Impact of big data on oral health outcomes

Digital health policy decoded: Mapping national strategies using Donabedian's model

National strategies are essential driving forces behind governments taking responsibility for setting the direction of digital health on a national level. This study employed a novel mixed-methods approach, integrating topic modeling, co-occurrence analysis, and qualitative content analysis, to comprehensively examine 22 national digital health strategies through the lens of Donabedian's structure-process-outcome model. The quantitative analysis identified 14 prevalent topics, while the qualitative analysis provided nuanced insights into the contexts underlying these topics. Leveraging Donabedian's framework, the topics were categorized into structure (training and digital health professionals, governance frameworks, computing infrastructure, public-private partnerships, regulatory frameworks), process (AI and big data, decision-support systems, shared digital health records, disease surveillance, information system interoperability), and outcome dimensions (improved health and social care, privacy and security, quality and efficiency of health services, universal coverage, sustainable development goals). This hybrid methodology offers a unique contribution by mapping the identified themes onto a widely accepted quality of care model, bridging the gap between policy analysis and healthcare quality assessment. The study unveils underaddressed themes, highlights the interrelationships between policy components, and provides a comprehensive understanding of the global digital health policy landscape. The findings inform future strategies, academic research directions, and potential policy considerations for governments formulating digital health regulations.

Evolution and development of methodologies in social and behavioural science research in relation to oral health

The aim of this introductory paper is to provide an overview of key methodological developments in social and behavioural research in oral health. In the first section, we provide a brief historical perspective on research in the field. In the second section, we outline key methodological issues and introduce the seven papers in the theme. Conceptual models can contextualize research findings and address the 'why' and 'how' instead of 'what' and 'how many'. Many models exist, albeit they need to be evaluated (and adapted) for use in oral health research and in specific settings. The increasing availability of big data can facilitate this with data linkage. Through data linkage, it is possible to explore and understand in a broader capacity the array of factors that influence oral health outcomes and how oral health can influences other factors. With advances in statistical approaches, it is feasible to consider casual inferences and to quantify these effects. There is a need for not only individual efforts to embrace causal inference research but also systematic and structural changes in the field to yield substantial results. The value of qualitative research in co-producing knowledge with and from human participants in addressing 'the how' and 'the why' factors is also key. There have been calls to employ more sophisticated qualitative methods together with mixed methods approaches as ways of helping to address the complex or Wicked Problems in population oral health. In the final section, we outline possible future methodological directions in social and behavioural oral health research including participatory approaches and the development of core outcome sets. Our overriding goal in the paper is to facilitate a critical debate in relation to methodological issues which can be used to improve understanding and generate knowledge in population oral health and that this, in turn, will help inform oral health policy and practices.

Translating Science into Improved Health for All

Our world is at a turning point with biological and social pathogens wreaking havoc at the same time that science and technology are exploding with new discoveries. It is a pivotal time for the new report Oral Health in America: Advances and Challenges to be released and a pivotal time for our profession to take action and lead. The art, science, and practice of dentistry is very different from 20 y ago when the original Surgeon General's report was released. We are on the precipice of individualized health care where providers will collaborate to deliver diagnostics and therapeutics that are data driven and inclusive of the social determinants of health. To move forward with alacrity requires a strong scientific foundation, effective educational approaches, an understanding of the upstream determinants of health, and partnerships across the health professions and beyond. Oral health has never been more important, and now is the time for our profession to further develop, elevate, and translate the science into practice and policy to improve the nation's health.

P4 Medicine as a model for precision periodontal care

Objectives

P4 Medicine is based on a proactive approach for clinical patient care incorporating the four “pillars” of prediction, prevention, personalization, and participation for patient management. The purpose of this review is to demonstrate how the concepts of P4 medicine can be incorporated into the management of periodontal diseases (particularly periodontitis) termed P4 periodontics.

Methods

This is a narrative review that used current literature to explore how P4 periodontics can be aligned with the 2018 Classification of Periodontal Diseases, current periodontal treatment paradigms, and periodontal regenerative technologies.

Results

The proposed model of P4 periodontics is highly aligned with the 2018 Classification of Periodontal Diseases and represents a logical extension of this classification into treatment paradigms. Each stage of periodontitis can be related to a holistic approach to clinical management. The role of “big data” in future P4 periodontics is discussed and the concepts of a treat-to-target focus for treatment outcomes are proposed as part of personalized periodontics. Personalized regenerative and rejuvenative periodontal therapies will refocus our thinking from risk management to regenerative solutions to manage the effects of disease and aging.

Conclusions

P4 Periodontics allows us to focus not only on early prevention and intervention but also allow for personalized late-stage reversal of the disease trajectory and the use of personalized regenerative procedures to reconstruct damaged tissues and restore them to health.

Clinical Significance

P4 Periodontics is a novel means of viewing a holistic, integrative, and proactive approach to periodontal treatment.

Clinical decision support systems in orthodontics: A narrative review of data science approaches

Advancements in technology and data collection generated immense amounts of information from various sources such as health records, clinical examination, imaging, medical devices, as well as experimental and biological data. Proper management and analysis of these data via high-end computing solutions, artificial intelligence and machine learning approaches can assist in extracting meaningful information that enhances population health and well-being. Furthermore, the extracted knowledge can provide new avenues for modern healthcare delivery via clinical decision support systems. This manuscript presents a narrative review of data science approaches for clinical decision support systems in orthodontics. We describe the fundamental components of data science approaches including (a) Data collection, storage and management; (b) Data processing; (c) In-depth data analysis; and (d) Data communication. Then, we introduce a web-based data management platform, the Data Storage for Computation and Integration, for temporomandibular joint and dental clinical decision support systems.

The Modern and Digital Transformation of Oral Health Care: A Mini Review

Dentistry is a part of the field of medicine which is advocated in this digital revolution. The increasing trend in dentistry digitalization has led to the advancement in computer-derived data processing and manufacturing. This progress has been exponentially supported by the Internet of medical things (IoMT), big data and analytical algorithm, internet and communication technologies (ICT) including digital social media, augmented and virtual reality (AR and VR), and artificial intelligence (AI). The interplay between these sophisticated digital aspects has dramatically changed the healthcare and biomedical sectors, especially for dentistry. This myriad of applications of technologies will not only be able to streamline oral health care, facilitate workflow, increase oral health at a fraction of the current conventional cost, relieve dentist and dental auxiliary staff from routine and laborious tasks, but also ignite participatory in personalized oral health care. This narrative article review highlights recent dentistry digitalization encompassing technological advancement, limitations, challenges, and conceptual theoretical modern approaches in oral health prevention and care, particularly in ensuring the quality, efficiency, and strategic dental care in the modern era of dentistry.

Update and review of the gerodontology prospective for 2020's: Linking the interactions of oral (hypo)-functions to health vs. systemic diseases

New lines of evidence suggest that the oral-systemic medical links and oral hypo-function are progressively transcending beyond the traditional clinical signs and symptoms of oral diseases. Research into the dysbiotic microbiome, host immune/inflammatory regulations and patho-physiologic changes and subsequent adaptations through the oral-systemic measures under ageism points to pathways leading to mastication deficiency, dysphagia, signature brain activities for (neuro)-cognition circuitries, dementia and certain cancers of the digestive system as well. Therefore, the coming era of oral health-linked systemic disorders will likely reshape the future of diagnostics in oral geriatrics, treatment modalities and professional therapies in clinical disciplines. In parallel to these highlights, a recent international symposium was jointly held by the International Association of Gerontology and Geriatrics (IAGG), Japanese Society of Gerodontology (JSG), the representative of USA and Taiwan Academy of Geriatric Dentistry (TAGD) on Oct 25th, 2019. Herein, specific notes are briefly addressed and updated for a summative prospective from this symposium and the recent literature.

Unravelling the Potential of Salivary Volatile Metabolites in Oral Diseases. A Review

Fostered by the advances in the instrumental and analytical fields, in recent years the analysis of volatile organic compounds (VOCs) has emerged as a new frontier in medical diagnostics. VOCs analysis is a non-invasive, rapid and inexpensive strategy with promising potential in clinical diagnostic procedures. Since cellular metabolism is altered by diseases, the resulting metabolic effects on VOCs may serve as biomarkers for any given pathophysiologic condition. Human VOCs are released from biomatrices such as saliva, urine, skin emanations and exhaled breath and are derived from many metabolic pathways. In this review, the potential of VOCs present in saliva will be explored as a monitoring tool for several oral diseases, including gingivitis and periodontal disease, dental caries, and oral cancer. Moreover, the analytical state-of-the-art for salivary volatomics, e.g., the most common extraction techniques along with the current challenges and future perspectives will be addressed unequivocally.

Using big data to promote precision oral health in the context of a learning healthcare system

There has been a call for evidence-based oral healthcare guidelines, to improve precision dentistry and oral healthcare delivery. The main challenges to this goal are the current lack of up-to-date evidence, the limited integrative analytical data sets, and the slow translations to routine care delivery. Overcoming these issues requires knowledge discovery pipelines based on big data and health analytics, intelligent integrative informatics approaches, and learning health systems. This article examines how this can be accomplished by utilizing big data. These data can be gathered from four major streams: patients, clinical data, biological data, and normative data sets. All these must then be uniformly combined for analysis and modelling and the meaningful findings can be implemented clinically. By executing data capture cycles and integrating the subsequent findings, practitioners are able to improve public oral health and care delivery.