skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: Opportunities for Oral Health Monitoring Technologies Beyond the Dental Clinic
Personal health and wellness technologies can improve people’s care at home, connect everyday activities to clinical settings, and allow more efficient use of clinical resources. Recently, the Human-Computer Interaction community has begun to develop tools to improve oral care. In this research, we investigate dental practices and information needs through surveys and interviews with a range of patients and oral health providers. We find that personal users want to track their progress—or lack thereof—between dental visits for feedback, so they can adjust their home care routines, or so they can seek an escalation in care if they identify a problem. Among providers and clinical health workers, there exists an opportunity for better screening and diagnostic tools to identify dental caries at early stages. Providers in rural areas desire better tools to communicate problem areas to patients and their caregivers to bridge oral health care disparities in areas with limited access to care. Our results can guide the development of dental technologies that can address currently unmet needs of patients and providers.  more » « less
Award ID(s):
1631146
PAR ID:
10107453
Author(s) / Creator(s):
; ; ; ;
Date Published:
Journal Name:
PervasiveHealth'18
Page Range / eLocation ID:
327 to 335
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; ; (, Experimental Biology and Medicine)
    Due to the essential role of dentists in stopping the COVID-19 pandemic, the purpose of this review is to help dentists to detect any weaknesses in their disinfection and cross-contamination prevention protocols, and to triage dental treatments to meet the needs of patients during the pandemic. We used PRISMA to identify peer-reviewed publications which supplemented guidance from the center for disease control about infection control and guidelines for dentists. Dentists must triage dental treatments to meet the needs of patients during the pandemic. The ongoing pandemic has changed the practice of dentistry forever, the changes make it more cumbersome, time-consuming, and costly due to the possible pathways of transmission and mitigation steps needed to prevent the spread of COVID-19. Dental chairside rapid tests for SARS-CoV-2 are urgently needed. Until then, dentists need to screen patients for COVID-19 even though 75% of people with COVID-19 have no symptoms. Despite the widespread anxiety and fear of the devastating health effects of COVID-19, only 61% of dentists have implemented a change to their treatment protocols. As an urgent matter of public health, all dentists must identify the additional steps they can take to prevent the spread of COVID-19. The most effective steps to stop the pandemic in dental offices are to; vaccinate all dentists, staff, and patients; triage dental treatments for patients, separate vulnerable patients, separate COVID-19 patients, prevent cross-contamination, disinfect areas touched by patients, maintain social distancing, and change personal protective equipment between patients. 
    more » « less
  2. ; ; ; ; ; ; (, JAMIA Open)
    Abstract BackgroundWhile most health-care providers now use electronic health records (EHRs) to document clinical care, many still treat them as digital versions of paper records. As a result, documentation often remains unstructured, with free-text entries in progress notes. This limits the potential for secondary use and analysis, as machine-learning and data analysis algorithms are more effective with structured data. ObjectiveThis study aims to use advanced artificial intelligence (AI) and natural language processing (NLP) techniques to improve diagnostic information extraction from clinical notes in a periodontal use case. By automating this process, the study seeks to reduce missing data in dental records and minimize the need for extensive manual annotation, a long-standing barrier to widespread NLP deployment in dental data extraction. Materials and MethodsThis research utilizes large language models (LLMs), specifically Generative Pretrained Transformer 4, to generate synthetic medical notes for fine-tuning a RoBERTa model. This model was trained to better interpret and process dental language, with particular attention to periodontal diagnoses. Model performance was evaluated by manually reviewing 360 clinical notes randomly selected from each of the participating site’s dataset. ResultsThe results demonstrated high accuracy of periodontal diagnosis data extraction, with the sites 1 and 2 achieving a weighted average score of 0.97-0.98. This performance held for all dimensions of periodontal diagnosis in terms of stage, grade, and extent. DiscussionSynthetic data effectively reduced manual annotation needs while preserving model quality. Generalizability across institutions suggests viability for broader adoption, though future work is needed to improve contextual understanding. ConclusionThe study highlights the potential transformative impact of AI and NLP on health-care research. Most clinical documentation (40%-80%) is free text. Scaling our method could enhance clinical data reuse. 
    more » « less
  3. ; ; ; ; ; ; (, Frontiers in Digital Health)
    Artificial Intelligence (AI)-driven Digital Health (DH) systems are poised to play a critical role in the future of healthcare. In 2021, $57.2 billion was invested in DH systems around the world, recognizing the promise this concept holds for aiding in delivery and care management. DH systems traditionally include a blend of various technologies, AI, and physiological biomarkers and have shown a potential to provide support for individuals with various health conditions. Digital therapeutics (DTx) is a more specific set of technology-enabled interventions within the broader DH sphere intended to produce a measurable therapeutic effect. DTx tools can empower both patients and healthcare providers, informing the course of treatment through data-driven interventions while collecting data in real-time and potentially reducing the number of patient office visits needed. In particular, socially assistive robots (SARs), as a DTx tool, can be a beneficial asset to DH systems since data gathered from sensors onboard the robot can help identify in-home behaviors, activity patterns, and health status of patients remotely. Furthermore, linking the robotic sensor data to other DH system components, and enabling SAR to function as part of an Internet of Things (IoT) ecosystem, can create a broader picture of patient health outcomes. The main challenge with DTx, and DH systems in general, is that the sheer volume and limited oversight of different DH systems and DTxs is hindering validation efforts (from technical, clinical, system, and privacy standpoints) and consequently slowing widespread adoption of these treatment tools. 
    more » « less
  4. ; ; ; ; ; ; ; ; ; (, JMIR Human Factors)
    Background Remote patient monitoring (RPM) technologies can support patients living with chronic conditions through self-monitoring of physiological measures and enhance clinicians’ diagnostic and treatment decisions. However, to date, large-scale pragmatic RPM implementation within health systems has been limited, and understanding of the impacts of RPM technologies on clinical workflows and care experience is lacking. Objective In this study, we evaluate the early implementation of operational RPM initiatives for chronic disease management within the ambulatory network of an academic medical center in New York City, focusing on the experiences of “early adopter” clinicians and patients. Methods Using a multimethod qualitative approach, we conducted (1) interviews with 13 clinicians across 9 specialties considered as early adopters and supporters of RPM and (2) speculative design sessions exploring the future of RPM in clinical care with 21 patients and patient representatives, to better understand experiences, preferences, and expectations of pragmatic RPM use for health care delivery. Results We identified themes relevant to RPM implementation within the following areas: (1) data collection and practices, including impacts of taking real-world measures and issues of data sharing, security, and privacy; (2) proactive and preventive care, including proactive and preventive monitoring, and proactive interventions and support; and (3) health disparities and equity, including tailored and flexible care and implicit bias. We also identified evidence for mitigation and support to address challenges in each of these areas. Conclusions This study highlights the unique contexts, perceptions, and challenges regarding the deployment of RPM in clinical practice, including its potential implications for clinical workflows and work experiences. Based on these findings, we offer implementation and design recommendations for health systems interested in deploying RPM-enabled health care. 
    more » « less
  5. ; ; ; (, Journal of Medical Internet Research)
    Amid the COVID-19 pandemic, it has been reported that greater than 35% of patients with confirmed or suspected COVID-19 develop postacute sequelae of SARS CoV-2 (PASC). PASC is still a disease for which preliminary medical data are being collected—mostly measurements collected during hospital or clinical visits—and pathophysiological understanding is yet in its infancy. The disease is notable for its prevalence and its variable symptom presentation, and as such, management plans could be more holistically made if health care providers had access to unobtrusive home-based wearable and contactless continuous physiologic and physical sensor data. Such between-hospital or between-clinic data can quantitatively elucidate a majority of the temporal evolution of PASC symptoms. Although not universally of comparable accuracy to gold standard medical devices, home-deployed sensors offer great insights into the development and progression of PASC. Suitable sensors include those providing vital signs and activity measurements that correlate directly or by proxy to documented PASC symptoms. Such continuous, home-based data can give care providers contextualized information from which symptom exacerbation or relieving factors may be classified. Such data can also improve the collective academic understanding of PASC by providing temporally and activity-associated symptom cataloging. In this viewpoint, we make a case for the utilization of home-based continuous sensing that can serve as a foundation from which medical professionals and engineers may develop and pursue long-term mitigation strategies for PASC. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email