Translating periodontal data to knowledge in a learning health system

Area of Science:

• Oral health research
• Health informatics
• Public health

Background:

• A learning health system (LHS) integrates patient and clinician collaboration for evidence-based care and discovery.
• Electronic health records (EHRs) make an LHS for dentistry feasible by capturing oral healthcare encounters.

Purpose of the Study:

• To assess the feasibility of using EHR data to track periodontal health outcomes within a dental LHS framework.
• To establish key performance indicators for periodontitis incidence and tooth loss due to periodontal disease progression.

Main Methods:

• Utilized EHR data from three large dental institutions to track new periodontitis cases and tooth loss.
• Analyzed 494,272 examinations from 194,984 patients, developing dynamic dashboards for performance monitoring.

Main Results:

• The incidence of new periodontitis was 4.3%, and tooth loss due to periodontal disease progression was 1.2%.
• Demonstrated the feasibility of automated data extraction and interpretation from EHRs for critical health elements.

Conclusions:

• Periodontal disease management is well-suited for an LHS model, enabling data-driven diagnosis, prevention, and treatment.
• Dental institutions can leverage EHR data for self-evaluation and targeted interventions to enhance oral health outcomes.