Modeling longitudinal oral health status and pneumonia risk: secondary data analyses of an integrated dental-medical cohort.

BACKGROUND: Mounting evidence indicates potential associations between poor oral health status (OHS) and increased pneumonia risk. Relative pneumonia risk was assessed in the context of longitudinally documented OHS. METHODS: Electronic medical/dental patient data captured from 2007 through 2019 were retrieved from the integrated health records of Marshfield Clinic Health Systems. Participant eligibility initiated with an assessment of OHS, stratified into the best, moderate, or worst OHS groups, with the additional criterion of 'no pneumonia diagnosis in the past 90 days'. Pneumonia incidence was longitudinally monitored for up to 1 year from each qualifying dental visit. Models were assessed, with and without adjustment for prior pneumonia incidence, adjusted for smoking and subjected to confounding mitigation attributable to known pneumonia risk factors by applying propensity score analysis. Time-to-event analysis and proportional hazard modeling were applied to investigate relative pneumonia risk over time among the OHS groups. RESULTS: Modeling identified associations between any incident pneumonia subtype and 'number of missing teeth' (p < 0.001) and 'clinically assessed periodontal status' (p < 0.01), which remained significant following adjustment for prior pneumonia incidence and smoking. The hazard ratio (HR) for 'any incident pneumonia' in the best OHS group for 'number of missing teeth' was 0.65, 95% confidence interval (CI) [0.54 - 0.79] (unadjusted) and 0.744, 95% CI [0.61 - 0.91] (adjusted). The HR for 'any incident pneumonia' in the best 'clinically assessed periodontal status' group was 0.72, 95% CI [0.58 - 0.90] (unadjusted) and 0.78, 95% CI [0.62 - 0.97] (adjusted). CONCLUSION/CLINICAL RELEVANCE: Poor OHS increased pneumonia risk. Proactive attention of medical providers to patient OHS and health literacy surrounding oral-systemic disease association is vital, especially in high-risk populations.

Identifying oral disease variables associated with pneumonia emergence by application of machine learning to integrated medical and dental big data to inform eHealth approaches.

Background: The objective of this study was to build models that define variables contributing to pneumonia risk by applying supervised Machine Learning-(ML) to medical and oral disease data to define key risk variables contributing to pneumonia emergence for any pneumonia/pneumonia subtypes. Methods: Retrospective medical and dental data were retrieved from Marshfield Clinic Health System's data warehouse and integrated electronic medical-dental health records (iEHR). Retrieved data were pre-processed prior to conducting analyses and included matching of cases to controls by (a) race/ethnicity and (b) 1:1 Case: Control ratio. Variables with >30% missing data were excluded from analysis. Datasets were divided into four subsets: (1) All Pneumonia (all cases and controls); (2) community (CAP)/healthcare associated (HCAP) pneumonias; (3) ventilator-associated (VAP)/hospital-acquired (HAP) pneumonias and (4) aspiration pneumonia (AP). Performance of five algorithms were compared across the four subsets: Naïve Bayes, Logistic Regression, Support Vector Machine (SVM), Multi-Layer Perceptron (MLP) and Random Forests. Feature (input variables) selection and ten-fold cross validation was performed on all the datasets. An evaluation set (10%) was extracted from the subsets for further validation. Model performance was evaluated in terms of total accuracy, sensitivity, specificity, F-measure, Mathews-correlation-coefficient and area under receiver operating characteristic curve (AUC). Results: In total, 6,034 records (cases and controls) met eligibility for inclusion in the main dataset. After feature selection, the variables retained in the subsets were: All Pneumonia (n = 29 variables), CAP-HCAP (n = 26 variables); VAP-HAP (n = 40 variables) and AP (n = 37 variables), respectively. Variables retained (n = 22) were common across all four pneumonia subsets. Of these, the number of missing teeth, periodontal status, periodontal pocket depth more than 5 mm and number of restored teeth contributed to all the subsets and were retained in the model. MLP outperformed other predictive models for All Pneumonia, CAP-HCAP and AP subsets, while SVM outperformed other models in VAP-HAP subset. Conclusion: This study validates previously described associations between poor oral health and pneumonia. Benefits of an integrated medical-dental record and care delivery environment for modeling pneumonia risk are highlighted. Based on findings, risk score development could inform referrals and follow-up in integrated healthcare delivery environment and coordinated patient management.

Positioning operations in the dental safety net to enhance value-based care delivery in an integrated health-care setting.

OBJECTIVES: Impact of implementing data-driven performance metric-tracking across a 10-dental center infrastructure established by Family Heath Center of Marshfield (FHC-M) was examined for relative impact on achieving value-based care delivery in serving a patient population characterized by 88% Medicaid representation. METHODS: To track progress toward national benchmarks for preventive care delivery, dental quality analytics dashboard tracking was implemented in real time with sharing of performance metrics across centers. Compliance rate with Uniform Data Systems reporting requirements for sealant placement on permanent first molars in children aged 6-9 years of age at moderate-to-high risk of caries was targeted at FHC-M dental centers for comparison with those of other community health centers statewide and nationally. Hygienist-to-dentist ratio to support robust sealant placement capacity was further examined. RESULTS: Uniform Data Systems data for rate of sealant placement between 2016-2018 revealed that FHC-M consistently exceeded rates reported statewide and nationally. For this quality indicator, performance across all dental practices in 27 states reported by Centers for Medicare and Medicaid Services in 2018 achieved 23% in 2017 compared to 73% and 52% placement rates reported by FHC-M and community health centers, respectively. A 1:1 hygienist-to-dentist was documented across FHC-M dental centers compared to 0.5:1 reported nationally. CONCLUSIONS: Implementation of quality metric dashboard and a 1:1 dentist-to-hygienist ratio supported realization of value-based dental care delivery relative to caries prevention in a moderate-to-high risk pediatric Medicaid population through achievement of robust sealant placement. Importance of adequate hygienist staffing, "same day" sealant placement and performance feedback supported by technology are highlighted.

Integrating Medical-Dental Care for Diabetic Patients: Qualitative Assessment of Provider Perspectives.

Globally, periodontal disease and diabetes have achieved epidemic proportions and have become a top health care priority. Mutual bidirectional exacerbation of these conditions is promoting creation of cross-disciplinary integrated care delivery (ICD) models that bridge the traditionally siloed health care domains of dentistry and medicine. By engaging focus groups inclusive of both medical and dental providers and one-on-one interviews, this qualitative study investigated provider knowledgeability, receptiveness, and readiness to engage ICD and sought input from the medical-dental primary care practitioner participants on perceived opportunities, benefits, and challenges to achieving ICD models for patients with diabetes/prediabetes. Statewide regional representation and inclusivity of diverse practice settings were emphasized in soliciting participants. Thematic analysis of focus group and interview transcripts was undertaken to establish current state of the art, gauge receptivity to alternative ICD models, and seek insights from practitioners surrounding opportunities and barriers to ICD achievement. Forty providers participated, and thematic analyses achieved saturation. Providers were well informed regarding disease interaction; were receptive to ICD, including implementation of better screening and referral processes; and favored improving interdisciplinary communication inclusive of access to integrated electronic health records. Perceived barriers and opportunities communicated by participants for advancing ICD were documented.

Status Update on Translation of Integrated Primary Dental-Medical Care Delivery for Management of Diabetic Patients.

Escalating prevalence of both diabetes and periodontal disease, two diseases associated with bi-directional exacerbation, has been reported. Periodontal disease represents a modifiable risk factor that may reduce diabetes onset or progression, and integrated models of cross-disciplinary care are needed to establish and manage glycemic control in affected patients. An ad-hoc environmental scan of current literature and media sought to characterize factors impacting status of integrated care models based on review of the existing evidence base in literature and media surrounding: (1) current cross-disciplinary practice patterns, (2) epidemiological updates, (3) status on risk assessment and screening for dysglycemia in the dental setting, (4) status on implementation of quality metrics for oral health, (5) care model pilots, and (6) public health perspectives. The survey revealed: escalating prevalence of diabetes and periodontitis globally; greater emphasis on oral health assessment for diabetic patients in recent medical clinical practice guidelines; high knowledgeability surrounding oral-systemic impacts on diabetes and growing receptivity to medical-dental integration among medical and dental providers; increasing numbers of programs/studies reporting on positive impact of emerging integrated dental-medical care models on diabetic patient healthcare access and health outcomes; a growing evidence base for clinically significant rates of undiagnosed dysglycemia among dental patients reported by point-of-care pilot studies; no current recommendation for population-based screening for dysglycemia in dental settings pending a stronger evidence base; improved definition of true periodontitis prevalence in (pre)/diabetics; emerging recognition of the need for oral health quality indicators and tracking; evidence of persistence in dental access disparity; updated status on barriers to integration. The potential benefit of creating clinically-applicable integrated care models to support holistic management of an escalating diabetic population by targeting modifiable risk factors including periodontitis is being recognized by the health industry. Cross-disciplinary efforts supported by high quality research are needed to mitigate previously- and newly-defined barriers of care integration and expedite development and implementation of integrated care models in various practice settings. Implementation of quality monitoring in the dental setting will support definition of the impact and efficacy of interventional clinical care models on patient outcomes.

Medical care providers' perspectives on dental information needs in electronic health records.

BACKGROUND: The authors conducted this study to identify the most relevant patient dental information in a medical-dental integrated electronic health record (iEHR) necessary for medical care providers to inform holistic treatment. METHODS: The authors collected input from a diverse sample of 65 participants from a large, regional health system representing 13 medical specialties and administrative units. The authors collected feedback from participants through 11 focus group sessions. Two independent reviewers analyzed focus group transcripts to identify major and minor themes. RESULTS: The authors identified 336 of 385 annotations that most medical care providers coded as relevant. Annotations strongly supporting relevancy to clinical practice aligned with 18 major thematic categories, with the top 6 categories being communication, appointments, system design, medications, treatment plan, and dental alerts. CONCLUSIONS: Study participants identified dental data of highest relevance to medical care providers and recommended implementation of user-friendly access to dental data in iEHRs as crucial to holistic care delivery. PRACTICAL IMPLICATIONS: Identification of the patients' dental information most relevant to medical care providers will inform strategies for improving the integration of that information into the medical-dental iEHR.

Medical Providers' Oral Health Knowledgeability, Attitudes, and Practice Behaviors: An Opportunity for Interprofessional Collaboration.

OBJECTIVE: Evaluation of current knowledgeability, attitudes, and practice behaviors of medical providers from a large health care system toward oral health was undertaken as a pilot effort to better understand and integrate oral health into the overall health care delivery. METHODS: Invitations to complete a 28-question survey, designed in a web-based platform (SurveyMonkey(®)), were emailed to 1407 medical multispecialty physicians, residents, and nurses within the health system. The questionnaire included sections on provider demographics, oral health knowledgeability and attitudes, and current practice conducting oral health screenings. RESULTS: A 14% (n = 199/1407) response rate was achieved for survey completion. There were 16% who reported good coverage of oral/dental health topics in their medical training curriculum. Competency level was <30% for identifying tooth decay and oral pathology. There were 95% who reported never applying fluoride varnish in their practice, while >80% answered knowledge-based questions correctly. Frequency rates for dental referral by the medical providers were 32% 'frequently' and 68% 'infrequently.' Perceptions of optimal frequency for conducting oral health assessment in their professional practices ranged from 69% indicating 'frequently' to 25% indicating 'infrequently.' CONCLUSION: Overall, positive attitudes were observed toward incorporation of oral health examination into medical practice. The study identified lack of oral health treatment and infrequent referral by medical providers to dental providers. Results support likelihood for acceptance of care models that incorporate a medical/dental team-based approach complemented by oral health training for medical providers to enhance holistic health care delivery. Limitations of this pilot study include potential selection bias and lack of generalizability beyond our institution; further studies are planned in additional settings statewide to validate findings.

The 4D hyperspherical diffusion wavelet: A new method for the detection of localized anatomical variation.

Recently, the HyperSPHARM algorithm was proposed to parameterize multiple disjoint objects in a holistic manner using the 4D hyperspherical harmonics. The HyperSPHARM coefficients are global; they cannot be used to directly infer localized variations in signal. In this paper, we present a unified wavelet framework that links Hyper-SPHARM to the diffusion wavelet transform. Specifically, we will show that the HyperSPHARM basis forms a subset of a wavelet-based multiscale representation of surface-based signals. This wavelet, termed the hyperspherical diffusion wavelet, is a consequence of the equivalence of isotropic heat diffusion smoothing and the diffusion wavelet transform on the hypersphere. Our framework allows for the statistical inference of highly localized anatomical changes, which we demonstrate in the first-ever developmental study on the hyoid bone investigating gender and age effects. We also show that the hyperspherical wavelet successfully picks up group-wise differences that are barely detectable using SPHARM.

Medical providers' dental information needs: a baseline survey.

Articulation of medical and dental practices has been strongly called for based on the many oral-systemic connections. With the rapid development and adoption of electronic health records, the feasibility of integrating medical and dental patient data should be strongly considered. The objective of this study was to develop an initial understanding of the medical providers' core dental information needs and opinion of integrated medical-dental electronic health record (iEHR) environment in their workflow. This was achieved by administering a 13 question survey to a group of 1,197 medical care providers employed by Marshfield Clinic in Wisconsin, United States. The survey received a response rate of 35%. The responses were analyzed based on provider 'Role' and 'Specialty'. The majority of the respondents felt the need for patient's dental information to coordinate or provide effective medical care. An integrated electronic health record environment could facilitate this holistic patient care approach.