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Objectives: To develop outcomes of care quality measures derived from the dental electronic health record (EHR) to assess the occurrence and timely treatment of tooth decay. Methods: Quality measures were developed to assess whether decay was treated within 6 months and if new decay occurred in patients seen. Using EHR-derived data of the state of each tooth surface, algorithms compared the patient's teeth at different dates to determine if decay was treated or new decay had occurred. Manual chart reviews were conducted at three sites to validate the measures. The measures were implemented and scores were calculated for three sites over four calendar years, 2016 through 2019. Results: About 954 charts were manually reviewed for the timely treatment of tooth decay measure, with measure performance of sensitivity 97%, specificity 85%, positive predictive value (PPV) 91%, negative predictive value (NPV) 95%. About 739 charts were reviewed for new decay measure, with sensitivity 94%, specificity 99%, PPV 99%, and NPV 94%. Across all sites and years, 52.8% of patients with decay were fully treated within 6 months of diagnosis (n = 247,959). A total of 23.8% of patients experienced new decay, measured at an annual exam (n = 640,004). Conclusion: Methods were developed and validated for assessing timely treatment of decay and occurrence of new decay derived from EHR data, creating effective outcome measures. These EHR-based quality measures produce accurate and reliable results that support efforts and advancement in quality assessment, quality improvement, patient care and research.

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 of harm is not always straightforward for dental practices. Mining data from electronic health records is a promising means of efficiently detecting possible adverse events (AEs). Methods: We developed 7 electronic triggers (electronic health record based) to flag patient charts that contain distinct events common to AEs. These electronic charts were then manually reviewed to identify AEs. Results: Of the 1,885 charts reviewed, 16.2% contained an AE. The positive predictive value of the triggers ranged from a high of 0.23 for the 2 best-performing triggers (failed implants and postsurgical complications) to 0.09 for the lowest-performing triggers. The most common types of AEs found were pain (27.5%), hard tissue (14.8%), soft tissue (14.8%), and nerve injuries (13.3%). Most AEs were classified as temporary harm (89.2%). Permanent harm was present in 9.6% of the AEs, and 1.2% required transfer to an emergency room. Conclusion: By developing these triggers and a process to identify harm, we can now start measuring AEs, which is the first step to mitigating harm in the future. Knowledge Transfer Statement: A retrospective review of patients’ health records is a useful approach for systematically identifying and measuring harm. Rather than random chart reviews, electronic health record–based dental trigger tools are an effective approach for practices to identify patient harm. Measurement is one of the first steps in improving the safety and quality of care delivered.

Caries indices, the basis of epidemiologic caries measures, are not easily obtained in clinical settings. This study’s objective was to design, test, and validate an automated program (Valid Electronic Health Record Dental Caries Indices Calculator Tool [VERDICT]) to calculate caries indices from an electronic health record (EHR). Synthetic use case scenarios and actual patient cases of primary, mixed, and permanent dentition, including decayed, missing, and filled teeth (DMFT/dmft) and tooth surfaces (DMFS/dmfs) were entered into the EHR. VERDICT measures were compared to a previously validated clinical electronic data capture (EDC) system and statistical program to calculate caries indices. Four university clinician-researchers abstracted EHR caries exam data for 45 synthetic use cases into the EDC and post-processed with SAS software creating a gold standard to compare the ­VERDICT-derived caries indices. Then, 2 senior researchers abstracted EHR caries exam data and calculated caries indices for 24 patients, allowing further comparisons to VERDICT indices. Agreement statistics were computed among abstractors, and discrepancies were resolved by consensus. Agreement statistics between the 2 final-phase abstractors and the VERDICT measures showed extremely high concordance: Lin’s concordance coefficients (LCCs) >0.99 for dmfs, dmft, DS, ds, DT, dt, ms, mt, FS, fs, FT, and ft; LCCs >0.95 for DMFS and DMFT; and LCCs of 0.92–0.93 for MS and MT. Caries indices, essential to developing primary health outcome measures for research, can be reliably derived from an EHR using VERDICT. Using these indices will enable population oral health management approaches and inform quality improvement efforts.

The routine use of standardized diagnostic terminologies (DxTMs) in dentistry has long been the subject of academic debate. This paper discusses the strategies suggested by a group of dental stakeholders to enhance the uptake of DxTMs. Through unstructured interviewing at the 'Toward a Diagnosis-Driven Profession' National Conference held on 19 March 2016 in Los Angeles, CA, USA participants were asked how enthusiastic they were about implementing and consistently using DxTMs at their work. They also brainstormed on strategies to improve the widespread use of DxTMs. Their responses are summarized by recursive abstraction and presented in themes. Conference participants were very enthusiastic about using a DxTM in their place of work. Participants enumerated several strategies to make DxTMs more appealing including: the use of mandates, a value proposition for providers, communication and education, and integration with EHRs and existing systems. All groups across the dental healthcare delivery spectrum will need to work together for the success of the widespread and consistent use of DxTMs. Understanding the provider perspective is however the most critical step in achieving this goal, as they are the group who will ultimately be saddled with the critical task of ensuring DxTM use at the point of care.

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.

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.

Laser irradiation has numerous favorable characteristics, such as ablation or vaporization, hemostasis, biostimulation (photobiomodulation) and microbial inhibition and destruction, which induce various beneficial therapeutic effects and biological responses. Therefore, the use of lasers is considered effective and suitable for treating a variety of inflammatory and infectious oral conditions. The CO2 , neodymium-doped yttrium-aluminium-garnet (Nd:YAG) and diode lasers have mainly been used for periodontal soft-tissue management. With development of the erbium-doped yttrium-aluminium-garnet (Er:YAG) and erbium, chromium-doped yttrium-scandium-gallium-garnet (Er,Cr:YSGG) lasers, which can be applied not only on soft tissues but also on dental hard tissues, the application of lasers dramatically expanded from periodontal soft-tissue management to hard-tissue treatment. Currently, various periodontal tissues (such as gingiva, tooth roots and bone tissue), as well as titanium implant surfaces, can be treated with lasers, and a variety of dental laser systems are being employed for the management of periodontal and peri-implant diseases. In periodontics, mechanical therapy has conventionally been the mainstream of treatment; however, complete bacterial eradication and/or optimal wound healing may not be necessarily achieved with conventional mechanical therapy alone. Consequently, in addition to chemotherapy consisting of antibiotics and anti-inflammatory agents, phototherapy using lasers and light-emitting diodes has been gradually integrated with mechanical therapy to enhance subsequent wound healing by achieving thorough debridement, decontamination and tissue stimulation. With increasing evidence of benefits, therapies with low- and high-level lasers play an important role in wound healing/tissue regeneration in the treatment of periodontal and peri-implant diseases. This article discusses the outcomes of laser therapy in soft-tissue management, periodontal nonsurgical and surgical treatment, osseous surgery and peri-implant treatment, focusing on postoperative wound healing of periodontal and peri-implant tissues, based on scientific evidence from currently available basic and clinical studies, as well as on case reports.

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.

ObjectiveTreatment planning, an essential component of clinical practice, has received little attention in the dental literature and there appears to be no consistent format being followed in the teaching and development of treatment plans within dental school curricula. No investigation, to our knowledge, has been carried out to explore the subject of treatment planning since the advent of electronic health record (EHR) use in dentistry. It is therefore important to examine the topic of treatment planning in the context of EHRs.MethodsThis paper reports on how 25 predoctoral dental students from two U.S. schools performed when asked to complete diagnosis and treatment planning exercises for two clinical scenarios in an EHR. Three calibrated clinical teaching faculty scored diagnosis entry, diagnosis-treatment (procedure) pairing, and sequencing of treatment according to criteria taught in their curriculum. Scores were then converted to percent correct and reported as means (with standard deviations).ResultsOverall, the participants earned 48.2% of the possible points. Participants at School 2 earned a mean of 54.3% compared with participants at School 1, who earned 41.9%. Students fared better selecting the appropriate treatment (59.8%) compared with choosing the correct diagnoses (41.9%) but performed least favorably when organizing the sequence of their treatment plans (41.7%).ConclusionOur results highlight the need to improve the current process by which treatment planning is taught and also to consider the impact of technology on the fundamental skills of diagnosis and treatment planning within the modern educational setting.

Advances in informatics, particularly the implementation of electronic health records (EHR), in dentistry have facilitated the exchange of information. The majority of dental schools in North America use the same EHR system, providing an unprecedented opportunity to integrate these data into a repository that can be used for oral health education and research. In 2007, fourteen dental schools formed the Consortium for Oral Health-Related Informatics (COHRI). Since its inception, COHRI has established structural and operational processes, governance and bylaws, and a number of work groups organized in two divisions: one focused on research (data standardization, integration, and analysis), and one focused on education (performance evaluations, virtual standardized patients, and objective structured clinical examinations). To date, COHRI (which now includes twenty dental schools) has been successful in developing a data repository, pilot-testing data integration, and sharing EHR enhancements among the group. This consortium has collaborated on standardizing medical and dental histories, developing diagnostic terminology, and promoting the utilization of informatics in dental education. The consortium is in the process of assembling the largest oral health database ever created. This will be an invaluable resource for research and provide a foundation for evidence-based dentistry for years to come.