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How Artificial Intelligence Is Reshaping Patient Care

AI is making its way into dental hygiene, offering new opportunities to enhance diagnostics, streamline workflows, and improve patient outcomes.

PURCHASE COURSE
This course was published in the May/June 2025 issue and expires June 2028. The authors have no commercial conflicts of interest to disclose. This 2 credit hour self-study activity is electronically mediated.

AGD Subject Code: 010

EDUCATIONAL OBJECTIVES

After reading this course, the participant should be able to:

  1. Identify ways in which artificial intelligence (AI) may be used in dentistry as well as possible concerns with its utilization.
  2. List the challenges faced by dental hygienists in providing comprehensive dental care.
  3. Discuss the types of AI tools currently available and how they may aid dental hygienists in providing patient care.

In the ever-evolving landscape of dental hygiene clinical expectations, improving care and workflow by incorporating new technology is a necessary step to advance the profession. One of the latest advancements in dentistry is artificial intelligence (AI). Thousands of literature reviews on the role of AI in healthcare and hundreds on the use of AI in dentistry have already been published.1–4 However, little of this research speaks specifically to how AI can benefit dental hygienists and improve the standards for dental hygiene practice. Like any emerging technology, it’s essential to understand what’s available; evaluate how it will affect workflow, efficiency, and quality; and identify the best ways to incorporate it into practice.

AI is defined as software capable of executing cognitive tasks similar to those of humans, including perception, reasoning, interacting with surroundings, and solving problems. To put it simply, AI is trained and AI learns.5 Figure 1 demonstrates the results of the 2024 AI in Dental Hygiene Survey conducted by Heartland Dental and the American Dental Hygienists’ Association on how AI is gaining traction in the dental hygiene profession.6

AI offers opportunities for offices still using paper charts to switch to electronic health records (EHRs). As Borna et al7 explain, EHRs can propel health information exchanges, allowing the gathering and sharing of patient information from different provider groups. Because the AI models in health information systems accomplish various tasks, such as data collection, clinical decision assistance, prognosis prediction, and health-related results, AI could enhance patient management.7,8 This would allow for an interdisciplinary approach to patient care and open the door for comprehensive oral-systemic care.

Most AI technology used in dentistry has already received clearance from the United States Food and Drug Administration; however, AI does have limitations including possible inherent bias and issues adhering to the Health Insurance Portability and Accountability Act.5

Technology may be a barrier to using AI if the dental equipment is outdated or there is insufficient access to system updates but, most significantly, a lack of education and training could cause poor adoption or misuse.5 Ahmed et al9 caution that there is a danger of automation bias, in which clinicians view AI as flawless, overshadowing the importance of their own clinical skills and critical thinking. AI should be seen as an auxiliary rather than a replacement for professional judgment.9 Patients, dental hygienists, and product developers must have open, informed conversations about how AI will facilitate dental treatment decisions.10

Challenges in the Current Standard of Care

In dentistry, AI may help enhance both thoroughness and quality of care. Since the introduction of the 2017 Classification of Periodontal and Peri-Implant Diseases and Conditions by the American Academy of Periodontology and the European Federation of Periodontology, the periodontal standard of care has expanded, requiring dental hygienists to adapt to the new system that evaluates the extent, severity, and progression of periodontal diseases and conditions.11 Although this shift was essential, it has resulted in an overwhelming amount of information for dental hygienists to handle.

Numerous demands are placed on dental hygienists to provide effective and efficient care. Periodontitis and gingivitis can be exacerbated by high A1C levels, which need to be monitored as they also increase the risk of infection, cause xerostomia, and delay wound healing.12 Dental hygienists are responsible for performing head and neck examinations to assess for cancer.13 Moreover, clinical chart notes must be accurate and comprehensive, including time-intensive documentation.

Dental hygienists have become frontline caregivers strategically placed to help inform patients of their overall wellness and the necessary steps to achieve health. As most dental hygiene appointments last an hour or less, time constraints can restrict opportunities for professional growth. This is further compounded by the presence of older, inadequate equipment.

According to Seneviratne et al,14 radiographic bone level must be assessed to complement periodontal charting. Reviewing a patient’s dental history by asking about oral trauma and past history of periodontal diseases is also required. Saliva tests should be performed to measure pH and microbiological factors, as periodontal pathogens may impact systemic health.14

Dental hygienists play a crucial role in evidence-based caries prevention by conducting thorough assessments of individual risk factors, identifying caries, integrating the patient’s medical and dental histories, and performing glucose monitoring along with A1C testing to evaluate for diabetes.15,16 Ideally, these data should be gathered and analyzed within the appointment to determine classification and treatment options. However, this requires adequate time, technology, and tools to ensure accurate results. Limitations in these areas may lead to compromises due to incomplete periodontal charts, missed medical assessments, skipped oral cancer screenings, or delayed radiographs. The dental hygiene profession may use AI to address these limitations by embracing autonomy and exploring AI’s potential.9

Radiographic Artificial Intelligence

Currently, AI appears to be most promising in the use of diagnostic imaging techniques. Radiographs offer a view of tenacious calculus, diagnostics for determining bone levels, and assistance in charting existing conditions. Dental hygienists arguably look at images more than anyone in the office and AI can help make the most of what radiographs have to tell about a patient’s health. AI can assist with a more thorough caries assessment and may help reduce human inaccuracy while supporting clinical expertise.15

Ossowska et al4 conducted a review to determine if radiographic AI could be as accurate as dentists in diagnosing across five different areas: restorative therapy, endodontics, orthodontics, oral surgery, and periodontics. While the AI was by no means perfect, it repeatedly outperformed dental professionals’ clinical findings. As such, clinical expertise, combined with AI, will improve diagnosis with better efficiency, accuracy, and precision.4

Radiographic AI may also expand a dental hygienist’s capacity by detecting incipient caries and automatically charting existing restorations. A recent study showed that dental AI models can detect carious lesions with 80% to 95% accuracy, reaching up to 93% in advanced systems for intraoral images.17 However, accuracy varies based on the AI platform, image quality, and lesion type.17 Accurate and up-to-date dental charting is essential because dental records are legal documents; if something isn’t noted in a dental chart, it is assumed that it wasn’t done.18 In confirming diagnostic findings, images make it easier to educate patients on areas of concern. This may increase the patient’s trust and confidence in treatment plans.

According to Alam et al,19 trained AI algorithms can recognize indicators of periodontal diseases in intraoral images. Its performance was evaluated in terms of sensitivity, specificity, and overall diagnostic accuracy. The algorithms achieved an overall accuracy of 87% in diagnosing periodontal diseases. The AI correctly identified 90% of true cases compared to an overall accuracy of 86% in clinical diagnoses, underscoring the promising potential of AI algorithms in diagnosing periodontal diseases through intraoral image analysis.19

Mesial and distal radiographic bone levels confirmed with periapical radiographic AI will aid the dental hygienist in classifying periodontal diseases to make an accurate diagnosis. An additional advantage lies in presenting patients with educational visual aids overlaid with their teeth, along with precise measurements of radiographic bone loss expressed in millimeters and percentages. Some AI systems can classify patients in accordance with the 2017 Classification of Periodontal and Peri-Implant Diseases and Conditions.20 This approach enhances patient education and significantly contributes to the calibration of dental hygienists.

Additionally, AI technology can greatly assist dental hygienists in accurately diagnosing periodontal bone levels in panoramic and cone-beam computed tomography. This intersection has the potential to enhance the classification, diagnosis, and treatment of gingivitis and periodontal diseases by reallocating the time needed for radiographic examinations toward more in-depth patient care.19 Incorporating AI with radiographs, intraoral photos, clinical findings, and periodontal examinations can significantly enhance the effectiveness of dental hygiene practices.21

Studies using intraoral images are being conducted to evaluate how well AI identifies inflammation in gingival tissue. The most recent epidemiological study on oral health found that 88% of adults experience gingivitis annually.22 Prompt treatment is essential to safeguard periodontal health because if gingivitis is not diagnosed early, it may lead to the loss of connective tissue, destruction of tooth support, and consequent bone loss.23

According to Pitchika et al,20 because early detection of gingival disease is paramount, AI-based smartphone applications may provide a way to self-monitor gingival health with patients’ taking photos of their own mouths (Figure 2). A recent study evaluated the effectiveness of AI-assisted self-monitoring by patients using images taken post-periodontal treatment.20 By receiving post-treatment alerts on their phones, patients experienced better compliance with treatment follow-up, improved oral health, reduced debris accumulation, and better periodontal health. If compatible EHRs are already in place, AI use from a smartphone will integrate seamlessly into dental hygiene workflow while ensuring the tools and technologies are accessible and user-friendly.20

Complete periodontal charting is the foundation for accurate assessment.24 If AI is poised to make a difference for dental hygienists, the optimal place is in identifying radiographic bone loss, assisting with periodontal charting, intuitive clinical notes, disease classification, patient education tools, and patient self-care recommendations.

Charting and Voice Activation

Clinical chart notes that utilize AI are now available. They allow AI to pull dental information from patient/​clinician conversations and fill in clinical chart notes, optimizing workflow and elevating the quality of patient care. Intuitive clinical notes gathered by AI allow dental hygienists to focus on patient care, which could be transformative in effective education and treatment. However, patients must give consent to the sharing of their data with AI and they need to understand who can access their data, how the information will be stored or used, and how their privacy will be protected.9

The use of AI voice-activated periodontal charting has myriad benefits (Figure 3). In the treatment of gingivitis and periodontal and peri-implant diseases, the technology may help create more time and flexibility to accurately document a complete periodontal chart, allowing proper classification and treatment.

Available AI tools can adapt to anyone’s voice and operate without an assistant. Charting out loud may enhance the patient experience by encouraging active listening and participation, allowing patients to become more engaged in discussions about their periodontal health and fostering a deeper understanding of their treatment options. This could also promote proper infection control and ergonomics by removing the need to touch a keyboard. It empowers dental hygienists to accurately classify, diagnose, and treat periodontal diseases by providing valuable support for their assessments.

AI can also generate reports and educational tools for patients, facilitating an interdisciplinary approach to care. AI that is qualified to pull information from medical histories may pave the way for a comprehensive oral-systemic approach to educating patients on their overall oral health and the application of self-care devices.

Li et al25 found that AI-driven patient self-care devices may empower patients to take ownership of their overall periodontal health. With power toothbrushes guided by AI, patients can track their toothbrushing duration by connecting it to a smartphone application. Depending on the application, they can assess brushing habits, track bleeding, collect rewards, and received personalized coaching on brushing techniques. Innovative dental AI tools have been shown to improve patient compliance, which is a pivotal step toward maintaining better oral hygiene.25

While AI is not yet fully integrated into dentistry, ongoing studies are exploring its potential for diagnosing, classifying, and predicting oral cancer.26–28 Combining AI with oral cancer screenings may offer a solution to combat oral cancer’s high mortality rates.

Conclusion

AI is already transforming dental hygienists’ workflows, but there is much still to discover. Limited studies are available that statistically quantify how current AI technology may benefit the dental hygiene profession. Independent studies on AI technologies are needed to verify claims and increase awareness and comprehension among clinicians and patients, ensuring that both dental hygienists and patients have access to accurate, critical data for informed decision-making.

In the meantime, dental hygienists must proactively explore AI technologies that enhance patient care both in the office and at home. By staying informed and evaluating AI advancements, they can assess available tools, understand their impact on workflow efficiency and care quality, and effectively integrate them into practice.

References

  1. PubMed. Database Search for “Artificial Intelligence” Medicine. Available at /https:/​/​pubmed.ncbi.nlm.nih.gov/?term=%22artificial+intelligence%22+medicine&filter=pubt.review&filter=years.2022-2024. Accessed April 2, 2025.
  2. PubMed. Database Search for “Artificial Intelligence” Dentistry. Available at /https:/​/​pubmed.ncbi.nlm.nih.gov/?term=%22artificial+intelligence%22+dentistry&filter=pubt.review&filter=years.2022-2024. Accessed April 2, 2025.
  3. Deshmukh R, Rathi P. Artificial intelliJ nce in medicine. J Assoc Physicians India. 2022;70:11-12.
  4. Ossowska A, Kusiak A, Świetlik D. Artificial intelligence in dentistry-narrative review. Int J Environ Res Public Health. 2022;19:3449.
  5. Stryker C, Kavlakoglu E. What is artificial intelligence (ai)? Available at ibm./​om/​topics/​artificial-intelligence. Accessed April 2, 2025.
  6. American Dental Hygienists’ Association. AI in Dentistry: Are Hygienists Ready? Available at adha.org/​wp-content/​uplo_​ds/떘/葐/떘_​Heartland-ADHA_떘_​Hygienist_​Dental_​AI_​Survey.pdf. Accessed April 2, 2025.
  7. Borna S, Maniaci MJ, Haider CR, et al. Artificial intelligence models in health information exchange: a systematic review of clinical implications. Healthcare (Basel). 2023;11:2584.
  8. Hossain E, Rana R, Higgins N, et al. Natural language processing in electronic health records in relation to healthcare decision-making: a systematic review. Comput Biol Med. 2023;155:106649.
  9. Ahmed MI, Spooner B, Isherwood J, Lane M, Orrock E, Dennison A. A systematic review of the barriers to the implementation of artificial intelligence in healthcare. Cureus. 2023;15(:e46454.
  10. Tang L, Li J, Fantus S. Medical artificial intelligence ethics: a systematic review of empirical studies. Digit Health. 2023;9:20552076231186064.
  11. Alkhafaji N, Patel TJ. Implementing the 2017 periodontal classification system. Dimensions of Dental Hygiene. 2023; 21(9):16-19.
  12. American Dental Association. Diabetes. Available at ada./​rg/​resources/​ada-library/​oral-health-topics/​diabetes. Accessed April 2, 2025.
  13. Laskin D, Swecker T. Oral cancer detection. Dimensions of Dental Hygiene. 2016;14(8):60-65.
  14. Seneviratne CJ, Balan P, Suriyanarayanan T, et al. Oral microbiome-systemic link studies: perspectives on current limitations and future artificial intelligence-based approaches. Crit Rev Microbiol. 2020;46:288-299.
  15. Pitts E, Fontana M. The role of the dental hygienist in caries risk assessment. Dimensions of Dental Hygiene. 2018;16(7):21-24.
  16. Ortiz M. The A1C score: The A1C score is well within the dental hygiene scope of practice Available at rdhmag.com/​patient-care/​article/ﶰ/​the-a1c-score-the-a1c-score-is-well-within-the-dental-hygiene-scope-of-practice. Accessed April 2, 2025.
  17. Zhang JW, Fan J, Zhao FB, Ma B, Shen XQ, Geng YM. Diagnostic accuracy of artificial intelligence-assisted caries detection: a clinical evaluation. BMC Oral Health. 2024;24:1095.
  18. American Dental Association. What and How to Write, or Change in the Dental Record. Available at ada.org/​resources/​practice/​practice-management/​writing-in-the-dental-record. Accessed April 2, 2025.
  19. Alam MK, Alanazi NH, Alshehri ADA, Chowdhury F. Accuracy of AI algorithms in diagnosing periodontal disease using intraoral J ages. J Pharm Bioallied Sci. 2024;16(Suppl 1):S583-S585.
  20. Pitchika V, Büttner M, Schwendicke F. Artificial intelligence and personalized diagnostics in periodontology: a narrative review. Periodontol 2000. 2024;95:220-231.
  21. Tariq A, Nakhi FB, Salah F, et al. Efficiency and accuracy of artificial intelligence in the radiographic detection of periodontal bone loss: a systematic review. Imaging Sci Dent. 2023;53:193.
  22. Li W, Guo E, Zhao H, et al. Evaluation of transfer ensemble learning-based convolutional neural network models for the identification of chronic gingivitis from oral photographs. BMC Oral Health. 2024;24:814.
  23. Alalharith DM, Alharthi HM, Alghamdi WM, et al. A deep learning-based approach for the detection of early signs of gingivitis in orthodontic patients using faster region-based convolutional neural networks. Int J Environ Res Public Health. 2020;17:8447.
  24. Salvi GE, Roccuzzo A, Imber J, Stähli A, Klinge B, Lang NP. Clinical periodontal diagnosis. Periodontol 2000. July 14, 2023.
  25. Li Y, Wu X, Liu M, et al. Enhanced control of periodontitis by an artificial intelligence‐enabled multimodal‐sensing toothbrush. J Clinic Periodontol. April 17, 2024.
  26. Khanagar SB, Alkadi L, Alghilan MA, et al. Application and performance of artificial intelligence (ai) in oral cancer diagnosis and prediction using histopathological images: a systematic review. Biomedicines. 2023;11:1612.
  27. Malhotra M, Shaw A, Priyadarshini SR, Metha S, Sahoo P, Gachake A. Diagnostic accuracy of artificial intelligence compared to biopsy in detecting early oral squamous cell carcinoma: a systematic review and meta analysis. Asian Pac J Cancer Prev. 2024;25:2593-2603.
  28. Yuan W, Rao J, Liu Y, Li S, Qin L, Huang X. Deep radiomics-based prognostic prediction of oral cancer using optical coherence tomography. BMC Oral Health. 2024;24:1117.

From Dimensions of Dental Hygiene. May/June 2025; 23(3):32-35.

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