Use of Learning Health Systems to Enhance Dental Care

A learning health system (LHS) in the practice of dentistry is now a practical tool, as an expanded number of oral health care encounters are captured in electronic health records (EHRs).

According to findings from a study published in the Journal of the American Dental Association, as value-based care predominates, EHR data will have a central role in generating significant knowledge in support of LHS for improving oral health. Moreover, periodontal disease, diagnosis, prevention, and treatment are especially well suited for an LHS model.  

Utilizing data from EHRs , researchers followed periodontal health outcomes at 3 large dental institutions. The 2 outcomes of interest included: a new periodontitis case (for patients who had not received a diagnosis of periodontitis previously) and tooth loss due to progression of periodontal disease.

In total, researchers evaluated 494,272 examinations (new periodontitis outcome: n = 168,442; new tooth loss outcome: n = 325,830), representing a total of 194,984 patients. The average (SD) age was 42.8 (16.4) years.

Dynamic dashboards displaying performance on both measures over time allow users to compare demographic and risk factors for patients. Moreover, the overall incidence of new periodontitis and tooth loss was 4.3% and 1.2%, respectively.

The new periodontitis measure scores were greater among male patients (5.59%) than female patients (3.59%) and expanded with age. The measure scores for new periodontitis were greater among those who smoked (10.75%) than those who did not (4.04%). The measure scores for new tooth loss were higher among those who had received a diagnosis of diabetes (10.66%) than those who had not (4.06%).

The new tooth loss measure scores were greater among male patients (1.5%) than female patients (0.9%) and increased with age. The measure scores for new tooth loss were higher among those who smoked (3.67%) than those who did not (0.99%). The measure scores for new tooth loss were greater among those who had received a diagnosis of diabetes (2.80%) than those who had not (1.04%).

The authors indicated that their findings demonstrated the feasibility of automated extraction and interpretation of critical data elements from the EHRs and concluded that dental institutions and practices are well positioned to learn from each other by way of sharing data, codeveloping improvement strategies, and disseminating these findings.

“We also recognize that EHR data alone may not be inclusive enough to conduct meaningful learning. Rather, the value of EHR data might be realized when linked to other data sources, such as patient-reported behaviors, quantified self-data, and clinical trial data. As value-based care predominates, EHR data will occupy a central role in generating meaningful knowledge in support of LHS for improving oral health”, the authors concluded.

Lastly, the authors noted that dental institutions of any size can perform contemporaneous self-evaluation and immediately execute targeted strategies to enhance oral health outcomes.

Reference

Tokede B, Yansane A, White J, et al. Translating periodontal data to knowledge in a learning health system. J Am Dent Assoc. 2022;153(10):996-1004. doi:10.1016/j.adaj.2022.06.007.