Computer-assisted guidance for dental office tobacco-cessation counseling: a randomized controlled trial

BACKGROUND

Decreases in smoking prevalence from recent decades have slowed, and national goals to reduce tobacco use remain unmet. Healthcare providers, including those in physician and dental teams, have access to evidence-based guidelines to help patients quit smoking. Translation of those guidelines into practice, however, remains low. Approaches that involve screening for drug use, brief intervention, and referral to treatment (SBIRT) are a promising, practical solution.

PURPOSE

This study examined whether dentists and dental hygienists would assess interest in quitting, deliver a brief tobacco intervention, and refer to a tobacco quitline more frequently as reported by patients if given computer-assisted guidance in an electronic patient record versus a control group providing usual care.

DESIGN

A blocked, group-randomized trial was conducted from November 2010 to April 2011. Randomization was conducted at the clinic level. Patients nested within clinics represented the lowest-level unit of observation.

SETTING/PARTICIPANTS

Participants were patients in HealthPartners dental clinics.

INTERVENTION

Intervention clinics were given a computer-assisted tool that suggested scripts for patient discussions. Usual care clinics provided care without the tool.

MAIN OUTCOME MEASURES

Primary outcomes were post-appointment patient reports of the provider assessing interest in quitting, delivering a brief intervention, and referring them to a quitline.

RESULTS

Patient telephone surveys (72% response rate) indicated that providers assessed interest in quitting (control 70% vs intervention 87%, p=0.0006); discussed specific strategies for quitting (control 26% vs intervention 47%, p=0.003); and referred the patient to a tobacco quitline (control 17% vs intervention 37%, p=0.007) more frequently with the support of a computer-assisted tool integrated into the electronic health record.

CONCLUSIONS

Clinical decision support embedded in electronic health records can effectively help providers deliver tobacco interventions. These results build on evidence in medical settings supporting this approach to improve provider-delivered tobacco cessation.

TRIAL REGISTRATION

This study is registered at ClinicalTrials.govNCT01584882.

Perceptions and attitudes toward performing risk assessment for periodontal disease: a focus group exploration

Background

Currently, many risk assessment tools are available for clinicians to assess a patient’s periodontal disease risk. Numerous studies demonstrate the potential of these tools to promote preventive management and reduce morbidity due to periodontal disease. Despite these promising results, solo and small group dental practices, where most people receive care, have not adopted risk assessment tools widely, primarily due to lack of studies in these settings. The objective of this study was to explore the knowledge, attitudes, and beliefs of dental providers in these settings toward risk-based care through focus groups.

Methods

We conducted six focus group sessions with 52 dentists and dental hygienists practicing in solo and small group practices in Pittsburgh, PA and New York City (NYC), NY. An experienced moderator and a note-taker conducted the six sessions, each including 8–10 participants and lasting approximately 90 min. All sessions were audio-recorded and transcribed verbatim. Two researchers coded the focus group transcripts. Using a thematic analysis approach, they reviewed the coding results to identify important themes and selected representative excerpts that best described each theme.

Results

Providers strongly believed identifying risk factors could predict periodontal disease and use this information to change their patients’ behavior. A successful risk assessment tool could assist them in educating and changing their patient’s behaviors to adopt a healthy lifestyle, thus enabling them to play a major role in their patients’ overall health. However, to achieve this goal, it is essential to educate all dental providers and not just dentists on performing risk assessment and translating the results into actionable recommendations for patients. According to study participants, the research community has focused more on translating research findings into a risk assessment tool, and less on how clinicians would use these tools during patient encounters and if it affects a patients’ risk or outcome.

Conclusions

Dental practitioners were open to performing risk assessment as routine care and playing a bigger role in their patients’ overall health. Recommendations to overcome major barriers included educating dental providers at all levels, conducting more research about their adoption and use in real-world settings and developing appropriate reimbursement models.

Electronic supplementary material

The online version of this article (10.1186/s12903-018-0550-2) contains supplementary material, which is available to authorized users.

Root Canal Treatment Survival Analysis in National Dental PBRN Practices

Few studies have examined the longevity of endodontically treated teeth in nonacademic clinical settings where most of the population receives its care. This study aimed to quantify the longevity of teeth treated endodontically in general dentistry practices and test the hypothesis that longevity significantly differed by the patient's age, gender, dental insurance, geographic region, and placement of a crown and/or other restoration soon after root canal treatment (RCT). This retrospective study used deidentified data of patients who underwent RCT of permanent teeth through October 2015 in 99 general dentistry practices in the National Dental Practice-Based Research Network (Network). The data set included 46,702 patients and 71,283 RCT permanent teeth. The Kaplan-Meier (product limit) estimator was performed to estimate survival rate after the first RCT performed on a specific tooth. The Cox proportional hazards model was done to account for patient- and tooth-specific covariates. The overall median survival time was 11.1 y; 26% of RCT teeth survived beyond 20 y. Tooth type, presence of dental insurance any time during dental care, placement of crown and/or receiving a filling soon after RCT, and Network region were significant predictors of survival time (P < 0.0001). Gender and age were not statistically significant predictors in univariable analysis, but in multivariable analyses, gender was significant after accounting for other variables. This study of Network practices geographically distributed across the United States observed shorter longevity of endodontically treated permanent teeth than in previous community-based studies. Also, having a crown placed following an RCT was associated with 5.3 y longer median survival time. Teeth that received a filling soon after the RCT before the crown was placed had a median survival time of 20.1 y compared to RCT teeth with only a crown (11.4 y), only a filling (11.2 y), or no filling and no crown (6.5 y).

Eligibility requirements for advanced health informatics certification

AMIA is leading the effort to strengthen the health informatics profession by creating an advanced health informatics certification (AHIC) for individuals whose informatics work directly impacts the practice of health care, public health, or personal health. The AMIA Board of Directors has endorsed a set of proposed AHIC eligibility requirements that will be presented to the future AHIC certifying entity for adoption. These requirements specifically establish who will be eligible to sit for the AHIC examination and more generally signal the depth and breadth of knowledge and experience expected from certified individuals. They also inform the development of the accreditation process and provide guidance to graduate health informatics programs as well as individuals interested in pursuing AHIC. AHIC eligibility will be determined by practice focus, education in primary field and health informatics, and significant health informatics experience.

Association between intracranial carotid artery calcifications and periodontitis. Cone-beam computed tomography (CBCT) study

BACKGROUND

Intracranial carotid artery calcifications (ICACs) are one type of calcification that may be detected as incidental findings in cone-beam computed tomography (CBCT). This retrospective study aimed to examine the prevalence of ICACs on CBCT images and their associations among age, gender, chronic periodontitis, and patient-reported cardiovascular diseases (CVDs).

METHODS

A total of 303 CBCT scans were reviewed and a total of 208 patients met the inclusion criteria. The presence or absence of ICACs was evaluated in the ophthalmic and cavernous segments of each scan. Patient demographic data, including age, gender, and medical history, specifically focused on CVDs were recorded. The presence or absence of periodontitis was recorded from each subject with full mouth radiographs and clinical measurements. Odds ratios (ORs) were calculated as part of the logistic regression analysis.

RESULTS

Overall, ICACs were found in 93 subjects (45%). The bilateral ICACs were found in 43 subjects (21% of the total subjects, 46% of the subjects with ICACs). There were statistically significant associations between presence of ICACs and periodontitis (OR = 4.55), hypertension (OR = 3.02), hyperlipidemia (OR = 2.87), increasing age (OR = 2.24), and the male gender (OR = 1.85). Smoking status was not significantly correlated with ICACs.

CONCLUSION

This study revealed that nearly half (45%) of the subjects displayed ICACs on the CBCT images. ICACs are significantly related to the status of chronic periodontitis, age, gender, and CVDs. A more careful review of CBCT scans is highly recommended to detect these calcifications and refer patients for further medical evaluation.

Leveraging Electronic Dental Record Data to Classify Patients Based on Their Smoking Intensity

Background Smoking is an established risk factor for oral diseases and, therefore, dental clinicians routinely assess and record their patients' detailed smoking status. Researchers have successfully extracted smoking history from electronic health records (EHRs) using text mining methods. However, they could not retrieve patients' smoking intensity due to its limited availability in the EHR. The presence of detailed smoking information in the electronic dental record (EDR) often under a separate section allows retrieving this information with less preprocessing.

Objective To determine patients' detailed smoking status based on smoking intensity from the EDR.

Methods First, the authors created a reference standard of 3,296 unique patients’ smoking histories from the EDR that classified patients based on their smoking intensity. Next, they trained three machine learning classifiers (support vector machine, random forest, and naïve Bayes) using the training set (2,176) and evaluated performances on test set (1,120) using precision (P), recall (R), and F-measure (F). Finally, they applied the best classifier to classify smoking status from an additional 3,114 patients’ smoking histories.

Results Support vector machine performed best to classify patients into smokers, nonsmokers, and unknowns (P, R, F: 98%); intermittent smoker (P: 95%, R: 98%, F: 96%); past smoker (P, R, F: 89%); light smoker (P, R, F: 87%); smokers with unknown intensity (P: 76%, R: 86%, F: 81%), and intermediate smoker (P: 90%, R: 88%, F: 89%). It performed moderately to differentiate heavy smokers (P: 90%, R: 44%, F: 60%). EDR could be a valuable source for obtaining patients’ detailed smoking information.

Conclusion EDR data could serve as a valuable source for obtaining patients' detailed smoking information based on their smoking intensity that may not be readily available in the EHR.

Structuring, reuse and analysis of electronic dental data using the Oral Health and Disease Ontology

Background

A key challenge for improving the quality of health care is to be able to use a common framework to work with patient information acquired in any of the health and life science disciplines. Patient information collected during dental care exposes many of the challenges that confront a wider scale approach. For example, to improve the quality of dental care, we must be able to collect and analyze data about dental procedures from multiple practices. However, a number of challenges make doing so difficult. First, dental electronic health record (EHR) information is often stored in complex relational databases that are poorly documented. Second, there is not a commonly accepted and implemented database schema for dental EHR systems. Third, integrative work that attempts to bridge dentistry and other settings in healthcare is made difficult by the disconnect between representations of medical information within dental and other disciplines’ EHR systems. As dentistry increasingly concerns itself with the general health of a patient, for example in increased efforts to monitor heart health and systemic disease, the impact of this disconnect becomes more and more severe.

To demonstrate how to address these problems, we have developed the open-source Oral Health and Disease Ontology (OHD) and our instance-based representation as a framework for dental and medical health care information. We envision a time when medical record systems use a common data back end that would make interoperating trivial and obviate the need for a dedicated messaging framework to move data between systems.

The OHD is not yet complete. It includes enough to be useful and to demonstrate how it is constructed. We demonstrate its utility in an analysis of longevity of dental restorations. Our first narrow use case provides a prototype, and is intended demonstrate a prospective design for a principled data backend that can be used consistently and encompass both dental and medical information in a single framework.

Results

The OHD contains over 1900 classes and 59 relationships. Most of the classes and relationships were imported from existing OBO Foundry ontologies. Using the LSW2 (LISP Semantic Web) software library, we translated data from a dental practice’s EHR system into a corresponding Web Ontology Language (OWL) representation based on the OHD framework. The OWL representation was then loaded into a triple store, and as a proof of concept, we addressed a question of clinical relevance – a survival analysis of the longevity of resin filling restorations. We provide queries using SPARQL and statistical analysis code in R to demonstrate how to perform clinical research using a framework such as the OHD, and we compare our results with previous studies.

Conclusions

This proof-of-concept project translated data from a single practice. By using dental practice data, we demonstrate that the OHD and the instance-based approach are sufficient to represent data generated in real-world, routine clinical settings. While the OHD is applicable to integration of data from multiple practices with different dental EHR systems, we intend our work to be understood as a prospective design for EHR data storage that would simplify medical informatics. The system has well-understood semantics because of our use of BFO-based realist ontology and its representation in OWL. The data model is a well-defined web standard.

Evaluation of a Dental Diagnostic Terminology Subset

The objective of this study was to determine how well a subset of SNODENT, specifically designed for general dentistry, meets the needs of dental practitioners. Participants were asked to locate their written diagnosis for tooth conditions among the SNODENT terminology uploaded into an electronic dental record. Investigators found that 65% of providers’ original written diagnoses were in “agreement” with their selected SNODENT dental diagnostic subset concept(s).

Development and initial validation of a content taxonomy for patient records in general dentistry

OBJECTIVE

Develop and validate an initial content taxonomy for patient records in general dentistry.

METHODS

Phase 1 - obtain 95 de-identified patient records from 11 general dentists in the United States. Phase 2 - extract individual data fields (information items), both explicit (labeled) and implicit (unlabeled), from records, and organize into categories mirroring original field context. Phase 3 - refine raw list of information items by eliminating duplicates/redundancies and focusing on general dentistry. Phase 4 - validate all items regarding inclusion and importance using a two-round Delphi study with a panel of 22 general dentists active in clinical practice, education, and research.

RESULTS

Analysis of 76 patient records from 9 dentists, combined with previous work, yielded a raw list of 1509 information items. Refinement reduced this list to 1107 items, subsequently rated by the Delphi panel. The final model contained 870 items, with 761 (88%) rated as mandatory. In Round 1, 95% (825) of the final items were accepted, in Round 2 the remaining 5% (45). Only 45 items on the initial list were rejected and 192 (or 17%) remained equivocal.

CONCLUSION

Grounded in the reality of clinical practice, our proposed content taxonomy represents a significant advance over existing guidelines and standards by providing a granular and comprehensive information representation for general dental patient records. It offers a significant foundational asset for implementing an interoperable health information technology infrastructure for general dentistry.

Differences in medication usage of dental patients by age, gender, race/ethnicity and insurance status

BACKGROUND

Limited studies have investigated the medication profile of young adult dental patients despite the high prevalence of prescription opioid abuse in this population.

OBJECTIVE

This study investigated the extent and differences in medication usage of dental patients older than 18 years by age, race/ethnicity, gender, insurance status and mechanism of action in an academic dental clinic setting.

METHODS

Using an automated approach, medication names in the Electronic Dental Record were retrieved and classified according to the National Drug Code directory. Descriptive statistics, multivariable ANOVA and Post hoc tests were performed to detect differences in the number of medications by patient demographics.

RESULTS

Of the 11,220 adult patients, 53 percent reported taking at least one medication with significant differences in medication usage by demographics. Hydroxymethylglutaryl-coenzyme A reductase inhibitors (21-36%), and angiotensin-converting enzyme inhibitors (19-23%) ranked the top two medication classes among patients 55 years and older. Opioid agonists (7-14%), and Selective Serotonin Reuptake Inhibitors (SSRIs) (5-12%) ranked the top two medication classes among patients aged 18-54 years.

CONCLUSIONS

The results underscore the importance of dental providers to review medical and medication histories of patients regardless of their age to avoid adverse events and to determine patient's risk for opioid abuse.

Survival analysis of posterior composite restorations in National Dental PBRN general dentistry practices

OBJECTIVE

Quantify the survival of posterior composite restorations (PCR) placed during the study period in permanent teeth in United States (US) general dental community practices and factors predictive of that survival.

METHODS

A retrospective cohort study was conducted utilizing de-identified electronic dental record (EDR) data of patients who received a PCR in 99 general dentistry practices in the National Dental Practice-Based Research Network (Network). The final analyzed data set included 700,885 PCRs from 200,988 patients. Descriptive statistics and Kaplan Meier (product limit) estimator were performed to estimate the survival rate (defined as the PCR not receiving any subsequent treatment) after the first PCR was observed in the EDR during the study time. The Cox proportional hazards model was done to account for patient- and tooth-specific covariates.

RESULTS

The overall median survival time was 13.3 years. The annual failure rates were 4.5-5.8 % for years 1-5; 5.3-5.7 %, 4.9-5.5 %, and 3.3-5.2 % for years 6-10, 11-15, and 16-20, respectively. The failure descriptions recorded for < 7 % failures were mostly caries (54 %) and broken or fractured tooth/restorations (23 %). The following variables significantly predicted PCR survival: number of surfaces that comprised the PCR; having at least one interproximal surface; tooth type; type of prior treatment received on the tooth; Network region; patient age and sex. Based on the magnitude of the multivariable estimates, no single factor predominated.

CONCLUSIONS

This study of Network practices geographically distributed across the US observed PCR survival rates and predictive factors comparable to studies done in academic settings and outside the US.

CLINICAL SIGNIFICANCE

Specific baseline factors significantly predict the survival of PCRs done in US community dental practices.

Assessing Information Congruence of Documented Cardiovascular Disease between Electronic Dental and Medical Records

Dentists are more often treating patients with Cardiovascular Diseases (CVD) in their clinics; therefore, dentists may need to alter treatment plans in the presence of CVD. However, it's unclear to what extent patient-reported CVD information is accurately captured in Electronic Dental Records (EDRs). In this pilot study, we aimed to measure the reliability of patient-reported CVD conditions in EDRs. We assessed information congruence by comparing patients' self-reported dental histories to their original diagnosis assigned by their medical providers in the Electronic Medical Record (EMR). To enable this comparison, we encoded patients CVD information from the free-text data of EDRs into a structured format using natural language processing (NLP). Overall, our NLP approach achieved promising performance extracting patients' CVD-related information. We observed disagreement between self-reported EDR data and physician-diagnosed EMR data.

Integrating tobacco dependence counseling into electronic dental records: a multi-method approach

Dentistry has historically seen tobacco dependence as a medical problem. As a consequence, dentistry has not adopted or developed effective interventions to deal with tobacco dependence. With the expanded use of electronic dental records, the authors identified an opportunity to incorporate standardized expert support for tobacco dependence counseling during the dental visit. Using qualitative results from observations and focus groups, a decision support system was designed that suggested discussion topics based on the patient's desire to quit and his or her level of nicotine addiction. Because dental providers are always pressed for time, the goal was a three-minute average intervention interval. To fulfill the provider's need for an easy way to track ongoing interventions, script usage was recorded. This process helped the provider track what he or she had said to the patient about tobacco dependence during previous encounters and to vary the messages. While the individual elements of the design process were not new, the combination of them proved to be very effective in designing a usable and accepted intervention. The heavy involvement of stakeholders in all components of the design gave providers and administrators ownership of the final product, which was ultimately adopted for use in all the clinics of a large dental group practice in Minnesota.

Feasibility of Utilizing Electronic Dental Record Data and Periodontitis Case Definition to Automate Diagnosis

Periodontitis is an irreversible disease leading to tooth loss, and 42% U.S. population suffers from periodontitis. Hence, diagnosing, monitoring, and determining its prevalence is critical to develop preventive strategies. However, a nationwide epidemiological study estimating the prevalence reported a concern about the discontinuation of such studies due to cost and ethical reasons. Therefore, this study determined the feasibility of utilizing electronic dental record (EDR) data and periodontitis case definition to automate periodontitis diagnosis. We utilized EDR data from the Indiana University School of Dentistry of 28,908 unique patients. We developed and tested a computer algorithm to diagnose periodontitis using the case definition. We found 44%, 22%, and 1% of patients with moderate, severe, and mild periodontitis, respectively. The algorithm worked with 100% sensitivity, specificity, and accuracy because of the excellent quality of the EDR data. We concluded the feasibility of providing automated periodontitis diagnosis from EDR data to conduct epidemiological studies across the US.

Identifying Patients' Smoking Status from Electronic Dental Records Data

Smoking is a significant risk factor for initiation and progression of oral diseases. A patient's current smoking status and tobacco dependency can aid clinical decision making and treatment planning. The free-text nature of this data limits accessibility causing obstacles during the time of care and research utility. No studies exist on extracting patient's smoking status automatically from the Electronic Dental Record. This study reports the development and evaluation of an NLP system for this purpose.

A pragmatic, stepped-wedge, hybrid type II trial of interoperable clinical decision support to improve venous thromboembolism prophylaxis for patients with traumatic brain injury

BACKGROUND

Venous thromboembolism (VTE) is a preventable medical condition which has substantial impact on patient morbidity, mortality, and disability. Unfortunately, adherence to the published best practices for VTE prevention, based on patient centered outcomes research (PCOR), is highly variable across U.S. hospitals, which represents a gap between current evidence and clinical practice leading to adverse patient outcomes. This gap is especially large in the case of traumatic brain injury (TBI), where reluctance to initiate VTE prevention due to concerns for potentially increasing the rates of intracranial bleeding drives poor rates of VTE prophylaxis. This is despite research which has shown early initiation of VTE prophylaxis to be safe in TBI without increased risk of delayed neurosurgical intervention or death. Clinical decision support (CDS) is an indispensable solution to close this practice gap; however, design and implementation barriers hinder CDS adoption and successful scaling across health systems. Clinical practice guidelines (CPGs) informed by PCOR evidence can be deployed using CDS systems to improve the evidence to practice gap. In the Scaling AcceptabLE cDs (SCALED) study, we will implement a VTE prevention CPG within an interoperable CDS system and evaluate both CPG effectiveness (improved clinical outcomes) and CDS implementation.

METHODS

The SCALED trial is a hybrid type 2 randomized stepped wedge effectiveness-implementation trial to scale the CDS across 4 heterogeneous healthcare systems. Trial outcomes will be assessed using the RE2-AIM planning and evaluation framework. Efforts will be made to ensure implementation consistency. Nonetheless, it is expected that CDS adoption will vary across each site. To assess these differences, we will evaluate implementation processes across trial sites using the Exploration, Preparation, Implementation, and Sustainment (EPIS) implementation framework (a determinant framework) using mixed-methods. Finally, it is critical that PCOR CPGs are maintained as evidence evolves. To date, an accepted process for evidence maintenance does not exist. We will pilot a "Living Guideline" process model for the VTE prevention CDS system.

DISCUSSION

The stepped wedge hybrid type 2 trial will provide evidence regarding the effectiveness of CDS based on the Berne-Norwood criteria for VTE prevention in patients with TBI. Additionally, it will provide evidence regarding a successful strategy to scale interoperable CDS systems across U.S. healthcare systems, advancing both the fields of implementation science and health informatics.

TRIAL REGISTRATION

Clinicaltrials.gov - NCT05628207. Prospectively registered 11/28/2022, https://classic.

CLINICALTRIALS

gov/ct2/show/NCT05628207 .

Opioid Prescriptions Prior to Emergency Department Dental Visits: A Comparison of Dental Health Professional Shortage Areas (DPSAs) and Non-DPSAs Using Electronic Health Records

Although prior research has linked dental conditions and opioid prescribing in the U.S., it is not yet known whether the receipt of opioid prescriptions prior to seeking emergency care for dental conditions differs in geographical areas that are underserved by health care professionals (Dental Professional Shortage Areas, DPSAs) compared to other areas. Using Indiana's state-wide electronic health records from January 1, 2016 to October 31, 2020, we examine if patients from DPSAs presenting at the emergency department (ED) for dental conditions are more likely to have received opioid prescriptions in the 30 days prior to their visit, compared to patients from other areas. A higher rate of opioid receipt among DPSA individuals may indicate an association between lower availability of dental professionals and the use of opioids as a coping strategy. We note that our study design has several limitations (such as a lack of data on prescription use after the ED visit) and does not prove causation. We find that individuals experiencing dental condition ED visits in DPSAs are 16% more likely (than those in non-DPSAs) to have filled an opioid prescription in the 30 days prior to the ED visit, after controlling for age, gender, and race/ethnicity. This result is statistically significant at the 1% level. The baseline rate of opioid filling in the 30 days prior to the ED visit is 12% in DPSAs. These correlational results suggest that unmet dental needs might be substantially connected to opioid prescriptions, although further research is needed to establish whether this relationship is causal.

Dentists' Information Needs and Opinions on Accessing Patient Information via Health Information Exchange: Survey Study

BACKGROUND

The integration of medical and dental records is gaining significance over the past 2 decades. However, few studies have evaluated the opinions of practicing dentists on patient medical histories. Questions remain on dentists' information needs; their perception of the reliability of patient-reported medical history; satisfaction with the available information and the methods to gather this information; and their attitudes to other options, such as a health information exchange (HIE) network, to collect patient medical history.

OBJECTIVE

This study aims to determine Indiana dentists' information needs regarding patients' medical information and their opinions about accessing it via an HIE.

METHODS

We administered a web-based survey to Indiana Dental Association members to assess their current medical information-retrieval approaches, the information critical for dental care, and their willingness to access or share information via an HIE. We used descriptive statistics to summarize survey results and multivariable regression to examine the associations between survey respondents' characteristics and responses.

RESULTS

Of the 161 respondents (161/2148, 7.5% response rate), 99.5% (n=160) respondents considered patients' medical histories essential to confirm no contraindications, including allergies or the need for antibiotic prophylaxis during dental care and other adverse drug events. The critical information required were medical conditions or diagnosis, current medications, and allergies, which were gathered from patient reports. Furthermore, 88.2% (n=142) of respondents considered patient-reported histories reliable; however, they experienced challenges obtaining information from patients and physicians. Additionally, 70.2% (n=113) of respondents, especially those who currently access an HIE or electronic health record, were willing to use an HIE to access or share their patient's information, and 91.3% (n=147) shared varying interests in such a service. However, usability, data accuracy, data safety, and cost are the driving factors in adopting an HIE.

CONCLUSIONS

Patients' medical histories are essential for dentists to optimize dental care, especially for those with chronic conditions. In addition, most dentists are interested in using an HIE to access patient medical histories. The findings from this study can provide an alternative option for improving communications between dental and medical professionals and help the health information technology system or tool developers identify critical requirements for more user-friendly designs.

Characterizing Restorative Dental Treatments of Sjögren's Syndrome Patients Using Electronic Dental Records Data

Scant knowledge exists on the type of restorative treatments Sjögren's syndrome patients (SSP) receive in spite of their high dental disease burden due to hyposalivation. Increased adoption of electronic dental records (EDR) could help in leveraging information from these records to assess dental treatment outcomes in SSP. In this study, we evaluated the feasibility of using EDR to characterize the dental treatments SSP received and assess the longevity of implants in these patients. We identified 180 SSP in ten years of patients' data at the Indiana University School of Dentistry clinics. A total of 104 (57.77%) patients received restorative or endodontic treatments. Eleven patients received 23 implants with a survival rate of 87% at 40 months follow-up. We conclude that EDR data could be used for characterizing the treatments received by SSP and for assessing treatment outcomes.

Extraction and Evaluation of Medication Data from Electronic Dental Records

With an increase in the geriatric population, dental care professionals are presented with older patients who are managing their comorbidities using multiple medications. In this study, we developed a system to extract medication information from electronic dental records (EDRs) and provided patient distribution by the number of medications.

Rule-Based Text Classification of Dental Diagnosis

Unstructured medical records boast an abundance of information that could greatly facilitate medical decision-making and improve patient care. With the development of Natural Language Processing (NLP) methodology, the free-text medical data starts to attract more and more research attention. Most existing studies try to leverage the power of such unstructured data using Machine Learning algorithms, which would usually require a relatively large training set, and high computational capacity. However, when faced with a smaller-scale project, opting for an alternative approach may be more effective and practical. This project proposes an efficient and light-weight rule-based approach to categorize dental diagnosis data. It not only fills the void of dental records in the medical free-text processing area, but also demonstrates that with expertly designed research structure and proper implementation, simple method could achieve our study goal very competently.