24 October 2022

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Dental schools can implement targeted strategies to improve oral health outcomes

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Background: A learning health system (LHS) is a system in which patients and clinicians work together to choose evidence-based care and to drive discovery as a natural outgrowth of every clinical encounter to ensure the right care at the right time. With an increased number of oral health care encounters now captured in electronic health records (EHRs), an LHS for dentistry is now feasible. 

EHR data, although ubiquitous, are an underused resource in dentistry.

The National Academy of Medicine has called for the development of these learning health systems to ensure innovation, quality and value at the point of care. In these systems, clinicians integrate internal data and experience with external evidence, putting the results into practice. Patients subsequently receive higher-quality, safer and more efficient care.

Periodontal disease management is well suited to serve as a model for a learning health system pilot implementation in dentistry. First, periodontal disease and caries represent the two biggest threats to oral health in the U.S. Second, periodontal disease is associated with other inflammatory and systemic conditions, such as cardiovascular disease and diabetes.

Methods: Led by researchers in the Department of Diagnostic and Biomedical Sciences at The University of Texas Health Science Center, the authors used EHRs data to track periodontal health outcomes at two dental schools and one accountable care organization. The outcomes of interest were a new periodontitis case — for patients who had not received a diagnosis of periodontitis previously — and tooth loss due to progression of periodontal disease.

Results: The authors assessed a total of 494,272 examinations (new periodontitis outcome: n = 168,442; new tooth loss outcome: n = 325,830), representing a total of 194,984 patients. Dynamic dashboards displaying performance on both measures over time allow users to compare demographic and risk factors for patients. The incidence of new periodontitis and tooth loss was 4.3% and 1.2%, respectively.

Conclusions: Periodontal disease, diagnosis, prevention and treatment are particularly well suited for an LHS model. The results showed the feasibility of automated extraction and interpretation of critical data elements from the EHRs. The two outcome measures are being implemented as part of a dental LHS. 

The authors are targeting the main drivers of poorer periodontal outcomes in a specific patient population, and they continue to use clinical health data for the purpose of learning and improvement.

Practical Implications: Dental institutions of any size can conduct contemporaneous self-evaluation and immediately implement targeted strategies to improve oral health outcomes.

Tokede, Bunmi et al. “Translating periodontal data to knowledge in a learning health system.” The Journal of the American Dental Association, Volume 153, Issue 10, October 2022, Pages 996-1004. doi.org/10.1016/j.adaj.2022.06.007