work provides practices with patient-centered and actionable sealant quality measures that aim to improve oral health outcomes.

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. METHODS: Epidemiologic analysis was performed by querying the medical and dental records of >2 million patients. We retrieved information on positive/negative history for endodontic pathologies and CVDs using diagnostic and treatment codes from a dental school-based and a hospital-based patient electronic health record system. A case-control genetic association study was also performed; 10 single nucleotide polymorphisms in genes identified as strongly associated with CVDs were genotyped in 195 cases with AP and 189 control individuals without AP. Data analyses were performed using the chi-square and Fisher exact tests. P ≤.05 indicates significant difference between groups. RESULTS: Significant associations were found between the presence of endodontic pathology and a history of hypertension, myocardial infarction, cerebrovascular accident, pacemaker, congestive heart failure, heart block, deep vein thrombosis, and cardiac surgery (0.0001 ≤ P ≤ .008). A modest association was found for heart murmur and atrial fibrillation (P = .04). A trend toward positive association (P = .05) was also found between AP and a single nucleotide polymorphism in KCNK3, a gene known to be involved in increased susceptibility to hypertension. CONCLUSIONS: Significant associations were found between endodontic pathology and various CVDs and CVD-related risk factors, particularly hypertension. A trend toward a positive association was also found between AP and KCNK3, suggesting that common genetic variations may underlie different diseases. Additional studies with larger sample sizes have the potential to elucidate common mechanisms underlying AP and CVD.

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. An automated electronic health record (EHR) query identified patients 18 years and older who were screened for tobacco use one or more times within 24 months, and who received cessation counseling intervention if identified as a tobacco user. We evaluated EHR query performance with a manual review of a subsample of charts. RESULTS: Across all four sites, in the reporting calendar year of 2015, a total of 143,675 patients met the inclusion criteria for the study. Within 24 months, including 2014 and 2015 calendar years, percentages of tobacco screening ranged from 79.7 to 99.9 percent, while cessation intervention percentages varied from 1 to 81 percent among sites. By employing DQM research methodology, we identified intervention gaps in clinical practice. CONCLUSIONS: We demonstrated the successful implementation of a DQM to evaluate screening rates for tobacco use and cessation intervention. There is substantial variation in the cessation intervention rates across sites, and these results are a call for action for the dental profession to employ tobacco evidence-based cessation strategies to improve oral health and general health outcomes.

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). The authors adapted and validated these measures at 4 sites: 3 dental schools and 1 large dental accountable care organization. RESULTS: The overall modified DQA and modified OHA measure scores in the 6- through 9-year-old age group were 37.0% and 31.6% and in the 10- through 14-year-old age group were 15.8% and 6.6%, respectively. Results from the manual review of charts showed that 67.6% of children who did not receive sealants did not have any teeth to seal because their molars had not yet erupted, had been extracted, had been sealed previously, or had existing caries or restorations. CONCLUSIONS: Both the DQA and OHA measures, which rely mainly on Current Dental Terminology procedure codes, led to underestimation of the care delivered from a practice perspective. Future sealant quality measures should exclude patients whose teeth cannot be sealed. PRACTICAL IMPLICATIONS: This study's results support the suitability of using electronic health record data for assessing the quality of oral health care, particularly for measuring sealant placement in children.

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.

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. dental school reported existing signs and symptoms of TMD/OFP, whether the dental students diagnosed the condition based on the reported signs and symptoms, and if the condition was then treated. The study was based on a retrospective analysis of electronic health record data over a three-year period. The results showed that, during the study period, 21,352 patients were treated by student providers. Of those patients, 5.33% reported signs or symptoms associated with TMD/OFP; 5.99% received a TMD/OFP diagnosis; and 0.26% received at least one form of TMD/OFP treatment that had either a diagnosis or signs/symptoms of TMD/OFP. In addition, a small percentage (0.24%) of patients with no documented diagnosis received some sort of TMD/OFP-related treatment. A randomly selected sample of 90 patient charts found that no diagnoses of TMD/OFP were recorded in any of them. The results suggested that students had only marginally diagnosed the problems. Training for students including comprehensive didactic courses and clinical experiences to gain knowledge, context, and skill may be required to ensure they reach the required level of competence and prepare them to face the diagnostic challenges of TMD/OFP after graduation.

BigMouth: a multi-institutional dental data repository.

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.

Are three methods better than one? A comparative assessment of usability evaluation methods in an EHR.

OBJECTIVE: To comparatively evaluate the effectiveness of three different methods involving end-users for detecting usability problems in an EHR: user testing, semi-structured interviews and surveys. MATERIALS AND METHODS: Data were collected at two major urban dental schools from faculty, residents and dental students to assess the usability of a dental EHR for developing a treatment plan. These included user testing (N=32), semi-structured interviews (N=36), and surveys (N=35). RESULTS: The three methods together identified a total of 187 usability violations: 54% via user testing, 28% via the semi-structured interview and 18% from the survey method, with modest overlap. These usability problems were classified into 24 problem themes in 3 broad categories. User testing covered the broadest range of themes (83%), followed by the interview (63%) and survey (29%) methods. DISCUSSION: Multiple evaluation methods provide a comprehensive approach to identifying EHR usability challenges and specific problems. The three methods were found to be complementary, and thus each can provide unique insights for software enhancement. Interview and survey methods were found not to be sufficient by themselves, but when used in conjunction with the user testing method, they provided a comprehensive evaluation of the EHR. CONCLUSION: We recommend using a multi-method approach when testing the usability of health information technology because it provides a more comprehensive picture of usability challenges.

Detection and characterization of usability problems in structured data entry interfaces in dentistry.

BACKGROUND: Poor usability is one of the major barriers for optimally using electronic health records (EHRs). Dentists are increasingly adopting EHRs, and are using structured data entry interfaces to enter data such that the data can be easily retrieved and exchanged. Until recently, dentists have lacked a standardized terminology to consistently represent oral health diagnoses. OBJECTIVES: In this study we evaluated the usability of a widely used EHR interface that allow the entry of diagnostic terms, using multi-faceted methods to identify problems and work with the vendor to correct them using an iterative design method. METHODS: Fieldwork was undertaken at two clinical sites, and dental providers as subjects participated in user testing (n=32), interviews (n=36) and observations (n=24). RESULTS: User testing revealed that only 22-41% of users were able to successfully complete a simple task of entering one diagnosis, while no user was able to complete a more complex task. We identified and characterized 24 high-level usability problems reducing efficiency and causing user errors. Interface-related problems included unexpected approaches for displaying diagnosis, lack of visibility, and inconsistent use of UI widgets. Terminology related issues included missing and mis-categorized concepts. Work domain issues involved both absent and superfluous functions. In collaboration with the vendor, each usability problem was prioritized and a timeline set to resolve the concerns. DISCUSSION: Mixed methods evaluations identified a number of critical usability issues relating to the user interface, underlying terminology of the work domain. The usability challenges were found to prevent most users from successfully completing the tasks. Our further work we will determine if changes to the interface, terminology and work domain do result in improved usability.