Using big data to promote precision oral health in the context of a learning healthcare system.

There has been a call for evidence-based oral healthcare guidelines, to improve precision dentistry and oral healthcare delivery. The main challenges to this goal are the current lack of up-to-date evidence, the limited integrative analytical data sets, and the slow translations to routine care delivery. Overcoming these issues requires knowledge discovery pipelines based on big data and health analytics, intelligent integrative informatics approaches, and learning health systems. This article examines how this can be accomplished by utilizing big data. These data can be gathered from four major streams: patients, clinical data, biological data, and normative data sets. All these must then be uniformly combined for analysis and modelling and the meaningful findings can be implemented clinically. By executing data capture cycles and integrating the subsequent findings, practitioners are able to improve public oral health and care delivery.

Mining Electronic Dental Records to Identify Dry Socket Risk Factors.

The goal of this study was to investigate risk factors for developing dry sockets in patients after dental extractions. Data were collected directly from electronic dental records (EDR) and were utilized for selecting dry socket cases and controls to conduct a nested case-control study. Case-control matching was based on sex, age range, maxilla-mandible location, and anterior-posterior location. From 83 self-reported health survey questions, 7 questions were found to have predictive potential based on a significant chi-squared test. Stepwise conditional logistic regression showed a statistically significant association between the development of dry socket and a history of serious illness (OR=1.4; 95% CI:1.02-1.95), cancer (OR=2.6; 95% CI:1.13-5.83), and frequent mouth sores (OR=1.9; 95% CI:1.09-3.33). These results corroborated previous reports on potential involvement of impaired immune response in dry socket development. EDR may be an important source for uncovering predictive factors that play a role in prevention and management of oral health.